From 6df420ed67c6978e76bf54679caafb29a17609e1 Mon Sep 17 00:00:00 2001
From: Artyom Anokhov <artyom.anokhov@intel.com>
Date: Mon, 18 Sep 2023 15:36:55 +0200
Subject: [PATCH 01/46] [Azure] Fix linux_debian.yml (#19911)

* Update linux_debian.yml

Fixed apt-get update

* More fixes

---------

Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
---
 .ci/azure/linux_debian.yml         | 2 +-
 .github/workflows/linux_debian.yml | 2 +-
 cmake/packaging/debian.cmake       | 1 +
 cmake/packaging/rpm.cmake          | 1 +
 4 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/.ci/azure/linux_debian.yml b/.ci/azure/linux_debian.yml
index 96db6129c72ee1..e94a0819705bd7 100644
--- a/.ci/azure/linux_debian.yml
+++ b/.ci/azure/linux_debian.yml
@@ -228,7 +228,7 @@ jobs:
       wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
       sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
       echo "deb https://apt.repos.intel.com/openvino/2023 ubuntu20 main" | sudo tee /etc/apt/sources.list.d/intel-openvino-2023.list
-      sudo apt-get update -o Dir::Etc::sourcelist=/etc/apt/sources.list.d/intel-openvino-2023.list
+      sudo apt-get update
       sudo apt-get install openvino -y
       # install our local one and make sure the conflicts are resolved
       sudo apt-get install --no-install-recommends dpkg-dev -y
diff --git a/.github/workflows/linux_debian.yml b/.github/workflows/linux_debian.yml
index b517a368c46ced..bff429be48c90a 100644
--- a/.github/workflows/linux_debian.yml
+++ b/.github/workflows/linux_debian.yml
@@ -219,7 +219,7 @@ jobs:
             wget https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
             sudo apt-key add GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB
             echo "deb https://apt.repos.intel.com/openvino/2023 ubuntu20 main" | sudo tee /etc/apt/sources.list.d/intel-openvino-2023.list
-            sudo apt-get update -o Dir::Etc::sourcelist=/etc/apt/sources.list.d/intel-openvino-2023.list
+            sudo apt-get update
             sudo apt-get install openvino -y
             # install our local one and make sure the conflicts are resolved
             sudo apt-get install --no-install-recommends dpkg-dev -y
diff --git a/cmake/packaging/debian.cmake b/cmake/packaging/debian.cmake
index 48adc7acf3980a..d359a40aa6df51 100644
--- a/cmake/packaging/debian.cmake
+++ b/cmake/packaging/debian.cmake
@@ -91,6 +91,7 @@ macro(ov_cpack_settings)
         # - 2022.3 is the first release where Debian updated packages are introduced, others 2022.3.X are LTS
         2022.3.0 2022.3.1 2022.3.2 2022.3.3 2022.3.4 2022.3.5
         2023.0.0 2023.0.1 2023.0.2 2023.0.3
+        2023.1.0
         )
 
     #
diff --git a/cmake/packaging/rpm.cmake b/cmake/packaging/rpm.cmake
index ad1172b6c833ae..077e970d138bc4 100644
--- a/cmake/packaging/rpm.cmake
+++ b/cmake/packaging/rpm.cmake
@@ -77,6 +77,7 @@ macro(ov_cpack_settings)
         # - 2022.3 is the first release where RPM updated packages are introduced, others 2022.3.X are LTS
         2022.3.0 2022.3.1 2022.3.2 2022.3.3 2022.3.4 2022.3.5
         2023.0.0 2023.0.1 2023.0.2 2023.0.3
+        2023.1.0
         )
 
     find_host_program(rpmlint_PROGRAM NAMES rpmlint DOC "Path to rpmlint")

From dbab89f04706c597c6a08ab68e91ae1ec2eaaeb2 Mon Sep 17 00:00:00 2001
From: Karol Blaszczak <karol.blaszczak@intel.com>
Date: Mon, 18 Sep 2023 16:24:26 +0200
Subject: [PATCH 02/46] [DOCS] minor post release tweaks (#19914)

---
 docs/Documentation/model_introduction.md      | 39 +++++++++++++------
 .../Convert_Model_From_PyTorch.md             |  2 +-
 docs/documentation.md                         |  4 +-
 docs/home.rst                                 |  4 +-
 .../installing-openvino-linux-header.md       | 13 ++++---
 .../installing-openvino-macos-header.md       | 20 +++++-----
 .../installing-openvino-windows-header.md     |  7 ++--
 7 files changed, 54 insertions(+), 35 deletions(-)

diff --git a/docs/Documentation/model_introduction.md b/docs/Documentation/model_introduction.md
index ad38d118a01922..cd24fccbec8dfe 100644
--- a/docs/Documentation/model_introduction.md
+++ b/docs/Documentation/model_introduction.md
@@ -15,18 +15,37 @@
    openvino_docs_OV_Converter_UG_prepare_model_convert_model_Converting_Model
 
 
-Every deep learning workflow begins with obtaining a model. You can choose to prepare a custom one, use a ready-made solution and adjust it to your needs, or even download and run a pre-trained network from an online database, such as `TensorFlow Hub <https://tfhub.dev/>`__, `Hugging Face <https://huggingface.co/>`__, or `Torchvision models <https://pytorch.org/hub/>`__.
-
-OpenVINO™ :doc:`supports several model formats <Supported_Model_Formats>` and can convert them into its own representation, `openvino.Model <api/ie_python_api/_autosummary/openvino.Model.html>`__ (`ov.Model <api/ie_python_api/_autosummary/openvino.runtime.Model.html>`__), providing a conversion API. Converted models can be used for inference with one or multiple OpenVINO Hardware plugins. There are two ways to use the conversion API: using a Python script or calling the ``ovc`` command line tool.
+Every deep learning workflow begins with obtaining a model. You can choose to prepare
+a custom one, use a ready-made solution and adjust it to your needs, or even download
+and run a pre-trained network from an online database, such as 
+`TensorFlow Hub <https://tfhub.dev/>`__, `Hugging Face <https://huggingface.co/>`__,
+or `Torchvision models <https://pytorch.org/hub/>`__.
+
+If your selected model is in one of the :doc:`OpenVINO™ supported model formats <Supported_Model_Formats>`,
+you can use it directly, without the need to save as the OpenVINO IR.
+(`openvino.Model <api/ie_python_api/_autosummary/openvino.Model.html>`__ -
+`ov.Model <api/ie_python_api/_autosummary/openvino.runtime.Model.html>`__). 
+For this purpose, you can use ``openvino.Core.read_model`` and ``openvino.Core.compile_model`` 
+methods, so that conversion is performed automatically before inference, for 
+maximum convenience (note that working with PyTorch differs slightly, the Python API
+being the only option, while TensorFlow may present additional considerations
+:doc:`TensorFlow Frontend Capabilities and Limitations <openvino_docs_MO_DG_TensorFlow_Frontend>`).
+
+
+For better performance and more optimization options, OpenVINO offers a conversion
+API with two possible approaches: the Python API functions (``openvino.convert_model`` 
+and ``openvino.save_model``) and the ``ovc`` command line tool, which are described in detail in this article. 
 
 .. note::
    
-   Prior to OpenVINO 2023.1, model conversion API was exposed as the ``openvino.tools.mo.convert_model`` 
-   function and the ``mo`` command line tool. Now, a new and simplified API is used: the
-   ``openvino.convert_model`` function and the ``ovc`` command line tool. 
+   Model conversion API prior to OpenVINO 2023.1 is considered deprecated. 
+   Both existing and new projects are recommended to transition to the new
+   solutions, keeping in mind that they are not fully backwards compatible 
+   with ``openvino.tools.mo.convert_model`` or the ``mo`` CLI tool.
+   For more details, see the :doc:`Model Conversion API Transition Guide <openvino_docs_OV_Converter_UG_prepare_model_convert_model_MO_OVC_transition>`.
+
+
 
-   All new projects are recommended to use the new tools, keeping in mind that they are not fully
-   backwards compatible. For more details, consult the :doc:`Model Conversion API Transition Guide <openvino_docs_OV_Converter_UG_prepare_model_convert_model_MO_OVC_transition>`.
 
 Convert a Model in Python: ``convert_model``
 ##############################################
@@ -209,12 +228,8 @@ Another option for model conversion is to use ``ovc`` command-line tool, which s
 
 The results of both ``ovc`` and ``openvino.convert_model``/``openvino.save_model`` conversion methods are the same. You can choose either of them based on your convenience. Note that there should not be any differences in the results of model conversion if the same set of parameters is used and the model is saved into OpenVINO IR.
 
-Cases when Model Preparation is not Required
-############################################
 
-If a model is represented as a single file from ONNX, PaddlePaddle, TensorFlow and TensorFlow Lite (check :doc:`TensorFlow Frontend Capabilities and Limitations <openvino_docs_MO_DG_TensorFlow_Frontend>`), it does not require a separate conversion and IR-saving step, that is ``openvino.convert_model`` and ``openvino.save_model``, or ``ovc``. 
 
-OpenVINO provides C++ and Python APIs for reading such models by just calling the ``openvino.Core.read_model`` or ``openvino.Core.compile_model`` methods. These methods perform conversion of the model from the original representation. While this conversion may take extra time compared to using prepared OpenVINO IR, it is convenient when you need to read a model in the original format in C++, since ``openvino.convert_model`` is only available in Python. However, for efficient model deployment with the OpenVINO Runtime, it is still recommended to prepare OpenVINO IR and then use it in your inference application.
 
 Additional Resources
 ####################
diff --git a/docs/MO_DG/prepare_model/convert_model/Convert_Model_From_PyTorch.md b/docs/MO_DG/prepare_model/convert_model/Convert_Model_From_PyTorch.md
index 055e94049a78ed..0cafd3066535ab 100644
--- a/docs/MO_DG/prepare_model/convert_model/Convert_Model_From_PyTorch.md
+++ b/docs/MO_DG/prepare_model/convert_model/Convert_Model_From_PyTorch.md
@@ -58,7 +58,7 @@ parameter to be set, for example:
 
 Sometimes ``convert_model`` will produce inputs of the model with dynamic rank or dynamic type. 
 Such model may not be supported by the hardware chosen for inference. To avoid this issue,
-use the ``input`` argument of ``convert_model``. For more information, refer to `Convert Models Represented as Python Objects <openvino_docs_MO_DG_Python_API>`. 
+use the ``input`` argument of ``convert_model``. For more information, refer to :doc:`Convert Models Represented as Python Objects <openvino_docs_MO_DG_Python_API>`. 
 
 .. important::
 
diff --git a/docs/documentation.md b/docs/documentation.md
index a25e784165b78f..276e4e6e0930a6 100644
--- a/docs/documentation.md
+++ b/docs/documentation.md
@@ -12,9 +12,9 @@
    :hidden:
 
    API Reference <api/api_reference>
-   OpenVINO IR format and Operation Sets <openvino_ir>  
+   OpenVINO IR format and Operation Sets <openvino_ir> 
+   Legacy Features <openvino_legacy_features> 
    Tool Ecosystem <openvino_ecosystem>
-   Legacy Features <openvino_legacy_features>
    OpenVINO Extensibility <openvino_docs_Extensibility_UG_Intro>
    Media Processing and CV Libraries <media_processing_cv_libraries>
    OpenVINO™ Security <openvino_docs_security_guide_introduction>
diff --git a/docs/home.rst b/docs/home.rst
index d8f359e65aaa5a..4ed32d3aea261b 100644
--- a/docs/home.rst
+++ b/docs/home.rst
@@ -24,10 +24,10 @@ OpenVINO 2023.0
          		<ul class="splide__list">
          			<li class="splide__slide">An open-source toolkit for optimizing and deploying deep learning models.<br>Boost your AI deep-learning inference performance!</li>
                   
-                  <li class="splide__slide"Better OpenVINO integration with PyTorch!<br>Use PyTorch models directly, without converting them first.
+                  <li class="splide__slide"Better OpenVINO integration with PyTorch!<br>Use PyTorch models directly, without converting them first.<br>
                      <a href="https://docs.openvino.ai/2023.1/openvino_docs_MO_DG_prepare_model_convert_model_Convert_Model_From_PyTorch.html">Learn more...</a>
                   </li>
-                  <li class="splide__slide">OpenVINO via PyTorch 2.0 torch.compile()<br>Use OpenVINO directly in PyTorch-native applications! 
+                  <li class="splide__slide">OpenVINO via PyTorch 2.0 torch.compile()<br>Use OpenVINO directly in PyTorch-native applications!<br>
                      <a href="https://docs.openvino.ai/2023.1/pytorch_2_0_torch_compile.html">Learn more...</a>
                   </li>
                   <li class="splide__slide">Do you like Generative AI? You will love how it performs with OpenVINO!<br>
diff --git a/docs/install_guides/installing-openvino-linux-header.md b/docs/install_guides/installing-openvino-linux-header.md
index f0bb87d87f0ade..a45b11d20e2f5e 100644
--- a/docs/install_guides/installing-openvino-linux-header.md
+++ b/docs/install_guides/installing-openvino-linux-header.md
@@ -22,14 +22,15 @@
    Use Docker <openvino_docs_install_guides_installing_openvino_docker>
 
 
-If you want to install OpenVINO™ Runtime on your Linux machine, these are your options: 
+If you want to install OpenVINO™ Runtime on Linux, you have the following options:
 
-* :doc:`Install OpenVINO Runtime using an Archive File <openvino_docs_install_guides_installing_openvino_from_archive_linux>`
+* :doc:`Install OpenVINO using an Archive File <openvino_docs_install_guides_installing_openvino_from_archive_linux>`
 * :doc:`Install OpenVINO using PyPI <openvino_docs_install_guides_installing_openvino_pip>`
-* :doc:`Install OpenVINO Runtime using APT <openvino_docs_install_guides_installing_openvino_apt>`
-* :doc:`Install OpenVINO Runtime using YUM <openvino_docs_install_guides_installing_openvino_yum>`
-* :doc:`Install OpenVINO Runtime using Conda Forge <openvino_docs_install_guides_installing_openvino_conda>`
-* :doc:`Install OpenVINO Runtime using Homebrew <openvino_docs_install_guides_installing_openvino_brew>`
+* :doc:`Install OpenVINO using APT <openvino_docs_install_guides_installing_openvino_apt>`
+* :doc:`Install OpenVINO using YUM <openvino_docs_install_guides_installing_openvino_yum>`
+* :doc:`Install OpenVINO using Conda Forge <openvino_docs_install_guides_installing_openvino_conda>`
+* :doc:`Install OpenVINO using vcpkg <openvino_docs_install_guides_installing_openvino_vcpkg>`
+* :doc:`Install OpenVINO using Homebrew <openvino_docs_install_guides_installing_openvino_brew>`
 * :doc:`Install OpenVINO using Docker <openvino_docs_install_guides_installing_openvino_docker>`
 
 
diff --git a/docs/install_guides/installing-openvino-macos-header.md b/docs/install_guides/installing-openvino-macos-header.md
index dff827ce9a89e8..2e0d70b61d04be 100644
--- a/docs/install_guides/installing-openvino-macos-header.md
+++ b/docs/install_guides/installing-openvino-macos-header.md
@@ -12,19 +12,21 @@
    :maxdepth: 3
    :hidden:
 
-   From Archive <openvino_docs_install_guides_installing_openvino_from_archive_macos>
-   Using Homebrew <openvino_docs_install_guides_installing_openvino_brew>
-   From PyPI <openvino_docs_install_guides_installing_openvino_pip>
-   Using Conda Forge <openvino_docs_install_guides_installing_openvino_conda>
+   Use Archive <openvino_docs_install_guides_installing_openvino_from_archive_macos>
+   Use Homebrew <openvino_docs_install_guides_installing_openvino_brew>
+   Use PyPI <openvino_docs_install_guides_installing_openvino_pip>
+   Use Conda Forge <openvino_docs_install_guides_installing_openvino_conda>
    Use vcpkg <openvino_docs_install_guides_installing_openvino_vcpkg>
 
 
-If you want to install OpenVINO™ Runtime on macOS, there are a few ways to accomplish this. We prepared following options for you:
+If you want to install OpenVINO™ Runtime on macOS, you have the following options:
 
-* :doc:`Install OpenVINO Runtime from an Archive File <openvino_docs_install_guides_installing_openvino_from_archive_macos>`
-* :doc:`Install OpenVINO from PyPI <openvino_docs_install_guides_installing_openvino_pip>`
-* :doc:`Install OpenVINO Runtime using Conda Forge <openvino_docs_install_guides_installing_openvino_conda>`
-* :doc:`Install OpenVINO Runtime via Homebrew <openvino_docs_install_guides_installing_openvino_brew>`
+
+* :doc:`Install OpenVINO using an Archive File <openvino_docs_install_guides_installing_openvino_from_archive_macos>`
+* :doc:`Install OpenVINO using PyPI <openvino_docs_install_guides_installing_openvino_pip>`
+* :doc:`Install OpenVINO using Conda Forge <openvino_docs_install_guides_installing_openvino_conda>`
+* :doc:`Install OpenVINO using Homebrew <openvino_docs_install_guides_installing_openvino_brew>`
+* :doc:`Install OpenVINO using vcpkg <openvino_docs_install_guides_installing_openvino_vcpkg>`
 
 
 
diff --git a/docs/install_guides/installing-openvino-windows-header.md b/docs/install_guides/installing-openvino-windows-header.md
index 3044c2accef729..65b1803ec711ff 100644
--- a/docs/install_guides/installing-openvino-windows-header.md
+++ b/docs/install_guides/installing-openvino-windows-header.md
@@ -22,9 +22,10 @@
 
 If you want to install OpenVINO™ Runtime on Windows, you have the following options:
 
-* :doc:`Install OpenVINO Runtime from an Archive File <openvino_docs_install_guides_installing_openvino_from_archive_windows>`
-* :doc:`Install OpenVINO Runtime using PyPI <openvino_docs_install_guides_installing_openvino_pip>`
-* :doc:`Install OpenVINO Runtime using Conda Forge <openvino_docs_install_guides_installing_openvino_conda>`
+* :doc:`Install OpenVINO using an Archive File <openvino_docs_install_guides_installing_openvino_from_archive_windows>`
+* :doc:`Install OpenVINO using PyPI <openvino_docs_install_guides_installing_openvino_pip>`
+* :doc:`Install OpenVINO using Conda Forge <openvino_docs_install_guides_installing_openvino_conda>`
+* :doc:`Install OpenVINO using vcpkg <openvino_docs_install_guides_installing_openvino_vcpkg>`
 * :doc:`Install OpenVINO using Docker <openvino_docs_install_guides_installing_openvino_docker>`
 
 

From c10b45fe9e1b22a42436c73a7ed64929f0f504ac Mon Sep 17 00:00:00 2001
From: Maxim Vafin <maxim.vafin@intel.com>
Date: Mon, 18 Sep 2023 17:04:39 +0200
Subject: [PATCH 03/46] [PT FE] Fix issue with http error when using torch.hub
 (#19901)

* [PT FE] Fix issue with http error when using torch.hub

* Mark failing models as xfail

* Remove incorrect model names
---
 .../models_hub_common/test_convert_model.py   |  2 +-
 .../models_hub_common/utils.py                |  2 +-
 .../torch_tests/test_torchvision_models.py    | 21 ++--
 .../torch_tests/torchvision_models            | 97 +++++++++++++++++++
 4 files changed, 112 insertions(+), 10 deletions(-)
 create mode 100644 tests/model_hub_tests/torch_tests/torchvision_models

diff --git a/tests/model_hub_tests/models_hub_common/test_convert_model.py b/tests/model_hub_tests/models_hub_common/test_convert_model.py
index 145da6b61761f7..d35061595fc0cb 100644
--- a/tests/model_hub_tests/models_hub_common/test_convert_model.py
+++ b/tests/model_hub_tests/models_hub_common/test_convert_model.py
@@ -99,7 +99,7 @@ def _run(self, model_name, model_link, ie_device):
         fw_outputs = self.infer_fw_model(fw_model, inputs)
         print("Infer ov::Model")
         ov_outputs = self.infer_ov_model(ov_model, inputs, ie_device)
-        print("Compare TensorFlow and OpenVINO results")
+        print("Compare framework and OpenVINO results")
         self.compare_results(fw_outputs, ov_outputs)
 
     def run(self, model_name, model_link, ie_device):
diff --git a/tests/model_hub_tests/models_hub_common/utils.py b/tests/model_hub_tests/models_hub_common/utils.py
index b5699a80e62b43..076cd8e2f1e4c0 100644
--- a/tests/model_hub_tests/models_hub_common/utils.py
+++ b/tests/model_hub_tests/models_hub_common/utils.py
@@ -22,7 +22,7 @@ def get_models_list(file_name: str):
                 model_name, model_link = model_info.split(',')
             elif len(model_info.split(',')) == 4:
                 model_name, model_link, mark, reason = model_info.split(',')
-                assert mark == "skip", "Incorrect failure mark for model info {}".format(model_info)
+                assert mark in ["skip", "xfail"], "Incorrect failure mark for model info {}".format(model_info)
             models.append((model_name, model_link, mark, reason))
 
     return models
diff --git a/tests/model_hub_tests/torch_tests/test_torchvision_models.py b/tests/model_hub_tests/torch_tests/test_torchvision_models.py
index a77af0ec07549e..a7722389e4132d 100644
--- a/tests/model_hub_tests/torch_tests/test_torchvision_models.py
+++ b/tests/model_hub_tests/torch_tests/test_torchvision_models.py
@@ -1,16 +1,18 @@
 # Copyright (C) 2018-2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+import os
 import pytest
 import torch
 import tempfile
 import torchvision.transforms.functional as F
-from models_hub_common.test_convert_model import TestConvertModel
 from openvino import convert_model
+from models_hub_common.test_convert_model import TestConvertModel
+from models_hub_common.utils import get_models_list
 
 
 def get_all_models() -> list:
-    m_list = torch.hub.list("pytorch/vision")
+    m_list = torch.hub.list("pytorch/vision", skip_validation=True)
     m_list.remove("get_model_weights")
     m_list.remove("get_weight")
     return m_list
@@ -36,7 +38,8 @@ def get_video():
 
 
 def prepare_frames_for_raft(name, frames1, frames2):
-    w = torch.hub.load("pytorch/vision", "get_model_weights", name=name).DEFAULT
+    w = torch.hub.load("pytorch/vision", "get_model_weights",
+                       name=name, skip_validation=True).DEFAULT
     img1_batch = torch.stack(frames1)
     img2_batch = torch.stack(frames2)
     img1_batch = F.resize(img1_batch, size=[520, 960], antialias=False)
@@ -50,13 +53,14 @@ def prepare_frames_for_raft(name, frames1, frames2):
 
 
 class TestTorchHubConvertModel(TestConvertModel):
-    def setup_method(self):
+    def setup_class(self):
         self.cache_dir = tempfile.TemporaryDirectory()
         # set temp dir for torch cache
         torch.hub.set_dir(str(self.cache_dir.name))
 
     def load_model(self, model_name, model_link):
-        m = torch.hub.load("pytorch/vision", model_name, weights='DEFAULT')
+        m = torch.hub.load("pytorch/vision", model_name,
+                           weights='DEFAULT', skip_validation=True)
         m.eval()
         if model_name == "s3d" or any([m in model_name for m in ["swin3d", "r3d_18", "mc3_18", "r2plus1d_18"]]):
             self.example = (torch.randn([1, 3, 224, 224, 224]),)
@@ -109,7 +113,8 @@ def teardown_method(self):
     def test_convert_model_precommit(self, model_name, ie_device):
         self.run(model_name, None, ie_device)
 
-    @pytest.mark.parametrize("model_name", get_all_models())
+    @pytest.mark.parametrize("name",
+                             [pytest.param(n, marks=pytest.mark.xfail) if m == "xfail" else n for n, _, m, r in get_models_list(os.path.join(os.path.dirname(__file__), "torchvision_models"))])
     @pytest.mark.nightly
-    def test_convert_model_all_models(self, model_name, ie_device):
-        self.run(model_name, None, ie_device)
+    def test_convert_model_all_models(self, name, ie_device):
+        self.run(name, None, ie_device)
diff --git a/tests/model_hub_tests/torch_tests/torchvision_models b/tests/model_hub_tests/torch_tests/torchvision_models
new file mode 100644
index 00000000000000..a13a0f606c6708
--- /dev/null
+++ b/tests/model_hub_tests/torch_tests/torchvision_models
@@ -0,0 +1,97 @@
+alexnet,none
+convnext_base,none
+convnext_large,none
+convnext_small,none
+convnext_tiny,none
+deeplabv3_mobilenet_v3_large,none
+deeplabv3_resnet101,none
+deeplabv3_resnet50,none
+densenet121,none
+densenet161,none
+densenet169,none
+densenet201,none
+efficientnet_b0,none
+efficientnet_b1,none
+efficientnet_b2,none
+efficientnet_b3,none
+efficientnet_b4,none
+efficientnet_b5,none
+efficientnet_b6,none
+efficientnet_b7,none
+efficientnet_v2_l,none
+efficientnet_v2_m,none
+efficientnet_v2_s,none
+fcn_resnet101,none
+fcn_resnet50,none
+googlenet,none
+inception_v3,none
+lraspp_mobilenet_v3_large,none
+maxvit_t,none
+mc3_18,none
+mnasnet0_5,none
+mnasnet0_75,none
+mnasnet1_0,none
+mnasnet1_3,none
+mobilenet_v2,none
+mobilenet_v3_large,none
+mobilenet_v3_small,none
+mvit_v1_b,none
+mvit_v2_s,none
+r2plus1d_18,none
+r3d_18,none
+raft_large,none
+raft_small,none
+regnet_x_16gf,none
+regnet_x_1_6gf,none
+regnet_x_32gf,none
+regnet_x_3_2gf,none
+regnet_x_400mf,none
+regnet_x_800mf,none
+regnet_x_8gf,none
+regnet_y_128gf,none
+regnet_y_16gf,none
+regnet_y_1_6gf,none
+regnet_y_32gf,none
+regnet_y_3_2gf,none
+regnet_y_400mf,none
+regnet_y_800mf,none
+regnet_y_8gf,none
+resnet101,none
+resnet152,none
+resnet18,none
+resnet34,none
+resnet50,none
+resnext101_32x8d,none
+resnext101_64x4d,none
+resnext50_32x4d,none
+s3d,none
+shufflenet_v2_x0_5,none
+shufflenet_v2_x1_0,none
+shufflenet_v2_x1_5,none
+shufflenet_v2_x2_0,none
+squeezenet1_0,none
+squeezenet1_1,none
+swin3d_b,none
+swin3d_s,none
+swin3d_t,none
+swin_b,none
+swin_s,none
+swin_t,none
+swin_v2_b,none
+swin_v2_s,none
+swin_v2_t,none
+vgg11,none
+vgg11_bn,none
+vgg13,none
+vgg13_bn,none
+vgg16,none
+vgg16_bn,none
+vgg19,none
+vgg19_bn,none
+vit_b_16,none,xfail,Tracing fails
+vit_b_32,none,xfail,Tracing fails
+vit_h_14,none,xfail,Tracing fails
+vit_l_16,none,xfail,Tracing fails
+vit_l_32,none,xfail,Tracing fails
+wide_resnet101_2,none
+wide_resnet50_2,none

From 10dc2d8b9ba8e6a311532906161fd710f8fef991 Mon Sep 17 00:00:00 2001
From: Mikhail Ryzhov <mikhail.ryzhov@intel.com>
Date: Mon, 18 Sep 2023 17:29:01 +0200
Subject: [PATCH 04/46] [GHA] Improvement of test execution time cache (#19881)

* renamed cache

* disabled PR cache

* corrected save condition

* removed id

* fixed path in save cache action

* corrected if condition
---
 .github/workflows/linux.yml | 18 +++++++++++++-----
 1 file changed, 13 insertions(+), 5 deletions(-)

diff --git a/.github/workflows/linux.yml b/.github/workflows/linux.yml
index 486cc879ec02d0..d7cba0bc390e59 100644
--- a/.github/workflows/linux.yml
+++ b/.github/workflows/linux.yml
@@ -585,7 +585,7 @@ jobs:
             --ignore=${{ env.INSTALL_TEST_DIR }}/pyopenvino/tests/test_utils/test_utils.py \
             --ignore=${{ env.INSTALL_TEST_DIR }}/pyopenvino/tests/test_onnx/test_zoo_models.py \
             --ignore=${{ env.INSTALL_TEST_DIR }}/pyopenvino/tests/test_onnx/test_backend.py
-      
+
       - name: Python API snippets
         run: |
           source ${{ env.INSTALL_DIR }}/setupvars.sh
@@ -774,12 +774,13 @@ jobs:
           python3 -m pip install --upgrade pip
           python3 -m pip install -r ${{ env.INSTALL_TEST_DIR }}/functional_test_utils/requirements.txt
 
-      - name: Cache Tests Execution Time
-        id: tests-functional-cpu-cache
-        uses: actions/cache@v3
+      - name: Restore tests execution time
+        uses: actions/cache/restore@v3
         with:
           path: ${{ env.PARALLEL_TEST_CACHE }}
-          key: ${{ runner.os }}-tests-functional-cpu-cache
+          key: ${{ runner.os }}-tests-functional-cpu-stamp-${{ github.sha }}
+          restore-keys: |
+            ${{ runner.os }}-tests-functional-cpu-stamp
 
       - name: Intel CPU plugin func tests (parallel)
         run: |
@@ -787,6 +788,13 @@ jobs:
           python3 ${{ env.PARALLEL_TEST_SCRIPT }} -e ${{ env.INSTALL_TEST_DIR }}/ov_cpu_func_tests -c ${{ env.PARALLEL_TEST_CACHE }} -w ${{ env.INSTALL_TEST_DIR }} -s suite -rf 0 -- --gtest_print_time=1 --gtest_filter=*smoke*
         timeout-minutes: 25
 
+      - name: Save tests execution time
+        uses: actions/cache/save@v3
+        if: github.ref_name == 'master'
+        with:
+          path: ${{ env.PARALLEL_TEST_CACHE }}
+          key: ${{ runner.os }}-tests-functional-cpu-stamp-${{ github.sha }}
+
       - name: Upload Test Results
         uses: actions/upload-artifact@v3
         if: ${{ always() }}

From 54609e7b72d9faa5a38fe7ac15c84aae77fbbc82 Mon Sep 17 00:00:00 2001
From: Ilya Lavrenov <ilya.lavrenov@intel.com>
Date: Tue, 19 Sep 2023 00:07:59 +0400
Subject: [PATCH 05/46] Removed FixRtInfo pass (#16870)

* Removed FixRtInfo pass

* Removed FixRtInfo pass

* Fixed macOS compilation
---
 CMakeLists.txt                                |  2 -
 .../docs/develop_cc_for_new_component.md      |  1 -
 src/common/snippets/src/pass/hash.cpp         |  2 +-
 .../include/transformations/fix_rt_info.hpp   | 38 -----------------
 .../src/transformations/fix_rt_info.cpp       | 42 -------------------
 .../src/transformations/init_node_info.cpp    |  5 +--
 src/core/CMakeLists.txt                       |  1 -
 src/core/src/pass/serialize.cpp               |  2 +-
 src/core/tests/CMakeLists.txt                 |  2 -
 src/inference/src/cnn_network_ngraph_impl.cpp |  8 ----
 src/inference/src/compilation_context.cpp     |  2 -
 .../tests/unit/compilation_context_test.cpp   |  3 +-
 .../functional/test_utils/cpu_test_utils.cpp  |  7 ++--
 .../functional/test_utils/cpu_test_utils.hpp  |  3 +-
 .../template/tests/functional/CMakeLists.txt  |  4 +-
 .../src/summary/op_summary.cpp                |  2 +-
 16 files changed, 13 insertions(+), 111 deletions(-)
 delete mode 100644 src/common/transformations/include/transformations/fix_rt_info.hpp
 delete mode 100644 src/common/transformations/src/transformations/fix_rt_info.cpp

diff --git a/CMakeLists.txt b/CMakeLists.txt
index 0b552b3da3406c..e9d4760eb86916 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -106,8 +106,6 @@ function(openvino_developer_export_targets)
         if(TARGET "${target_name}")
             get_target_property(original_name ${target_name} ALIASED_TARGET)
             if(TARGET "${original_name}")
-                message(STATUS "The name ${target_name} is an ALIAS for ${original_name}. "
-                        "It will be exported to the OpenVINODeveloperPackage with the original name.")
                 list(REMOVE_ITEM ${EXPORT_COMPONENT} ${target_name})
                 list(APPEND ${EXPORT_COMPONENT} ${original_name})
             endif()
diff --git a/src/common/conditional_compilation/docs/develop_cc_for_new_component.md b/src/common/conditional_compilation/docs/develop_cc_for_new_component.md
index 4166a907434b13..32c10478dc6310 100644
--- a/src/common/conditional_compilation/docs/develop_cc_for_new_component.md
+++ b/src/common/conditional_compilation/docs/develop_cc_for_new_component.md
@@ -69,7 +69,6 @@ It checks whether the code region in this module is active or inactive by the ma
 
 There is an example of `conditional_compilation_gen.h`:
 ```
-#define ov_pass_FixRtInfo_run_on_function 1
 #define ov_pass_GraphRewrite_run_on_model 1
 #define ov_pass_InitNodeInfo_run_on_function 1
 #define ov_pass_ConstantFolding_run_on_model 1
diff --git a/src/common/snippets/src/pass/hash.cpp b/src/common/snippets/src/pass/hash.cpp
index 8d509b568867fc..48dd9586ae4337 100644
--- a/src/common/snippets/src/pass/hash.cpp
+++ b/src/common/snippets/src/pass/hash.cpp
@@ -62,7 +62,7 @@ static uint64_t hash_combine(uint64_t seed, const T &v) {
 namespace rt_info {
 
 // some node attr is not type of ov::RuntimeAttribute, need dedicate visitor.
-const std::vector<std::string> list_of_names{
+static const std::vector<std::string> list_of_names{
     "PrimitivesPriority",
     "alt_width",
 };
diff --git a/src/common/transformations/include/transformations/fix_rt_info.hpp b/src/common/transformations/include/transformations/fix_rt_info.hpp
deleted file mode 100644
index a9c33645633074..00000000000000
--- a/src/common/transformations/include/transformations/fix_rt_info.hpp
+++ /dev/null
@@ -1,38 +0,0 @@
-// Copyright (C) 2018-2023 Intel Corporation
-// SPDX-License-Identifier: Apache-2.0
-//
-
-#pragma once
-
-/**
- * @brief Defines initialize node runtime information pass
- * @file init_node_info.hpp
- */
-
-#include <memory>
-#include <vector>
-
-#include "openvino/pass/graph_rewrite.hpp"
-#include "transformations_visibility.hpp"
-
-namespace ov {
-namespace pass {
-
-class TRANSFORMATIONS_API FixRtInfo;
-
-}  // namespace pass
-}  // namespace ov
-
-/**
- * @ingroup ie_transformation_common_api
- * @brief FixRtInfo transformation helps to fix info attributes in a single place.
- *        User can pass runtime attribute using various types.
- *        This Pass should generalize them runtime info representation.
- *
- * Used to extract runtime attributes from shared pointer to `ov::RuntimeAttributeWrapper` to standard or trivial types
- */
-class ov::pass::FixRtInfo : public ov::pass::ModelPass {
-public:
-    OPENVINO_RTTI("FixRtInfo", "0");
-    bool run_on_model(const std::shared_ptr<ov::Model>& m) override;
-};
diff --git a/src/common/transformations/src/transformations/fix_rt_info.cpp b/src/common/transformations/src/transformations/fix_rt_info.cpp
deleted file mode 100644
index b70176ca7aecd1..00000000000000
--- a/src/common/transformations/src/transformations/fix_rt_info.cpp
+++ /dev/null
@@ -1,42 +0,0 @@
-// Copyright (C) 2018-2023 Intel Corporation
-// SPDX-License-Identifier: Apache-2.0
-//
-
-#include "transformations/fix_rt_info.hpp"
-
-#include <memory>
-#include <vector>
-
-#include "itt.hpp"
-#include "openvino/core/rt_info.hpp"
-#include "openvino/opsets/opset1.hpp"
-#include "transformations/rt_info/primitives_priority_attribute.hpp"
-
-bool ov::pass::FixRtInfo::run_on_model(const std::shared_ptr<ov::Model>& f) {
-    RUN_ON_FUNCTION_SCOPE(FixRtInfo);
-
-    for (auto& node : f->get_ops()) {
-        // Recursively apply transformation for sub-graph based operations
-        if (auto sub_graph_node = std::dynamic_pointer_cast<op::util::SubGraphOp>(node)) {
-            if (auto sub_graph = sub_graph_node->get_function()) {
-                run_on_model(sub_graph);
-            }
-        }
-        auto& rt_info = node->get_rt_info();
-        {
-            auto it_info = rt_info.find("PrimitivesPriority");
-            if (it_info != rt_info.end()) {
-                if (it_info->second.is<ov::PrimitivesPriority>()) {
-                    rt_info.emplace(ov::PrimitivesPriority::get_type_info_static(),
-                                    it_info->second.as<ov::PrimitivesPriority>());
-                }
-                if (it_info->second.is<std::string>()) {
-                    rt_info.emplace(ov::PrimitivesPriority::get_type_info_static(),
-                                    ov::PrimitivesPriority{it_info->second.as<std::string>()});
-                }
-                rt_info.erase(it_info);
-            }
-        }
-    }
-    return false;
-}
diff --git a/src/common/transformations/src/transformations/init_node_info.cpp b/src/common/transformations/src/transformations/init_node_info.cpp
index 93c958d14f661b..efc2627199c723 100644
--- a/src/common/transformations/src/transformations/init_node_info.cpp
+++ b/src/common/transformations/src/transformations/init_node_info.cpp
@@ -8,9 +8,7 @@
 #include <vector>
 
 #include "itt.hpp"
-#include "openvino/core/rt_info.hpp"
-#include "openvino/opsets/opset1.hpp"
-#include "transformations/fix_rt_info.hpp"
+#include "openvino/op/util/sub_graph_base.hpp"
 #include "transformations/rt_info/fused_names_attribute.hpp"
 #include "transformations/rt_info/primitives_priority_attribute.hpp"
 
@@ -27,6 +25,5 @@ bool ov::pass::InitNodeInfo::run_on_model(const std::shared_ptr<ov::Model>& f) {
         auto& rtInfo = node->get_rt_info();
         rtInfo.emplace(FusedNames::get_type_info_static(), FusedNames{node->get_friendly_name()});
     }
-    FixRtInfo{}.run_on_model(f);
     return false;
 }
diff --git a/src/core/CMakeLists.txt b/src/core/CMakeLists.txt
index 4d8545a5a21802..03580613532e7b 100644
--- a/src/core/CMakeLists.txt
+++ b/src/core/CMakeLists.txt
@@ -122,7 +122,6 @@ file(GLOB_RECURSE smart_reshape_srcs ${CMAKE_CURRENT_SOURCE_DIR}/src/pass/smart_
 file(GLOB_RECURSE rt_info_srcs ${CMAKE_CURRENT_SOURCE_DIR}/src/pass/rt_info/*.cpp)
 set_source_files_properties("${CMAKE_CURRENT_SOURCE_DIR}/src/pass/convert_precision.cpp"
                             "${CMAKE_CURRENT_SOURCE_DIR}/src/pass/convert_fp32_to_fp16.cpp"
-                            "${CMAKE_CURRENT_SOURCE_DIR}/src/pass/fix_rt_info.cpp"
                             "${CMAKE_CURRENT_SOURCE_DIR}/src/pass/init_node_info.cpp"
                             "${CMAKE_CURRENT_SOURCE_DIR}/src/pass/serialize.cpp"
                             "${CMAKE_CURRENT_SOURCE_DIR}/src/op/type_relaxed.cpp"
diff --git a/src/core/src/pass/serialize.cpp b/src/core/src/pass/serialize.cpp
index de2fcd8c46b8fe..70b91b7e97bf81 100644
--- a/src/core/src/pass/serialize.cpp
+++ b/src/core/src/pass/serialize.cpp
@@ -197,7 +197,7 @@ void ngfunction_2_ir(pugi::xml_node& node,
                      bool deterministic);
 
 namespace rt_info {
-const std::vector<std::string> list_of_names{
+static const std::vector<std::string> list_of_names{
     "PrimitivesPriority",
     "alt_width",
 };
diff --git a/src/core/tests/CMakeLists.txt b/src/core/tests/CMakeLists.txt
index e42513bd939ebb..b5298b9e5eea3c 100644
--- a/src/core/tests/CMakeLists.txt
+++ b/src/core/tests/CMakeLists.txt
@@ -11,8 +11,6 @@ ov_try_use_gold_linker()
 
 add_definitions(-DSERIALIZED_ZOO=\"${TEST_MODEL_ZOO}/core/models\")
 
-message(STATUS "OpenVINO Core unit tests enabled")
-
 # For type relaxed types
 set_source_files_properties(${CMAKE_CURRENT_SOURCE_DIR}/threading.cpp
         PROPERTIES INCLUDE_DIRECTORIES $<TARGET_PROPERTY:inference_engine_transformations,INTERFACE_INCLUDE_DIRECTORIES>)
diff --git a/src/inference/src/cnn_network_ngraph_impl.cpp b/src/inference/src/cnn_network_ngraph_impl.cpp
index cb26e63e7c2626..74f80f39e2f641 100644
--- a/src/inference/src/cnn_network_ngraph_impl.cpp
+++ b/src/inference/src/cnn_network_ngraph_impl.cpp
@@ -29,7 +29,6 @@
 #include "transformations/common_optimizations/nop_elimination.hpp"
 #include "transformations/common_optimizations/remove_concat_zero_dim_input.hpp"
 #include "transformations/common_optimizations/remove_multi_subgraph_op_dangling_params.hpp"
-#include "transformations/fix_rt_info.hpp"
 #include "transformations/smart_reshape/set_batch_size.hpp"
 #include "transformations/smart_reshape/smart_reshape.hpp"
 #include "transformations/utils/utils.hpp"
@@ -136,7 +135,6 @@ CNNNetworkNGraphImpl::CNNNetworkNGraphImpl(const std::shared_ptr<Function>& nGra
     {
         ov::pass::Manager m;
         using namespace ov::pass;
-        REGISTER_PASS(m, FixRtInfo)
         REGISTER_PASS(m, EliminateScatterUpdate)
         REGISTER_PASS(m, RemoveConcatZeroDimInput)
         REGISTER_PASS(m, RemoveMultiSubGraphOpDanglingParamsResults)
@@ -199,12 +197,6 @@ CNNNetworkNGraphImpl::CNNNetworkNGraphImpl(const CNNNetwork& network) {
     }
 
     _ngraph_function = ngraph::clone_function(*network.getFunction());
-    {
-        ov::pass::Manager m;
-        using namespace ov::pass;
-        REGISTER_PASS(m, FixRtInfo)
-        m.run_passes(_ngraph_function);
-    }
     validateFunctionNames();
     InputsDataMap inputs = network.getInputsInfo();
     OutputsDataMap outputs = network.getOutputsInfo();
diff --git a/src/inference/src/compilation_context.cpp b/src/inference/src/compilation_context.cpp
index e4a373f1c0223b..7c0b9cfba869c6 100644
--- a/src/inference/src/compilation_context.cpp
+++ b/src/inference/src/compilation_context.cpp
@@ -18,7 +18,6 @@
 #include "itt.hpp"
 #include "ngraph/opsets/opset6.hpp"
 #include "openvino/pass/manager.hpp"
-#include "transformations/fix_rt_info.hpp"
 #include "transformations/hash.hpp"
 #include "transformations/rt_info/fused_names_attribute.hpp"
 #include "transformations/rt_info/primitives_priority_attribute.hpp"
@@ -86,7 +85,6 @@ std::string ModelCache::compute_hash(const std::shared_ptr<const ov::Model>& mod
     uint64_t seed = 0;
     // 1. Calculate hash on function
     ov::pass::Manager m;
-    m.register_pass<ov::pass::FixRtInfo>();
     m.register_pass<ov::pass::Hash>(seed);
     m.run_passes(std::const_pointer_cast<ov::Model>(model));
 
diff --git a/src/inference/tests/unit/compilation_context_test.cpp b/src/inference/tests/unit/compilation_context_test.cpp
index 1f3d5266729c61..2070f2302e29ef 100644
--- a/src/inference/tests/unit/compilation_context_test.cpp
+++ b/src/inference/tests/unit/compilation_context_test.cpp
@@ -189,8 +189,7 @@ TEST(NetworkContext, HashWithPrimitivesPriority) {
     op3["PrimitivesPriority"] = "testPriority";
 
     ASSERT_NE(ModelCache::compute_hash(net1, {}), ModelCache::compute_hash(net2, {}));
-
-    ASSERT_EQ(ModelCache::compute_hash(net2, {}), ModelCache::compute_hash(net3, {}));
+    ASSERT_NE(ModelCache::compute_hash(net2, {}), ModelCache::compute_hash(net3, {}));
 }
 
 TEST(NetworkContext, HashWithFusedNames) {
diff --git a/src/plugins/intel_cpu/tests/functional/test_utils/cpu_test_utils.cpp b/src/plugins/intel_cpu/tests/functional/test_utils/cpu_test_utils.cpp
index e76d6caf9bdd33..e355ee79b75bcc 100644
--- a/src/plugins/intel_cpu/tests/functional/test_utils/cpu_test_utils.cpp
+++ b/src/plugins/intel_cpu/tests/functional/test_utils/cpu_test_utils.cpp
@@ -6,6 +6,7 @@
 #include "ie_ngraph_utils.hpp"
 #include "openvino/core/type/element_type.hpp"
 #include "utils/rt_info/memory_formats_attribute.hpp"
+#include "transformations/rt_info/primitives_priority_attribute.hpp"
 #include "utils/general_utils.h"
 #include <cstdint>
 
@@ -101,7 +102,7 @@ std::string CPUTestsBase::fmts2str(const std::vector<cpu_memory_format_t> &fmts,
     return str;
 }
 
-std::string CPUTestsBase::impls2str(const std::vector<std::string> &priority) {
+ov::PrimitivesPriority CPUTestsBase::impls2primProiority(const std::vector<std::string> &priority) {
     std::string str;
     for (auto &impl : priority) {
         ((str += "cpu:") += impl) += ",";
@@ -109,7 +110,7 @@ std::string CPUTestsBase::impls2str(const std::vector<std::string> &priority) {
     if (!str.empty()) {
         str.pop_back();
     }
-    return str;
+    return ov::PrimitivesPriority(str);
 }
 
 void CPUTestsBase::CheckPluginRelatedResults(InferenceEngine::ExecutableNetwork &execNet, const std::set<std::string>& nodeType) const {
@@ -321,7 +322,7 @@ CPUTestsBase::makeCPUInfo(const std::vector<cpu_memory_format_t>& inFmts,
                         ov::intel_cpu::OutputMemoryFormats(fmts2str(outFmts, "cpu:"))});
     }
     if (!priority.empty()) {
-        cpuInfo.insert({"PrimitivesPriority", impls2str(priority)});
+        cpuInfo.emplace(ov::PrimitivesPriority::get_type_info_static(), impls2primProiority(priority));
     }
 
     cpuInfo.insert({"enforceBF16evenForGraphTail", true});
diff --git a/src/plugins/intel_cpu/tests/functional/test_utils/cpu_test_utils.hpp b/src/plugins/intel_cpu/tests/functional/test_utils/cpu_test_utils.hpp
index b1e77e48fe70d4..d8deddfebe5d69 100644
--- a/src/plugins/intel_cpu/tests/functional/test_utils/cpu_test_utils.hpp
+++ b/src/plugins/intel_cpu/tests/functional/test_utils/cpu_test_utils.hpp
@@ -7,6 +7,7 @@
 #include <string>
 #include "ie_system_conf.h"
 #include "shared_test_classes/base/layer_test_utils.hpp"
+#include "transformations/rt_info/primitives_priority_attribute.hpp"
 #include <exec_graph_info.hpp>
 #include <openvino/runtime/compiled_model.hpp>
 #include "ie_system_conf.h"
@@ -122,7 +123,7 @@ class CPUTestsBase {
     static const char *cpu_fmt2str(cpu_memory_format_t v);
     static cpu_memory_format_t cpu_str2fmt(const char *str);
     static std::string fmts2str(const std::vector<cpu_memory_format_t> &fmts, const std::string &prefix);
-    static std::string impls2str(const std::vector<std::string> &priority);
+    static ov::PrimitivesPriority impls2primProiority(const std::vector<std::string> &priority);
     static CPUInfo makeCPUInfo(const std::vector<cpu_memory_format_t>& inFmts,
                                const std::vector<cpu_memory_format_t>& outFmts,
                                const std::vector<std::string>& priority);
diff --git a/src/plugins/template/tests/functional/CMakeLists.txt b/src/plugins/template/tests/functional/CMakeLists.txt
index a4ba476c4c2200..983ee2534a497c 100644
--- a/src/plugins/template/tests/functional/CMakeLists.txt
+++ b/src/plugins/template/tests/functional/CMakeLists.txt
@@ -28,11 +28,11 @@ ov_add_test_target(
 find_package(OpenCV QUIET COMPONENTS core imgproc)
 
 if(OpenCV_FOUND AND OpenCV_VERSION VERSION_GREATER_EQUAL 3.4)
-    message("-- Reference preprocessing: OpenCV tests are enabled")
+    message(STATUS "Reference preprocessing: OpenCV tests are enabled")
     target_compile_definitions(${TARGET_NAME} PRIVATE OPENCV_TEMPLATE_TESTS)
     target_link_libraries(${TARGET_NAME} PRIVATE opencv_imgproc opencv_core)
 else()
-    message("-- Reference preprocessing: OpenCV tests are disabled, because OpenCV ver. 3.4+ is not found")
+    message(WARNING "Reference preprocessing: OpenCV tests are disabled, because OpenCV ver. 3.4+ is not found")
 endif()
 
 if (ENABLE_INTEL_CPU)
diff --git a/src/tests/test_utils/functional_test_utils/src/summary/op_summary.cpp b/src/tests/test_utils/functional_test_utils/src/summary/op_summary.cpp
index 626cce43c2048d..08a0d9c0a2486e 100644
--- a/src/tests/test_utils/functional_test_utils/src/summary/op_summary.cpp
+++ b/src/tests/test_utils/functional_test_utils/src/summary/op_summary.cpp
@@ -140,7 +140,7 @@ void OpSummary::updateOPsStats(const std::shared_ptr<ov::Model>& model, const Pa
         return;
     }
     bool isFunctionalGraph = false;
-    for (const auto &op : model->get_ordered_ops()) {
+    for (const auto& op : model->get_ordered_ops()) {
         if (!std::dynamic_pointer_cast<ov::op::v0::Parameter>(op) &&
             !std::dynamic_pointer_cast<ov::op::v0::Constant>(op) &&
             !std::dynamic_pointer_cast<ov::op::v0::Result>(op)) {

From c7850276ddc55784b5a785cef687289508c07d0c Mon Sep 17 00:00:00 2001
From: Ilya Lavrenov <ilya.lavrenov@intel.com>
Date: Tue, 19 Sep 2023 00:11:05 +0400
Subject: [PATCH 06/46] Check only build requirements for Python API (#19919)

---
 src/bindings/python/CMakeLists.txt | 31 +++++++++++-------------------
 1 file changed, 11 insertions(+), 20 deletions(-)

diff --git a/src/bindings/python/CMakeLists.txt b/src/bindings/python/CMakeLists.txt
index 4c4c9bce4d7804..24089b38531c27 100644
--- a/src/bindings/python/CMakeLists.txt
+++ b/src/bindings/python/CMakeLists.txt
@@ -20,8 +20,7 @@ endif()
 # Check python requirements
 #
 
-set(ov_python_req "${OpenVINOPython_SOURCE_DIR}/requirements.txt")
-set(ie_python_req "${OpenVINOPython_SOURCE_DIR}/src/compatibility/openvino/requirements-dev.txt")
+set(ie_build_python_req "${OpenVINOPython_SOURCE_DIR}/src/compatibility/openvino/requirements-dev.txt")
 
 function(ov_check_python_build_conditions)
     # user explicitly specified ENABLE_PYTHON=ON
@@ -81,31 +80,23 @@ function(ov_check_python_build_conditions)
         message(${message_mode} "Python 3.x interpreter is not found. OpenVINO Python API will be turned off (ENABLE_PYTHON is OFF)")
     endif()
 
-    # check pyopenvino requirements to OV 2.0 API
-    ov_check_pip_packages(REQUIREMENTS_FILE ${ov_python_req}
-                          RESULT_VAR ov_python_req_FOUND
-                          WARNING_MESSAGE "install python3 -m pip install -r ${ov_python_req} for OV API 2.0 requirements"
-                          MESSAGE_MODE TRACE)
-    # ov_python_req are not mandatory for build
-    set(ov_python_req_FOUND ON)
-
     # check for Cython requirement for build IE API 1.0
-    ov_check_pip_packages(REQUIREMENTS_FILE ${ie_python_req}
-                          RESULT_VAR ie_python_req_FOUND
-                          WARNING_MESSAGE "install python3 -m pip install -r ${ie_python_req} for IE API 1.0 requirements"
+    ov_check_pip_packages(REQUIREMENTS_FILE ${ie_build_python_req}
+                          RESULT_VAR ie_build_python_req_FOUND
+                          WARNING_MESSAGE "install python3 -m pip install -r ${ie_build_python_req} for IE API 1.0 requirements"
                           MESSAGE_MODE TRACE)
 
     # cython can be installed as a debian package, so pip requirements can be unsatisfied
     # so, let's check to find cython anyway
-    if(NOT ie_python_req_FOUND)
+    if(NOT ie_build_python_req_FOUND)
         find_package(Cython QUIET
                      PATHS "${OpenVINOPython_SOURCE_DIR}/src/compatibility/openvino/cmake"
                      NO_CMAKE_FIND_ROOT_PATH
                      NO_DEFAULT_PATH)
         if(CYTHON_VERSION VERSION_GREATER_EQUAL 0.29)
-            set(ie_python_req_FOUND ON)
+            set(ie_build_python_req_FOUND ON)
         else()
-            message(${message_mode} "Python requirements '${ie_python_req}' are missed, IE Python API 1.0 will not be built (ENABLE_PYTHON is OFF)")
+            message(${message_mode} "Python requirements '${ie_build_python_req}' are missed, IE Python API 1.0 will not be built (ENABLE_PYTHON is OFF)")
         endif()
     endif()
 
@@ -116,14 +107,14 @@ function(ov_check_python_build_conditions)
         set(python_debug OFF)
     endif()
 
-    if(PYTHONLIBS_FOUND AND ov_python_req_FOUND AND ie_python_req_FOUND AND NOT python_debug)
+    if(PYTHONLIBS_FOUND AND ie_build_python_req_FOUND AND NOT python_debug)
         set(ENABLE_PYTHON_DEFAULT ON PARENT_SCOPE)
     else()
         set(ENABLE_PYTHON_DEFAULT OFF PARENT_SCOPE)
     endif()
 
     # to disable API 1.0
-    set(ie_python_req_FOUND ${ie_python_req_FOUND} PARENT_SCOPE)
+    set(ie_build_python_req_FOUND ${ie_build_python_req_FOUND} PARENT_SCOPE)
     # set pybind11 minimal version
     set(pybind11_min_version ${pybind11_min_version} PARENT_SCOPE)
 endfunction()
@@ -178,7 +169,7 @@ ie_dependent_option(ENABLE_WHEEL "Build wheel packages for PyPI" ${ENABLE_WHEEL_
 
 if(NOT ENABLE_PYTHON)
     if(CMAKE_SOURCE_DIR STREQUAL OpenVINOPython_SOURCE_DIR)
-        message(FATAL_ERROR "Python OpenVINO API requirements are not satisfied. Please, install ${ie_python_req} and ${ov_python_req}")
+        message(FATAL_ERROR "Python OpenVINO API requirements are not satisfied. Please, install ${ie_build_python_req}")
     else()
         return()
     endif()
@@ -201,7 +192,7 @@ endif()
 add_subdirectory(src/compatibility/pyngraph)
 add_subdirectory(src/pyopenvino)
 
-if(ie_python_req_FOUND)
+if(ie_build_python_req_FOUND)
     add_subdirectory(src/compatibility/openvino)
 else()
     message(WARNING "NOTE: Python API for OpenVINO 1.0 is disabled")

From 6556d07c321476618ea4e88a98588f7df349aaca Mon Sep 17 00:00:00 2001
From: Roman Kazantsev <roman.kazantsev@intel.com>
Date: Tue, 19 Sep 2023 00:25:44 +0400
Subject: [PATCH 07/46] [TF FE][Tests] Fix sporadic failure in CTCLoss test
 (#19920)

---
 tests/layer_tests/tensorflow_tests/test_tf_CTCLoss.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/layer_tests/tensorflow_tests/test_tf_CTCLoss.py b/tests/layer_tests/tensorflow_tests/test_tf_CTCLoss.py
index 5a9b024f509ae6..78289a7144ba7a 100644
--- a/tests/layer_tests/tensorflow_tests/test_tf_CTCLoss.py
+++ b/tests/layer_tests/tensorflow_tests/test_tf_CTCLoss.py
@@ -58,4 +58,4 @@ def test_ctcloss_placeholder_const(self, params, ie_device, precision, ir_versio
                                        use_new_frontend, use_old_api):
         self._test(*self.create_ctcloss_placeholder_const_net(**params),
                    ie_device, precision, ir_version, temp_dir=temp_dir,
-                   use_new_frontend=use_new_frontend, use_old_api=use_old_api, custom_eps=1e-3)
+                   use_new_frontend=use_new_frontend, use_old_api=use_old_api, custom_eps=1e-2)

From e34c5a09c6ccd42dacc360dd780496107d537bf8 Mon Sep 17 00:00:00 2001
From: Przemyslaw Wysocki <przemyslaw.wysocki@intel.com>
Date: Mon, 18 Sep 2023 22:36:13 +0200
Subject: [PATCH 08/46] [PyOV] Add an `__init__.py` alignment check in CMake
 (#19882)

* Add init check

* Apply CR
---
 src/bindings/python/CMakeLists.txt            | 31 +++++++++++++++++
 .../src/compatibility/openvino/__init__.py    |  2 +-
 tools/openvino_dev/CMakeLists.txt             | 33 +++++++++++++++++++
 3 files changed, 65 insertions(+), 1 deletion(-)

diff --git a/src/bindings/python/CMakeLists.txt b/src/bindings/python/CMakeLists.txt
index 24089b38531c27..a273184c4b8d1d 100644
--- a/src/bindings/python/CMakeLists.txt
+++ b/src/bindings/python/CMakeLists.txt
@@ -121,6 +121,37 @@ endfunction()
 
 ov_check_python_build_conditions()
 
+# check __init__.py files alignment
+
+function(ov_check_init_files_alignment)
+    # check the files in pairs
+    list(APPEND init_files
+        "${OpenVINOPython_SOURCE_DIR}/src/openvino/__init__.py"
+        "${OpenVINOPython_SOURCE_DIR}/src/compatibility/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/mo/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/pot/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/ovc/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/benchmark_tool/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/openvino_dev/src/openvino/__init__.py")
+
+    list(LENGTH init_files init_files_count)
+    math(EXPR file_loop_range "${init_files_count}-2")
+    foreach(init_file_idx RANGE 0 ${file_loop_range})
+        math(EXPR init_file_idx_next "${init_file_idx}+1")
+        list(GET init_files ${init_file_idx} file1)
+        list(GET init_files ${init_file_idx_next} file2)
+
+        execute_process(COMMAND ${CMAKE_COMMAND} -E compare_files ${file1} ${file2}
+            RESULT_VARIABLE compare_result
+        )
+        if(compare_result EQUAL 1)
+            message(FATAL_ERROR "The __init__.py files are misaligned: ${file1} and ${file2}")
+        endif()
+    endforeach()
+endfunction()
+
+ov_check_init_files_alignment()
+
 ie_option(ENABLE_PYTHON "Enables OpenVINO Python API build" ${ENABLE_PYTHON_DEFAULT})
 
 #
diff --git a/src/bindings/python/src/compatibility/openvino/__init__.py b/src/bindings/python/src/compatibility/openvino/__init__.py
index 8f0113d5bcaf6c..90552e0befed68 100644
--- a/src/bindings/python/src/compatibility/openvino/__init__.py
+++ b/src/bindings/python/src/compatibility/openvino/__init__.py
@@ -57,6 +57,6 @@
 # Tools
 try:
     # Model Conversion API - ovc should reside in the main namespace
-    from openvino.tools.ovc import convert_model, InputCutInfo
+    from openvino.tools.ovc import convert_model
 except ImportError:
     pass
diff --git a/tools/openvino_dev/CMakeLists.txt b/tools/openvino_dev/CMakeLists.txt
index 2d2066d660dca3..42ad4031d69955 100644
--- a/tools/openvino_dev/CMakeLists.txt
+++ b/tools/openvino_dev/CMakeLists.txt
@@ -54,6 +54,39 @@ foreach(EXTRAS IN LISTS EXTRAS_LIST)
             ${OV_CPACK_COMP_OPENVINO_DEV_REQ_FILES_EXCLUDE_ALL})
 endforeach()
 
+# check __init__.py files alignment
+
+function(ov_check_init_files_alignment)
+    # check the files in pairs
+    list(APPEND init_files
+        "${OpenVINO_SOURCE_DIR}/src/bindings/python/src/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/src/bindings/python/src/compatibility/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/mo/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/pot/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/ovc/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/benchmark_tool/openvino/__init__.py"
+        "${OpenVINO_SOURCE_DIR}/tools/openvino_dev/src/openvino/__init__.py")
+
+    list(LENGTH init_files init_files_count)
+    math(EXPR file_loop_range "${init_files_count}-2")
+    foreach(init_file_idx RANGE 0 ${file_loop_range})
+        math(EXPR init_file_idx_next "${init_file_idx}+1")
+        list(GET init_files ${init_file_idx} file1)
+        list(GET init_files ${init_file_idx_next} file2)
+
+        execute_process(COMMAND ${CMAKE_COMMAND} -E compare_files ${file1} ${file2}
+            RESULT_VARIABLE compare_result
+        )
+        if(compare_result EQUAL 1)
+            message(STATUS ${file1})
+            message(STATUS ${file2})
+            message(FATAL_ERROR "The __init__.py files are misaligned: ${file1} and ${file2}")
+        endif()
+    endforeach()
+endfunction()
+
+ov_check_init_files_alignment()
+
 # openvino_dev build
 
 if(NOT ENABLE_WHEEL)

From 03918c2cac9ace8a78d963dd1191b1318a8b3f14 Mon Sep 17 00:00:00 2001
From: Paul Youngsoo Ahn <paul.y.ahn@intel.com>
Date: Tue, 19 Sep 2023 06:13:38 +0900
Subject: [PATCH 09/46] bug fix update (#19568)

* [GPU] Fix gpu functional test failures
* set m_max_batch to 1
* add debug log for condition operation

* Add debug logs for condition and constant

* To fix zero byte allocation issue, Convert zero dimension to 1 dimension in constant

* Add the code to check if output shape is dynamic in split offset calculation and checking allow_new_shape_infer in program_builder

* Add unit test for fix checking output shape

* Add test case for zero dimennsion allocation and debug message

* Fix build failure for condition unit test

* Follow up code review
---
 .../intel_gpu/primitives/condition.hpp        | 10 +--
 .../src/graph/impls/common/condition.cpp      |  3 +
 src/plugins/intel_gpu/src/graph/network.cpp   | 15 +++-
 .../intel_gpu/src/plugin/ops/condition.cpp    |  7 ++
 .../intel_gpu/src/plugin/ops/constant.cpp     |  8 +-
 .../intel_gpu/src/plugin/ops/split.cpp        | 23 ++++-
 .../intel_gpu/src/plugin/program_builder.cpp  |  8 ++
 .../single_layer_tests/dynamic/shapeof.cpp    | 85 +++++++++++++++++++
 .../single_layer_tests/dynamic/split.cpp      | 16 ++++
 .../functional/subgraph_tests/condition.cpp   | 82 ++++++++++++++++--
 10 files changed, 240 insertions(+), 17 deletions(-)

diff --git a/src/plugins/intel_gpu/include/intel_gpu/primitives/condition.hpp b/src/plugins/intel_gpu/include/intel_gpu/primitives/condition.hpp
index 664b240cba8a8a..5ad37c7dfa55bf 100644
--- a/src/plugins/intel_gpu/include/intel_gpu/primitives/condition.hpp
+++ b/src/plugins/intel_gpu/include/intel_gpu/primitives/condition.hpp
@@ -26,19 +26,17 @@ struct condition : public primitive_base<condition> {
 
         std::string str() {
             std::stringstream ss;
-            ss << "branch: { " << std::endl;
-            ss<< "* input_map : [(outer_id,inner_id),";
+            ss << "branch: {input_map : [(outer_id,inner_id),";
             for (auto& in_iter : input_map) {
                 ss << "(" << in_iter.first << "," << in_iter.second << "),";
             }
-            ss << "]," << std::endl;
+            ss << "],";
 
-            ss << "* output_map : [(outer_idx,inner_id),";
+            ss << " output_map : [(outer_idx,inner_id),";
             for (auto& out_iter : output_map) {
                 ss << "(" << out_iter.first << ","<< out_iter.second << "),";
             }
-            ss << "]" << std::endl;
-            ss << "}" << std::endl;
+            ss << "]}";
             return ss.str();
         }
     };
diff --git a/src/plugins/intel_gpu/src/graph/impls/common/condition.cpp b/src/plugins/intel_gpu/src/graph/impls/common/condition.cpp
index 4a1a8b414f0b0a..fbcdf6b277645b 100644
--- a/src/plugins/intel_gpu/src/graph/impls/common/condition.cpp
+++ b/src/plugins/intel_gpu/src/graph/impls/common/condition.cpp
@@ -39,6 +39,7 @@ struct condition_impl : typed_primitive_impl<condition> {
         auto pred = condition_inst::get_pred_from_memory(instance.pred_memory_ptr(), instance.get_network().get_stream());
         network::ptr executed_net = pred? instance.get_net_true() : instance.get_net_false();
         auto branch = pred? instance.get_branch_true() : instance.get_branch_false();
+        GPU_DEBUG_LOG << "predicate: " << (pred ? "True" : "False") << std::endl;
 
         // Set input memory of inner network before its execution
         for (size_t mem_idx = 0; mem_idx < instance.inputs_memory_count(); mem_idx++) {
@@ -48,6 +49,7 @@ struct condition_impl : typed_primitive_impl<condition> {
                 const primitive_id& input_internal_id = iter->second;
                 auto mem_ptr = instance.input_memory_ptr(mem_idx);
                 executed_net->set_input_data(input_internal_id, mem_ptr);
+                GPU_DEBUG_LOG << "Inner net - Inputs[" << mem_idx << "]" << mem_ptr->get_layout().to_short_string() << std::endl;
             }
         }
 
@@ -62,6 +64,7 @@ struct condition_impl : typed_primitive_impl<condition> {
             auto inner_out_id = out_mem_map.second;
             auto mem_ptr = executed_net->get_output(inner_out_id).get_memory();
             instance.set_output_memory(mem_ptr, false, out_mem_idx);
+            GPU_DEBUG_LOG << "Inner net - Outputs[" << out_mem_idx << "]" << mem_ptr->get_layout().to_short_string() << std::endl;
         }
 
         ev->set();
diff --git a/src/plugins/intel_gpu/src/graph/network.cpp b/src/plugins/intel_gpu/src/graph/network.cpp
index eb971ae9410e5f..ea2225b48844d1 100644
--- a/src/plugins/intel_gpu/src/graph/network.cpp
+++ b/src/plugins/intel_gpu/src/graph/network.cpp
@@ -1234,9 +1234,18 @@ void network::execute_impl(const std::vector<event::ptr>& events) {
             GPU_DEBUG_COUT << inst->id() << std::endl;
             if (inst->get_node().is_type<loop>()) {
                 auto& loop_node = inst->get_node().as<loop>();
-                auto loop_body_primitives = loop_node.get_body_topology().get_primitives_ids();
-                for (auto& primitive_id : loop_body_primitives) {
-                    GPU_DEBUG_COUT << "\t" << primitive_id << std::endl;
+                for (auto& prim : loop_node.get_body_program()->get_processing_order()) {
+                    GPU_DEBUG_COUT << "\t" << prim->id() << std::endl;
+                }
+            } else if (inst->get_node().is_type<condition>()) {
+                auto& cond_node = inst->get_node().as<condition>();
+                GPU_DEBUG_COUT << "* Branch_True" << std::endl;
+                for (auto& prim : cond_node.get_branch_true().inner_program->get_processing_order()) {
+                    GPU_DEBUG_COUT << "\t" << prim->id() << std::endl;
+                }
+                GPU_DEBUG_COUT << "* Branch_False" << std::endl;
+                for (auto& prim : cond_node.get_branch_false().inner_program->get_processing_order()) {
+                    GPU_DEBUG_COUT << "\t" << prim->id() << std::endl;
                 }
             }
         }
diff --git a/src/plugins/intel_gpu/src/plugin/ops/condition.cpp b/src/plugins/intel_gpu/src/plugin/ops/condition.cpp
index fde2e65d62c474..d9b4e77314e600 100644
--- a/src/plugins/intel_gpu/src/plugin/ops/condition.cpp
+++ b/src/plugins/intel_gpu/src/plugin/ops/condition.cpp
@@ -14,6 +14,12 @@ const size_t idx_false = 1;
 static cldnn::condition::branch gen_branch(ProgramBuilder& p, const std::shared_ptr<ov::op::v8::If>& op, size_t idx) {
     cldnn::condition::branch branch;
     const auto& internal_body = (idx == idx_true)? op->get_then_body() : op->get_else_body();
+    GPU_DEBUG_LOG << "Generate inner program for " << "op::v"
+                    << op->get_type_info().version_id << "::"
+                    << op->get_type_name() << " operation "
+                    << "(friendly_name=" << op->get_friendly_name() << ") : "
+                    << internal_body->get_friendly_name()
+                    << ", num inputs: " << op->get_input_size() << std::endl;
 
     auto config = p.get_config();
     config.set_property(ov::intel_gpu::max_dynamic_batch(1));
@@ -40,6 +46,7 @@ static cldnn::condition::branch gen_branch(ProgramBuilder& p, const std::shared_
         output_map.insert({out_desc->m_output_index, internal_id});
     }
 
+    GPU_DEBUG_LOG << op->get_friendly_name() << " branch_info[" << internal_body->get_friendly_name() << "] : " << branch << std::endl;
     return branch;
 }
 
diff --git a/src/plugins/intel_gpu/src/plugin/ops/constant.cpp b/src/plugins/intel_gpu/src/plugin/ops/constant.cpp
index 664098477e82aa..10eaa80327ff9c 100644
--- a/src/plugins/intel_gpu/src/plugin/ops/constant.cpp
+++ b/src/plugins/intel_gpu/src/plugin/ops/constant.cpp
@@ -97,8 +97,14 @@ static void create_data(ProgramBuilder& p, const ov::Shape& constDims, const std
         p.primitive_ids[initialconstPrimID] = constPrimID;
         p.profiling_ids.push_back(initialconstPrimID);
     } else {
-        GPU_DEBUG_LOG << "[" << initialconstPrimID << ": constant]" << std::endl;
+        if (constLayout.count() == 0) {
+            // Convert zero dimension constant layout to 1 dimension to fix the issue
+            // that memory allocation is failed on windows when constant layout is zero dimension.
+            constLayout = cldnn::layout(ov::PartialShape({1}), constLayout.data_type, constLayout.format);
+        }
         cldnn::memory::ptr mem = p.get_engine().allocate_memory(constLayout, false);
+        GPU_DEBUG_LOG << "[" << initialconstPrimID << ": constant] layout: "
+                        << constLayout.to_short_string() << ", mem_ptr(" << mem << ", " << mem->size() << " bytes)"<< std::endl;
         auto& stream = p.get_engine().get_service_stream();
         cldnn::mem_lock<char> lock{mem, stream};
         auto buf = lock.data();
diff --git a/src/plugins/intel_gpu/src/plugin/ops/split.cpp b/src/plugins/intel_gpu/src/plugin/ops/split.cpp
index be35125f1b4689..be7d2dad4b0942 100644
--- a/src/plugins/intel_gpu/src/plugin/ops/split.cpp
+++ b/src/plugins/intel_gpu/src/plugin/ops/split.cpp
@@ -13,6 +13,21 @@
 namespace ov {
 namespace intel_gpu {
 
+static bool IsDynamic(const std::shared_ptr<ov::Node>& op) {
+    if (op->is_dynamic()) {
+        return true;
+    }
+
+    for (size_t i = 0; i < op->get_output_size(); i++) {
+        const auto outPartialShape = op->get_output_partial_shape(i);
+        if (outPartialShape.is_dynamic()) {
+            return true;
+        }
+    }
+
+    return false;
+}
+
 static void CreateCommonSplitOp(ProgramBuilder& p, const std::shared_ptr<ov::Node>& op) {
     auto get_layer_name = [&](size_t idx)->std::string {
         return layer_type_name_ID(op) + ((op->get_output_size() == 1)? "" : ".out" + std::to_string(idx));
@@ -22,11 +37,15 @@ static void CreateCommonSplitOp(ProgramBuilder& p, const std::shared_ptr<ov::Nod
     if (p.use_new_shape_infer() || op->is_dynamic()) {
         std::vector<cldnn::tensor> offsets;
 
-        if (!op->is_dynamic()) {
+        // op->is_dynamic() does not check if output shape is dynamic. it only check dynamism for input shapes
+        // Even if op->is_dynamic() is false, output shape can be dynamic.
+        // Thus, it is necessary to check if output shape is dynamic.
+        if (!IsDynamic(op)) {
             auto input_pshape = op->get_input_partial_shape(0);
             ov::Shape start_offset(input_pshape.size());
             for (size_t i = 0; i < op->get_output_size(); i++) {
                 const auto outPartialShape = op->get_output_partial_shape(i);
+
                 auto offsetTensor = tensor_from_dims(start_offset, 0);
                 offsets.push_back(offsetTensor);
 
@@ -49,7 +68,7 @@ static void CreateCommonSplitOp(ProgramBuilder& p, const std::shared_ptr<ov::Nod
             auto cropPrim = cldnn::crop(get_layer_name(i),
                                         inputs,
                                         cldnn::tensor(1),
-                                        (op->is_dynamic() ? cldnn::tensor(0) : offsets[i]),
+                                        (offsets.empty() ? cldnn::tensor(0) : offsets[i]),
                                         op_mode,
                                         static_cast<int>(i),
                                         num_splits);
diff --git a/src/plugins/intel_gpu/src/plugin/program_builder.cpp b/src/plugins/intel_gpu/src/plugin/program_builder.cpp
index 231ee37252a2a5..404818ce92ce8c 100644
--- a/src/plugins/intel_gpu/src/plugin/program_builder.cpp
+++ b/src/plugins/intel_gpu/src/plugin/program_builder.cpp
@@ -314,6 +314,14 @@ bool ProgramBuilder::requires_new_shape_infer(const ov::Node& op) const {
         return true;
     }
 
+    // When input node has dynamic shape with 4 dimension, this function return false
+    // because op.is_dynamic() which only checks input shapes return false.
+    // So, in the case of input data, we need to check output shape.
+    for (size_t i = 0; i < op.get_output_size(); i++) {
+        if (op.get_output_partial_shape(i).is_dynamic())
+            return true;
+    }
+
     if (ov::is_type<op::FullyConnectedCompressed>(&op))
         return true;
 
diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/shapeof.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/shapeof.cpp
index 7f4f6d6689e79f..f9244790e9fc7a 100644
--- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/shapeof.cpp
+++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/shapeof.cpp
@@ -215,4 +215,89 @@ INSTANTIATE_TEST_SUITE_P(smoke_ShapeOf_5d_compareWithRefs_static,
 
 } // namespace
 
+using ShapeOfParams = typename std::tuple<
+        InputShape,                     // Shape
+        InferenceEngine::Precision,     // Precision
+        LayerTestsUtils::TargetDevice   // Device name
+>;
+
+class ShapeOfDynamicInputGPUTest : public testing::WithParamInterface<ShapeOfParams>,
+                                virtual public SubgraphBaseTest {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<ShapeOfParams>& obj) {
+        InputShape inputShapes;
+        InferenceEngine::Precision dataPrc;
+        std::string targetDevice;
+
+        std::tie(inputShapes, dataPrc, targetDevice) = obj.param;
+        std::ostringstream result;
+        result << "IS=(";
+        result << ov::test::utils::partialShape2str({inputShapes.first}) << "_";
+        for (size_t i = 0lu; i < inputShapes.second.size(); i++) {
+            result << "{";
+            result << ov::test::utils::vec2str(inputShapes.second[i]) << "_";
+            result << "}_";
+        }
+        result << ")_";
+        result << "netPRC=" << dataPrc << "_";
+        result << "targetDevice=" << targetDevice << "_";
+        auto res_str = result.str();
+        std::replace(res_str.begin(), res_str.end(), '-', '_');
+        return res_str;
+    }
+
+protected:
+    void SetUp() override {
+        InputShape inputShapes;
+        InferenceEngine::Precision dataPrc;
+        targetDevice = ov::test::utils::DEVICE_GPU;
+
+        std::tie(inputShapes, dataPrc, targetDevice) = GetParam();
+
+        init_input_shapes({inputShapes});
+
+        InferenceEngine::PreProcessInfo pre_process_info;
+        pre_process_info.setVariant(InferenceEngine::MeanVariant::MEAN_VALUE);
+
+        const auto prc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(dataPrc);
+
+        auto input = std::make_shared<ngraph::opset9::Parameter>(prc, inputShapes.first);
+        input->get_output_tensor(0).get_rt_info()["ie_legacy_preproc"] = pre_process_info;
+        input->set_friendly_name("input_data");
+
+        auto shape_of_01 = std::make_shared<ngraph::opset9::ShapeOf>(input);
+        shape_of_01->set_friendly_name("shape_of_01");
+
+        auto shape_of_02 = std::make_shared<ngraph::opset9::ShapeOf>(shape_of_01);
+        shape_of_02->set_friendly_name("shape_of_02");
+
+        auto result = std::make_shared<ngraph::opset1::Result>(shape_of_02);
+        result->set_friendly_name("outer_result");
+
+        function = std::make_shared<ngraph::Function>(ngraph::OutputVector{result}, ngraph::ParameterVector{input});
+        function->set_friendly_name("shape_of_test");
+    }
+};
+
+TEST_P(ShapeOfDynamicInputGPUTest, CompareWithRefs) {
+    SKIP_IF_CURRENT_TEST_IS_DISABLED()
+
+    run();
+}
+
+const std::vector<ov::test::InputShape> dynamicInputShapes = {
+    ov::test::InputShape(ov::PartialShape({-1, -1, -1, -1, -1}), {{4, 1, 1, 64, 32}, {6, 1, 1, 8, 4}, {8, 1, 1, 24, 16}}),
+};
+
+const std::vector<InferenceEngine::Precision> dynamicInputPrec = {
+    InferenceEngine::Precision::FP16,
+};
+
+INSTANTIATE_TEST_SUITE_P(smoke_Check, ShapeOfDynamicInputGPUTest,
+                testing::Combine(
+                    testing::ValuesIn(dynamicInputShapes),                          // input shapes
+                    testing::ValuesIn(dynamicInputPrec),                               // network precision
+                    testing::Values<std::string>(ov::test::utils::DEVICE_GPU)),     // device type
+                ShapeOfDynamicInputGPUTest::getTestCaseName);
+
 } // namespace GPULayerTestsDefinitions
diff --git a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/split.cpp b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/split.cpp
index c652a9770aa0c4..7a0b3fda62bcfe 100644
--- a/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/split.cpp
+++ b/src/plugins/intel_gpu/tests/functional/single_layer_tests/dynamic/split.cpp
@@ -264,4 +264,20 @@ INSTANTIATE_TEST_SUITE_P(smoke_VariadicSplitsCheck6D, VariadicSplitLayerGPUDynam
                                 ::testing::ValuesIn(restInputTypes)),                       // input type of splitLength
                         VariadicSplitLayerGPUDynamicTest::getTestCaseName);
 
+
+const std::vector<InputShape> inputShapes4d_static = {
+        {
+            {5, 16, 10, 8}, {{5, 16, 10, 8}, }
+        }
+};
+
+INSTANTIATE_TEST_SUITE_P(smoke_VariadicSplitsCheck4D_static_input_dyn_output, VariadicSplitLayerGPUDynamicTest,
+                        ::testing::Combine(
+                                ::testing::Values(1),                                       // axes
+                                ::testing::Values(std::vector<int32_t>{2, 1, -1}),          // splitLength
+                                ::testing::Values(ElementType::f16),                        // netPrec
+                                ::testing::ValuesIn(inputShapes4d_static),                         // inShapes
+                                ::testing::ValuesIn(restInputTypes)),                       // input type of splitLength
+                        VariadicSplitLayerGPUDynamicTest::getTestCaseName);
+
 } // namespace GPULayerTestsDefinitions
diff --git a/src/plugins/intel_gpu/tests/functional/subgraph_tests/condition.cpp b/src/plugins/intel_gpu/tests/functional/subgraph_tests/condition.cpp
index 3f7e7f4bf4ff25..67cada5dbf661e 100644
--- a/src/plugins/intel_gpu/tests/functional/subgraph_tests/condition.cpp
+++ b/src/plugins/intel_gpu/tests/functional/subgraph_tests/condition.cpp
@@ -13,6 +13,8 @@
 #include "common_test_utils/test_constants.hpp"
 #include "shared_test_classes/base/utils/ranges.hpp"
 #include <common_test_utils/ov_tensor_utils.hpp>
+#include "shared_test_classes/base/utils/compare_results.hpp"
+#include "openvino/pass/constant_folding.hpp"
 
 
 using namespace InferenceEngine;
@@ -45,7 +47,11 @@ enum InnerBodyType {
     /**
      * Inner body with nested condition case
      */
-    Type05 = 5
+    Type05 = 5,
+    /**
+     * Inner body with single constant with zero dimensions
+     */
+    Type06 = 6
 };
 
 public:
@@ -251,6 +257,24 @@ class InnerBodyType05 : public InnerBodyGenerator {
     }
 };
 
+class InnerBodyType06 : public InnerBodyGenerator {
+protected:
+    std::shared_ptr<ngraph::Function> generate(ov::PartialShape& input_shape, ngraph::element::Type prc) override {
+        auto constant   = ngraph::opset9::Constant::create(prc, ov::Shape(input_shape.rank().get_length(), 0), {2.0f});
+        constant->set_friendly_name("body1_constant");
+        // constant->get_rt_info().emplace(ov::pass::DisableConstantFolding::get_type_info_static(), ov::pass::DisableConstantFolding{});
+        // constant->get_rt_info().emplace("can_be_folded", false);
+        auto result     = std::make_shared<ngraph::opset1::Result>(constant);
+        auto o_layout = result->get_layout();
+        result->set_friendly_name("body1_result");
+        auto body       = std::make_shared<ngraph::Function>(
+            ngraph::OutputVector {result},
+            ngraph::ParameterVector{},
+            "constant_only");
+        return body;
+    }
+};
+
 static std::shared_ptr<InnerBodyGenerator> get_inner_body_generator(InnerBodyGenerator::InnerBodyType type) {
     std::shared_ptr<InnerBodyGenerator> generator_ptr;
     switch (type) {
@@ -274,6 +298,10 @@ static std::shared_ptr<InnerBodyGenerator> get_inner_body_generator(InnerBodyGen
         {
             return std::make_shared<InnerBodyType05>();
         }
+        case InnerBodyGenerator::InnerBodyType::Type06:
+        {
+            return std::make_shared<InnerBodyType06>();
+        }
         default:
         {
             OPENVINO_ASSERT(false, "Not supported type");
@@ -314,9 +342,22 @@ class TestModelGenerator {
                             cond->set_then_body(body_then_generator->get_function());
                             cond->set_input(data, body_then_generator->get_input(), body_else_generator->get_input());
                             cond->set_output(body_then_generator->get_result(), body_else_generator->get_result());
-                            auto result = std::make_shared<ngraph::opset1::Result>(cond);
-                            result->set_friendly_name("outer_result");
-                            function = std::make_shared<ngraph::Function>(ngraph::OutputVector {result}, params);
+                            if (then_body_type == InnerBodyGenerator::InnerBodyType::Type06 || else_body_type == InnerBodyGenerator::InnerBodyType::Type06) {
+                                auto constant = create_condition_input(params, prc, ngraph::Shape{1}, 0, true);
+                                auto addition = std::make_shared<ngraph::opset9::Add>(cond, constant);
+                                auto shapeof1 = std::make_shared<ngraph::opset9::ShapeOf>(addition);
+                                auto convert = std::make_shared<ngraph::opset9::Convert>(shapeof1, prc);
+                                auto mul = std::make_shared<ngraph::opset9::Multiply>(convert, constant);
+                                auto shapePatternsNode = create_condition_input(params, ov::element::Type_t::i64, ngraph::Shape{1}, 0, true);
+                                auto reshapeOp = std::make_shared<ngraph::opset1::Reshape>(mul, shapePatternsNode, true);
+                                auto result = std::make_shared<ngraph::opset1::Result>(reshapeOp);
+                                result->set_friendly_name("outer_result");
+                                function = std::make_shared<ngraph::Function>(ngraph::OutputVector {result}, params);
+                            } else {
+                                auto result = std::make_shared<ngraph::opset1::Result>(cond);
+                                result->set_friendly_name("outer_result");
+                                function = std::make_shared<ngraph::Function>(ngraph::OutputVector {result}, params);
+                            }
                         }
     std::shared_ptr<ngraph::Function> get_function() { return function; }
 
@@ -394,6 +435,11 @@ static std::ostream& operator<<(std::ostream& os, const InnerBodyGenerator::Inne
             os << "Type05";
             break;
         }
+        case InnerBodyGenerator::InnerBodyType::Type06:
+        {
+            os << "Type06";
+            break;
+        }
         default:
         {
             os << "NONE";
@@ -596,7 +642,8 @@ class DynamicConditionLayerGPUTest : public testing::WithParamInterface<Conditio
     void generate_inputs(const std::vector<ov::Shape>& targetInputStaticShapes) override {
         ov::Shape input_shape;
         for (auto& shape : targetInputStaticShapes) {
-            if (shape.size() > 1) {
+            // Change condition to cover 1 dim input shape
+            if (shape.size() > 0) {
                 input_shape = shape;
                 break;
             }
@@ -622,6 +669,7 @@ class DynamicConditionLayerGPUTest : public testing::WithParamInterface<Conditio
             }
         }
     }
+
     size_t niter = 0;
 };
 
@@ -648,6 +696,10 @@ const std::vector<ov::test::InputShape> dynamicInputShapes_f16 = {
     ov::test::InputShape(ov::PartialShape({-1, -1, -1}), {{2, 24, 16}, {2, 64, 32}, {2, 8, 4}})
 };
 
+const std::vector<ov::test::InputShape> dynamicInputShapes_zero_dims = {
+    ov::test::InputShape(ov::PartialShape({-1}), {{24}, {64}, {8}})
+};
+
 const std::vector<InnerBodyTypeParams> innerBodyTypes_f32 = {
     {
         InnerBodyGenerator::InnerBodyType::Type01,
@@ -670,11 +722,22 @@ const std::vector<InnerBodyTypeParams> innerBodyTypes_f16 = {
     }
 };
 
+const std::vector<InnerBodyTypeParams> innerBodyTypes_zero_dims = {
+    {
+        InnerBodyGenerator::InnerBodyType::Type02,
+        InnerBodyGenerator::InnerBodyType::Type06
+    },
+};
+
 const std::vector<TestModelGenerator::PredicateTypes> condTypes = {
     TestModelGenerator::PredicateTypes::PARAM,
     TestModelGenerator::PredicateTypes::NODE
 };
 
+const std::vector<TestModelGenerator::PredicateTypes> condTypes_zero_dims = {
+    TestModelGenerator::PredicateTypes::PARAM
+};
+
 INSTANTIATE_TEST_SUITE_P(smoke_ConditionGPUTest_dynamic_f32, DynamicConditionLayerGPUTest,
                 testing::Combine(
                     testing::ValuesIn(dynamicInputShapes_f32),                          // input shapes
@@ -693,4 +756,13 @@ INSTANTIATE_TEST_SUITE_P(smoke_ConditionGPUTest_dynamic_f16, DynamicConditionLay
                     testing::ValuesIn(condTypes),                                       // cond type
                     testing::Values<std::string>(ov::test::utils::DEVICE_GPU)),         // device type
                 DynamicConditionLayerGPUTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_ConditionGPUTest_zero_dims, DynamicConditionLayerGPUTest,
+                testing::Combine(
+                    testing::ValuesIn(dynamicInputShapes_zero_dims),                    // input shapes
+                    testing::ValuesIn(innerBodyTypes_zero_dims),                        // inner body type
+                    testing::ValuesIn(netPrecisions_f32),                               // network precision
+                    testing::ValuesIn(condTypes_zero_dims),                             // cond type
+                    testing::Values<std::string>(ov::test::utils::DEVICE_GPU)),         // device type
+                DynamicConditionLayerGPUTest::getTestCaseName);
 } // namespace GPULayerTestsDefinitions

From 691f5938d27820d409eb681e0d00c08a806e5222 Mon Sep 17 00:00:00 2001
From: Sofya Balandina <sofya.balandina@intel.com>
Date: Tue, 19 Sep 2023 02:51:17 +0100
Subject: [PATCH 10/46] [template] Add faked hint property (#19887)

* [template] Add faked hint property

* fix comments
---
 src/plugins/template/src/config.cpp           | 24 +++++++++++++++++++
 src/plugins/template/src/config.hpp           |  7 +++++-
 src/plugins/template/src/plugin.cpp           |  4 ++++
 .../ov_executable_network/properties.cpp      |  2 +-
 .../behavior/ov_plugin/properties_tests.cpp   |  2 +-
 .../ov_executable_network/properties.cpp      | 11 +++++++++
 .../behavior/ov_plugin/properties_tests.cpp   |  7 ------
 7 files changed, 47 insertions(+), 10 deletions(-)

diff --git a/src/plugins/template/src/config.cpp b/src/plugins/template/src/config.cpp
index 155ed29ecd937a..683439d97018e5 100644
--- a/src/plugins/template/src/config.cpp
+++ b/src/plugins/template/src/config.cpp
@@ -36,6 +36,24 @@ Configuration::Configuration(const ov::AnyMap& config, const Configuration& defa
         } else if (ov::hint::performance_mode == key) {
             std::stringstream strm{value.as<std::string>()};
             strm >> performance_mode;
+        } else if (ov::hint::inference_precision == key) {
+            inference_precision = value.as<ov::element::Type>();
+        } else if (ov::hint::execution_mode == key) {
+            execution_mode = value.as<ov::hint::ExecutionMode>();
+            if ((execution_mode != ov::hint::ExecutionMode::ACCURACY) &&
+                (execution_mode != ov::hint::ExecutionMode::PERFORMANCE)) {
+                OPENVINO_THROW("Unsupported execution mode, should be ACCURACY or PERFORMANCE, but was: ",
+                               value.as<std::string>());
+            }
+        } else if (ov::num_streams == key) {
+            streams_executor_config.set_property(key, value);
+        } else if (ov::hint::num_requests == key) {
+            auto tmp_val = value.as<std::string>();
+            int tmp_i = std::stoi(tmp_val);
+            if (tmp_i >= 0)
+                num_requests = tmp_i;
+            else
+                OPENVINO_THROW("Incorrect value, it should be unsigned integer: ", key);
         } else if (throwOnUnsupported) {
             OPENVINO_THROW("Property was not found: ", key);
         }
@@ -66,6 +84,12 @@ ov::Any Configuration::Get(const std::string& name) const {
         return {std::to_string(streams_executor_config._threadsPerStream)};
     } else if (name == ov::hint::performance_mode) {
         return performance_mode;
+    } else if (name == ov::hint::inference_precision) {
+        return inference_precision;
+    } else if (name == ov::hint::execution_mode) {
+        return execution_mode;
+    } else if (name == ov::hint::num_requests) {
+        return num_requests;
     } else {
         OPENVINO_THROW("Property was not found: ", name);
     }
diff --git a/src/plugins/template/src/config.hpp b/src/plugins/template/src/config.hpp
index e2fb945e977895..d891fd472deddc 100644
--- a/src/plugins/template/src/config.hpp
+++ b/src/plugins/template/src/config.hpp
@@ -31,11 +31,16 @@ struct Configuration {
     // Plugin configuration parameters
 
     int device_id = 0;
-    bool perf_count = true;
+    bool perf_count = false;
     ov::threading::IStreamsExecutor::Config streams_executor_config;
     ov::hint::PerformanceMode performance_mode = ov::hint::PerformanceMode::LATENCY;
+    uint32_t num_requests = 1;
     bool disable_transformations = false;
     bool exclusive_async_requests = false;
+
+    // unused
+    ov::element::Type inference_precision = ov::element::undefined;
+    ov::hint::ExecutionMode execution_mode = ov::hint::ExecutionMode::ACCURACY;
 };
 // ! [configuration:header]
 
diff --git a/src/plugins/template/src/plugin.cpp b/src/plugins/template/src/plugin.cpp
index bcdd9b5ec3a0b4..2261204e5d7833 100644
--- a/src/plugins/template/src/plugin.cpp
+++ b/src/plugins/template/src/plugin.cpp
@@ -233,6 +233,10 @@ ov::Any ov::template_plugin::Plugin::get_property(const std::string& name, const
         std::vector<ov::PropertyName> rw_properties{ov::device::id,
                                                     ov::enable_profiling,
                                                     ov::hint::performance_mode,
+                                                    ov::hint::num_requests,
+                                                    ov::hint::inference_precision,
+                                                    ov::hint::execution_mode,
+                                                    ov::num_streams,
                                                     ov::template_plugin::disable_transformations};
         return rw_properties;
     };
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/properties.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/properties.cpp
index f180776721f23e..64b6fc0c1722b1 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/properties.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/properties.cpp
@@ -34,7 +34,7 @@ INSTANTIATE_TEST_SUITE_P(smoke_AutoBatch_BehaviorTests,
                          OVClassCompiledModelPropertiesIncorrectTests::getTestCaseName);
 
 const std::vector<ov::AnyMap> default_properties = {
-    {ov::enable_profiling(true)},
+    {ov::enable_profiling(false)},
     {{ov::loaded_from_cache.name(), false}},
     {ov::device::id("0")},
 };
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/properties_tests.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/properties_tests.cpp
index 03d05b6ea9f9bf..0f05a09f4da99d 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/properties_tests.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/properties_tests.cpp
@@ -22,7 +22,7 @@ INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
                          OVPropertiesIncorrectTests::getTestCaseName);
 
 const std::vector<ov::AnyMap> default_properties = {
-    {ov::enable_profiling(true)},
+    {ov::enable_profiling(false)},
     {ov::device::id(0)},
 };
 
diff --git a/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_executable_network/properties.cpp b/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_executable_network/properties.cpp
index 5efdb3dba35e0d..bb361ab03088d8 100644
--- a/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_executable_network/properties.cpp
+++ b/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_executable_network/properties.cpp
@@ -70,4 +70,15 @@ INSTANTIATE_TEST_SUITE_P(
 INSTANTIATE_TEST_SUITE_P(ov_plugin_mandatory, OVCompiledModelIncorrectDevice,
         ::testing::Values(targetDevice));
 
+const std::vector<ov::AnyMap> multiModelPriorityConfigs = {
+        {ov::hint::model_priority(ov::hint::Priority::HIGH)},
+        {ov::hint::model_priority(ov::hint::Priority::MEDIUM)},
+        {ov::hint::model_priority(ov::hint::Priority::LOW)},
+        {ov::hint::model_priority(ov::hint::Priority::DEFAULT)}};
+
+INSTANTIATE_TEST_SUITE_P(ov_compiled_model_mandatory,
+                         OVClassCompiledModelGetPropertyTest_MODEL_PRIORITY,
+                         ::testing::Combine(::testing::ValuesIn(return_all_possible_device_combination()),
+                                            ::testing::ValuesIn(multiModelPriorityConfigs)));
+
 } // namespace
diff --git a/src/tests/functional/plugin/shared/src/behavior/ov_plugin/properties_tests.cpp b/src/tests/functional/plugin/shared/src/behavior/ov_plugin/properties_tests.cpp
index 82affbe613bec0..b5cbff685b6340 100644
--- a/src/tests/functional/plugin/shared/src/behavior/ov_plugin/properties_tests.cpp
+++ b/src/tests/functional/plugin/shared/src/behavior/ov_plugin/properties_tests.cpp
@@ -254,13 +254,6 @@ std::vector<ov::AnyMap> OVPropertiesTestsWithCompileModelProps::getRWMandatoryPr
         }
     }
 
-    if (props.empty() || std::find(props.begin(), props.end(), ov::hint::model_priority.name()) != props.end()) {
-        ov::hint::Priority priorities[] = {ov::hint::Priority::LOW , ov::hint::Priority::MEDIUM, ov::hint::Priority::HIGH};
-        for (auto &priority : priorities) {
-            res.push_back({{ov::hint::model_priority(priority)}});
-        }
-    }
-
     if (props.empty() || std::find(props.begin(), props.end(), ov::hint::performance_mode.name()) != props.end()) {
         ov::hint::PerformanceMode performance_modes[] = {ov::hint::PerformanceMode::LATENCY,
                 ov::hint::PerformanceMode::THROUGHPUT, ov::hint::PerformanceMode::CUMULATIVE_THROUGHPUT};

From 9c4bc1cc2b955e76b350616fe12ce92de2b862a0 Mon Sep 17 00:00:00 2001
From: Zhang Yi <yi3.zhang@intel.com>
Date: Tue, 19 Sep 2023 14:30:33 +0800
Subject: [PATCH 11/46] [CPU] Fix OMP thread count for MLAS ThreadPool
 initialization (#19731)

---
 src/plugins/intel_cpu/src/mlas/sgemm.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/plugins/intel_cpu/src/mlas/sgemm.cpp b/src/plugins/intel_cpu/src/mlas/sgemm.cpp
index 2b3ebf9ecf9a9f..b2c868ddb1ba55 100644
--- a/src/plugins/intel_cpu/src/mlas/sgemm.cpp
+++ b/src/plugins/intel_cpu/src/mlas/sgemm.cpp
@@ -54,7 +54,7 @@ void mlas_sgemm(const char* transa,
     sgemmParam.beta = beta;
     auto _transa = *transa == 'N' ? CblasNoTrans : CblasTrans;
     auto _transb = *transb == 'N' ? CblasNoTrans : CblasTrans;
-    ov::cpu::OVMlasThreadPool threadPool(0 == thread_num ? parallel_get_num_threads() : thread_num);
+    ov::cpu::OVMlasThreadPool threadPool(0 == thread_num ? parallel_get_max_threads() : thread_num);
     MlasGemmBatch(_transa, _transb, M, N, K, &sgemmParam, 1, &threadPool);
 }
 
@@ -74,7 +74,7 @@ void mlas_sgemm_compute(const char* transa,
                         const float* bias,
                         size_t thread_num) {
     // C = alpha*op( A )op( B ) + beta * C
-    ov::cpu::OVMlasThreadPool threadPool(0 == thread_num ? parallel_get_num_threads() : thread_num);
+    ov::cpu::OVMlasThreadPool threadPool(0 == thread_num ? parallel_get_max_threads() : thread_num);
     MLAS_SGEMM_DATA_PARAMS sgemmParam;
     sgemmParam.BIsPacked = true;
     sgemmParam.A = A;

From e961ce307be7820f8cb333f0cda5a2e12a031a53 Mon Sep 17 00:00:00 2001
From: Chenhu Wang <chenhu.wang@intel.com>
Date: Tue, 19 Sep 2023 14:41:38 +0800
Subject: [PATCH 12/46] [CPU] Eliminate dependency for emitters tails process
 (#19527)

---
 .../src/emitters/x64/jit_load_store_emitters.cpp     | 12 ++++++++++++
 1 file changed, 12 insertions(+)

diff --git a/src/plugins/intel_cpu/src/emitters/x64/jit_load_store_emitters.cpp b/src/plugins/intel_cpu/src/emitters/x64/jit_load_store_emitters.cpp
index ce09fb071ea4ce..67159c582b0d33 100644
--- a/src/plugins/intel_cpu/src/emitters/x64/jit_load_store_emitters.cpp
+++ b/src/plugins/intel_cpu/src/emitters/x64/jit_load_store_emitters.cpp
@@ -234,6 +234,18 @@ void jit_load_emitter::load_bytes(const Vmm &vmm, const Xbyak::Reg64 &reg, int o
             has_xmm_block = true;
         }
 
+        // Cornerstone of partial load is combinaion of vpinsrb/w/d.
+        // As vpinsrb/w/d will not only write(insert) values into vmm, but also read values in vmm to copy from to positions that not in imm mask,
+        // this could introduce RAW false dependency(we actually do not care about values not in imm mask).
+        // To eliminate this false dependency,
+        // 1. For 1/2/3/4 bytes tails, replace vpinsrb/w/d with mov,shl etc instructions that don't read vmm.
+        //    Besides eliminate RAW, these instructions have smaller latency, which also bring better perf, especially for small loop iteration case.
+        // 2. For 8/16 bytes, use vmovq/vmovdqu instructions to load, which also don't read src vmm.
+        // 3. For other size, insert vpxor before vpinsrb/w/d. vpxor and read vmm instructions in previous loop have WAR(write after read) relationship.
+        //    CPU can identify this scenario and assign another physical vector register(register renameing) in next loop to eliminate RAW.
+        if (!one_of(bytes_to_load, 0, 1, 2, 3, 4, 8, 16)) {
+            h->uni_vpxor(vmm, vmm, vmm);
+        }
         if (bytes_to_load >= 8 && bytes_to_load < 16)
             h->uni_vmovq(xmm, addr(start_bytes));
         else if (bytes_to_load == 16)

From 933d9c1c0abe9c33f4ee330eec95e2035016459c Mon Sep 17 00:00:00 2001
From: Karol Blaszczak <karol.blaszczak@intel.com>
Date: Tue, 19 Sep 2023 08:56:45 +0200
Subject: [PATCH 13/46] [DOCS] OVC docs adjustments  (#19918) (#19924)

authored-by: Tatiana Savina <tatiana.savina@intel.com>
---
 docs/Documentation/model_introduction.md                      | 2 +-
 .../prepare_model/convert_model/Convert_Model_From_Paddle.md  | 2 +-
 .../prepare_model/convert_model/Convert_Model_From_PyTorch.md | 4 ++--
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/docs/Documentation/model_introduction.md b/docs/Documentation/model_introduction.md
index cd24fccbec8dfe..cadd407ba0b6a6 100644
--- a/docs/Documentation/model_introduction.md
+++ b/docs/Documentation/model_introduction.md
@@ -221,7 +221,7 @@ The figure below illustrates the typical workflow for deploying a trained deep-l
 Convert a Model in CLI: ``ovc``
 ###############################
 
-Another option for model conversion is to use ``ovc`` command-line tool, which stands for OpenVINO Model Converter. The tool combines both ``openvino.convert_model`` and ``openvino.save_model`` functionalities. It is convenient to use when the original model is ready for inference and is in one of the supported file formats: ONNX, TensorFlow, TensorFlow Lite, or PaddlePaddle. As a result, ``ovc`` produces an OpenVINO IR, consisting of ``.xml`` and ``.bin`` files, which needs to be read with the ``ov.read_model()`` method. You can compile and infer the ``ov.Model`` later with :doc:`OpenVINO™ Runtime <openvino_docs_OV_UG_OV_Runtime_User_Guide>`
+Another option for model conversion is to use ``ovc`` command-line tool, which stands for OpenVINO Model Converter. The tool combines both ``openvino.convert_model`` and ``openvino.save_model`` functionalities. It is convenient to use when the original model is ready for inference and is in one of the supported file formats: ONNX, TensorFlow, TensorFlow Lite, or PaddlePaddle. As a result, ``ovc`` produces an OpenVINO IR, consisting of ``.xml`` and ``.bin`` files, which needs to be read with the ``openvino.Core.read_model`` method. You can compile and infer the ``ov.Model`` later with :doc:`OpenVINO™ Runtime <openvino_docs_OV_UG_OV_Runtime_User_Guide>`
 
 .. note::
    PyTorch models cannot be converted with ``ovc``, use ``openvino.convert_model`` instead.
diff --git a/docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_Paddle.md b/docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_Paddle.md
index dd3f821229bf99..8b4c549547ebbd 100644
--- a/docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_Paddle.md
+++ b/docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_Paddle.md
@@ -89,7 +89,7 @@ Some PaddlePaddle models may require setting ``example_input`` or ``output`` for
 
 * Example of converting ``paddle.fluid.dygraph.layers.Layer`` format model:
 
-  ``example_input`` is required while ``output`` is optional, which accept the following formats:
+  ``example_input`` is required while ``output`` is optional.  ``example_input`` accepts the following formats:
 
   ``list`` with tensor (``paddle.Tensor``) or InputSpec (``paddle.static.input.InputSpec``)
 
diff --git a/docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_PyTorch.md b/docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_PyTorch.md
index 83005b7e978e8c..6fcd6d7c03aaa8 100644
--- a/docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_PyTorch.md
+++ b/docs/OV_Converter_UG/prepare_model/convert_model/Convert_Model_From_PyTorch.md
@@ -40,8 +40,8 @@ The value for the ``example_input`` parameter can be easily derived from knowing
    import torch
    import openvino as ov
 
-   model = torchvision.models.resnet50(pretrained=True)
-   ov_model = ov.convert_model(model, example_input=example_input=torch.rand(1, 3, 224, 224))
+   model = torchvision.models.resnet50(weights='DEFAULT')
+   ov_model = ov.convert_model(model, example_input=torch.rand(1, 3, 224, 224))
 
 In practice, the code to evaluate or test the PyTorch model is usually provided with the model itself and can be used to generate a proper ``example_input`` value. A modified example of using ``resnet50`` model from ``torchvision`` is presented below. It demonstrates how to switch inference in the existing PyTorch application to OpenVINO and how to get value for ``example_input``:
 

From e34f3a1feef0e71633f510d1bd1c98e52b8bc9bd Mon Sep 17 00:00:00 2001
From: River Li <river.li@intel.com>
Date: Tue, 19 Sep 2023 15:13:57 +0800
Subject: [PATCH 14/46] Fix warning in template plugin (#19932)

---
 src/plugins/template/src/compiled_model.cpp          | 10 ----------
 src/plugins/template/src/plugin.cpp                  | 10 ----------
 .../template/tests/functional/op_reference/loop.cpp  |  4 ++--
 .../tests/functional/op_reference/memory.cpp         |  1 -
 .../subgraph_reference/preprocess_legacy.cpp         | 12 ------------
 5 files changed, 2 insertions(+), 35 deletions(-)

diff --git a/src/plugins/template/src/compiled_model.cpp b/src/plugins/template/src/compiled_model.cpp
index e550bd1e6571bb..3227621305741f 100644
--- a/src/plugins/template/src/compiled_model.cpp
+++ b/src/plugins/template/src/compiled_model.cpp
@@ -126,9 +126,6 @@ std::shared_ptr<const ov::template_plugin::Plugin> ov::template_plugin::Compiled
 
 // ! [compiled_model:get_property]
 ov::Any ov::template_plugin::CompiledModel::get_property(const std::string& name) const {
-    const auto& add_ro_properties = [](const std::string& name, std::vector<ov::PropertyName>& properties) {
-        properties.emplace_back(ov::PropertyName{name, ov::PropertyMutability::RO});
-    };
     const auto& default_ro_properties = []() {
         std::vector<ov::PropertyName> ro_properties{ov::model_name,
                                                     ov::supported_properties,
@@ -141,13 +138,6 @@ ov::Any ov::template_plugin::CompiledModel::get_property(const std::string& name
         std::vector<ov::PropertyName> rw_properties{ov::device::id, ov::enable_profiling};
         return rw_properties;
     };
-    const auto& to_string_vector = [](const std::vector<ov::PropertyName>& properties) {
-        std::vector<std::string> ret;
-        for (const auto& property : properties) {
-            ret.emplace_back(property);
-        }
-        return ret;
-    };
     if (ov::model_name == name) {
         auto model_name = m_model->get_friendly_name();
         return decltype(ov::model_name)::value_type(model_name);
diff --git a/src/plugins/template/src/plugin.cpp b/src/plugins/template/src/plugin.cpp
index 2261204e5d7833..e1f3f114715222 100644
--- a/src/plugins/template/src/plugin.cpp
+++ b/src/plugins/template/src/plugin.cpp
@@ -217,9 +217,6 @@ void ov::template_plugin::Plugin::set_property(const ov::AnyMap& properties) {
 
 // ! [plugin:get_property]
 ov::Any ov::template_plugin::Plugin::get_property(const std::string& name, const ov::AnyMap& arguments) const {
-    const auto& add_ro_properties = [](const std::string& name, std::vector<ov::PropertyName>& properties) {
-        properties.emplace_back(ov::PropertyName{name, ov::PropertyMutability::RO});
-    };
     const auto& default_ro_properties = []() {
         std::vector<ov::PropertyName> ro_properties{ov::available_devices,
                                                     ov::supported_properties,
@@ -240,13 +237,6 @@ ov::Any ov::template_plugin::Plugin::get_property(const std::string& name, const
                                                     ov::template_plugin::disable_transformations};
         return rw_properties;
     };
-    const auto& to_string_vector = [](const std::vector<ov::PropertyName>& properties) {
-        std::vector<std::string> ret;
-        for (const auto& property : properties) {
-            ret.emplace_back(property);
-        }
-        return ret;
-    };
     if (ov::supported_properties == name) {
         auto ro_properties = default_ro_properties();
         auto rw_properties = default_rw_properties();
diff --git a/src/plugins/template/tests/functional/op_reference/loop.cpp b/src/plugins/template/tests/functional/op_reference/loop.cpp
index 3a760b0b8095b0..3e7f9ad63b51bf 100644
--- a/src/plugins/template/tests/functional/op_reference/loop.cpp
+++ b/src/plugins/template/tests/functional/op_reference/loop.cpp
@@ -153,7 +153,7 @@ struct LoopStaticInputs : public LoopFunctionalBase {
 
         // Body
         std::shared_ptr<ov::Node> Zo = body_params[0];
-        for (int i = 1; i < body_params.size(); ++i) {
+        for (size_t i = 1; i < body_params.size(); ++i) {
             Zo = std::make_shared<ov::opset8::Add>(body_params[i], Zo);
         }
 
@@ -164,7 +164,7 @@ struct LoopStaticInputs : public LoopFunctionalBase {
         loop->set_function(body);
         loop->set_special_body_ports(ov::opset8::Loop::SpecialBodyPorts{-1, 0});
 
-        for (int i = 0; i < body_params.size(); ++i) {
+        for (size_t i = 0; i < body_params.size(); ++i) {
             if (loop_in_type[i] == LOOP_IN_TYPE::INVARIANT) {
                 loop->set_invariant_input(body_params[i], loop_params[i]);
             } else if (loop_in_type[i] == LOOP_IN_TYPE::MERGED) {
diff --git a/src/plugins/template/tests/functional/op_reference/memory.cpp b/src/plugins/template/tests/functional/op_reference/memory.cpp
index f0492964cab1ce..01c7a321b53e5e 100644
--- a/src/plugins/template/tests/functional/op_reference/memory.cpp
+++ b/src/plugins/template/tests/functional/op_reference/memory.cpp
@@ -286,7 +286,6 @@ class ReferenceMemoryTest : public testing::TestWithParam<MemoryTestParams> {
     void CommonTestSteps(const std::function<void(size_t, ov::InferRequest&)>& custom_step = nullptr) {
         auto params = GetParam();
 
-        const auto& functionParams = function->get_parameters();
         inferRequest.set_tensor(executableNetwork.input(0), params.m_input_data);
         for (size_t i = 0; i < params.m_count_runs; ++i) {
             if (custom_step) {
diff --git a/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp b/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
index f4f984726b81ba..574b8f618be473 100644
--- a/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
+++ b/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
@@ -41,18 +41,6 @@ static std::shared_ptr<Model> create_simple_function(element::Type type, const P
     return std::make_shared<ov::Model>(ResultVector{res}, ParameterVector{data1});
 }
 
-static std::shared_ptr<Model> create_simple_function_yuv(const PartialShape& shape) {
-    auto data1 = std::make_shared<op::v0::Parameter>(element::u8, shape);
-    data1->set_friendly_name("input1");
-    data1->get_output_tensor(0).set_names({"tensor_input1", "input1"});
-    auto op = std::make_shared<op::v0::Convert>(data1, element::f32);
-    op->set_friendly_name("Convert1");
-    auto res = std::make_shared<op::v0::Result>(op);
-    res->set_friendly_name("Result1");
-    res->get_output_tensor(0).set_names({"tensor_output1", "Result1", "Convert1"});
-    return std::make_shared<ov::Model>(ResultVector{res}, ParameterVector{data1});
-}
-
 TEST_F(ReferencePreprocessLegacyTest, mean) {
     function = create_simple_function(element::f32, Shape{1, 3, 2, 2});
     auto p = PrePostProcessor(function);

From 475ad32cc43a9689a6a40f578db59f560c1df526 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 19 Sep 2023 11:19:35 +0400
Subject: [PATCH 15/46] Update numpy requirement in /src/bindings/python
 (#19897)

Updates the requirements on [numpy](https://github.com/numpy/numpy) to permit the latest version.
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst)
- [Commits](https://github.com/numpy/numpy/compare/v1.16.6...v1.26.0)

---
updated-dependencies:
- dependency-name: numpy
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
---
 src/bindings/python/constraints.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/bindings/python/constraints.txt b/src/bindings/python/constraints.txt
index 30be494ea327bc..1762fa681551d3 100644
--- a/src/bindings/python/constraints.txt
+++ b/src/bindings/python/constraints.txt
@@ -1,5 +1,5 @@
 # used in multiple components
-numpy>=1.16.6,<1.26  # Python bindings, frontends
+numpy>=1.16.6,<1.27  # Python bindings, frontends
 
 # pytest
 pytest>=5.0,<7.5

From 6b5a22a656ba976ea2bcb5152845a7857e870822 Mon Sep 17 00:00:00 2001
From: Vitaliy Urusovskij <vitaliy.urusovskij@intel.com>
Date: Tue, 19 Sep 2023 11:27:23 +0400
Subject: [PATCH 16/46] Add `bert-base-ner` in MemLeak tests (#19817)

* Add `bert-base-ner` in MemLeak tests

* Fix segfault caused by `fillTensorRandom()`
---
 tests/lib/src/common_utils.h                  | 88 ++++++++++---------
 .../nightly_configs/desktop_test_config.xml   |  8 ++
 .../precommit_configs/desktop_test_config.xml |  8 ++
 .../weekly_configs/desktop_test_config.xml    | 10 ++-
 4 files changed, 73 insertions(+), 41 deletions(-)

diff --git a/tests/lib/src/common_utils.h b/tests/lib/src/common_utils.h
index ac15570f38ce2e..a3bd72d844ff5d 100644
--- a/tests/lib/src/common_utils.h
+++ b/tests/lib/src/common_utils.h
@@ -10,6 +10,13 @@
 #include <random>
 
 
+template <typename T>
+using uniformDistribution = typename std::conditional<
+    std::is_floating_point<T>::value,
+    std::uniform_real_distribution<T>,
+    typename std::conditional<std::is_integral<T>::value, std::uniform_int_distribution<T>, void>::type>::type;
+
+
 /**
  * @brief Determine if InferenceEngine blob means image or not (OV API 1.0)
  */
@@ -84,27 +91,20 @@ void fillBlobRandom(InferenceEngine::Blob::Ptr &inputBlob) {
 /**
  * @brief Fill InferenceEngine tensor with random values (OV API 2.0)
  */
-template<typename T, typename U>
-ov::Tensor fillTensorRandom(T &input) {
-    ov::Tensor tensor{input.get_element_type(), input.get_shape()};
-    std::vector<U> values(ov::shape_size(input.get_shape()));
-
-    std::random_device rd;
-    std::mt19937 gen(rd());
-
-    if (std::is_floating_point<U>::value == true) {
-        std::uniform_real_distribution<> distrib_f = std::uniform_real_distribution<>(0, std::numeric_limits<U>::max());
-        for (size_t i = 0; i < values.size(); ++i)
-            values[i] = distrib_f(gen);
-    } else {
-        std::uniform_int_distribution<> distrib_i = std::uniform_int_distribution<>(0, std::numeric_limits<U>::max());
-        for (size_t i = 0; i < values.size(); ++i)
-            values[i] = distrib_i(gen);
+template<typename T, typename T2>
+void fillTensorRandom(ov::Tensor& tensor,
+                      T rand_min = std::numeric_limits<uint8_t>::min(),
+                      T rand_max = std::numeric_limits<uint8_t>::max()) {
+    std::mt19937 gen(0);
+    size_t tensor_size = tensor.get_size();
+    if (0 == tensor_size) {
+        throw std::runtime_error(
+            "Models with dynamic shapes aren't supported. Input tensors must have specific shapes before inference");
     }
-
-    std::memcpy(tensor.data(), values.data(), sizeof(U) * values.size());
-
-    return tensor;
+    T* data = tensor.data<T>();
+    uniformDistribution<T2> distribution(rand_min, rand_max);
+    for (size_t i = 0; i < tensor_size; i++)
+        data[i] = static_cast<T>(distribution(gen));
 }
 
 
@@ -141,26 +141,34 @@ void fillBlobImInfo(InferenceEngine::Blob::Ptr &inputBlob,
 template<typename T>
 void fillTensors(ov::InferRequest &infer_request, std::vector<T> &inputs) {
     for (size_t i = 0; i < inputs.size(); ++i) {
-        ov::Tensor input_tensor;
-
-        if (inputs[i].get_element_type() == ov::element::f32) {
-            input_tensor = fillTensorRandom<T, float>(inputs[i]);
-        } else if (inputs[i].get_element_type() == ov::element::f64) {
-            input_tensor = fillTensorRandom<T, double>(inputs[i]);
-        } else if (inputs[i].get_element_type() == ov::element::f16) {
-            input_tensor = fillTensorRandom<T, short>(inputs[i]);
-        } else if (inputs[i].get_element_type() == ov::element::i32) {
-            input_tensor = fillTensorRandom<T, int32_t>(inputs[i]);
-        } else if (inputs[i].get_element_type() == ov::element::i64) {
-            input_tensor = fillTensorRandom<T, int64_t>(inputs[i]);
-        } else if (inputs[i].get_element_type() == ov::element::u8) {
-            input_tensor = fillTensorRandom<T, uint8_t>(inputs[i]);
-        } else if (inputs[i].get_element_type() == ov::element::i8) {
-            input_tensor = fillTensorRandom<T, int8_t>(inputs[i]);
-        } else if (inputs[i].get_element_type() == ov::element::u16) {
-            input_tensor = fillTensorRandom<T, uint16_t>(inputs[i]);
-        } else if (inputs[i].get_element_type() == ov::element::i16) {
-            input_tensor = fillTensorRandom<T, int16_t>(inputs[i]);
+        auto input_tensor = infer_request.get_tensor(inputs[i]);
+        auto type = inputs[i].get_element_type();
+        if (type == ov::element::f32) {
+            fillTensorRandom<float, float>(input_tensor);
+        } else if (type == ov::element::f64) {
+            fillTensorRandom<double, double>(input_tensor);
+        } else if (type == ov::element::f16) {
+            fillTensorRandom<ov::float16, float>(input_tensor);
+        } else if (type == ov::element::i32) {
+            fillTensorRandom<int32_t, int32_t>(input_tensor);
+        } else if (type == ov::element::i64) {
+            fillTensorRandom<int64_t, int64_t>(input_tensor);
+        } else if ((type == ov::element::u8) || (type == ov::element::boolean)) {
+            // uniform_int_distribution<uint8_t> is not allowed in the C++17
+            // standard and vs2017/19
+            fillTensorRandom<uint8_t, uint32_t>(input_tensor);
+        } else if (type == ov::element::i8) {
+            // uniform_int_distribution<int8_t> is not allowed in the C++17 standard
+            // and vs2017/19
+            fillTensorRandom<int8_t, int32_t>(input_tensor,
+                                              std::numeric_limits<int8_t>::min(),
+                                              std::numeric_limits<int8_t>::max());
+        } else if (type == ov::element::u16) {
+            fillTensorRandom<uint16_t, uint16_t>(input_tensor);
+        } else if (type == ov::element::i16) {
+            fillTensorRandom<int16_t, int16_t>(input_tensor);
+        } else if (type == ov::element::boolean) {
+            fillTensorRandom<uint8_t, uint32_t>(input_tensor, 0, 1);
         } else {
             throw std::logic_error(
                     "Input precision is not supported for " + inputs[i].get_element_type().get_type_name());
diff --git a/tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml b/tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml
index 3058ceaa5f51a6..cca3ec23df13c8 100644
--- a/tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml
+++ b/tests/stress_tests/.automation/memleaks_tests/nightly_configs/desktop_test_config.xml
@@ -24,6 +24,14 @@
         <model name="mtcnn-r" precision="FP32" source="omz" />
     </device>
 
+    <device name="CPU" iterations="1000" processes="1" threads="1">
+        <model name="bert-base-ner" precision="FP32" source="omz" />
+    </device>
+
+    <device name="GPU" iterations="1000" processes="1" threads="1">
+        <model name="bert-base-ner" precision="FP32" source="omz" />
+    </device>
+
     <device name="CPU" iterations="1000" processes="1" threads="1">
         <model name="alexnet" precision="FP32" source="omz" />
         <model name="mobilenet-ssd" precision="FP32" source="omz" />
diff --git a/tests/stress_tests/.automation/memleaks_tests/precommit_configs/desktop_test_config.xml b/tests/stress_tests/.automation/memleaks_tests/precommit_configs/desktop_test_config.xml
index 4909b6411f1fa9..29d54db3f3c142 100644
--- a/tests/stress_tests/.automation/memleaks_tests/precommit_configs/desktop_test_config.xml
+++ b/tests/stress_tests/.automation/memleaks_tests/precommit_configs/desktop_test_config.xml
@@ -8,4 +8,12 @@
         <model name="mobilenet-ssd" precision="FP32" source="omz" />
     </device>
 
+    <device name="CPU" iterations="30" processes="1" threads="1">
+        <model name="bert-base-ner" precision="FP32" source="omz" />
+    </device>
+
+    <device name="GPU" iterations="30" processes="1" threads="1">
+        <model name="bert-base-ner" precision="FP32" source="omz" />
+    </device>
+
 </cases>
diff --git a/tests/stress_tests/.automation/memleaks_tests/weekly_configs/desktop_test_config.xml b/tests/stress_tests/.automation/memleaks_tests/weekly_configs/desktop_test_config.xml
index d9240cc239aaec..57fd6c160caa60 100644
--- a/tests/stress_tests/.automation/memleaks_tests/weekly_configs/desktop_test_config.xml
+++ b/tests/stress_tests/.automation/memleaks_tests/weekly_configs/desktop_test_config.xml
@@ -23,7 +23,15 @@
     <device name="GPU" iterations="5000" processes="1" threads="1">
         <model name="mtcnn-r" precision="FP32" source="omz" />
     </device>
-    
+
+    <device name="CPU" iterations="5000" processes="1" threads="1">
+        <model name="bert-base-ner" precision="FP32" source="omz" />
+    </device>
+
+    <device name="GPU" iterations="5000" processes="1" threads="1">
+        <model name="bert-base-ner" precision="FP32" source="omz" />
+    </device>
+
     <device name="CPU" iterations="5000" processes="1" threads="1">
         <model name="alexnet" precision="FP32" source="omz" />
         <model name="mobilenet-ssd" precision="FP32" source="omz" />

From 068cd4473d076c8a985899a0c62fe1acbf251c3a Mon Sep 17 00:00:00 2001
From: Oleg Pipikin <oleg.pipikin@intel.com>
Date: Tue, 19 Sep 2023 09:40:29 +0200
Subject: [PATCH 17/46] Refactor AdaPool, BatchToSpace, and BatchNorm shared
 tests (#19597)

* Refactor AdaPool, BatchToSpace, and BatchNorm shared tests
---
 .../single_layer_tests/adaptive_pooling.cpp   | 65 +++++++++--------
 .../single_layer_tests/batch_norm.cpp         | 36 +++++-----
 .../single_layer_tests/batch_to_space.cpp     | 71 +++++++------------
 .../single_layer_tests/adaptive_pooling.hpp   |  2 +-
 .../single_op_tests/adaptive_pooling.hpp      | 15 ++++
 .../include/single_op_tests/batch_norm.hpp    | 15 ++++
 .../single_op_tests/batch_to_space.hpp        | 17 +++++
 .../single_op/adaptive_pooling.hpp            | 27 +++++++
 .../single_op/batch_norm.hpp                  | 27 +++++++
 .../single_op/batch_to_space.hpp              | 32 +++++++++
 .../single_op/comparison.hpp                  |  2 -
 .../single_op/gru_sequence.hpp                |  3 -
 .../src/base/utils/generate_inputs.cpp        | 45 ++++++++++++
 .../src/single_op/adaptive_pooling.cpp        | 60 ++++++++++++++++
 .../src/single_op/batch_norm.cpp              | 61 ++++++++++++++++
 .../src/single_op/batch_to_space.cpp          | 53 ++++++++++++++
 .../src/single_op/comparison.cpp              | 36 +---------
 .../src/single_op/gru_sequence.cpp            | 29 +++-----
 18 files changed, 440 insertions(+), 156 deletions(-)
 create mode 100644 src/tests/functional/plugin/shared/include/single_op_tests/adaptive_pooling.hpp
 create mode 100644 src/tests/functional/plugin/shared/include/single_op_tests/batch_norm.hpp
 create mode 100644 src/tests/functional/plugin/shared/include/single_op_tests/batch_to_space.hpp
 create mode 100644 src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/adaptive_pooling.hpp
 create mode 100644 src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/batch_norm.hpp
 create mode 100644 src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/batch_to_space.hpp
 create mode 100644 src/tests/functional/shared_test_classes/src/single_op/adaptive_pooling.cpp
 create mode 100644 src/tests/functional/shared_test_classes/src/single_op/batch_norm.cpp
 create mode 100644 src/tests/functional/shared_test_classes/src/single_op/batch_to_space.cpp

diff --git a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/adaptive_pooling.cpp b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/adaptive_pooling.cpp
index d4d87b825e7164..837844e4fcf625 100644
--- a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/adaptive_pooling.cpp
+++ b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/adaptive_pooling.cpp
@@ -4,55 +4,62 @@
 
 #include <vector>
 
-#include "single_layer_tests/adaptive_pooling.hpp"
+#include "single_op_tests/adaptive_pooling.hpp"
 #include "common_test_utils/test_constants.hpp"
 
-using namespace LayerTestsDefinitions;
+namespace {
+using ov::test::AdaPoolLayerTest;
 
+const std::vector<ov::element::Type> types = {
+        ov::element::f16,
+        ov::element::f32
+};
 
-const std::vector<InferenceEngine::Precision> netPRCs = {
-        InferenceEngine::Precision::FP16,
-        InferenceEngine::Precision::FP32
+const std::vector<std::vector<ov::Shape>> input_shapes_3d_static = {
+        {{ 1, 2, 1}},
+        {{ 1, 1, 3 }},
+        {{ 3, 17, 5 }}
 };
 
-const auto AdaPool3DCases = ::testing::Combine(
-        ::testing::ValuesIn(
-                std::vector<std::vector<size_t>> {
-                        { 1, 2, 1},
-                        { 1, 1, 3 },
-                        { 3, 17, 5 }}),
+const auto ada_pool_3d_cases = ::testing::Combine(
+        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(input_shapes_3d_static)),
         ::testing::ValuesIn(std::vector<std::vector<int>>{ {1}, {3}, {5} }),
         ::testing::ValuesIn(std::vector<std::string>{"max", "avg"}),
-        ::testing::ValuesIn(netPRCs),
+        ::testing::ValuesIn(types),
         ::testing::Values(ov::test::utils::DEVICE_CPU)
 );
 
-INSTANTIATE_TEST_SUITE_P(smoke_TestsAdaPool3D, AdaPoolLayerTest, AdaPool3DCases, AdaPoolLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TestsAdaPool3D, AdaPoolLayerTest, ada_pool_3d_cases, AdaPoolLayerTest::getTestCaseName);
+
+const std::vector<std::vector<ov::Shape>> input_shapes_4d_static = {
+        {{ 1, 2, 1, 2 }},
+        {{ 1, 1, 3, 2 }},
+        {{ 3, 17, 5, 1 }}
+};
 
-const auto AdaPool4DCases = ::testing::Combine(
-        ::testing::ValuesIn(
-                std::vector<std::vector<size_t>> {
-                        { 1, 2, 1, 2},
-                        { 1, 1, 3, 2},
-                        { 3, 17, 5, 1}}),
+const auto ada_pool_4d_cases = ::testing::Combine(
+        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(input_shapes_4d_static)),
         ::testing::ValuesIn(std::vector<std::vector<int>>{ {1, 1}, {3, 5}, {5, 5} }),
         ::testing::ValuesIn(std::vector<std::string>{"max", "avg"}),
-        ::testing::ValuesIn(netPRCs),
+        ::testing::ValuesIn(types),
         ::testing::Values(ov::test::utils::DEVICE_CPU)
 );
 
-INSTANTIATE_TEST_SUITE_P(smoke_TestsAdaPool4D, AdaPoolLayerTest, AdaPool4DCases, AdaPoolLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TestsAdaPool4D, AdaPoolLayerTest, ada_pool_4d_cases, AdaPoolLayerTest::getTestCaseName);
+
+const std::vector<std::vector<ov::Shape>> input_shapes_5d_static = {
+        {{ 1, 2, 1, 2, 2 }},
+        {{ 1, 1, 3, 2, 3 }},
+        {{ 3, 17, 5, 1, 2 }}
+};
 
-const auto AdaPool5DCases = ::testing::Combine(
-        ::testing::ValuesIn(
-                std::vector<std::vector<size_t>> {
-                        { 1, 2, 1, 2, 2},
-                        { 1, 1, 3, 2, 3},
-                        { 3, 17, 5, 1, 2}}),
+const auto ada_pool_5d_cases = ::testing::Combine(
+        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(input_shapes_5d_static)),
         ::testing::ValuesIn(std::vector<std::vector<int>>{ {1, 1, 1}, {3, 5, 3}, {5, 5, 5} }),
         ::testing::ValuesIn(std::vector<std::string>{"max", "avg"}),
-        ::testing::ValuesIn(netPRCs),
+        ::testing::ValuesIn(types),
         ::testing::Values(ov::test::utils::DEVICE_CPU)
 );
 
-INSTANTIATE_TEST_SUITE_P(smoke_TestsAdaPool5D, AdaPoolLayerTest, AdaPool5DCases, AdaPoolLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TestsAdaPool5D, AdaPoolLayerTest, ada_pool_5d_cases, AdaPoolLayerTest::getTestCaseName);
+} //  namespace
diff --git a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/batch_norm.cpp b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/batch_norm.cpp
index 467e32c26689d2..a7850b4e94329c 100644
--- a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/batch_norm.cpp
+++ b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/batch_norm.cpp
@@ -4,14 +4,14 @@
 
 #include <vector>
 
-#include "single_layer_tests/batch_norm.hpp"
-
-using namespace LayerTestsDefinitions;
+#include "single_op_tests/batch_norm.hpp"
 
 namespace {
-const std::vector<InferenceEngine::Precision> netPrecisions = {
-        InferenceEngine::Precision::FP32,
-        InferenceEngine::Precision::FP16
+using ov::test::BatchNormLayerTest;
+
+const std::vector<ov::element::Type> model_type = {
+        ov::element::f32,
+        ov::element::f16
 };
 
 const std::vector<double> epsilon = {
@@ -20,30 +20,26 @@ const std::vector<double> epsilon = {
     1e-5,
     1e-4
 };
-const std::vector<std::vector<size_t>> inputShapes = {
-        {1, 3},
-        {2, 5},
-        {1, 3, 10},
-        {1, 3, 1, 1},
-        {2, 5, 4, 4},
+const std::vector<std::vector<ov::Shape>> input_shapes_static = {
+        {{1, 3}},
+        {{2, 5}},
+        {{1, 3, 10}},
+        {{1, 3, 1, 1}},
+        {{2, 5, 4, 4}},
 };
 
 
-const auto batchNormParams = testing::Combine(
+const auto batch_norm_params = testing::Combine(
         testing::ValuesIn(epsilon),
-        testing::ValuesIn(netPrecisions),
-        testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        testing::Values(InferenceEngine::Layout::ANY),
-        testing::Values(InferenceEngine::Layout::ANY),
-        testing::ValuesIn(inputShapes),
+        testing::ValuesIn(model_type),
+        testing::ValuesIn(ov::test::static_shapes_to_test_representation(input_shapes_static)),
         testing::Values(ov::test::utils::DEVICE_CPU)
 );
 
 INSTANTIATE_TEST_SUITE_P(
         smoke_BatchNorm,
         BatchNormLayerTest,
-        batchNormParams,
+        batch_norm_params,
         BatchNormLayerTest::getTestCaseName
 );
 
diff --git a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/batch_to_space.cpp b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/batch_to_space.cpp
index 2883915a91055f..dc7c4f41afb1c8 100644
--- a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/batch_to_space.cpp
+++ b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/batch_to_space.cpp
@@ -2,23 +2,20 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
-#include "single_layer_tests/batch_to_space.hpp"
+#include "single_op_tests/batch_to_space.hpp"
 #include "common_test_utils/test_constants.hpp"
 
-using namespace LayerTestsDefinitions;
-
 namespace {
+using ov::test::BatchToSpaceLayerTest;
 
-const std::vector<InferenceEngine::Precision> net_precisions = {
-        InferenceEngine::Precision::FP32,
-        InferenceEngine::Precision::I32
+const std::vector<ov::element::Type> net_types = {
+        ov::element::f32,
+        ov::element::i32
 };
 
-const std::vector<std::vector<size_t>> data_shapes_2D = {
-        {12, 4},
-        {48, 3}
+const std::vector<std::vector<ov::Shape>> data_shapes_2D_static = {
+        {{12, 4}},
+        {{48, 3}}
 };
 
 const std::vector<std::vector<int64_t>> block_shapes_2D = {
@@ -35,12 +32,8 @@ const auto batch_to_space_2d_tests = ::testing::Combine(
         ::testing::ValuesIn(block_shapes_2D),
         ::testing::ValuesIn(crops_2D),
         ::testing::ValuesIn(crops_2D),
-        ::testing::ValuesIn(data_shapes_2D),
-        ::testing::ValuesIn(net_precisions),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(InferenceEngine::Layout::ANY),
+        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(data_shapes_2D_static)),
+        ::testing::ValuesIn(net_types),
         ::testing::Values(ov::test::utils::DEVICE_CPU));
 
 INSTANTIATE_TEST_SUITE_P(
@@ -49,10 +42,10 @@ INSTANTIATE_TEST_SUITE_P(
         batch_to_space_2d_tests,
         BatchToSpaceLayerTest::getTestCaseName);
 
-const std::vector<std::vector<size_t>> data_shapes_4D = {
-        {4, 1, 2, 2},
-        {4, 3, 2, 2},
-        {8, 1, 3, 2}
+const std::vector<std::vector<ov::Shape>> data_shapes_4D_static = {
+        {{4, 1, 2, 2}},
+        {{4, 3, 2, 2}},
+        {{8, 1, 3, 2}}
 };
 
 const std::vector<std::vector<int64_t>> block_shapes_4D = {
@@ -76,24 +69,16 @@ const auto batch_to_space_4d_spatial_dims_tests = ::testing::Combine(
         ::testing::Values(block_shapes_4D[0]),
         ::testing::ValuesIn(crops_begin_4D),
         ::testing::ValuesIn(crops_end_4D),
-        ::testing::ValuesIn(data_shapes_4D),
-        ::testing::ValuesIn(net_precisions),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(InferenceEngine::Layout::ANY),
+        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(data_shapes_4D_static)),
+        ::testing::ValuesIn(net_types),
         ::testing::Values(ov::test::utils::DEVICE_CPU));
 
 const auto batch_to_space_4d_channel_dim_tests = ::testing::Combine(
         ::testing::Values(block_shapes_4D[1]),
         ::testing::Values(crops_begin_4D[0]),
         ::testing::Values(crops_end_4D[0]),
-        ::testing::ValuesIn(data_shapes_4D),
-        ::testing::ValuesIn(net_precisions),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(InferenceEngine::Layout::ANY),
+        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(data_shapes_4D_static)),
+        ::testing::ValuesIn(net_types),
         ::testing::Values(ov::test::utils::DEVICE_CPU));
 
 INSTANTIATE_TEST_SUITE_P(
@@ -108,8 +93,8 @@ INSTANTIATE_TEST_SUITE_P(
         batch_to_space_4d_channel_dim_tests,
         BatchToSpaceLayerTest::getTestCaseName);
 
-const std::vector<std::vector<size_t>> data_shapes_5D = {
-        {12, 1, 2, 1, 2}
+const std::vector<std::vector<ov::Shape>> data_shapes_5D_static = {
+        {{12, 1, 2, 1, 2}}
 };
 
 const std::vector<std::vector<int64_t>> block_shapes_5D = {
@@ -133,24 +118,16 @@ const auto batch_to_space_5d_spatial_dims_tests = ::testing::Combine(
         ::testing::Values(block_shapes_5D[0]),
         ::testing::ValuesIn(crops_begin_5D),
         ::testing::ValuesIn(crops_end_5D),
-        ::testing::ValuesIn(data_shapes_5D),
-        ::testing::ValuesIn(net_precisions),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(InferenceEngine::Layout::ANY),
+        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(data_shapes_5D_static)),
+        ::testing::ValuesIn(net_types),
         ::testing::Values(ov::test::utils::DEVICE_CPU));
 
 const auto batch_to_space_5d_channel_dim_tests = ::testing::Combine(
         ::testing::Values(block_shapes_5D[1]),
         ::testing::Values(crops_begin_5D[0]),
         ::testing::Values(crops_end_5D[0]),
-        ::testing::ValuesIn(data_shapes_5D),
-        ::testing::ValuesIn(net_precisions),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(InferenceEngine::Layout::ANY),
+        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(data_shapes_5D_static)),
+        ::testing::ValuesIn(net_types),
         ::testing::Values(ov::test::utils::DEVICE_CPU));
 
 INSTANTIATE_TEST_SUITE_P(
diff --git a/src/tests/functional/plugin/shared/include/single_layer_tests/adaptive_pooling.hpp b/src/tests/functional/plugin/shared/include/single_layer_tests/adaptive_pooling.hpp
index f4d41b2b122294..3caf98b7566cfd 100644
--- a/src/tests/functional/plugin/shared/include/single_layer_tests/adaptive_pooling.hpp
+++ b/src/tests/functional/plugin/shared/include/single_layer_tests/adaptive_pooling.hpp
@@ -9,7 +9,7 @@
 namespace LayerTestsDefinitions {
 
 TEST_P(AdaPoolLayerTest, CompareWithRefs) {
-Run();
+    Run();
 }
 
 }  // namespace LayerTestsDefinitions
diff --git a/src/tests/functional/plugin/shared/include/single_op_tests/adaptive_pooling.hpp b/src/tests/functional/plugin/shared/include/single_op_tests/adaptive_pooling.hpp
new file mode 100644
index 00000000000000..74b49d5f66387f
--- /dev/null
+++ b/src/tests/functional/plugin/shared/include/single_op_tests/adaptive_pooling.hpp
@@ -0,0 +1,15 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/single_op/adaptive_pooling.hpp"
+
+namespace ov {
+namespace test {
+TEST_P(AdaPoolLayerTest, Inference) {
+    run();
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/plugin/shared/include/single_op_tests/batch_norm.hpp b/src/tests/functional/plugin/shared/include/single_op_tests/batch_norm.hpp
new file mode 100644
index 00000000000000..d7cad68321cbe3
--- /dev/null
+++ b/src/tests/functional/plugin/shared/include/single_op_tests/batch_norm.hpp
@@ -0,0 +1,15 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/single_op/batch_norm.hpp"
+
+namespace ov {
+namespace test {
+TEST_P(BatchNormLayerTest, Inference) {
+    run();
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/plugin/shared/include/single_op_tests/batch_to_space.hpp b/src/tests/functional/plugin/shared/include/single_op_tests/batch_to_space.hpp
new file mode 100644
index 00000000000000..d894fd039ab61c
--- /dev/null
+++ b/src/tests/functional/plugin/shared/include/single_op_tests/batch_to_space.hpp
@@ -0,0 +1,17 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/single_op/batch_to_space.hpp"
+
+namespace ov {
+namespace test {
+
+TEST_P(BatchToSpaceLayerTest, Inference) {
+    run();
+};
+
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/adaptive_pooling.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/adaptive_pooling.hpp
new file mode 100644
index 00000000000000..5f3e5932a41a70
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/adaptive_pooling.hpp
@@ -0,0 +1,27 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/base/ov_subgraph.hpp"
+
+namespace ov {
+namespace test {
+using adapoolParams = std::tuple<
+        std::vector<InputShape>,            // feature map shape
+        std::vector<int>,                   // pooled spatial shape
+        std::string,                        // pooling mode
+        ov::element::Type,                  // model type
+        std::string>;                       // device name
+
+class AdaPoolLayerTest : public testing::WithParamInterface<adapoolParams>,
+                         virtual public ov::test::SubgraphBaseTest {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<adapoolParams>& obj);
+
+protected:
+    void SetUp() override;
+};
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/batch_norm.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/batch_norm.hpp
new file mode 100644
index 00000000000000..f28b24d088a900
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/batch_norm.hpp
@@ -0,0 +1,27 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/base/ov_subgraph.hpp"
+
+namespace ov {
+namespace test {
+typedef std::tuple<
+        double,                        // epsilon
+        ov::element::Type,             // Model type
+        std::vector<InputShape>,       // Input shape
+        std::string                    // Target device name
+> BatchNormLayerTestParams;
+
+class BatchNormLayerTest : public testing::WithParamInterface<BatchNormLayerTestParams>,
+                           virtual public ov::test::SubgraphBaseTest {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<BatchNormLayerTestParams>& obj);
+protected:
+    void SetUp() override;
+};
+
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/batch_to_space.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/batch_to_space.hpp
new file mode 100644
index 00000000000000..07ac5c21542603
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/batch_to_space.hpp
@@ -0,0 +1,32 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <string>
+#include <tuple>
+#include <vector>
+
+#include "shared_test_classes/base/ov_subgraph.hpp"
+
+namespace ov {
+namespace test {
+using batchToSpaceParamsTuple = typename std::tuple<
+        std::vector<int64_t>,              // block shape
+        std::vector<int64_t>,              // crops begin
+        std::vector<int64_t>,              // crops end
+        std::vector<InputShape>,           // Input shapes
+        ov::element::Type,                 // Model type
+        std::string>;                      // Device name>;
+
+class BatchToSpaceLayerTest : public testing::WithParamInterface<batchToSpaceParamsTuple>,
+                              virtual public ov::test::SubgraphBaseTest {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<batchToSpaceParamsTuple> &obj);
+
+protected:
+    void SetUp() override;
+};
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/comparison.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/comparison.hpp
index 0e29e65f22c122..d3eb67f907dcb7 100644
--- a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/comparison.hpp
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/comparison.hpp
@@ -26,10 +26,8 @@ typedef std::tuple<
 
 class ComparisonLayerTest : public testing::WithParamInterface<ComparisonTestParams>,
     virtual public ov::test::SubgraphBaseTest {
-    ngraph::helpers::ComparisonTypes comparison_op_type;
 protected:
     void SetUp() override;
-    void generate_inputs(const std::vector<ov::Shape>& targetInputStaticShapes) override;
 public:
     static std::string getTestCaseName(const testing::TestParamInfo<ComparisonTestParams> &obj);
 };
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/gru_sequence.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/gru_sequence.hpp
index 0b2b053cd4880f..507739669a22e5 100644
--- a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/gru_sequence.hpp
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/gru_sequence.hpp
@@ -30,9 +30,6 @@ class GRUSequenceTest : public testing::WithParamInterface<GRUSequenceParams>,
 
 protected:
     void SetUp() override;
-    void generate_inputs(const std::vector<ov::Shape>& targetInputStaticShapes) override;
-    ov::test::utils::SequenceTestsMode m_mode;
-    int64_t m_max_seq_len = 0;
 };
 } //  namespace test
 } //  namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/base/utils/generate_inputs.cpp b/src/tests/functional/shared_test_classes/src/base/utils/generate_inputs.cpp
index 369b6dedcd7a68..7a7e2bc4a89879 100644
--- a/src/tests/functional/shared_test_classes/src/base/utils/generate_inputs.cpp
+++ b/src/tests/functional/shared_test_classes/src/base/utils/generate_inputs.cpp
@@ -963,6 +963,51 @@ ov::runtime::Tensor generate(const
     return tensor;
 }
 
+namespace comparison {
+void fill_tensor(ov::Tensor& tensor) {
+    auto data_ptr = static_cast<float*>(tensor.data());
+    auto data_ptr_int = static_cast<int*>(tensor.data());
+    auto range = tensor.get_size();
+    auto start = -static_cast<float>(range) / 2.f;
+    testing::internal::Random random(1);
+    for (size_t i = 0; i < range; i++) {
+        if (i % 7 == 0) {
+            data_ptr[i] = std::numeric_limits<float>::infinity();
+        } else if (i % 7 == 1) {
+            data_ptr[i] = -std::numeric_limits<float>::infinity();
+        } else if (i % 7 == 2) {
+            data_ptr_int[i] = 0x7F800000 + random.Generate(range);
+        } else if (i % 7 == 3) {
+            data_ptr[i] = std::numeric_limits<double>::quiet_NaN();
+        } else if (i % 7 == 5) {
+            data_ptr[i] = -std::numeric_limits<double>::quiet_NaN();
+        } else {
+            data_ptr[i] = start + static_cast<float>(random.Generate(range));
+        }
+    }
+}
+} // namespace comparison
+
+ov::runtime::Tensor generate(const
+                             std::shared_ptr<ov::op::v10::IsFinite>& node,
+                             size_t port,
+                             const ov::element::Type& elemType,
+                             const ov::Shape& targetShape) {
+    ov::Tensor tensor(elemType, targetShape);
+    comparison::fill_tensor(tensor);
+    return tensor;
+}
+
+ov::runtime::Tensor generate(const
+                             std::shared_ptr<ov::op::v10::IsNaN>& node,
+                             size_t port,
+                             const ov::element::Type& elemType,
+                             const ov::Shape& targetShape) {
+    ov::Tensor tensor{elemType, targetShape};
+    comparison::fill_tensor(tensor);
+    return tensor;
+}
+
 template<typename T>
 ov::runtime::Tensor generateInput(const std::shared_ptr<ov::Node>& node,
                                   size_t port,
diff --git a/src/tests/functional/shared_test_classes/src/single_op/adaptive_pooling.cpp b/src/tests/functional/shared_test_classes/src/single_op/adaptive_pooling.cpp
new file mode 100644
index 00000000000000..17a848c8475ff1
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/src/single_op/adaptive_pooling.cpp
@@ -0,0 +1,60 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "shared_test_classes/single_op/adaptive_pooling.hpp"
+
+namespace ov {
+namespace test {
+
+std::string AdaPoolLayerTest::getTestCaseName(const testing::TestParamInfo<adapoolParams>& obj) {
+    std::vector<InputShape> shapes;
+    std::vector<int> pooled_spatial_shape;
+
+    std::string pooling_mode;
+    ov::element::Type model_type;
+    std::string target_device;
+    std::tie(shapes, pooled_spatial_shape, pooling_mode, model_type, target_device) = obj.param;
+
+    std::ostringstream result;
+
+    result << "IS=(";
+    for (const auto& shape : shapes) {
+        result << ov::test::utils::partialShape2str({shape.first}) << "_";
+    }
+    result << ")_TS=(";
+    for (const auto& shape : shapes) {
+        for (const auto& item : shape.second) {
+            result << ov::test::utils::vec2str(item) << "_";
+        }
+    }
+    result << "pooled_spatial_shape=" << ov::test::utils::vec2str(pooled_spatial_shape) << "_";
+    result << "mode=" << pooling_mode << "_";
+    result << "IT=" << model_type.get_type_name() << "_";
+    result << "dev=" << target_device;
+    return result.str();
+}
+
+void AdaPoolLayerTest::SetUp() {
+    std::vector<InputShape> shapes;
+    std::vector<int> pooled_spatial_shape;
+    std::string pooling_mode;
+    ov::element::Type model_type;
+    std::tie(shapes, pooled_spatial_shape, pooling_mode, model_type, targetDevice) = this->GetParam();
+    init_input_shapes(shapes);
+
+    ov::ParameterVector params{std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes.front())};
+
+    ov::Shape pooled_shape = {pooled_spatial_shape.size()};
+    auto pooled_param = std::make_shared<ov::op::v0::Constant>(ov::element::i32, pooled_shape, pooled_spatial_shape);
+
+    // we cannot create abstract Op to use polymorphism
+    auto adapoolMax = std::make_shared<ov::op::v8::AdaptiveMaxPool>(params[0], pooled_param, ov::element::i32);
+    auto adapoolAvg = std::make_shared<ov::op::v8::AdaptiveAvgPool>(params[0], pooled_param);
+
+    function = (pooling_mode == "max" ?
+                std::make_shared<ov::Model>(adapoolMax->outputs(), params, "AdaPoolMax") :
+                std::make_shared<ov::Model>(adapoolAvg->outputs(), params, "AdaPoolAvg"));
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/single_op/batch_norm.cpp b/src/tests/functional/shared_test_classes/src/single_op/batch_norm.cpp
new file mode 100644
index 00000000000000..f2df32ba5048f4
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/src/single_op/batch_norm.cpp
@@ -0,0 +1,61 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "shared_test_classes/single_op/batch_norm.hpp"
+
+#include "common_test_utils/ov_tensor_utils.hpp"
+
+namespace ov {
+namespace test {
+std::string BatchNormLayerTest::getTestCaseName(const testing::TestParamInfo<BatchNormLayerTestParams>& obj) {
+    ov::element::Type model_type;
+    std::vector<InputShape> shapes;
+    double epsilon;
+    std::string target_device;
+    std::tie(epsilon, model_type, shapes, target_device) = obj.param;
+
+    std::ostringstream result;
+    result << "IS=(";
+    for (const auto& shape : shapes) {
+        result << ov::test::utils::partialShape2str({shape.first}) << "_";
+    }
+    result << ")_TS=(";
+    for (const auto& shape : shapes) {
+        for (const auto& item : shape.second) {
+            result << ov::test::utils::vec2str(item) << "_";
+        }
+    }
+    result << "inT=" << model_type.get_type_name() << "_";
+    result << "epsilon=" << epsilon << "_";
+    result << "trgDev=" << target_device;
+    return result.str();
+}
+
+void BatchNormLayerTest::SetUp() {
+    ov::element::Type model_type;
+    std::vector<InputShape> shapes;
+    double epsilon;
+    std::tie(epsilon, model_type, shapes, targetDevice) = this->GetParam();
+    init_input_shapes(shapes);
+    ov::ParameterVector params {std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes.front())};
+
+    auto constant_shape = ov::Shape{params[0]->get_shape().at(1)};
+    auto gamma_tensor = ov::test::utils::create_and_fill_tensor(model_type, constant_shape, 1, 0);
+    auto gamma = std::make_shared<ov::op::v0::Constant>(gamma_tensor);
+
+    auto beta_tensor = ov::test::utils::create_and_fill_tensor(model_type, constant_shape, 1, 0);
+    auto beta = std::make_shared<ov::op::v0::Constant>(beta_tensor);
+
+    auto mean_tensor = ov::test::utils::create_and_fill_tensor(model_type, constant_shape, 1, 0);
+    auto mean = std::make_shared<ov::op::v0::Constant>(mean_tensor);
+
+    // Fill the vector for variance with positive values
+    auto variance_tensor = ov::test::utils::create_and_fill_tensor(model_type, constant_shape, 10, 0);
+    auto variance = std::make_shared<ov::op::v0::Constant>(variance_tensor);
+    auto batch_norm = std::make_shared<ov::op::v5::BatchNormInference>(params[0], gamma, beta, mean, variance, epsilon);
+
+    function = std::make_shared<ov::Model>(ov::OutputVector{batch_norm}, params, "BatchNormInference");
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/single_op/batch_to_space.cpp b/src/tests/functional/shared_test_classes/src/single_op/batch_to_space.cpp
new file mode 100644
index 00000000000000..b814d07304d964
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/src/single_op/batch_to_space.cpp
@@ -0,0 +1,53 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "shared_test_classes/single_op/batch_to_space.hpp"
+
+namespace ov {
+namespace test {
+std::string BatchToSpaceLayerTest::getTestCaseName(const testing::TestParamInfo<batchToSpaceParamsTuple> &obj) {
+    std::vector<InputShape> shapes;
+    std::vector<int64_t> block_shape, crops_begin, crops_end;
+    ov::element::Type model_type;
+    std::string target_name;
+    std::tie(block_shape, crops_begin, crops_end, shapes, model_type, target_name) = obj.param;
+    std::ostringstream result;
+    result << "IS=(";
+    for (const auto& shape : shapes) {
+        result << ov::test::utils::partialShape2str({shape.first}) << "_";
+    }
+    result << ")_TS=(";
+    for (const auto& shape : shapes) {
+        for (const auto& item : shape.second) {
+            result << ov::test::utils::vec2str(item) << "_";
+        }
+    }
+    result << "inT=" << model_type.get_type_name() << "_";
+    result << "BS=" << ov::test::utils::vec2str(block_shape) << "_";
+    result << "CB=" << ov::test::utils::vec2str(crops_begin) << "_";
+    result << "CE=" << ov::test::utils::vec2str(crops_end) << "_";
+    result << "trgDev=" << target_name << "_";
+    return result.str();
+}
+
+void BatchToSpaceLayerTest::SetUp() {
+    std::vector<InputShape> shapes;
+    std::vector<int64_t> block_shape, crops_begin, crops_end;
+    ov::element::Type model_type;
+    std::tie(block_shape, crops_begin, crops_end, shapes, model_type, targetDevice) = this->GetParam();
+    init_input_shapes(shapes);
+
+    ov::ParameterVector params{std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes.front())};
+
+    auto const_shape = ov::Shape{inputDynamicShapes.front().size()};
+    auto block_shape_node = std::make_shared<ov::op::v0::Constant>(ov::element::i64, const_shape, block_shape.data());
+    auto crops_begin_node = std::make_shared<ov::op::v0::Constant>(ov::element::i64, const_shape, crops_begin.data());
+    auto crops_end_node = std::make_shared<ov::op::v0::Constant>(ov::element::i64, const_shape, crops_end.data());
+
+    auto b2s = std::make_shared<ov::op::v1::BatchToSpace>(params[0], block_shape_node, crops_begin_node, crops_end_node);
+    ov::OutputVector results{std::make_shared<ov::op::v0::Result>(b2s)};
+    function = std::make_shared<ov::Model>(results, params, "BatchToSpace");
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/single_op/comparison.cpp b/src/tests/functional/shared_test_classes/src/single_op/comparison.cpp
index 7dacd12bc9d74c..f7ea71c95bb4b3 100644
--- a/src/tests/functional/shared_test_classes/src/single_op/comparison.cpp
+++ b/src/tests/functional/shared_test_classes/src/single_op/comparison.cpp
@@ -51,6 +51,7 @@ void ComparisonLayerTest::SetUp() {
     InputLayerType second_input_type;
     std::map<std::string, std::string> additional_config;
     ov::element::Type model_type;
+    ngraph::helpers::ComparisonTypes comparison_op_type;
     std::tie(shapes,
              comparison_op_type,
              second_input_type,
@@ -74,40 +75,5 @@ void ComparisonLayerTest::SetUp() {
     auto comparisonNode = ngraph::builder::makeComparison(inputs[0], second_input, comparison_op_type);
     function = std::make_shared<ov::Model>(comparisonNode, inputs, "Comparison");
 }
-
-void ComparisonLayerTest::generate_inputs(const std::vector<ov::Shape>& target_input_static_shapes) {
-    if (comparison_op_type == ComparisonTypes::IS_FINITE || comparison_op_type == ComparisonTypes::IS_NAN) {
-        inputs.clear();
-        auto params = function->get_parameters();
-        OPENVINO_ASSERT(target_input_static_shapes.size() >= params.size());
-        for (int i = 0; i < params.size(); i++) {
-            ov::Tensor tensor(params[i]->get_element_type(), target_input_static_shapes[i]);
-            auto data_ptr = static_cast<float*>(tensor.data());
-            auto data_ptr_int = static_cast<int*>(tensor.data());
-            auto range = tensor.get_size();
-            auto start = -static_cast<float>(range) / 2.f;
-            testing::internal::Random random(1);
-            for (size_t i = 0; i < range; i++) {
-                if (i % 7 == 0) {
-                    data_ptr[i] = std::numeric_limits<float>::infinity();
-                } else if (i % 7 == 1) {
-                    data_ptr[i] = -std::numeric_limits<float>::infinity();
-                } else if (i % 7 == 2) {
-                    data_ptr_int[i] = 0x7F800000 + random.Generate(range);
-                } else if (i % 7 == 3) {
-                    data_ptr[i] = std::numeric_limits<double>::quiet_NaN();
-                } else if (i % 7 == 5) {
-                    data_ptr[i] = -std::numeric_limits<double>::quiet_NaN();
-                } else {
-                    data_ptr[i] = start + static_cast<float>(random.Generate(range));
-                }
-            }
-            inputs.insert({params[i], tensor});
-        }
-    } else {
-        SubgraphBaseTest::generate_inputs(target_input_static_shapes);
-    }
-}
-
 } // namespace test
 } // namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/single_op/gru_sequence.cpp b/src/tests/functional/shared_test_classes/src/single_op/gru_sequence.cpp
index 54e7140830d2ec..e98b04c5aa8ffc 100644
--- a/src/tests/functional/shared_test_classes/src/single_op/gru_sequence.cpp
+++ b/src/tests/functional/shared_test_classes/src/single_op/gru_sequence.cpp
@@ -61,7 +61,8 @@ void GRUSequenceTest::SetUp() {
     bool linear_before_reset;
     ov::op::RecurrentSequenceDirection direction;
     InputLayerType wbr_type;
-    std::tie(m_mode, shapes, activations, clip, linear_before_reset, direction, wbr_type,
+    ov::test::utils::SequenceTestsMode mode;
+    std::tie(mode, shapes, activations, clip, linear_before_reset, direction, wbr_type,
             inType, targetDevice) = this->GetParam();
     outType = inType;
     init_input_shapes(shapes);
@@ -87,15 +88,15 @@ void GRUSequenceTest::SetUp() {
     const auto& b_shape = ov::Shape{num_directions, (linear_before_reset ? 4 : 3) * hidden_size};
 
     std::shared_ptr<ov::Node> seq_lengths_node;
-    if (m_mode == SequenceTestsMode::CONVERT_TO_TI_MAX_SEQ_LEN_PARAM ||
-        m_mode == SequenceTestsMode::CONVERT_TO_TI_RAND_SEQ_LEN_PARAM ||
-        m_mode == SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM) {
+    if (mode == SequenceTestsMode::CONVERT_TO_TI_MAX_SEQ_LEN_PARAM ||
+        mode == SequenceTestsMode::CONVERT_TO_TI_RAND_SEQ_LEN_PARAM ||
+        mode == SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM) {
         auto param = std::make_shared<ov::op::v0::Parameter>(ov::element::i64, inputDynamicShapes[2]);
         param->set_friendly_name("seq_lengths");
         params.push_back(param);
         seq_lengths_node = param;
-    } else if (m_mode == SequenceTestsMode::CONVERT_TO_TI_RAND_SEQ_LEN_CONST ||
-               m_mode == SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST) {
+    } else if (mode == SequenceTestsMode::CONVERT_TO_TI_RAND_SEQ_LEN_CONST ||
+               mode == SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST) {
         auto tensor = ov::test::utils::create_and_fill_tensor(ov::element::i64, targetStaticShapes[0][2], seq_lengths, 0);
         seq_lengths_node = std::make_shared<ov::op::v0::Constant>(tensor);
     } else {
@@ -131,9 +132,9 @@ void GRUSequenceTest::SetUp() {
                              std::make_shared<ov::op::v0::Result>(gru_sequence->output(1))};
     function = std::make_shared<ov::Model>(results, params, "gru_sequence");
 
-    bool is_pure_sequence = (m_mode == SequenceTestsMode::PURE_SEQ ||
-                             m_mode == SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM ||
-                             m_mode == SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST);
+    bool is_pure_sequence = (mode == SequenceTestsMode::PURE_SEQ ||
+                             mode == SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_PARAM ||
+                             mode == SequenceTestsMode::PURE_SEQ_RAND_SEQ_LEN_CONST);
     if (!is_pure_sequence) {
         ov::pass::Manager manager;
         if (direction == ov::op::RecurrentSequenceDirection::BIDIRECTIONAL)
@@ -147,15 +148,5 @@ void GRUSequenceTest::SetUp() {
         EXPECT_EQ(ti_found, false);
     }
 }
-
-void GRUSequenceTest::generate_inputs(const std::vector<ov::Shape>& target_input_static_shapes) {
-    inputs.clear();
-    auto params = function->get_parameters();
-    OPENVINO_ASSERT(target_input_static_shapes.size() >= params.size());
-    for (int i = 0; i < params.size(); i++) {
-        auto tensor = ov::test::utils::create_and_fill_tensor(params[i]->get_element_type(), target_input_static_shapes[i], m_max_seq_len, 0);
-        inputs.insert({params[i], tensor});
-    }
-}
 } //  namespace test
 } //  namespace ov

From 9c908f5245588ee677bdeacec796d21059be7453 Mon Sep 17 00:00:00 2001
From: Ilya Churaev <ilya.churaev@intel.com>
Date: Tue, 19 Sep 2023 11:46:11 +0400
Subject: [PATCH 18/46] Migrate template backend to new api (#19843)

* Added set_element_type for tensor

* Moved template backend to new API

* Revert "Added set_element_type for tensor"

This reverts commit 27608d2ea0acdf0f9fe3504b95e83f988f63c3a9.

* Fixed build

* Fixed more errors

* Fixed loop implementation

* Fixed ONNX tests

* Small change

* Fixed set_shape for host tensor

* Fixed ReadValue Assign tests

* Fixed template tests

* Fixed build

* Fix Windows build

* Fixed more errors

* Fixed CTCLoss

* Fixed comments

* Removed all comments

* Fixed tensors update

* Try to fix tests
---
 src/core/CMakeLists.txt                       |   1 +
 src/core/include/openvino/op/loop.hpp         |   5 +-
 src/core/reference/CMakeLists.txt             |   1 +
 .../include/openvino/reference/abs.hpp        |   1 +
 .../openvino/reference/adaptive_max_pool.hpp  |   1 +
 .../openvino/reference/convert_color_nv12.hpp |  60 +-
 .../include/openvino/reference/ctc_loss.hpp   |   2 +
 .../include/openvino/reference/einsum.hpp     |   2 +-
 .../include/openvino/reference/fft.hpp        |  10 +-
 .../include/openvino/reference/function.hpp   |   2 +-
 .../openvino/reference/hard_sigmoid.hpp       |   1 +
 .../include/openvino/reference/if.hpp         |   4 +-
 .../include/openvino/reference/is_finite.hpp  |   1 +
 .../include/openvino/reference/is_inf.hpp     |   3 +
 .../include/openvino/reference/is_nan.hpp     |   1 +
 .../include/openvino/reference/loop.hpp       |   4 +-
 .../include/openvino/reference/lstm_cell.hpp  |   1 +
 .../reference/non_max_suppression.hpp         |   4 +-
 .../openvino/reference/roi_pooling.hpp        |   3 +
 .../openvino/reference/tensor_iterator.hpp    |  11 +-
 src/core/reference/src/op/einsum.cpp          | 377 ++++----
 src/core/reference/src/op/fft.cpp             |  13 +-
 src/core/reference/src/op/function.cpp        |  11 +-
 src/core/reference/src/op/if.cpp              |  15 +-
 src/core/reference/src/op/loop.cpp            |  86 +-
 .../reference/src/op/non_max_suppression.cpp  |  46 +-
 src/core/reference/src/op/tensor_iterator.cpp |  48 +-
 src/core/reference/src/op/tile.cpp            |   2 -
 src/core/src/node.cpp                         |   9 +-
 src/core/src/op/loop.cpp                      |   5 +-
 src/core/src/runtime/host_tensor.cpp          |  12 +-
 src/inference/src/dev/make_tensor.cpp         |   2 +
 src/plugins/template/backend/backend.cpp      |   2 -
 .../template/backend/evaluates_map.cpp        |  64 +-
 .../template/backend/evaluates_map.hpp        |  26 +-
 src/plugins/template/backend/executable.hpp   |   4 +-
 .../template/backend/int_executable.cpp       |  77 +-
 .../template/backend/int_executable.hpp       |   5 +-
 src/plugins/template/backend/ops/abs.cpp      |  92 +-
 .../backend/ops/adaptive_avg_pool.cpp         | 123 +--
 .../backend/ops/adaptive_max_pool.cpp         | 143 ++-
 src/plugins/template/backend/ops/assign.cpp   |  60 +-
 src/plugins/template/backend/ops/avg_pool.cpp |  93 +-
 .../template/backend/ops/batch_norm.cpp       | 260 ++---
 .../backend/ops/binary_convolution.cpp        | 147 ++-
 .../template/backend/ops/bucketize.cpp        | 271 +++---
 src/plugins/template/backend/ops/ceiling.cpp  |  91 +-
 src/plugins/template/backend/ops/convert.cpp  | 208 ++--
 .../backend/ops/convert_color_nv12.cpp        | 403 +++-----
 .../template/backend/ops/convolution.cpp      | 148 ++-
 .../backend/ops/convolution_backprop_data.cpp | 158 ++-
 .../backend/ops/ctc_greedy_decoder.cpp        | 129 +--
 .../ops/ctc_greedy_decoder_seq_len.cpp        | 203 ++--
 src/plugins/template/backend/ops/ctc_loss.cpp | 162 ++--
 src/plugins/template/backend/ops/cum_sum.cpp  | 113 ++-
 .../backend/ops/deformable_convolution.cpp    | 367 +++----
 .../backend/ops/deformable_psroi_pooling.cpp  | 161 ++-
 .../template/backend/ops/detection_output.cpp | 274 ++----
 src/plugins/template/backend/ops/einsum.cpp   |  82 +-
 src/plugins/template/backend/ops/elu.cpp      |  89 +-
 .../backend/ops/embedding_bag_offsets_sum.cpp | 155 ++-
 .../backend/ops/embedding_bag_packed_sum.cpp  | 156 ++-
 .../backend/ops/embedding_segments_sum.cpp    | 155 ++-
 src/plugins/template/backend/ops/equal.cpp    | 105 +-
 .../template/backend/ops/evaluate_node.hpp    |  82 +-
 src/plugins/template/backend/ops/exp.cpp      |  87 +-
 ...xperimental_detectron_detection_output.cpp | 198 ++--
 ...imental_detectron_prior_grid_generator.cpp | 207 ++--
 ...mental_detectron_proposal_single_image.cpp | 142 ++-
 ...mental_detectron_roi_feature_extractor.cpp | 201 ++--
 .../ops/experimental_detectron_topk_rois.cpp  | 177 ++--
 .../backend/ops/extract_image_patches.cpp     | 153 ++-
 src/plugins/template/backend/ops/fft.cpp      | 182 ++--
 src/plugins/template/backend/ops/gather.cpp   | 103 +-
 .../template/backend/ops/gather_elements.cpp  | 151 ++-
 .../template/backend/ops/gather_nd.cpp        | 234 +++--
 .../template/backend/ops/gather_tree.cpp      |  97 +-
 src/plugins/template/backend/ops/gelu.cpp     | 180 ++--
 .../backend/ops/generate_proposal.cpp         | 144 ++-
 src/plugins/template/backend/ops/greater.cpp  | 106 +-
 .../template/backend/ops/grid_sample.cpp      | 130 +--
 src/plugins/template/backend/ops/grn.cpp      |  88 +-
 .../backend/ops/group_convolution.cpp         | 148 ++-
 .../ops/group_convolution_backprop_data.cpp   | 199 ++--
 .../backend/ops/group_normalization.cpp       |  41 +-
 src/plugins/template/backend/ops/gru_cell.cpp | 248 ++---
 .../template/backend/ops/hard_sigmoid.cpp     | 132 +--
 src/plugins/template/backend/ops/if.cpp       | 154 +--
 .../template/backend/ops/interpolate.cpp      | 340 +++----
 src/plugins/template/backend/ops/irdft.cpp    | 101 +-
 .../template/backend/ops/is_finite.cpp        | 146 ++-
 src/plugins/template/backend/ops/is_inf.cpp   | 125 ++-
 src/plugins/template/backend/ops/is_nan.cpp   | 121 ++-
 src/plugins/template/backend/ops/log.cpp      |  87 +-
 .../template/backend/ops/log_softmax.cpp      | 125 +--
 src/plugins/template/backend/ops/lrn.cpp      |  89 +-
 .../template/backend/ops/lstm_cell.cpp        | 237 +++--
 .../template/backend/ops/matrix_nms.cpp       | 189 ++--
 src/plugins/template/backend/ops/mod.cpp      |  93 +-
 .../template/backend/ops/multiclass_nms.cpp   | 271 ++----
 src/plugins/template/backend/ops/mvn.cpp      | 194 ++--
 .../backend/ops/non_max_suppression.cpp       | 913 +++++++-----------
 .../template/backend/ops/normalize_l2.cpp     | 121 +--
 .../template/backend/ops/ops_evaluates.hpp    | 792 ++++++++-------
 src/plugins/template/backend/ops/pad.cpp      |  93 +-
 src/plugins/template/backend/ops/prelu.cpp    |  95 +-
 src/plugins/template/backend/ops/proposal.cpp | 214 ++--
 .../template/backend/ops/psroi_pooling.cpp    | 101 +-
 src/plugins/template/backend/ops/rdft.cpp     | 100 +-
 .../template/backend/ops/read_value.cpp       |  80 +-
 .../template/backend/ops/region_yolo.cpp      | 123 +--
 src/plugins/template/backend/ops/relu.cpp     |  87 +-
 .../template/backend/ops/reorg_yolo.cpp       |  83 +-
 .../template/backend/ops/reverse_sequence.cpp | 185 ++--
 src/plugins/template/backend/ops/rnn_cell.cpp | 109 +--
 .../template/backend/ops/roi_align.cpp        | 108 +--
 .../template/backend/ops/roi_pooling.cpp      | 128 +--
 src/plugins/template/backend/ops/roll.cpp     |  96 +-
 .../backend/ops/scatter_nd_update.cpp         | 137 +--
 src/plugins/template/backend/ops/selu.cpp     |  97 +-
 .../template/backend/ops/sequences.cpp        | 847 +++++++---------
 src/plugins/template/backend/ops/sigmoid.cpp  |  91 +-
 src/plugins/template/backend/ops/sign.cpp     |  87 +-
 src/plugins/template/backend/ops/softsign.cpp | 121 ++-
 .../backend/ops/squared_difference.cpp        | 127 +--
 src/plugins/template/backend/ops/tanh.cpp     |  92 +-
 .../template/backend/ops/tensor_iterator.cpp  | 130 +--
 src/plugins/template/backend/ops/unique.cpp   | 137 ++-
 .../template/backend/opset_int_tbl.hpp        |  54 +-
 129 files changed, 7002 insertions(+), 9318 deletions(-)

diff --git a/src/core/CMakeLists.txt b/src/core/CMakeLists.txt
index 03580613532e7b..c12a30d5a6f639 100644
--- a/src/core/CMakeLists.txt
+++ b/src/core/CMakeLists.txt
@@ -8,6 +8,7 @@ set(CMAKE_INTERPROCEDURAL_OPTIMIZATION_RELEASE ${ENABLE_LTO})
 add_definitions(-DIN_OV_CORE_LIBRARY)
 
 set(OV_CORE_INCLUDE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/include)
+set(OV_CORE_DEV_API_PATH ${CMAKE_CURRENT_SOURCE_DIR}/dev_api)
 
 file(GLOB_RECURSE LIBRARY_SRC ${CMAKE_CURRENT_SOURCE_DIR}/src/*.cpp
                               ${CMAKE_CURRENT_SOURCE_DIR}/src/*.hpp)
diff --git a/src/core/include/openvino/op/loop.hpp b/src/core/include/openvino/op/loop.hpp
index cb174d588b7bc3..c1ad30e5308e4a 100644
--- a/src/core/include/openvino/op/loop.hpp
+++ b/src/core/include/openvino/op/loop.hpp
@@ -10,6 +10,7 @@
 #include "openvino/op/constant.hpp"
 #include "openvino/op/parameter.hpp"
 #include "openvino/op/util/sub_graph_base.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 namespace ov {
 namespace op {
@@ -61,9 +62,7 @@ class OPENVINO_API Loop : public op::util::SubGraphOp {
     bool visit_attributes(AttributeVisitor& visitor) override;
     std::shared_ptr<Node> clone_with_new_inputs(const OutputVector& new_args) const override;
 
-    OPENVINO_SUPPRESS_DEPRECATED_START
-    bool evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const override;
-    OPENVINO_SUPPRESS_DEPRECATED_END
+    bool evaluate(ov::TensorVector& outputs, const ov::TensorVector& inputs) const override;
     bool has_evaluate() const override;
 
 protected:
diff --git a/src/core/reference/CMakeLists.txt b/src/core/reference/CMakeLists.txt
index dbd126d84a4bf0..0a6c16313d7ccb 100644
--- a/src/core/reference/CMakeLists.txt
+++ b/src/core/reference/CMakeLists.txt
@@ -35,6 +35,7 @@ endif()
 
 target_include_directories(${TARGET_NAME} PUBLIC
     $<BUILD_INTERFACE:${REF_IMPL_INCLUDE_DIR}>
+    $<BUILD_INTERFACE:${OV_CORE_DEV_API_PATH}>
     $<BUILD_INTERFACE:${OV_CORE_INCLUDE_PATH}>)
 
 target_include_directories(${TARGET_NAME} SYSTEM PRIVATE
diff --git a/src/core/reference/include/openvino/reference/abs.hpp b/src/core/reference/include/openvino/reference/abs.hpp
index c58e70c5b4de02..426634a63a2d34 100644
--- a/src/core/reference/include/openvino/reference/abs.hpp
+++ b/src/core/reference/include/openvino/reference/abs.hpp
@@ -4,6 +4,7 @@
 
 #pragma once
 
+#include <algorithm>
 #include <cstddef>
 #include <type_traits>
 
diff --git a/src/core/reference/include/openvino/reference/adaptive_max_pool.hpp b/src/core/reference/include/openvino/reference/adaptive_max_pool.hpp
index 9aa0c3afa2af83..69c8ef2c940834 100644
--- a/src/core/reference/include/openvino/reference/adaptive_max_pool.hpp
+++ b/src/core/reference/include/openvino/reference/adaptive_max_pool.hpp
@@ -10,6 +10,7 @@
 
 #include "ngraph/axis_vector.hpp"
 #include "ngraph/shape.hpp"
+#include "openvino/reference/adaptive_avg_pool.hpp"
 
 namespace ov {
 namespace reference {
diff --git a/src/core/reference/include/openvino/reference/convert_color_nv12.hpp b/src/core/reference/include/openvino/reference/convert_color_nv12.hpp
index 4e8db24eb29668..a42aff6184c17f 100644
--- a/src/core/reference/include/openvino/reference/convert_color_nv12.hpp
+++ b/src/core/reference/include/openvino/reference/convert_color_nv12.hpp
@@ -107,12 +107,12 @@ void color_convert_i420(const T* arg_y,
     }
 }
 
-OPENVINO_SUPPRESS_DEPRECATED_START
-template <ov::element::Type_t ET>
+template <ov::element::Type_t T>
 inline bool color_convert_nv12(const std::shared_ptr<Node>& op,
-                               const ov::HostTensorVector& outputs,
-                               const ov::HostTensorVector& inputs,
+                               ov::TensorVector& outputs,
+                               const ov::TensorVector& inputs,
                                ov::op::util::ConvertColorNV12Base::ColorConversion type) {
+    using ET = typename ov::element_type_traits<T>::value_type;
     static const size_t N_DIM = 0;
     static const size_t H_DIM = 1;
     static const size_t W_DIM = 2;
@@ -122,17 +122,17 @@ inline bool color_convert_nv12(const std::shared_ptr<Node>& op,
     auto single_plane = op->get_input_size() == 1;
 
     const auto& y_tensor = inputs[0];
-    auto batch_size = y_tensor->get_shape()[N_DIM];
-    auto image_w = y_tensor->get_shape()[W_DIM];
-    auto image_h = y_tensor->get_shape()[H_DIM];
+    auto batch_size = y_tensor.get_shape()[N_DIM];
+    auto image_w = y_tensor.get_shape()[W_DIM];
+    auto image_h = y_tensor.get_shape()[H_DIM];
     if (single_plane) {
         image_h = image_h * 2 / 3;
     }
-    outputs[0]->set_shape({batch_size, image_h, image_w, 3});  // 3 is RGB
+    outputs[0].set_shape({batch_size, image_h, image_w, 3});  // 3 is RGB
     if (single_plane) {
-        color_convert_nv12(y_tensor->get_data_ptr<ET>(),
-                           y_tensor->get_data_ptr<ET>() + image_w * image_h,
-                           outputs[0]->get_data_ptr<ET>(),
+        color_convert_nv12(y_tensor.data<ET>(),
+                           y_tensor.data<ET>() + image_w * image_h,
+                           outputs[0].data<ET>(),
                            batch_size,
                            image_h,
                            image_w,
@@ -141,9 +141,9 @@ inline bool color_convert_nv12(const std::shared_ptr<Node>& op,
                            type);
     } else {
         const auto& uv_tensor = inputs[1];
-        color_convert_nv12(y_tensor->get_data_ptr<ET>(),
-                           uv_tensor->get_data_ptr<ET>(),
-                           outputs[0]->get_data_ptr<ET>(),
+        color_convert_nv12(y_tensor.data<ET>(),
+                           uv_tensor.data<ET>(),
+                           outputs[0].data<ET>(),
                            batch_size,
                            image_h,
                            image_w,
@@ -154,11 +154,12 @@ inline bool color_convert_nv12(const std::shared_ptr<Node>& op,
     return true;
 }
 
-template <ov::element::Type_t ET>
+template <ov::element::Type_t T>
 inline bool color_convert_i420(const std::shared_ptr<Node>& op,
-                               const ov::HostTensorVector& outputs,
-                               const ov::HostTensorVector& inputs,
+                               ov::TensorVector& outputs,
+                               const ov::TensorVector& inputs,
                                ov::op::util::ConvertColorI420Base::ColorConversion type) {
+    using ET = typename ov::element_type_traits<T>::value_type;
     static const size_t N_DIM = 0;
     static const size_t H_DIM = 1;
     static const size_t W_DIM = 2;
@@ -168,18 +169,18 @@ inline bool color_convert_i420(const std::shared_ptr<Node>& op,
     auto single_plane = op->get_input_size() == 1;
 
     const auto& y_tensor = inputs[0];
-    auto batch_size = y_tensor->get_shape()[N_DIM];
-    auto image_w = y_tensor->get_shape()[W_DIM];
-    auto image_h = y_tensor->get_shape()[H_DIM];
+    auto batch_size = y_tensor.get_shape()[N_DIM];
+    auto image_w = y_tensor.get_shape()[W_DIM];
+    auto image_h = y_tensor.get_shape()[H_DIM];
     if (single_plane) {
         image_h = image_h * 2 / 3;
     }
-    outputs[0]->set_shape({batch_size, image_h, image_w, 3});  // 3 is RGB
+    outputs[0].set_shape({batch_size, image_h, image_w, 3});  // 3 is RGB
     if (single_plane) {
-        color_convert_i420(y_tensor->get_data_ptr<ET>(),
-                           y_tensor->get_data_ptr<ET>() + image_w * image_h,
-                           y_tensor->get_data_ptr<ET>() + 5 * image_w * image_h / 4,
-                           outputs[0]->get_data_ptr<ET>(),
+        color_convert_i420(y_tensor.data<ET>(),
+                           y_tensor.data<ET>() + image_w * image_h,
+                           y_tensor.data<ET>() + 5 * image_w * image_h / 4,
+                           outputs[0].data<ET>(),
                            batch_size,
                            image_h,
                            image_w,
@@ -189,10 +190,10 @@ inline bool color_convert_i420(const std::shared_ptr<Node>& op,
     } else {
         const auto& u_tensor = inputs[1];
         const auto& v_tensor = inputs[2];
-        color_convert_i420(y_tensor->get_data_ptr<ET>(),
-                           u_tensor->get_data_ptr<ET>(),
-                           v_tensor->get_data_ptr<ET>(),
-                           outputs[0]->get_data_ptr<ET>(),
+        color_convert_i420(y_tensor.data<ET>(),
+                           u_tensor.data<ET>(),
+                           v_tensor.data<ET>(),
+                           outputs[0].data<ET>(),
                            batch_size,
                            image_h,
                            image_w,
@@ -203,6 +204,5 @@ inline bool color_convert_i420(const std::shared_ptr<Node>& op,
     return true;
 }
 
-OPENVINO_SUPPRESS_DEPRECATED_END
 }  // namespace reference
 }  // namespace ov
diff --git a/src/core/reference/include/openvino/reference/ctc_loss.hpp b/src/core/reference/include/openvino/reference/ctc_loss.hpp
index 03fae356ad69a7..1b16b352eb4870 100644
--- a/src/core/reference/include/openvino/reference/ctc_loss.hpp
+++ b/src/core/reference/include/openvino/reference/ctc_loss.hpp
@@ -6,6 +6,8 @@
 
 #include <math.h>
 
+#include <unordered_set>
+
 #include "ngraph/shape_util.hpp"
 
 namespace ov {
diff --git a/src/core/reference/include/openvino/reference/einsum.hpp b/src/core/reference/include/openvino/reference/einsum.hpp
index 667a923739ce9c..8e477959bcba37 100644
--- a/src/core/reference/include/openvino/reference/einsum.hpp
+++ b/src/core/reference/include/openvino/reference/einsum.hpp
@@ -11,6 +11,6 @@
 
 namespace ov {
 namespace reference {
-void einsum(const HostTensorVector& outputs, const HostTensorVector& inputs, const std::string& equation);
+void einsum(ov::TensorVector& outputs, const ov::TensorVector& inputs, const std::string& equation);
 }  // namespace reference
 }  // namespace ov
diff --git a/src/core/reference/include/openvino/reference/fft.hpp b/src/core/reference/include/openvino/reference/fft.hpp
index f35ef8ce79b981..474da3734157ed 100644
--- a/src/core/reference/include/openvino/reference/fft.hpp
+++ b/src/core/reference/include/openvino/reference/fft.hpp
@@ -23,13 +23,9 @@
 #include <cstddef>
 #include <functional>
 #include <map>
-#include <ngraph/runtime/host_tensor.hpp>
 #include <vector>
 
-#include "ngraph/node.hpp"
-#include "ngraph/op/util/op_types.hpp"
-#include "ngraph/ops.hpp"
-#include "ngraph/shape_util.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 namespace ov {
 namespace reference {
@@ -43,8 +39,8 @@ void fft(const float* input_data,
          const Shape& output_shape,
          FFTKind fft_kind);
 
-void fft_postprocessing(const HostTensorVector& outputs,
-                        const ngraph::element::Type output_type,
+void fft_postprocessing(ov::TensorVector& outputs,
+                        const ov::element::Type output_type,
                         const std::vector<float>& fft_result);
 
 std::vector<int64_t> canonicalize_axes(const int64_t* axes_data,
diff --git a/src/core/reference/include/openvino/reference/function.hpp b/src/core/reference/include/openvino/reference/function.hpp
index 575821e81b4a0f..24c10da48b40b8 100644
--- a/src/core/reference/include/openvino/reference/function.hpp
+++ b/src/core/reference/include/openvino/reference/function.hpp
@@ -12,6 +12,6 @@
 
 namespace ov {
 namespace reference {
-void function(const std::shared_ptr<Model>& function, const HostTensorVector& inputs, HostTensorVector& outputs);
+void function(const std::shared_ptr<Model>& function, const ov::TensorVector& inputs, ov::TensorVector& outputs);
 }
 }  // namespace ov
diff --git a/src/core/reference/include/openvino/reference/hard_sigmoid.hpp b/src/core/reference/include/openvino/reference/hard_sigmoid.hpp
index 4dd92870791bdb..dd2cb98df1da4c 100644
--- a/src/core/reference/include/openvino/reference/hard_sigmoid.hpp
+++ b/src/core/reference/include/openvino/reference/hard_sigmoid.hpp
@@ -4,6 +4,7 @@
 
 #pragma once
 
+#include <algorithm>
 #include <cmath>
 #include <cstddef>
 
diff --git a/src/core/reference/include/openvino/reference/if.hpp b/src/core/reference/include/openvino/reference/if.hpp
index aaa47d0624ba29..27fc71ed393027 100644
--- a/src/core/reference/include/openvino/reference/if.hpp
+++ b/src/core/reference/include/openvino/reference/if.hpp
@@ -13,7 +13,7 @@ namespace reference {
 void if_reference(const std::vector<std::shared_ptr<Model>>& body,
                   const std::vector<op::util::MultiSubGraphOp::MultiSubgraphOutputDescriptionVector>& out_descs,
                   const std::vector<op::util::MultiSubGraphOp::MultiSubgraphInputDescriptionVector>& input_descs,
-                  const HostTensorVector& out,
-                  const HostTensorVector& args);
+                  ov::TensorVector& out,
+                  const ov::TensorVector& args);
 }
 }  // namespace ov
diff --git a/src/core/reference/include/openvino/reference/is_finite.hpp b/src/core/reference/include/openvino/reference/is_finite.hpp
index 21677d0f9f9066..302da8485d3c83 100644
--- a/src/core/reference/include/openvino/reference/is_finite.hpp
+++ b/src/core/reference/include/openvino/reference/is_finite.hpp
@@ -4,6 +4,7 @@
 
 #pragma once
 
+#include <algorithm>
 #include <cmath>
 #include <cstddef>
 
diff --git a/src/core/reference/include/openvino/reference/is_inf.hpp b/src/core/reference/include/openvino/reference/is_inf.hpp
index 156dafcfe6e9b0..210248ff2fcd2b 100644
--- a/src/core/reference/include/openvino/reference/is_inf.hpp
+++ b/src/core/reference/include/openvino/reference/is_inf.hpp
@@ -4,9 +4,12 @@
 
 #pragma once
 
+#include <algorithm>
 #include <cmath>
 #include <cstddef>
 
+#include "openvino/op/is_inf.hpp"
+
 namespace ov {
 namespace reference {
 template <typename T, typename U>
diff --git a/src/core/reference/include/openvino/reference/is_nan.hpp b/src/core/reference/include/openvino/reference/is_nan.hpp
index 47eed0e9944800..7b96e3abb08a79 100644
--- a/src/core/reference/include/openvino/reference/is_nan.hpp
+++ b/src/core/reference/include/openvino/reference/is_nan.hpp
@@ -4,6 +4,7 @@
 
 #pragma once
 
+#include <algorithm>
 #include <cmath>
 #include <cstddef>
 
diff --git a/src/core/reference/include/openvino/reference/loop.hpp b/src/core/reference/include/openvino/reference/loop.hpp
index f233aaf0089576..19e16c2067d564 100644
--- a/src/core/reference/include/openvino/reference/loop.hpp
+++ b/src/core/reference/include/openvino/reference/loop.hpp
@@ -15,7 +15,7 @@ void loop(const std::shared_ptr<Model>& body,
           const op::util::OutputDescriptionVector& out_descs,
           const op::util::InputDescriptionVector& input_descs,
           const op::v5::Loop::SpecialBodyPorts& special_ports,
-          const HostTensorVector& out,
-          const HostTensorVector& args);
+          ov::TensorVector& out,
+          const ov::TensorVector& args);
 }
 }  // namespace ov
diff --git a/src/core/reference/include/openvino/reference/lstm_cell.hpp b/src/core/reference/include/openvino/reference/lstm_cell.hpp
index b82eef98ba95d6..1a21f21cb3e497 100644
--- a/src/core/reference/include/openvino/reference/lstm_cell.hpp
+++ b/src/core/reference/include/openvino/reference/lstm_cell.hpp
@@ -6,6 +6,7 @@
 
 #include <cmath>
 
+#include "openvino/op/lstm_cell.hpp"
 #include "openvino/reference/add.hpp"
 #include "openvino/reference/clamp.hpp"
 #include "openvino/reference/matmul.hpp"
diff --git a/src/core/reference/include/openvino/reference/non_max_suppression.hpp b/src/core/reference/include/openvino/reference/non_max_suppression.hpp
index ca4d9ef49c2955..b9e37e28c6a365 100644
--- a/src/core/reference/include/openvino/reference/non_max_suppression.hpp
+++ b/src/core/reference/include/openvino/reference/non_max_suppression.hpp
@@ -36,7 +36,7 @@ void non_max_suppression5(const float* boxes_data,
                           int64_t* valid_outputs,
                           const bool sort_result_descending);
 
-void nms5_postprocessing(const HostTensorVector& outputs,
+void nms5_postprocessing(ov::TensorVector& outputs,
                          const ngraph::element::Type output_type,
                          const std::vector<int64_t>& selected_indices,
                          const std::vector<float>& selected_scores,
@@ -58,7 +58,7 @@ void non_max_suppression(const float* boxes_data,
                          int64_t* valid_outputs,
                          const bool sort_result_descending);
 
-void nms_postprocessing(const HostTensorVector& outputs,
+void nms_postprocessing(ov::TensorVector& outputs,
                         const ngraph::element::Type output_type,
                         const std::vector<int64_t>& selected_indices,
                         const std::vector<float>& selected_scores,
diff --git a/src/core/reference/include/openvino/reference/roi_pooling.hpp b/src/core/reference/include/openvino/reference/roi_pooling.hpp
index 7efa4daf38467d..5dbe13d1de51b6 100644
--- a/src/core/reference/include/openvino/reference/roi_pooling.hpp
+++ b/src/core/reference/include/openvino/reference/roi_pooling.hpp
@@ -4,6 +4,9 @@
 
 #pragma once
 
+#include <cmath>
+#include <limits>
+
 #include "ngraph/shape.hpp"
 
 namespace ov {
diff --git a/src/core/reference/include/openvino/reference/tensor_iterator.hpp b/src/core/reference/include/openvino/reference/tensor_iterator.hpp
index f4ff4d8919ee76..05a66f2e640eb3 100644
--- a/src/core/reference/include/openvino/reference/tensor_iterator.hpp
+++ b/src/core/reference/include/openvino/reference/tensor_iterator.hpp
@@ -5,18 +5,21 @@
 #pragma once
 
 #include <cmath>
-#include <ngraph/opsets/opset5.hpp>
+
+#include "openvino/core/model.hpp"
+#include "openvino/op/util/sub_graph_base.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 namespace ov {
 namespace reference {
 using custom_evaluate_function = std::function<
-    void(const std::shared_ptr<Model>& function, const HostTensorVector& inputs, HostTensorVector& outputs)>;
+    void(const std::shared_ptr<Model>& function, const ov::TensorVector& inputs, ov::TensorVector& outputs)>;
 void tensor_iterator(uint64_t num_iterations,
                      const std::shared_ptr<Model>& body,
                      const op::util::OutputDescriptionVector& out_descs,
                      const op::util::InputDescriptionVector& input_descs,
-                     const HostTensorVector& out,
-                     const HostTensorVector& args,
+                     ov::TensorVector& out,
+                     const ov::TensorVector& args,
                      const custom_evaluate_function& evaluate = nullptr);
 }  // namespace reference
 }  // namespace ov
diff --git a/src/core/reference/src/op/einsum.cpp b/src/core/reference/src/op/einsum.cpp
index 1901073f184a8a..125e33e3aa6b49 100644
--- a/src/core/reference/src/op/einsum.cpp
+++ b/src/core/reference/src/op/einsum.cpp
@@ -5,9 +5,8 @@
 #include "openvino/reference/einsum.hpp"
 
 #include <algorithm>
-#include <ngraph/opsets/opset7.hpp>
 
-#include "ngraph/shape.hpp"
+#include "openvino/op/einsum.hpp"
 #include "openvino/reference/broadcast.hpp"
 #include "openvino/reference/matmul.hpp"
 #include "openvino/reference/multiply.hpp"
@@ -16,7 +15,6 @@
 #include "openvino/reference/transpose.hpp"
 #include "openvino/reference/utils/span.hpp"
 
-NGRAPH_SUPPRESS_DEPRECATED_START
 namespace ov {
 namespace reference {
 namespace {
@@ -27,7 +25,7 @@ namespace {
 std::vector<std::pair<size_t, size_t>> compute_einsum_path(size_t num_inputs) {
     // TODO: implement algorithm for finding (pseudo-)optimal einsum_path
     std::vector<std::pair<size_t, size_t>> einsum_path;
-    NGRAPH_CHECK(num_inputs > 0);
+    OPENVINO_ASSERT(num_inputs > 0);
     for (size_t input_ind = num_inputs - 1; input_ind > 0; --input_ind) {
         einsum_path.push_back(std::make_pair(0, input_ind));
     }
@@ -96,7 +94,7 @@ std::string generate_grouping_subscript(const std::string& input_subscript,
         return input_subscript;
     }
 
-    auto labels = ngraph::opset7::Einsum::extract_labels(input_subscript);
+    auto labels = ov::op::v7::Einsum::extract_labels(input_subscript);
     std::string required_subscript = "";
     for (auto index : labels_inds) {
         required_subscript += labels[index];
@@ -108,15 +106,15 @@ std::string generate_grouping_subscript(const std::string& input_subscript,
 std::unordered_map<std::string, ov::TensorLabel> compute_label_dim_map(const Rank& input_rank,
                                                                        const std::string& input_subscript) {
     constexpr char ellipsis[] = "...";
-    auto labels = ngraph::opset7::Einsum::extract_labels(input_subscript);
+    auto labels = ov::op::v7::Einsum::extract_labels(input_subscript);
     size_t input_rank_length = labels.size();
-    NGRAPH_CHECK(input_rank.is_static() || (std::find(labels.begin(), labels.end(), ellipsis) == labels.end()),
-                 "Input rank cannot be dynamic in case of ellipsis in input subscript");
+    OPENVINO_ASSERT(input_rank.is_static() || (std::find(labels.begin(), labels.end(), ellipsis) == labels.end()),
+                    "Input rank cannot be dynamic in case of ellipsis in input subscript");
     if (input_rank.is_static()) {
         input_rank_length = input_rank.get_length();
     }
     std::unordered_map<std::string, ov::TensorLabel> resulted_map;
-    NGRAPH_CHECK(input_rank_length >= labels.size());
+    OPENVINO_ASSERT(input_rank_length >= labels.size());
     size_t num_broadcasted_dims = input_rank_length - labels.size() + 1;
 
     size_t current_dim = 0;
@@ -146,7 +144,7 @@ std::unordered_map<std::string, ov::TensorLabel> compute_label_dim_map(const Ran
 /// range [s_begin;s_end)
 ///
 Shape compute_sub_shape(const Shape& input_shape, size_t begin, size_t end, bool is_product = false) {
-    NGRAPH_CHECK(end <= input_shape.size());
+    OPENVINO_ASSERT(end <= input_shape.size());
     if (end <= begin) {
         // return empty shape
         return Shape();
@@ -179,17 +177,17 @@ void compute_ranges(const Rank& input_rank,
     constexpr char ellipsis[] = "...";
     size_t common_rank = common_labels.size();
     if (std::find(common_labels.begin(), common_labels.end(), ellipsis) != common_labels.end()) {
-        NGRAPH_CHECK(label_to_dim_map.find(ellipsis) != label_to_dim_map.end());
+        OPENVINO_ASSERT(label_to_dim_map.find(ellipsis) != label_to_dim_map.end());
         common_rank += label_to_dim_map[ellipsis].size() - 1;
     }
     size_t sep_rank = sep_labels.size();
     if (std::find(sep_labels.begin(), sep_labels.end(), ellipsis) != sep_labels.end()) {
-        NGRAPH_CHECK(label_to_dim_map.find(ellipsis) != label_to_dim_map.end());
+        OPENVINO_ASSERT(label_to_dim_map.find(ellipsis) != label_to_dim_map.end());
         sep_rank += label_to_dim_map[ellipsis].size() - 1;
     }
     size_t reduced_rank = reduced_labels.size();
     if (std::find(reduced_labels.begin(), reduced_labels.end(), ellipsis) != reduced_labels.end()) {
-        NGRAPH_CHECK(label_to_dim_map.find(ellipsis) != label_to_dim_map.end());
+        OPENVINO_ASSERT(label_to_dim_map.find(ellipsis) != label_to_dim_map.end());
         reduced_rank += label_to_dim_map[ellipsis].size() - 1;
     }
 
@@ -255,15 +253,15 @@ Shape compute_matmul_output_shape(const Shape& common_sub_shape,
 /// inputs with indices input_ind1 and input_ind2 and inserted new input and
 /// the corresponsing subscript in the tail
 ///
-void update_operands(HostTensorVector& inputs,
+void update_operands(ov::TensorVector& inputs,
                      std::vector<std::string>& input_subscripts,
                      size_t input_ind1,
                      size_t input_ind2,
-                     const HostTensorPtr& new_input,
+                     const ov::Tensor& new_input,
                      const std::string& new_subscript) {
-    NGRAPH_CHECK(input_ind1 < input_ind2);
-    NGRAPH_CHECK(input_ind2 < inputs.size());
-    NGRAPH_CHECK(input_ind2 < input_subscripts.size());
+    OPENVINO_ASSERT(input_ind1 < input_ind2);
+    OPENVINO_ASSERT(input_ind2 < inputs.size());
+    OPENVINO_ASSERT(input_ind2 < input_subscripts.size());
     inputs.erase(inputs.begin() + input_ind2);
     inputs.erase(inputs.begin() + input_ind1);
     inputs.push_back(new_input);
@@ -275,26 +273,28 @@ void update_operands(HostTensorVector& inputs,
 /// \brief      Unsqueeze input by given dimensions if a vector of unsqueezing
 /// dimensions is not empty
 template <typename T>
-HostTensorPtr unsqueeze_input(const HostTensorPtr& input, std::vector<int64_t>& unsqueeze_axes) {
+ov::Tensor unsqueeze_input(const ov::Tensor& input, std::vector<int64_t>& unsqueeze_axes) {
     if (unsqueeze_axes.empty()) {
         return input;
     }
 
-    Shape input_shape = input->get_shape();
+    Shape input_shape = input.get_shape();
     Shape output_shape = input_shape;
     std::sort(unsqueeze_axes.begin(), unsqueeze_axes.end());
     for (auto unsqueeze_axis : unsqueeze_axes) {
-        NGRAPH_CHECK(unsqueeze_axis >= 0);
-        NGRAPH_CHECK(static_cast<size_t>(unsqueeze_axis) <= output_shape.size());
+        OPENVINO_ASSERT(unsqueeze_axis >= 0);
+        OPENVINO_ASSERT(static_cast<size_t>(unsqueeze_axis) <= output_shape.size());
         output_shape.insert(output_shape.begin() + unsqueeze_axis, 1);
     }
 
-    HostTensorPtr output = std::shared_ptr<HostTensor>(new HostTensor(input->get_element_type(), output_shape));
-    const AxisVector order = ngraph::get_default_order(input->get_shape());
-    const auto element_type = input->get_element_type();
+    auto output = ov::Tensor(input.get_element_type(), output_shape);
+    OPENVINO_SUPPRESS_DEPRECATED_START
+    const AxisVector order = ngraph::get_default_order(input.get_shape());
+    OPENVINO_SUPPRESS_DEPRECATED_END
+    const auto element_type = input.get_element_type();
 
-    reference::reshape(reinterpret_cast<const char*>(input->get_data_ptr<T>()),
-                       reinterpret_cast<char*>(output->get_data_ptr<T>()),
+    reference::reshape(reinterpret_cast<const char*>(input.data<T>()),
+                       reinterpret_cast<char*>(output.data<T>()),
                        input_shape,
                        order,
                        output_shape,
@@ -307,31 +307,31 @@ HostTensorPtr unsqueeze_input(const HostTensorPtr& input, std::vector<int64_t>&
 /// equation and reduce dimensions corresponding to such labels
 ///
 template <typename T>
-void reduce_input(HostTensorVector& inputs,
+void reduce_input(ov::TensorVector& inputs,
                   std::vector<std::string>& input_subscripts,
                   const std::string& output_subscript,
                   size_t input_ind) {
     // perform sanity check for arguments
     auto num_inputs = inputs.size();
-    NGRAPH_CHECK(num_inputs == input_subscripts.size(), "Each input must have own subscript.");
-    NGRAPH_CHECK(input_ind < num_inputs, "Input index is out of range.");
+    OPENVINO_ASSERT(num_inputs == input_subscripts.size(), "Each input must have own subscript.");
+    OPENVINO_ASSERT(input_ind < num_inputs, "Input index is out of range.");
 
     const auto& input_ptr = inputs[input_ind];
     const auto& input_subscript = input_subscripts[input_ind];
-    const auto input_shape = input_ptr->get_shape();
+    const auto input_shape = input_ptr.get_shape();
 
     // compute output shape and axes to reduce
-    ngraph::Shape output_shape;
-    ngraph::AxisSet reduced_axes;
-    auto labels = ngraph::opset7::Einsum::extract_labels(input_subscripts[input_ind]);
-    auto label_dim_map = compute_label_dim_map(input_ptr->get_partial_shape().rank(), input_subscript);
+    ov::Shape output_shape;
+    ov::AxisSet reduced_axes;
+    auto labels = ov::op::v7::Einsum::extract_labels(input_subscripts[input_ind]);
+    auto label_dim_map = compute_label_dim_map(input_ptr.get_shape().size(), input_subscript);
     std::string new_input_subscript = "";
     for (const auto& label : labels) {
         // check if the current label is met in the other input subscripts
         // or the output subscript
         bool is_dim_reduced = is_dimension_reduced(input_subscripts, output_subscript, label, {input_ind});
 
-        NGRAPH_CHECK(label_dim_map.find(label) != label_dim_map.end());
+        OPENVINO_ASSERT(label_dim_map.find(label) != label_dim_map.end());
         auto label_dims = label_dim_map[label];
 
         // if label is not met, dimension corresponding to the label is to reduce
@@ -350,9 +350,9 @@ void reduce_input(HostTensorVector& inputs,
         return;
     }
 
-    HostTensorPtr output_ptr = std::shared_ptr<HostTensor>(new HostTensor(input_ptr->get_element_type(), output_shape));
+    auto output_ptr = ov::Tensor(input_ptr.get_element_type(), output_shape);
 
-    reference::sum<T>(input_ptr->get_data_ptr<T>(), output_ptr->get_data_ptr<T>(), input_shape, reduced_axes);
+    reference::sum<T>(input_ptr.data<T>(), output_ptr.data<T>(), input_shape, reduced_axes);
 
     // update a vector of inputs and input subscripts
     inputs[input_ind] = output_ptr;
@@ -362,14 +362,14 @@ void reduce_input(HostTensorVector& inputs,
 /// \brief      Transpose input to layout specified through the required subscript
 ///
 template <typename T>
-void transpose_input(HostTensorVector& inputs,
+void transpose_input(ov::TensorVector& inputs,
                      std::vector<std::string>& input_subscripts,
                      const std::string& required_subscript,
                      size_t input_ind) {
     // perform sanity check for arguments
     auto num_inputs = inputs.size();
-    NGRAPH_CHECK(num_inputs == input_subscripts.size(), "Each input must have own subscript.");
-    NGRAPH_CHECK(input_ind < num_inputs, "Input index is out of range.");
+    OPENVINO_ASSERT(num_inputs == input_subscripts.size(), "Each input must have own subscript.");
+    OPENVINO_ASSERT(input_ind < num_inputs, "Input index is out of range.");
 
     // generate permutation vector by searching for bijection between
     // input_subscripts and required_subscript
@@ -384,29 +384,29 @@ void transpose_input(HostTensorVector& inputs,
 
     // find permutation that establishes bijection between the input subscript
     // and the required one
-    auto label_dim_map = compute_label_dim_map(input_ptr->get_partial_shape().rank(), input_subscript);
-    auto labels = ngraph::opset7::Einsum::extract_labels(input_subscript);
-    auto required_labels = ngraph::opset7::Einsum::extract_labels(required_subscript);
-    NGRAPH_CHECK(labels.size() == required_labels.size());
+    auto label_dim_map = compute_label_dim_map(input_ptr.get_shape().size(), input_subscript);
+    auto labels = ov::op::v7::Einsum::extract_labels(input_subscript);
+    auto required_labels = ov::op::v7::Einsum::extract_labels(required_subscript);
+    OPENVINO_ASSERT(labels.size() == required_labels.size());
     for (const auto& required_label : required_labels) {
-        NGRAPH_CHECK(label_dim_map.find(required_label) != label_dim_map.end());
+        OPENVINO_ASSERT(label_dim_map.find(required_label) != label_dim_map.end());
         auto label_dims = label_dim_map[required_label];
         permutation.insert(permutation.end(), label_dims.begin(), label_dims.end());
     }
 
-    const auto input_shape = input_ptr->get_shape();
-    const auto element_type = input_ptr->get_element_type();
+    const auto input_shape = input_ptr.get_shape();
+    const auto element_type = input_ptr.get_element_type();
 
     Shape output_shape(input_shape.size());
     std::transform(permutation.begin(), permutation.end(), output_shape.begin(), [&](const int64_t& v) {
-        NGRAPH_CHECK(v >= 0, "Negative values for transpose axes order are not supported.");
-        NGRAPH_CHECK(v < int64_t(input_shape.size()), "Transpose axis ", v, " is out of shape range.");
+        OPENVINO_ASSERT(v >= 0, "Negative values for transpose axes order are not supported.");
+        OPENVINO_ASSERT(v < int64_t(input_shape.size()), "Transpose axis ", v, " is out of shape range.");
         return input_shape[v];
     });
-    HostTensorPtr output_ptr = std::shared_ptr<HostTensor>(new HostTensor(element_type, output_shape));
+    auto output_ptr = ov::Tensor(element_type, output_shape);
 
-    reference::transpose(reinterpret_cast<const char*>(input_ptr->get_data_ptr<T>()),
-                         reinterpret_cast<char*>(output_ptr->get_data_ptr<T>()),
+    reference::transpose(reinterpret_cast<const char*>(input_ptr.data<T>()),
+                         reinterpret_cast<char*>(output_ptr.data<T>()),
                          input_shape,
                          element_type.size(),
                          permutation.data(),
@@ -421,15 +421,15 @@ void transpose_input(HostTensorVector& inputs,
 /// same shape of both operands in the common (or batch) dimensionsy.
 ///
 template <typename T>
-void broadcast_input(HostTensorVector& inputs,
+void broadcast_input(ov::TensorVector& inputs,
                      size_t input_ind,
                      const Shape& new_common_shape,
                      const Shape& separate_shape,
                      const Shape& reduced_shape,
                      bool is_separate_first) {
-    NGRAPH_CHECK(input_ind < inputs.size());
-    HostTensorPtr& input = inputs[input_ind];
-    const Shape old_shape = input->get_shape();
+    OPENVINO_ASSERT(input_ind < inputs.size());
+    ov::Tensor& input = inputs[input_ind];
+    const Shape old_shape = input.get_shape();
     Shape new_shape;
     new_shape.insert(new_shape.end(), new_common_shape.begin(), new_common_shape.end());
     if (is_separate_first) {
@@ -440,22 +440,22 @@ void broadcast_input(HostTensorVector& inputs,
         new_shape.insert(new_shape.end(), separate_shape.begin(), separate_shape.end());
     }
 
-    if (input->get_shape() == new_shape) {
+    if (input.get_shape() == new_shape) {
         return;
     }
-    NGRAPH_CHECK(old_shape.size() <= new_shape.size());
+    OPENVINO_ASSERT(old_shape.size() <= new_shape.size());
 
-    HostTensorPtr output = std::shared_ptr<HostTensor>(new HostTensor(input->get_element_type(), new_shape));
+    auto output = ov::Tensor(input.get_element_type(), new_shape);
 
     std::vector<size_t> broadcast_axes(old_shape.size());
     std::iota(broadcast_axes.begin(), broadcast_axes.end(), new_shape.size() - old_shape.size());
 
-    reference::broadcast(reinterpret_cast<const char*>(input->get_data_ptr<T>()),
-                         reinterpret_cast<char*>(output->get_data_ptr<T>()),
-                         input->get_shape(),
-                         output->get_shape(),
+    reference::broadcast(reinterpret_cast<const char*>(input.data<T>()),
+                         reinterpret_cast<char*>(output.data<T>()),
+                         input.get_shape(),
+                         output.get_shape(),
                          broadcast_axes,
-                         input->get_element_type().size());
+                         input.get_element_type().size());
 
     input = output;
 }
@@ -465,21 +465,21 @@ void broadcast_input(HostTensorVector& inputs,
 /// identity
 ///
 template <typename T>
-HostTensorPtr build_identity(const HostTensorPtr& input_ptr, const ov::TensorLabel& repeated_label_dims) {
+ov::Tensor build_identity(const ov::Tensor& input, const ov::TensorLabel& repeated_label_dims) {
     // allocate HostTensor for building identity tensor
-    NGRAPH_CHECK(repeated_label_dims.size() > 1);
-    Shape input_shape = input_ptr->get_shape();
+    OPENVINO_ASSERT(repeated_label_dims.size() > 1);
+    Shape input_shape = input.get_shape();
     Shape identity_shape(input_shape.size(), 1);
     size_t repeated_label_dim_size = input_shape[repeated_label_dims[0]];
     for (auto dim : repeated_label_dims) {
-        NGRAPH_CHECK(dim < input_shape.size());
-        NGRAPH_CHECK(repeated_label_dim_size == input_shape[dim]);
+        OPENVINO_ASSERT(dim < input_shape.size());
+        OPENVINO_ASSERT(repeated_label_dim_size == input_shape[dim]);
         identity_shape[dim] = repeated_label_dim_size;
     }
-    HostTensorPtr identity = std::shared_ptr<HostTensor>(new HostTensor(input_ptr->get_element_type(), identity_shape));
+    auto identity = ov::Tensor(input.get_element_type(), identity_shape);
 
-    T* identity_data_ptr = identity->get_data_ptr<T>();
-    size_t data_size = shape_size(identity_shape) * identity->get_element_type().size();
+    T* identity_data_ptr = identity.data<T>();
+    size_t data_size = shape_size(identity_shape) * identity.get_element_type().size();
     std::memset(identity_data_ptr, 0, data_size);
 
     // Identity[k,k,...,k] element is placed in k*p^(n-1) + ... + k*p + k position,
@@ -507,35 +507,32 @@ HostTensorPtr build_identity(const HostTensorPtr& input_ptr, const ov::TensorLab
 /// repeated label
 ///
 template <typename T>
-HostTensorPtr build_multi_identity(const HostTensorPtr& input_ptr,
-                                   const std::vector<std::string>& repeated_labels,
-                                   std::unordered_map<std::string, ov::TensorLabel>& label_dim_map) {
-    Shape input_shape = input_ptr->get_shape();
+ov::Tensor build_multi_identity(const ov::Tensor& input,
+                                const std::vector<std::string>& repeated_labels,
+                                std::unordered_map<std::string, ov::TensorLabel>& label_dim_map) {
+    Shape input_shape = input.get_shape();
 
     // initially set multi-identity with identity for the first repeated label
-    NGRAPH_CHECK(repeated_labels.size() > 0);
+    OPENVINO_ASSERT(repeated_labels.size() > 0);
     auto first_repeated_label = repeated_labels[0];
-    NGRAPH_CHECK(label_dim_map.find(first_repeated_label) != label_dim_map.end());
+    OPENVINO_ASSERT(label_dim_map.find(first_repeated_label) != label_dim_map.end());
     auto repeated_label_dims = label_dim_map[first_repeated_label];
-    HostTensorPtr multi_identity = build_identity<T>(input_ptr, repeated_label_dims);
+    ov::Tensor multi_identity = build_identity<T>(input, repeated_label_dims);
 
     for (size_t label_ind = 1; label_ind < repeated_labels.size(); ++label_ind) {
-        NGRAPH_CHECK(label_dim_map.find(repeated_labels[label_ind]) != label_dim_map.end());
+        OPENVINO_ASSERT(label_dim_map.find(repeated_labels[label_ind]) != label_dim_map.end());
         repeated_label_dims = label_dim_map[repeated_labels[label_ind]];
-        HostTensorPtr identity = build_identity<T>(input_ptr, repeated_label_dims);
-
-        PartialShape output_shape = multi_identity->get_partial_shape();
-        PartialShape::broadcast_merge_into(output_shape,
-                                           identity->get_partial_shape(),
-                                           ngraph::op::AutoBroadcastType::NUMPY);
-        HostTensorPtr mul_output =
-            std::shared_ptr<HostTensor>(new HostTensor(identity->get_element_type(), output_shape.get_shape()));
-        reference::multiply<T>(multi_identity->get_data_ptr<T>(),
-                               identity->get_data_ptr<T>(),
-                               mul_output->get_data_ptr<T>(),
-                               multi_identity->get_shape(),
-                               identity->get_shape(),
-                               ngraph::op::AutoBroadcastType::NUMPY);
+        ov::Tensor identity = build_identity<T>(input, repeated_label_dims);
+
+        PartialShape output_shape = multi_identity.get_shape();
+        PartialShape::broadcast_merge_into(output_shape, identity.get_shape(), ov::op::AutoBroadcastType::NUMPY);
+        auto mul_output = ov::Tensor(identity.get_element_type(), output_shape.get_shape());
+        reference::multiply<T>(multi_identity.data<T>(),
+                               identity.data<T>(),
+                               mul_output.data<T>(),
+                               multi_identity.get_shape(),
+                               identity.get_shape(),
+                               ov::op::AutoBroadcastType::NUMPY);
         multi_identity = mul_output;
     }
     return multi_identity;
@@ -545,28 +542,28 @@ HostTensorPtr build_multi_identity(const HostTensorPtr& input_ptr,
 /// labels) is diagonal
 ///
 template <typename T>
-void extract_diagonal(HostTensorVector& inputs, std::vector<std::string>& input_subscripts, size_t input_ind) {
+void extract_diagonal(ov::TensorVector& inputs, std::vector<std::string>& input_subscripts, size_t input_ind) {
     // perform sanity check for arguments
     auto num_inputs = inputs.size();
-    NGRAPH_CHECK(num_inputs == input_subscripts.size(), "Each input must have own subscript.");
-    NGRAPH_CHECK(input_ind < num_inputs, "Input index is out of range.");
+    OPENVINO_ASSERT(num_inputs == input_subscripts.size(), "Each input must have own subscript.");
+    OPENVINO_ASSERT(input_ind < num_inputs, "Input index is out of range.");
 
     const auto& input_ptr = inputs[input_ind];
     const auto& input_subscript = input_subscripts[input_ind];
-    const auto input_shape = input_ptr->get_shape();
+    const auto input_shape = input_ptr.get_shape();
 
     std::string resultant_subscript = "";
     constexpr char ellipsis[] = "...";
-    auto labels = ngraph::opset7::Einsum::extract_labels(input_subscript);
-    auto label_dim_map = compute_label_dim_map(input_ptr->get_partial_shape().rank(), input_subscript);
+    auto labels = ov::op::v7::Einsum::extract_labels(input_subscript);
+    auto label_dim_map = compute_label_dim_map(input_ptr.get_shape().size(), input_subscript);
     std::vector<std::string> repeated_labels;
     Shape result_shape;
     AxisSet reduced_axes;
     for (const auto& label : labels) {
         if (resultant_subscript.find(label) == std::string::npos) {
-            NGRAPH_CHECK(label_dim_map.find(label) != label_dim_map.end());
+            OPENVINO_ASSERT(label_dim_map.find(label) != label_dim_map.end());
             auto dims = label_dim_map[label];
-            NGRAPH_CHECK(dims.size() > 0);
+            OPENVINO_ASSERT(dims.size() > 0);
             if (label != ellipsis && dims.size() > 1) {
                 // repeated label is found
                 for (size_t dim_ind = 1; dim_ind < dims.size(); ++dim_ind) {
@@ -578,7 +575,7 @@ void extract_diagonal(HostTensorVector& inputs, std::vector<std::string>& input_
             }
             resultant_subscript += label;
             for (auto dim : dims) {
-                NGRAPH_CHECK(dim < input_shape.size());
+                OPENVINO_ASSERT(dim < input_shape.size());
                 result_shape.push_back(input_shape[dim]);
             }
         }
@@ -587,18 +584,18 @@ void extract_diagonal(HostTensorVector& inputs, std::vector<std::string>& input_
         return;
     }
 
-    HostTensorPtr multi_identity = build_multi_identity<T>(input_ptr, repeated_labels, label_dim_map);
+    ov::Tensor multi_identity = build_multi_identity<T>(input_ptr, repeated_labels, label_dim_map);
 
-    HostTensorPtr mul_output = input_ptr;
-    reference::multiply<T>(input_ptr->get_data_ptr<T>(),
-                           multi_identity->get_data_ptr<T>(),
-                           mul_output->get_data_ptr<T>(),
-                           input_ptr->get_shape(),
-                           multi_identity->get_shape(),
-                           ngraph::op::AutoBroadcastType::NUMPY);
+    ov::Tensor mul_output = input_ptr;
+    reference::multiply<T>(input_ptr.data<T>(),
+                           multi_identity.data<T>(),
+                           mul_output.data<T>(),
+                           input_ptr.get_shape(),
+                           multi_identity.get_shape(),
+                           ov::op::AutoBroadcastType::NUMPY);
 
-    HostTensorPtr result = std::shared_ptr<HostTensor>(new HostTensor(input_ptr->get_element_type(), result_shape));
-    reference::sum<T>(mul_output->get_data_ptr<T>(), result->get_data_ptr<T>(), mul_output->get_shape(), reduced_axes);
+    auto result = ov::Tensor(input_ptr.get_element_type(), result_shape);
+    reference::sum<T>(mul_output.data<T>(), result.data<T>(), mul_output.get_shape(), reduced_axes);
     inputs[input_ind] = result;
     input_subscripts[input_ind] = resultant_subscript;
 }
@@ -608,11 +605,11 @@ void extract_diagonal(HostTensorVector& inputs, std::vector<std::string>& input_
 /// acceptable by MatMul
 ///
 template <typename T>
-HostTensorPtr reshape_input_for_matmul(const HostTensorPtr& input,
-                                       const Shape& common_sub_shape,
-                                       const Shape& separate_sub_shape,
-                                       const Shape& reduced_sub_shape_prod,
-                                       bool is_separate_first) {
+ov::Tensor reshape_input_for_matmul(const ov::Tensor& input,
+                                    const Shape& common_sub_shape,
+                                    const Shape& separate_sub_shape,
+                                    const Shape& reduced_sub_shape_prod,
+                                    bool is_separate_first) {
     Shape new_shape;
     new_shape.insert(new_shape.end(), common_sub_shape.begin(), common_sub_shape.end());
 
@@ -643,17 +640,19 @@ HostTensorPtr reshape_input_for_matmul(const HostTensorPtr& input,
 
     // when new shape is equal to the current one,
     // there is no need in reshape
-    if (new_shape == input->get_shape()) {
+    if (new_shape == input.get_shape()) {
         return input;
     }
 
-    const auto element_type = input->get_element_type();
-    const auto input_shape = input->get_shape();
-    HostTensorPtr output = std::shared_ptr<HostTensor>(new HostTensor(element_type, new_shape));
+    const auto element_type = input.get_element_type();
+    const auto input_shape = input.get_shape();
+    auto output = ov::Tensor(element_type, new_shape);
+    OPENVINO_SUPPRESS_DEPRECATED_START
     const AxisVector order = ngraph::get_default_order(input_shape);
+    OPENVINO_SUPPRESS_DEPRECATED_END
 
-    reference::reshape(reinterpret_cast<const char*>(input->get_data_ptr<T>()),
-                       reinterpret_cast<char*>(output->get_data_ptr<T>()),
+    reference::reshape(reinterpret_cast<const char*>(input.data<T>()),
+                       reinterpret_cast<char*>(output.data<T>()),
                        input_shape,
                        order,
                        new_shape,
@@ -667,7 +666,7 @@ HostTensorPtr reshape_input_for_matmul(const HostTensorPtr& input,
 /// inputs along with their input subscripts
 ///
 template <typename T>
-void contract_two_inputs(HostTensorVector& inputs,
+void contract_two_inputs(ov::TensorVector& inputs,
                          std::vector<std::string>& input_subscripts,
                          const std::string& output_subscript,
                          size_t input_ind1,
@@ -680,8 +679,8 @@ void contract_two_inputs(HostTensorVector& inputs,
 
     // perform sanity check for arguments
     auto num_inputs = inputs.size();
-    NGRAPH_CHECK(num_inputs == input_subscripts.size(), "Each input must have own subscript.");
-    NGRAPH_CHECK(input_ind2 < num_inputs && input_ind1 != input_ind2, "Incorrect input index is specified.");
+    OPENVINO_ASSERT(num_inputs == input_subscripts.size(), "Each input must have own subscript.");
+    OPENVINO_ASSERT(input_ind2 < num_inputs && input_ind1 != input_ind2, "Incorrect input index is specified.");
 
     const auto& input1 = inputs[input_ind1];
     const auto& input2 = inputs[input_ind2];
@@ -705,9 +704,9 @@ void contract_two_inputs(HostTensorVector& inputs,
     // corresponding label are met in neither the output subscript nor the input
     // subscripts for other Einsum inputs excluding two given inputs
     auto& input_subscript1 = input_subscripts[input_ind1];
-    auto labels1 = ngraph::opset7::Einsum::extract_labels(input_subscript1);
+    auto labels1 = ov::op::v7::Einsum::extract_labels(input_subscript1);
     auto& input_subscript2 = input_subscripts[input_ind2];
-    auto labels2 = ngraph::opset7::Einsum::extract_labels(input_subscript2);
+    auto labels2 = ov::op::v7::Einsum::extract_labels(input_subscript2);
     std::string common_part = "";
     std::string separate_part1 = "";
     std::string separate_part2 = "";
@@ -756,27 +755,27 @@ void contract_two_inputs(HostTensorVector& inputs,
         // for further unsqueezing
         transpose_input<T>(inputs, input_subscripts, convenient_subscript, input_ind2);
 
-        auto separate_labels1 = ngraph::opset7::Einsum::extract_labels(separate_part1);
-        auto separate_labels2 = ngraph::opset7::Einsum::extract_labels(separate_part2);
-        auto label_to_dim_map1 = compute_label_dim_map(input1->get_partial_shape().rank(), input_subscript1);
-        auto label_to_dim_map2 = compute_label_dim_map(input2->get_partial_shape().rank(), input_subscript2);
+        auto separate_labels1 = ov::op::v7::Einsum::extract_labels(separate_part1);
+        auto separate_labels2 = ov::op::v7::Einsum::extract_labels(separate_part2);
+        auto label_to_dim_map1 = compute_label_dim_map(input1.get_shape().size(), input_subscript1);
+        auto label_to_dim_map2 = compute_label_dim_map(input2.get_shape().size(), input_subscript2);
 
         // unsqueeze the first operand with new dimensions in the tail
         // and the number of them is equal to the number of separate labels in the
         // second subscript
-        int64_t input_rank1 = input1->get_shape().size();
+        int64_t input_rank1 = input1.get_shape().size();
         int64_t unsqueeze_dim = input_rank1;
         std::vector<int64_t> unsqueeze_axis1;
         std::vector<int64_t> unsqueeze_axis2;
         for (const auto& sep_label2 : separate_labels2) {
-            NGRAPH_CHECK(label_to_dim_map2.find(sep_label2) != label_to_dim_map2.end());
+            OPENVINO_ASSERT(label_to_dim_map2.find(sep_label2) != label_to_dim_map2.end());
             auto label_dims = label_to_dim_map2[sep_label2];
             for (size_t dim_ind = 0; dim_ind < label_dims.size(); ++dim_ind) {
                 unsqueeze_axis1.push_back(unsqueeze_dim + static_cast<int64_t>(dim_ind));
             }
         }
         for (const auto& sep_label1 : separate_labels1) {
-            NGRAPH_CHECK(label_to_dim_map1.find(sep_label1) != label_to_dim_map1.end());
+            OPENVINO_ASSERT(label_to_dim_map1.find(sep_label1) != label_to_dim_map1.end());
             auto label_dims = label_to_dim_map1[sep_label1];
             for (auto label_dim : label_dims) {
                 unsqueeze_axis2.push_back(label_dim);
@@ -784,22 +783,21 @@ void contract_two_inputs(HostTensorVector& inputs,
         }
 
         // unsqueeze input operands for elementwise-multiplication with broadcasting
-        HostTensorPtr unsqueeze_output1 = unsqueeze_input<T>(input1, unsqueeze_axis1);
-        HostTensorPtr unsqueeze_output2 = unsqueeze_input<T>(input2, unsqueeze_axis2);
+        ov::Tensor unsqueeze_output1 = unsqueeze_input<T>(input1, unsqueeze_axis1);
+        ov::Tensor unsqueeze_output2 = unsqueeze_input<T>(input2, unsqueeze_axis2);
 
         // multiply both operands with broadcasting
-        PartialShape output_shape = unsqueeze_output1->get_partial_shape();
+        PartialShape output_shape = unsqueeze_output1.get_shape();
         PartialShape::broadcast_merge_into(output_shape,
-                                           unsqueeze_output2->get_partial_shape(),
-                                           ngraph::op::AutoBroadcastType::NUMPY);
-        HostTensorPtr mul_output = std::shared_ptr<HostTensor>(
-            new HostTensor(unsqueeze_output1->get_element_type(), output_shape.get_shape()));
-        reference::multiply<T>(unsqueeze_output1->get_data_ptr<T>(),
-                               unsqueeze_output2->get_data_ptr<T>(),
-                               mul_output->get_data_ptr<T>(),
-                               unsqueeze_output1->get_shape(),
-                               unsqueeze_output2->get_shape(),
-                               ngraph::op::AutoBroadcastType::NUMPY);
+                                           unsqueeze_output2.get_shape(),
+                                           ov::op::AutoBroadcastType::NUMPY);
+        auto mul_output = ov::Tensor(unsqueeze_output1.get_element_type(), output_shape.get_shape());
+        reference::multiply<T>(unsqueeze_output1.data<T>(),
+                               unsqueeze_output2.data<T>(),
+                               mul_output.data<T>(),
+                               unsqueeze_output1.get_shape(),
+                               unsqueeze_output2.get_shape(),
+                               ov::op::AutoBroadcastType::NUMPY);
 
         // update input operand and input subscript for Einsum operation
         update_operands(inputs, input_subscripts, input_ind1, input_ind2, mul_output, resultant_subscript);
@@ -830,11 +828,11 @@ void contract_two_inputs(HostTensorVector& inputs,
     // [B1, ..., Bm, X1, Y] or [B1, ..., Bm, Y, X2], where B1, ..., Bm are common
     // dimensions, X1 and X2 are collapsed dimensions for separate labels and Y is
     // collapsed dimension for reduced labels
-    Shape input_shape1 = input1->get_shape();
-    Shape input_shape2 = input2->get_shape();
+    Shape input_shape1 = input1.get_shape();
+    Shape input_shape2 = input2.get_shape();
     size_t common_dims_begin, common_dims_end, reduced_dims_begin, reduced_dims_end, separate1_dims_begin,
         separate1_dims_end;
-    compute_ranges(input1->get_partial_shape().rank(),
+    compute_ranges(input1.get_shape().size(),
                    input_subscript1,
                    common_labels,
                    sep_labels1,
@@ -849,7 +847,7 @@ void contract_two_inputs(HostTensorVector& inputs,
 
     size_t common_dims_begin2, common_dims_end2, reduced_dims_begin2, reduced_dims_end2, separate2_dims_begin,
         separate2_dims_end;
-    compute_ranges(input2->get_partial_shape().rank(),
+    compute_ranges(input2.get_shape().size(),
                    input_subscript2,
                    common_labels,
                    sep_labels2,
@@ -888,29 +886,28 @@ void contract_two_inputs(HostTensorVector& inputs,
                        reduced_sub_shape,
                        is_separate_first2);
 
-    HostTensorPtr matmul_operand1 = reshape_input_for_matmul<T>(input1,
-                                                                common_sub_shape,
-                                                                separate1_sub_shape,
-                                                                reduced_sub_shape_prod,
-                                                                is_separate_first1);
-    HostTensorPtr matmul_operand2 = reshape_input_for_matmul<T>(input2,
-                                                                common_sub_shape,
-                                                                separate2_sub_shape,
-                                                                reduced_sub_shape_prod,
-                                                                is_separate_first2);
+    ov::Tensor matmul_operand1 = reshape_input_for_matmul<T>(input1,
+                                                             common_sub_shape,
+                                                             separate1_sub_shape,
+                                                             reduced_sub_shape_prod,
+                                                             is_separate_first1);
+    ov::Tensor matmul_operand2 = reshape_input_for_matmul<T>(input2,
+                                                             common_sub_shape,
+                                                             separate2_sub_shape,
+                                                             reduced_sub_shape_prod,
+                                                             is_separate_first2);
 
     // step 3. apply MatMul operation for formatted inputs
     Shape matmul_output_shape = compute_matmul_output_shape(common_sub_shape, separate1_sub_shape, separate2_sub_shape);
-    HostTensorPtr matmul_output =
-        std::shared_ptr<HostTensor>(new HostTensor(matmul_operand1->get_element_type(), matmul_output_shape));
+    auto matmul_output = ov::Tensor(matmul_operand1.get_element_type(), matmul_output_shape);
 
     bool transpose_a = (is_separate_first1 ? false : true);
     bool transpose_b = (is_separate_first2 ? true : false);
-    reference::matmul(matmul_operand1->get_data_ptr<T>(),
-                      matmul_operand2->get_data_ptr<T>(),
-                      matmul_output->get_data_ptr<T>(),
-                      matmul_operand1->get_shape(),
-                      matmul_operand2->get_shape(),
+    reference::matmul(matmul_operand1.data<T>(),
+                      matmul_operand2.data<T>(),
+                      matmul_output.data<T>(),
+                      matmul_operand1.get_shape(),
+                      matmul_operand2.get_shape(),
                       matmul_output_shape,
                       transpose_a,
                       transpose_b);
@@ -928,38 +925,39 @@ void contract_two_inputs(HostTensorVector& inputs,
     back_shape.insert(back_shape.end(), separate1_sub_shape.begin(), separate1_sub_shape.end());
     back_shape.insert(back_shape.end(), separate2_sub_shape.begin(), separate2_sub_shape.end());
 
-    HostTensorPtr contract_output =
-        std::shared_ptr<HostTensor>(new HostTensor(matmul_output->get_element_type(), back_shape));
-    const AxisVector order = ngraph::get_default_order(matmul_output->get_shape());
-    reference::reshape(reinterpret_cast<const char*>(matmul_output->get_data_ptr<T>()),
-                       reinterpret_cast<char*>(contract_output->get_data_ptr<T>()),
-                       matmul_output->get_shape(),
+    auto contract_output = ov::Tensor(matmul_output.get_element_type(), back_shape);
+    OPENVINO_SUPPRESS_DEPRECATED_START
+    const AxisVector order = ngraph::get_default_order(matmul_output.get_shape());
+    OPENVINO_SUPPRESS_DEPRECATED_END
+    reference::reshape(reinterpret_cast<const char*>(matmul_output.data<T>()),
+                       reinterpret_cast<char*>(contract_output.data<T>()),
+                       matmul_output.get_shape(),
                        order,
                        back_shape,
-                       matmul_output->get_element_type().size());
+                       matmul_output.get_element_type().size());
 
     update_operands(inputs, input_subscripts, input_ind1, input_ind2, contract_output, resultant_subscript);
 }
 
 template <typename T>
-void einsum_impl(const HostTensorVector& inputs, const HostTensorVector& outputs, const std::string& equation) {
+void einsum_impl(const ov::TensorVector& inputs, ov::TensorVector& outputs, const std::string& equation) {
     std::vector<std::string> input_subscripts;
     std::string output_subscript;
-    ngraph::opset7::Einsum::parse_equation(equation, input_subscripts, output_subscript);
+    ov::op::v7::Einsum::parse_equation(equation, input_subscripts, output_subscript);
 
     // compute einsum path that is used to contract a pair of operands
     // in more optimal order
     size_t num_inputs = inputs.size();
     auto einsum_path = compute_einsum_path(num_inputs);
 
-    HostTensorVector int_inputs = inputs;
+    ov::TensorVector int_inputs = inputs;
 
     // contract inputs by Einsum until just one is remained
     for (auto const& inds_pair : einsum_path) {
         contract_two_inputs<T>(int_inputs, input_subscripts, output_subscript, inds_pair.first, inds_pair.second);
     }
 
-    NGRAPH_CHECK(int_inputs.size() == 1);
+    OPENVINO_ASSERT(int_inputs.size() == 1);
 
     // extract diagonal for the single operand
     extract_diagonal<T>(int_inputs, input_subscripts, 0);
@@ -970,26 +968,23 @@ void einsum_impl(const HostTensorVector& inputs, const HostTensorVector& outputs
     // transpose dimensions to layout required by the output subscript
     transpose_input<T>(int_inputs, input_subscripts, output_subscript, 0);
 
-    auto output_shape = int_inputs[0]->get_shape();
-    const auto& element_type = int_inputs[0]->get_element_type();
-    const auto& buf_size = shape_size(output_shape) * element_type.size();
-    outputs[0]->write(int_inputs[0]->get_data_ptr(), buf_size);
+    int_inputs[0].copy_to(outputs[0]);
 }
 
 }  // namespace
 
-void einsum(const HostTensorVector& outputs, const HostTensorVector& inputs, const std::string& equation) {
-    NGRAPH_CHECK(inputs.size() > 0, "Einsum must accept at least one input.");
-    auto input_type = inputs[0]->get_element_type();
+void einsum(ov::TensorVector& outputs, const ov::TensorVector& inputs, const std::string& equation) {
+    OPENVINO_ASSERT(inputs.size() > 0, "Einsum must accept at least one input.");
+    auto input_type = inputs[0].get_element_type();
     for (size_t input_ind = 1; input_ind < inputs.size(); ++input_ind) {
-        NGRAPH_CHECK(inputs[input_ind]->get_element_type() == input_type, "Input types must be the same.");
+        OPENVINO_ASSERT(inputs[input_ind].get_element_type() == input_type, "Input types must be the same.");
     }
     if (input_type == element::Type_t::f32) {
         einsum_impl<float>(inputs, outputs, equation);
     } else if (input_type == element::Type_t::i32) {
         einsum_impl<int>(inputs, outputs, equation);
     } else {
-        NGRAPH_CHECK(false, "Unsupported input type for Einsum operation.");
+        OPENVINO_ASSERT(false, "Unsupported input type for Einsum operation.");
     }
 }
 
diff --git a/src/core/reference/src/op/fft.cpp b/src/core/reference/src/op/fft.cpp
index 012969f278f8f5..9c88b21fd8d1b8 100644
--- a/src/core/reference/src/op/fft.cpp
+++ b/src/core/reference/src/op/fft.cpp
@@ -25,7 +25,6 @@
 #include <utility>
 #include <vector>
 
-#include "ngraph/shape.hpp"
 #include "openvino/reference/utils/fft_common.hpp"
 
 namespace ov {
@@ -446,32 +445,30 @@ void fft(const float* input_data,
     }
 }
 
-OPENVINO_SUPPRESS_DEPRECATED_START
-void fft_postprocessing(const HostTensorVector& outputs,
-                        const ngraph::element::Type output_type,
+void fft_postprocessing(ov::TensorVector& outputs,
+                        const ov::element::Type output_type,
                         const std::vector<float>& fft_result) {
     size_t fft_result_size = fft_result.size();
 
     switch (output_type) {
     case element::Type_t::bf16: {
-        bfloat16* result_ptr = outputs[0]->get_data_ptr<bfloat16>();
+        bfloat16* result_ptr = outputs[0].data<bfloat16>();
         for (size_t i = 0; i < fft_result_size; ++i) {
             result_ptr[i] = bfloat16(fft_result[i]);
         }
     } break;
     case element::Type_t::f16: {
-        float16* result_ptr = outputs[0]->get_data_ptr<float16>();
+        float16* result_ptr = outputs[0].data<float16>();
         for (size_t i = 0; i < fft_result_size; ++i) {
             result_ptr[i] = float16(fft_result[i]);
         }
     } break;
     case element::Type_t::f32: {
-        float* result_ptr = outputs[0]->get_data_ptr<float>();
+        float* result_ptr = outputs[0].data<float>();
         memcpy(result_ptr, fft_result.data(), fft_result_size * sizeof(float));
     } break;
     default:;
     }
 }
-OPENVINO_SUPPRESS_DEPRECATED_END
 }  // namespace reference
 }  // namespace ov
diff --git a/src/core/reference/src/op/function.cpp b/src/core/reference/src/op/function.cpp
index cfd370e38a5c80..a0bedfa1241728 100644
--- a/src/core/reference/src/op/function.cpp
+++ b/src/core/reference/src/op/function.cpp
@@ -11,18 +11,21 @@
 #include "ngraph/runtime/tensor.hpp"
 #include "openvino/core/deprecated.hpp"
 #include "openvino/reference/concat.hpp"
+#include "shape_util.hpp"
 
 namespace ov {
 namespace reference {
-OPENVINO_SUPPRESS_DEPRECATED_START
-void function(const std::shared_ptr<Model>& function, const HostTensorVector& inputs, HostTensorVector& outputs) {
+void function(const std::shared_ptr<Model>& function, const ov::TensorVector& inputs, ov::TensorVector& outputs) {
     const auto& results = function->get_results();
     outputs.reserve(results.size());
     for (size_t i = 0; i < results.size(); ++i) {
-        outputs.push_back(std::make_shared<HostTensor>());
+        OPENVINO_SUPPRESS_DEPRECATED_START
+        auto shape = results[i]->get_output_partial_shape(0).is_static() ? results[i]->get_output_shape(0)
+                                                                         : ov::util::make_dynamic_shape();
+        OPENVINO_SUPPRESS_DEPRECATED_END
+        outputs.push_back(ov::Tensor(results[i]->get_element_type(), shape));
     }
     function->evaluate(outputs, inputs);
 }
-OPENVINO_SUPPRESS_DEPRECATED_END
 }  // namespace reference
 }  // namespace ov
diff --git a/src/core/reference/src/op/if.cpp b/src/core/reference/src/op/if.cpp
index 3fe42b61719809..25a04a7057f106 100644
--- a/src/core/reference/src/op/if.cpp
+++ b/src/core/reference/src/op/if.cpp
@@ -7,20 +7,19 @@
 #include "ngraph/op/if.hpp"
 #include "openvino/reference/function.hpp"
 
-OPENVINO_SUPPRESS_DEPRECATED_START
 namespace ov {
 namespace reference {
 void if_reference(const std::vector<std::shared_ptr<Model>>& bodies,
                   const std::vector<op::util::MultiSubGraphOp::MultiSubgraphOutputDescriptionVector>& out_descs,
                   const std::vector<op::util::MultiSubGraphOp::MultiSubgraphInputDescriptionVector>& input_descs,
-                  const HostTensorVector& out,
-                  const HostTensorVector& args) {
+                  ov::TensorVector& out,
+                  const ov::TensorVector& args) {
     NGRAPH_CHECK(args.size() > 0, "If operation must have input condition value");
 
-    auto condition_value = args[0]->get_data_ptr<bool>()[0];
+    auto condition_value = args[0].data<bool>()[0];
     auto branch_index = (condition_value) ? op::v8::If::THEN_BODY_INDEX : op::v8::If::ELSE_BODY_INDEX;
-    HostTensorVector inputs_to_body;
-    HostTensorVector outs_from_body;
+    ov::TensorVector inputs_to_body;
+    ov::TensorVector outs_from_body;
     inputs_to_body.resize(input_descs[branch_index].size());
     auto inputs_size = args.size();
     auto output_size = out.size();
@@ -36,8 +35,8 @@ void if_reference(const std::vector<std::shared_ptr<Model>>& bodies,
                      "Incorrect associating! If has not output with id ",
                      out_descr->m_output_index);
         auto res = outs_from_body[out_descr->m_body_value_index];
-        out[out_descr->m_output_index]->set_shape(res->get_shape());
-        out[out_descr->m_output_index]->write(res->get_data_ptr(), res->get_size_in_bytes());
+        out[out_descr->m_output_index].set_shape(res.get_shape());
+        res.copy_to(out[out_descr->m_output_index]);
     }
 }
 }  // namespace reference
diff --git a/src/core/reference/src/op/loop.cpp b/src/core/reference/src/op/loop.cpp
index 0a1ee146664a74..0582f18f438e59 100644
--- a/src/core/reference/src/op/loop.cpp
+++ b/src/core/reference/src/op/loop.cpp
@@ -4,12 +4,13 @@
 
 #include "openvino/reference/loop.hpp"
 
+#include <algorithm>
+
 #include "openvino/op/tensor_iterator.hpp"
 #include "openvino/reference/concat.hpp"
 #include "openvino/reference/function.hpp"
 #include "openvino/reference/split.hpp"
-
-OPENVINO_SUPPRESS_DEPRECATED_START
+#include "openvino/runtime/tensor.hpp"
 
 namespace ov {
 namespace reference {
@@ -17,8 +18,8 @@ void loop(const std::shared_ptr<Model>& func,
           const op::util::OutputDescriptionVector& out_descs,
           const op::util::InputDescriptionVector& input_descs,
           const op::v5::Loop::SpecialBodyPorts& special_ports,
-          const HostTensorVector& out,
-          const HostTensorVector& args) {
+          ov::TensorVector& out,
+          const ov::TensorVector& args) {
     const auto& cur_iter_idx = special_ports.current_iteration_input_idx;
     auto val = std::find_if(input_descs.begin(),
                             input_descs.end(),
@@ -32,9 +33,9 @@ void loop(const std::shared_ptr<Model>& func,
     // should allocate input_descs.size() + 1 inputs and set default value (0) for
     // current_iteration input.
     int64_t inputs_count = input_descs.size() + (cur_iter_idx >= 0 ? !cur_iter_initial_value_exist : 0);
-    HostTensorVector inputs_to_body;
+    ov::TensorVector inputs_to_body;
     for (int64_t i = 0; i < inputs_count; ++i)
-        inputs_to_body.push_back(std::make_shared<HostTensor>(element::dynamic, PartialShape::dynamic()));
+        inputs_to_body.push_back(ov::Tensor());
     if (cur_iter_idx >= 0 && !cur_iter_initial_value_exist) {
         const auto& cur_iter = func->get_parameters().at(cur_iter_idx);
         if (cur_iter->get_partial_shape().is_dynamic()) {
@@ -45,8 +46,10 @@ void loop(const std::shared_ptr<Model>& func,
         auto init = std::make_shared<op::v0::Constant>(func->get_parameters().at(cur_iter_idx)->get_element_type(),
                                                        func->get_parameters().at(cur_iter_idx)->get_shape(),
                                                        0);
-        inputs_to_body.at(cur_iter_idx)->initialize(init);
-        // reinterpret_cast<int64_t*>(inputs_to_body.at(cur_iter_idx).data())[0] = 0;
+        ov::Tensor in_tensor(func->get_parameters().at(cur_iter_idx)->get_element_type(),
+                             func->get_parameters().at(cur_iter_idx)->get_shape());
+        std::memset(in_tensor.data(), 0, in_tensor.get_byte_size());
+        inputs_to_body.at(cur_iter_idx) = in_tensor;
     }
 
     // Port map processing: inputs and back edges
@@ -65,19 +68,19 @@ void loop(const std::shared_ptr<Model>& func,
 
     // Get TripCount
     int64_t trip_count = 0;
-    if (args[0]->get_element_type() == ngraph::element::i32) {
-        auto* trip_count_p = args[0]->get_data_ptr<int32_t>();
+    if (args[0].get_element_type() == ov::element::i32) {
+        auto* trip_count_p = args[0].data<int32_t>();
         trip_count = trip_count_p[0];
-    } else if (args[0]->get_element_type() == ngraph::element::i64) {
-        auto* trip_count_p = args[0]->get_data_ptr<int64_t>();
+    } else if (args[0].get_element_type() == ov::element::i64) {
+        auto* trip_count_p = args[0].data<int64_t>();
         trip_count = trip_count_p[0];
     } else {
-        NGRAPH_CHECK(false, "Unsupported element type for trip_count input. Expected int32 or int64.");
+        OPENVINO_THROW("Unsupported element type for trip_count input. Expected int32 or int64.");
     }
-    NGRAPH_CHECK(trip_count != 0, "Zero count of iteration not supported");
+    OPENVINO_ASSERT(trip_count != 0, "Zero count of iteration not supported");
 
     // Loop iterations
-    auto exec_condition = args[1]->get_data_ptr<bool>();
+    auto exec_condition = args[1].data<bool>();
     if (exec_condition[0]) {
         // Find all ConcatOutputDescription
         std::vector<std::shared_ptr<op::v5::Loop::ConcatOutputDescription>> concat_outputs;
@@ -89,28 +92,28 @@ void loop(const std::shared_ptr<Model>& func,
 
         // Slicing
         std::vector<std::shared_ptr<op::v0::TensorIterator::SliceInputDescription>> slice_inputs;
-        std::vector<HostTensorVector> sliced_values;
+        std::vector<ov::TensorVector> sliced_values;
         int slice_in_idx = 0;
         for (const auto& desc : input_descs) {
             if (const auto& slice_desc =
                     std::dynamic_pointer_cast<op::v0::TensorIterator::SliceInputDescription>(desc)) {
-                const auto el_size = args[slice_desc->m_input_index]->get_element_type().size();
+                const auto el_size = args[slice_desc->m_input_index].get_element_type().size();
                 slice_inputs.push_back(slice_desc);
-                auto shape = args[slice_desc->m_input_index]->get_shape();
+                auto shape = args[slice_desc->m_input_index].get_shape();
                 uint64_t num_iterations = shape.at(slice_desc->m_axis);
                 shape.at(slice_desc->m_axis) = 1;
-                sliced_values.emplace_back(HostTensorVector());
+                sliced_values.emplace_back(ov::TensorVector());
                 for (uint64_t i = 0; i < num_iterations; ++i) {
                     sliced_values.back().emplace_back(
-                        std::make_shared<HostTensor>(args[slice_desc->m_input_index]->get_element_type(), shape));
+                        ov::Tensor(args[slice_desc->m_input_index].get_element_type(), shape));
                 }
                 std::vector<char*> pointers_to_data(num_iterations);
                 for (size_t j = 0; j < pointers_to_data.size(); ++j) {
                     pointers_to_data[slice_desc->m_stride > 0 ? j : (pointers_to_data.size() - j - 1)] =
-                        sliced_values[slice_in_idx][j]->get_data_ptr<char>();
+                        static_cast<char*>(sliced_values[slice_in_idx][j].data());
                 }
-                reference::split(args[slice_desc->m_input_index]->get_data_ptr<char>(),
-                                 args[slice_desc->m_input_index]->get_shape(),
+                reference::split(static_cast<char*>(args[slice_desc->m_input_index].data()),
+                                 args[slice_desc->m_input_index].get_shape(),
                                  el_size,
                                  slice_desc->m_axis,
                                  num_iterations,
@@ -120,8 +123,8 @@ void loop(const std::shared_ptr<Model>& func,
         }
 
         // Allocate vectors for store output values
-        std::vector<HostTensorVector> values_to_concat(concat_outputs.size());
-        HostTensorVector body_outputs;
+        std::vector<ov::TensorVector> values_to_concat(concat_outputs.size());
+        ov::TensorVector body_outputs;
 
         // Negative value means infinity count of iterations
         trip_count = trip_count >= 0 ? trip_count : std::numeric_limits<int64_t>::max();
@@ -145,7 +148,7 @@ void loop(const std::shared_ptr<Model>& func,
             bool body_exec_condition(false);
             if (static_cast<int64_t>(body_outputs.size()) > special_ports.body_condition_output_idx &&
                 body_outputs[special_ports.body_condition_output_idx])
-                body_outputs[special_ports.body_condition_output_idx]->read(&body_exec_condition, sizeof(bool));
+                body_exec_condition = body_outputs[special_ports.body_condition_output_idx].data<bool>()[0];
             if (!body_exec_condition)
                 break;
 
@@ -155,21 +158,24 @@ void loop(const std::shared_ptr<Model>& func,
                 const auto& cur_iter_param = func->get_parameters().at(cur_iter_idx);
                 int64_t iter_num = cur_iter + 1;
                 if (cur_iter_param->get_element_type() == element::i64)
-                    inputs_to_body.at(cur_iter_idx)->write(&iter_num, cur_iter_param->get_element_type().size());
+                    std::memcpy(inputs_to_body.at(cur_iter_idx).data(),
+                                &iter_num,
+                                cur_iter_param->get_element_type().size());
                 else if (cur_iter_param->get_element_type() == element::i32) {
                     int32_t iter_num_i32 = static_cast<int32_t>(iter_num);
-                    inputs_to_body.at(cur_iter_idx)->write(&iter_num_i32, cur_iter_param->get_element_type().size());
+                    std::memcpy(inputs_to_body.at(cur_iter_idx).data(),
+                                &iter_num_i32,
+                                cur_iter_param->get_element_type().size());
                 } else
-                    NGRAPH_CHECK(false,
-                                 "Unsupported element type for current iteration "
-                                 "input. Expected int32 or int64.");
+                    OPENVINO_THROW("Unsupported element type for current iteration "
+                                   "input. Expected int32 or int64.");
             }
 
             // Back-edge processing
             bool need_validate = false;
             for (auto& back_edge : back_edges) {
-                const auto& input_shape = inputs_to_body[back_edge.param_idx]->get_shape();
-                const auto& result_shape = body_outputs[back_edge.result_idx]->get_shape();
+                const auto& input_shape = inputs_to_body[back_edge.param_idx].get_shape();
+                const auto& result_shape = body_outputs[back_edge.result_idx].get_shape();
                 // when output shape does not equal to input shape in a back-edge, such as
                 //          Parameter(out:1)->|
                 //                            |->Concat(out:2)->Result(out:2)
@@ -190,8 +196,8 @@ void loop(const std::shared_ptr<Model>& func,
         for (const auto& desc : out_descs) {
             if (const auto& body_desc = std::dynamic_pointer_cast<op::v5::Loop::BodyOutputDescription>(desc)) {
                 const auto& res = body_outputs[body_desc->m_body_value_index];
-                out[body_desc->m_output_index]->set_shape(res->get_shape());
-                out[body_desc->m_output_index]->write(res->get_data_ptr(), res->get_size_in_bytes());
+                out[body_desc->m_output_index].set_shape(res.get_shape());
+                res.copy_to(out[body_desc->m_output_index]);
             }
         }
 
@@ -201,21 +207,21 @@ void loop(const std::shared_ptr<Model>& func,
             auto shape = func->get_results().at(concat_desc->m_body_value_index)->get_shape();
             std::vector<Shape> shapes_to_concat(values_to_concat[i].size(), shape);
             shape.at(concat_desc->m_axis) = values_to_concat[i].size();
-            out[concat_desc->m_output_index]->set_shape(shape);
+            out[concat_desc->m_output_index].set_shape(shape);
             std::vector<const char*> pointers_on_values;
             pointers_on_values.reserve(values_to_concat[i].size());
             for (const auto& vec : values_to_concat[i]) {
-                pointers_on_values.push_back(vec->get_data_ptr<char>());
+                pointers_on_values.push_back(static_cast<char*>(vec.data()));
             }
             reference::concat(pointers_on_values,
-                              out[concat_desc->m_output_index]->get_data_ptr<char>(),
+                              static_cast<char*>(out[concat_desc->m_output_index].data()),
                               shapes_to_concat,
                               shape,
                               concat_desc->m_axis,
-                              out[concat_desc->m_output_index]->get_element_type().size());
+                              out[concat_desc->m_output_index].get_element_type().size());
         }
     } else {
-        NGRAPH_CHECK(false, "ExecutionCondition is false. Zero count of iteration not supported.");
+        OPENVINO_THROW("ExecutionCondition is false. Zero count of iteration not supported.");
     }
 }
 }  // namespace reference
diff --git a/src/core/reference/src/op/non_max_suppression.cpp b/src/core/reference/src/op/non_max_suppression.cpp
index e0032c3f5b4ecb..1dc7373bc17654 100644
--- a/src/core/reference/src/op/non_max_suppression.cpp
+++ b/src/core/reference/src/op/non_max_suppression.cpp
@@ -2,15 +2,15 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include "ngraph/op/non_max_suppression.hpp"
+#include "openvino/op/non_max_suppression.hpp"
 
 #include <algorithm>
 #include <cmath>
 #include <queue>
 #include <vector>
 
-#include "ngraph/shape.hpp"
 #include "openvino/reference/non_max_suppression.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 namespace ov {
 namespace reference {
@@ -366,35 +366,33 @@ void non_max_suppression(const float* boxes_data,
     }
 }
 
-OPENVINO_SUPPRESS_DEPRECATED_START
-void nms_postprocessing(const HostTensorVector& outputs,
-                        const ngraph::element::Type output_type,
+void nms_postprocessing(ov::TensorVector& outputs,
+                        const ov::element::Type output_type,
                         const std::vector<int64_t>& selected_indices,
                         const std::vector<float>& selected_scores,
                         int64_t valid_outputs,
-                        const ngraph::element::Type selected_scores_type) {
-    outputs[0]->set_element_type(output_type);
-    outputs[0]->set_shape(Shape{static_cast<size_t>(valid_outputs), 3});
+                        const ov::element::Type selected_scores_type) {
+    // outputs[0].set_element_type(output_type);
+    outputs[0].set_shape(Shape{static_cast<size_t>(valid_outputs), 3});
 
     size_t num_of_outputs = outputs.size();
 
     if (num_of_outputs >= 2) {
-        outputs[1]->set_element_type(selected_scores_type);
-        outputs[1]->set_shape(Shape{static_cast<size_t>(valid_outputs), 3});
+        // outputs[1].set_element_type(selected_scores_type);
+        outputs[1].set_shape(Shape{static_cast<size_t>(valid_outputs), 3});
     }
 
     if (num_of_outputs >= 3) {
-        outputs[2]->set_element_type(output_type);
-        outputs[2]->set_shape(Shape{1});
+        outputs[2].set_shape(Shape{1});
     }
 
     size_t selected_size = valid_outputs * 3;
 
-    if (output_type == ngraph::element::i64) {
-        int64_t* indices_ptr = outputs[0]->get_data_ptr<int64_t>();
+    if (output_type == ov::element::i64) {
+        int64_t* indices_ptr = outputs[0].data<int64_t>();
         memcpy(indices_ptr, selected_indices.data(), selected_size * sizeof(int64_t));
     } else {
-        int32_t* indices_ptr = outputs[0]->get_data_ptr<int32_t>();
+        int32_t* indices_ptr = outputs[0].data<int32_t>();
         for (size_t i = 0; i < selected_size; ++i) {
             indices_ptr[i] = static_cast<int32_t>(selected_indices[i]);
         }
@@ -408,19 +406,19 @@ void nms_postprocessing(const HostTensorVector& outputs,
 
     switch (selected_scores_type) {
     case element::Type_t::bf16: {
-        bfloat16* scores_ptr = outputs[1]->get_data_ptr<bfloat16>();
+        bfloat16* scores_ptr = outputs[1].data<bfloat16>();
         for (size_t i = 0; i < selected_scores_size; ++i) {
             scores_ptr[i] = bfloat16(selected_scores[i]);
         }
     } break;
     case element::Type_t::f16: {
-        float16* scores_ptr = outputs[1]->get_data_ptr<float16>();
+        float16* scores_ptr = outputs[1].data<float16>();
         for (size_t i = 0; i < selected_scores_size; ++i) {
             scores_ptr[i] = float16(selected_scores[i]);
         }
     } break;
     case element::Type_t::f32: {
-        float* scores_ptr = outputs[1]->get_data_ptr<float>();
+        float* scores_ptr = outputs[1].data<float>();
         memcpy(scores_ptr, selected_scores.data(), selected_size * sizeof(float));
     } break;
     default:;
@@ -430,21 +428,21 @@ void nms_postprocessing(const HostTensorVector& outputs,
         return;
     }
 
-    if (output_type == ngraph::element::i64) {
-        int64_t* valid_outputs_ptr = outputs[2]->get_data_ptr<int64_t>();
+    if (output_type == ov::element::i64) {
+        int64_t* valid_outputs_ptr = outputs[2].data<int64_t>();
         *valid_outputs_ptr = valid_outputs;
     } else {
-        int32_t* valid_outputs_ptr = outputs[2]->get_data_ptr<int32_t>();
+        int32_t* valid_outputs_ptr = outputs[2].data<int32_t>();
         *valid_outputs_ptr = static_cast<int32_t>(valid_outputs);
     }
 }
 
-void nms5_postprocessing(const HostTensorVector& outputs,
-                         const ngraph::element::Type output_type,
+void nms5_postprocessing(ov::TensorVector& outputs,
+                         const ov::element::Type output_type,
                          const std::vector<int64_t>& selected_indices,
                          const std::vector<float>& selected_scores,
                          int64_t valid_outputs,
-                         const ngraph::element::Type selected_scores_type) {
+                         const ov::element::Type selected_scores_type) {
     nms_postprocessing(outputs, output_type, selected_indices, selected_scores, valid_outputs, selected_scores_type);
 }
 }  // namespace reference
diff --git a/src/core/reference/src/op/tensor_iterator.cpp b/src/core/reference/src/op/tensor_iterator.cpp
index 26646536372c98..6ac83923f5b9a8 100644
--- a/src/core/reference/src/op/tensor_iterator.cpp
+++ b/src/core/reference/src/op/tensor_iterator.cpp
@@ -4,23 +4,25 @@
 
 #include "openvino/reference/tensor_iterator.hpp"
 
+#include "openvino/op/loop.hpp"
+#include "openvino/op/tensor_iterator.hpp"
 #include "openvino/reference/concat.hpp"
 #include "openvino/reference/function.hpp"
 #include "openvino/reference/split.hpp"
+#include "openvino/runtime/tensor.hpp"
 
-OPENVINO_SUPPRESS_DEPRECATED_START
 namespace ov {
 namespace reference {
 void tensor_iterator(uint64_t num_iterations,
                      const std::shared_ptr<Model>& func,
                      const op::util::OutputDescriptionVector& out_descs,
                      const op::util::InputDescriptionVector& input_descs,
-                     const HostTensorVector& out,
-                     const HostTensorVector& args,
+                     ov::TensorVector& out,
+                     const ov::TensorVector& args,
                      const custom_evaluate_function& evaluate) {
-    HostTensorVector inputs_to_body;
+    ov::TensorVector inputs_to_body;
     for (size_t i = 0; i < input_descs.size(); ++i)
-        inputs_to_body.push_back(std::make_shared<HostTensor>(element::dynamic, PartialShape::dynamic()));
+        inputs_to_body.push_back(ov::Tensor());
 
     // Port map processing: inputs and back edges
     struct BackEdge {
@@ -30,12 +32,12 @@ void tensor_iterator(uint64_t num_iterations,
     std::vector<BackEdge> back_edges;
     for (const auto& desc : input_descs) {
         inputs_to_body[desc->m_body_parameter_index] = args[desc->m_input_index];
-        if (const auto& merged_desc = std::dynamic_pointer_cast<op::v5::Loop::MergedInputDescription>(desc)) {
+        if (const auto& merged_desc = std::dynamic_pointer_cast<ov::op::v5::Loop::MergedInputDescription>(desc)) {
             back_edges.push_back({merged_desc->m_body_parameter_index, merged_desc->m_body_value_index});
         }
     }
     // Find all ConcatOutputDescription
-    std::vector<std::shared_ptr<op::v0::TensorIterator::ConcatOutputDescription>> concat_outputs;
+    std::vector<std::shared_ptr<ov::op::v0::TensorIterator::ConcatOutputDescription>> concat_outputs;
     for (const auto& desc : out_descs) {
         if (const auto& concat_desc =
                 std::dynamic_pointer_cast<op::v0::TensorIterator::ConcatOutputDescription>(desc)) {
@@ -45,26 +47,26 @@ void tensor_iterator(uint64_t num_iterations,
 
     // Slicing
     std::vector<std::shared_ptr<op::v0::TensorIterator::SliceInputDescription>> slice_inputs;
-    std::vector<HostTensorVector> sliced_values;
+    std::vector<ov::TensorVector> sliced_values;
     int slice_in_idx = 0;
     for (const auto& desc : input_descs) {
         if (const auto& slice_desc = std::dynamic_pointer_cast<op::v0::TensorIterator::SliceInputDescription>(desc)) {
-            const auto el_size = args[slice_desc->m_input_index]->get_element_type().size();
+            const auto el_size = args[slice_desc->m_input_index].get_element_type().size();
             slice_inputs.push_back(slice_desc);
-            auto shape = args[slice_desc->m_input_index]->get_shape();
+            auto shape = args[slice_desc->m_input_index].get_shape();
             shape.at(slice_desc->m_axis) = 1;
-            sliced_values.emplace_back(HostTensorVector());
+            sliced_values.emplace_back(ov::TensorVector());
             for (uint64_t i = 0; i < num_iterations; ++i) {
                 sliced_values.back().emplace_back(
-                    std::make_shared<HostTensor>(args[slice_desc->m_input_index]->get_element_type(), shape));
+                    ov::Tensor(args[slice_desc->m_input_index].get_element_type(), shape));
             }
             std::vector<char*> pointers_to_data(num_iterations);
             for (size_t j = 0; j < pointers_to_data.size(); ++j) {
                 pointers_to_data[slice_desc->m_stride > 0 ? j : (pointers_to_data.size() - j - 1)] =
-                    sliced_values[slice_in_idx][j]->get_data_ptr<char>();
+                    static_cast<char*>(sliced_values[slice_in_idx][j].data());
             }
-            reference::split(args[slice_desc->m_input_index]->get_data_ptr<char>(),
-                             args[slice_desc->m_input_index]->get_shape(),
+            reference::split(static_cast<char*>(args[slice_desc->m_input_index].data()),
+                             args[slice_desc->m_input_index].get_shape(),
                              el_size,
                              slice_desc->m_axis,
                              num_iterations,
@@ -74,8 +76,8 @@ void tensor_iterator(uint64_t num_iterations,
     }
 
     // Allocate vectors for store output values
-    std::vector<HostTensorVector> values_to_concat(concat_outputs.size());
-    HostTensorVector body_outputs;
+    std::vector<ov::TensorVector> values_to_concat(concat_outputs.size());
+    ov::TensorVector body_outputs;
 
     for (uint64_t cur_iter = 0; cur_iter < num_iterations; ++cur_iter) {
         // Copy new values for sliced inputs
@@ -107,8 +109,8 @@ void tensor_iterator(uint64_t num_iterations,
         if (const auto& body_desc = std::dynamic_pointer_cast<op::v0::TensorIterator::BodyOutputDescription>(desc)) {
             // Copy output values from the last iteration
             const auto& res = body_outputs[body_desc->m_body_value_index];
-            out[body_desc->m_output_index]->set_shape(res->get_shape());
-            out[body_desc->m_output_index]->write(res->get_data_ptr(), res->get_size_in_bytes());
+            out[body_desc->m_output_index].set_shape(res.get_shape());
+            res.copy_to(out[body_desc->m_output_index]);
         }
     }
 
@@ -120,20 +122,20 @@ void tensor_iterator(uint64_t num_iterations,
         auto shape = func->get_results().at(concat_desc->m_body_value_index)->get_shape();
         std::vector<Shape> shapes_to_concat(values_to_concat[i].size(), shape);
         shape.at(concat_desc->m_axis) = values_to_concat[i].size();
-        out[concat_desc->m_output_index]->set_shape(shape);
+        out[concat_desc->m_output_index].set_shape(shape);
         std::vector<const char*> pointers_on_values;
         pointers_on_values.reserve(values_to_concat[i].size());
         for (size_t j = 0; j < values_to_concat[i].size(); ++j) {
             size_t idx = concat_desc->m_stride > 0 ? j : (values_to_concat[i].size() - j - 1);
             if (values_to_concat[i].size() > idx && values_to_concat[i][idx])
-                pointers_on_values.push_back(values_to_concat[i][idx]->get_data_ptr<char>());
+                pointers_on_values.push_back(static_cast<char*>(values_to_concat[i][idx].data()));
         }
         reference::concat(pointers_on_values,
-                          out[concat_desc->m_output_index]->get_data_ptr<char>(),
+                          static_cast<char*>(out[concat_desc->m_output_index].data()),
                           shapes_to_concat,
                           shape,
                           concat_desc->m_axis,
-                          out[concat_desc->m_output_index]->get_element_type().size());
+                          out[concat_desc->m_output_index].get_element_type().size());
     }
 }
 }  // namespace reference
diff --git a/src/core/reference/src/op/tile.cpp b/src/core/reference/src/op/tile.cpp
index b027613d980623..f88e56392a26a8 100644
--- a/src/core/reference/src/op/tile.cpp
+++ b/src/core/reference/src/op/tile.cpp
@@ -9,8 +9,6 @@
 #include <cstdio>
 #include <numeric>
 
-#include "ngraph/check.hpp"
-
 using namespace ov;
 
 namespace {
diff --git a/src/core/src/node.cpp b/src/core/src/node.cpp
index 10ebc91b976d92..1cce81d2f9fb7d 100644
--- a/src/core/src/node.cpp
+++ b/src/core/src/node.cpp
@@ -740,7 +740,14 @@ inline void update_output_tensors(ov::TensorVector& output_values, const ngraph:
             if (!tensor && outputs[i]->get_partial_shape().is_static()) {
                 tensor = ov::Tensor(outputs[i]->get_element_type(), outputs[i]->get_shape());
             }
-            output_values[i] = tensor;
+            if (output_values[i]) {
+                // Copy value to the original tensor
+                output_values[i].set_shape(tensor.get_shape());
+                tensor.copy_to(output_values[i]);
+            } else {
+                // Tensor is not initialized, so create the new tensor
+                output_values[i] = tensor;
+            }
         }
     }
 }
diff --git a/src/core/src/op/loop.cpp b/src/core/src/op/loop.cpp
index 419e564b19f35e..ef623af65814b6 100644
--- a/src/core/src/op/loop.cpp
+++ b/src/core/src/op/loop.cpp
@@ -12,6 +12,7 @@
 #include "ngraph/graph_util.hpp"
 #include "ngraph/opsets/opset5.hpp"
 #include "openvino/reference/loop.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 using namespace std;
 using namespace ngraph;
@@ -347,8 +348,7 @@ Output<Node> op::v5::Loop::get_concatenated_slices(const Output<Node>& value,
     return SubGraphOp::get_concatenated_slices(value, start, stride, part_size, end, axis);
 }
 
-OPENVINO_SUPPRESS_DEPRECATED_START
-bool op::v5::Loop::evaluate(const HostTensorVector& outputs, const HostTensorVector& inputs) const {
+bool op::v5::Loop::evaluate(ov::TensorVector& outputs, const ov::TensorVector& inputs) const {
     OV_OP_SCOPE(v5_Loop_evaluate);
     ov::reference::loop(m_bodies[0],
                         m_output_descriptions[0],
@@ -358,7 +358,6 @@ bool op::v5::Loop::evaluate(const HostTensorVector& outputs, const HostTensorVec
                         inputs);
     return true;
 }
-OPENVINO_SUPPRESS_DEPRECATED_END
 
 bool op::v5::Loop::has_evaluate() const {
     OV_OP_SCOPE(v5_Loop_has_evaluate);
diff --git a/src/core/src/runtime/host_tensor.cpp b/src/core/src/runtime/host_tensor.cpp
index 712b6df02203c0..28ad2526b82529 100644
--- a/src/core/src/runtime/host_tensor.cpp
+++ b/src/core/src/runtime/host_tensor.cpp
@@ -139,11 +139,13 @@ void runtime::HostTensor::set_element_type(const element::Type& element_type) {
 }
 
 void runtime::HostTensor::set_shape(const Shape& shape) {
-    NGRAPH_CHECK(PartialShape(shape).refines(get_partial_shape()),
-                 "Allocation shape ",
-                 shape,
-                 " must be compatible with the partial shape: ",
-                 get_partial_shape());
+    NGRAPH_CHECK(
+        PartialShape(shape).refines(get_partial_shape()) ||
+            (m_descriptor->m_partial_shape.is_static() && m_descriptor->m_partial_shape.to_shape() == ov::Shape{0}),
+        "Allocation shape ",
+        shape,
+        " must be compatible with the partial shape: ",
+        get_partial_shape());
     m_descriptor->m_partial_shape = shape;
     m_descriptor->m_shape_changed = true;
 }
diff --git a/src/inference/src/dev/make_tensor.cpp b/src/inference/src/dev/make_tensor.cpp
index ddd0ea293966c0..94ddf723eabc4c 100644
--- a/src/inference/src/dev/make_tensor.cpp
+++ b/src/inference/src/dev/make_tensor.cpp
@@ -188,6 +188,8 @@ class AllocatedTensor : public ViewTensor {
     }
 
     void set_shape(ov::Shape new_shape) override {
+        if (m_shape == new_shape)
+            return;
         auto old_byte_size = get_byte_size();
         m_shape = std::move(new_shape);
         if (get_byte_size() > old_byte_size) {
diff --git a/src/plugins/template/backend/backend.cpp b/src/plugins/template/backend/backend.cpp
index 7605b8b5fb110a..a8153bfca2ee7f 100644
--- a/src/plugins/template/backend/backend.cpp
+++ b/src/plugins/template/backend/backend.cpp
@@ -7,8 +7,6 @@
 #include <sstream>
 
 #include "int_backend.hpp"
-#include "ngraph/file_util.hpp"
-#include "ngraph/util.hpp"
 #include "openvino/core/except.hpp"
 #include "openvino/util/file_util.hpp"
 
diff --git a/src/plugins/template/backend/evaluates_map.cpp b/src/plugins/template/backend/evaluates_map.cpp
index 2bb18904e6a45b..f88efae92d0f35 100644
--- a/src/plugins/template/backend/evaluates_map.cpp
+++ b/src/plugins/template/backend/evaluates_map.cpp
@@ -6,26 +6,25 @@
 
 #include "ops/ops_evaluates.hpp"
 
-OPENVINO_SUPPRESS_DEPRECATED_START
-std::vector<float> get_floats(const std::shared_ptr<ngraph::HostTensor>& input, const ngraph::Shape& shape) {
-    size_t input_size = ngraph::shape_size(shape);
+std::vector<float> get_floats(const ov::Tensor& input, const ov::Shape& shape) {
+    size_t input_size = ov::shape_size(shape);
     std::vector<float> result(input_size);
 
-    switch (input->get_element_type()) {
-    case ngraph::element::Type_t::bf16: {
-        ngraph::bfloat16* p = input->get_data_ptr<ngraph::bfloat16>();
+    switch (input.get_element_type()) {
+    case ov::element::bf16: {
+        ov::bfloat16* p = input.data<ov::bfloat16>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = float(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::f16: {
-        ngraph::float16* p = input->get_data_ptr<ngraph::float16>();
+    case ov::element::f16: {
+        ov::float16* p = input.data<ov::float16>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = float(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::f32: {
-        float* p = input->get_data_ptr<float>();
+    case ov::element::f32: {
+        float* p = input.data<float>();
         memcpy(result.data(), p, input_size * sizeof(float));
     } break;
     default:
@@ -36,55 +35,55 @@ std::vector<float> get_floats(const std::shared_ptr<ngraph::HostTensor>& input,
     return result;
 }
 
-std::vector<int64_t> get_integers(const std::shared_ptr<ngraph::HostTensor>& input, const ngraph::Shape& shape) {
-    size_t input_size = ngraph::shape_size(shape);
+std::vector<int64_t> get_integers(const ov::Tensor& input, const ov::Shape& shape) {
+    size_t input_size = ov::shape_size(shape);
     std::vector<int64_t> result(input_size);
 
-    switch (input->get_element_type()) {
-    case ngraph::element::Type_t::i8: {
-        auto p = input->get_data_ptr<int8_t>();
+    switch (input.get_element_type()) {
+    case ov::element::Type_t::i8: {
+        auto p = input.data<int8_t>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = int64_t(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::i16: {
-        auto p = input->get_data_ptr<int16_t>();
+    case ov::element::Type_t::i16: {
+        auto p = input.data<int16_t>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = int64_t(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::i32: {
-        auto p = input->get_data_ptr<int32_t>();
+    case ov::element::Type_t::i32: {
+        auto p = input.data<int32_t>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = int64_t(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::i64: {
-        auto p = input->get_data_ptr<int64_t>();
+    case ov::element::Type_t::i64: {
+        auto p = input.data<int64_t>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = int64_t(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::u8: {
-        auto p = input->get_data_ptr<uint8_t>();
+    case ov::element::Type_t::u8: {
+        auto p = input.data<uint8_t>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = int64_t(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::u16: {
-        auto p = input->get_data_ptr<uint16_t>();
+    case ov::element::Type_t::u16: {
+        auto p = input.data<uint16_t>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = int64_t(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::u32: {
-        auto p = input->get_data_ptr<uint32_t>();
+    case ov::element::Type_t::u32: {
+        auto p = input.data<uint32_t>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = int64_t(p[i]);
         }
     } break;
-    case ngraph::element::Type_t::u64: {
-        auto p = input->get_data_ptr<uint64_t>();
+    case ov::element::Type_t::u64: {
+        auto p = input.data<uint64_t>();
         for (size_t i = 0; i < input_size; ++i) {
             result[i] = int64_t(p[i]);
         }
@@ -97,16 +96,15 @@ std::vector<int64_t> get_integers(const std::shared_ptr<ngraph::HostTensor>& inp
     return result;
 }
 
-std::vector<int64_t> get_signal_size(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs,
-                                     size_t num_of_axes) {
+std::vector<int64_t> get_signal_size(const ov::TensorVector& inputs, size_t num_of_axes) {
     if (inputs.size() == 3) {
-        return get_integers(inputs[2], inputs[2]->get_shape());
+        return get_integers(inputs[2], inputs[2].get_shape());
     }
 
     return std::vector<int64_t>(num_of_axes, static_cast<int64_t>(-1));
 }
 
-ngraph::runtime::interpreter::EvaluatorsMap& ngraph::runtime::interpreter::get_evaluators_map() {
+ov::runtime::interpreter::EvaluatorsMap& ov::runtime::interpreter::get_evaluators_map() {
     static runtime::interpreter::EvaluatorsMap evaluatorsMap{
 #define _OPENVINO_OP_REG(NAME, NAMESPACE) {NAMESPACE::NAME::get_type_info_static(), evaluate_node<NAMESPACE::NAME>},
 
diff --git a/src/plugins/template/backend/evaluates_map.hpp b/src/plugins/template/backend/evaluates_map.hpp
index d141a3896202ea..7fb249229e3365 100644
--- a/src/plugins/template/backend/evaluates_map.hpp
+++ b/src/plugins/template/backend/evaluates_map.hpp
@@ -3,23 +3,27 @@
 //
 
 #pragma once
-#include "ngraph/node.hpp"
 
-std::vector<float> get_floats(const std::shared_ptr<ngraph::HostTensor>& input, const ngraph::Shape& shape);
+#include <vector>
 
-std::vector<int64_t> get_integers(const std::shared_ptr<ngraph::HostTensor>& input, const ngraph::Shape& shape);
+#include "openvino/core/node.hpp"
+#include "openvino/core/shape.hpp"
+#include "openvino/runtime/tensor.hpp"
 
-std::vector<int64_t> get_signal_size(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs,
-                                     size_t num_of_axes);
+std::vector<float> get_floats(const ov::Tensor& input, const ov::Shape& shape);
 
-namespace ngraph {
+std::vector<int64_t> get_integers(const ov::Tensor& input, const ov::Shape& shape);
+
+std::vector<int64_t> get_signal_size(const ov::TensorVector& inputs, size_t num_of_axes);
+
+namespace ov {
 namespace runtime {
 namespace interpreter {
-using EvaluatorsMap = std::map<ngraph::NodeTypeInfo,
-                               std::function<bool(const std::shared_ptr<ngraph::Node>& node,
-                                                  const ngraph::HostTensorVector& outputs,
-                                                  const ngraph::HostTensorVector& inputs)>>;
+using EvaluatorsMap = std::map<
+    ov::NodeTypeInfo,
+    std::function<
+        bool(const std::shared_ptr<ov::Node>& node, ov::TensorVector& outputs, const ov::TensorVector& inputs)>>;
 EvaluatorsMap& get_evaluators_map();
 }  // namespace interpreter
 }  // namespace runtime
-}  // namespace ngraph
+}  // namespace ov
diff --git a/src/plugins/template/backend/executable.hpp b/src/plugins/template/backend/executable.hpp
index 4e9e00cab52642..2259cc5192a4c0 100644
--- a/src/plugins/template/backend/executable.hpp
+++ b/src/plugins/template/backend/executable.hpp
@@ -52,11 +52,11 @@ class Executable {
     void validate(const std::vector<ov::Tensor>& outputs, const std::vector<ov::Tensor>& inputs);
 
     /// \brief Query the input Parameters
-    /// \returns an ngraph::op::ParameterVector of all input parameters
+    /// \returns an ov::op::ParameterVector of all input parameters
     const ov::ParameterVector& get_parameters() const;
 
     /// \brief Query the output Results
-    /// \returns an ngraph::ResultVector of all input parameters
+    /// \returns an ov::ResultVector of all input parameters
     const ov::ResultVector& get_results() const;
 
     /// \brief Query the internal model
diff --git a/src/plugins/template/backend/int_executable.cpp b/src/plugins/template/backend/int_executable.cpp
index f7a06f407cb42c..f866d77b6528b6 100644
--- a/src/plugins/template/backend/int_executable.cpp
+++ b/src/plugins/template/backend/int_executable.cpp
@@ -6,72 +6,15 @@
 
 #include <cstring>
 #include <limits>
-#include <openvino/op/util/variable_context.hpp>
 
 #include "evaluates_map.hpp"
 #include "openvino/core/except.hpp"
 #include "openvino/op/parameter.hpp"
 #include "openvino/op/result.hpp"
 #include "openvino/op/util/op_types.hpp"
+#include "openvino/op/util/variable_context.hpp"
 #include "perf_counter.hpp"
-#include "tensor_conversion_util.hpp"
-
-OPENVINO_SUPPRESS_DEPRECATED_START
-namespace {
-
-class DynamicTensor : public ngraph::runtime::HostTensor {
-private:
-    ov::Tensor tensor;
-
-public:
-    DynamicTensor(const ov::element::Type& type) : ngraph::runtime::HostTensor(type, ov::PartialShape::dynamic()) {}
-
-    ov::Tensor get_tensor() {
-        return tensor;
-    }
-
-protected:
-    void allocate_buffer() override {
-        OPENVINO_ASSERT(get_partial_shape().is_static(),
-                        "Attempt to allocate buffer for tensor with partial shape: ",
-                        get_partial_shape());
-        OPENVINO_ASSERT(get_element_type().is_static(),
-                        "Attempt to allocate buffer for tensor with dynamic type: ",
-                        get_element_type());
-        m_buffer_size = m_descriptor->size();
-        tensor = ov::Tensor(get_element_type(), get_partial_shape().get_shape());
-        m_memory_pointer = tensor.data();
-        m_aligned_buffer_pool = m_memory_pointer;
-    }
-};
-
-inline ngraph::HostTensorPtr make_tmp_host_tensor(const ov::Tensor& t) {
-    if (!t) {
-        return std::make_shared<DynamicTensor>(ov::element::dynamic);
-    } else if (t.get_shape() == ov::Shape{0, std::numeric_limits<size_t>::max()}) {
-        return std::make_shared<DynamicTensor>(t.get_element_type());
-    } else {
-        return std::make_shared<ngraph::runtime::HostTensor>(t.get_element_type(), t.get_shape(), t.data());
-    }
-}
-inline ngraph::HostTensorVector create_tmp_tensors(const ov::TensorVector& tensors) {
-    ngraph::HostTensorVector result;
-    result.reserve(tensors.size());
-    for (const auto& tensor : tensors) {
-        result.push_back(make_tmp_host_tensor(tensor));
-    }
-    return result;
-}
-
-inline void update_output_tensors(ov::TensorVector& output_values, const ngraph::HostTensorVector& outputs) {
-    OPENVINO_ASSERT(output_values.size() == outputs.size());
-    for (size_t i = 0; i < outputs.size(); i++) {
-        if (auto dyn_output = std::dynamic_pointer_cast<DynamicTensor>(outputs[i])) {
-            output_values[i] = dyn_output->get_tensor();
-        }
-    }
-}
-}  // namespace
+#include "shape_util.hpp"
 
 class TemporaryOverrideOutputs {
     std::shared_ptr<ov::Model> model;
@@ -184,10 +127,11 @@ bool ov::runtime::interpreter::INTExecutable::call(std::vector<ov::Tensor>& outp
             auto it = tensor_map.find(tensor);
             auto output = op->output(i);
             if (op::util::is_output(op) || it == tensor_map.end() || !it->second) {
-                host_tensor = ov::Tensor(output.get_element_type(),
-                                         output.get_partial_shape().is_dynamic()
-                                             ? ov::Shape{0, std::numeric_limits<size_t>::max()}
-                                             : output.get_shape());
+                OPENVINO_SUPPRESS_DEPRECATED_START
+                host_tensor = ov::Tensor(
+                    output.get_element_type(),
+                    output.get_partial_shape().is_dynamic() ? ov::util::make_dynamic_shape() : output.get_shape());
+                OPENVINO_SUPPRESS_DEPRECATED_END
             } else {
                 host_tensor = it->second;
             }
@@ -268,17 +212,14 @@ std::vector<ov::Tensor> ov::runtime::interpreter::INTExecutable::create_output_t
 bool ov::runtime::interpreter::INTExecutable::evaluate_node(const std::shared_ptr<Node>& node,
                                                             ov::TensorVector& outputs,
                                                             const ov::TensorVector& inputs) const {
-    auto& map = ngraph::runtime::interpreter::get_evaluators_map();
+    auto& map = ov::runtime::interpreter::get_evaluators_map();
     auto it = map.find(node->get_type_info());
     bool res = false;
-    const auto tensor_inputs = create_tmp_tensors(inputs);
-    auto tensor_outputs = create_tmp_tensors(outputs);
     OPENVINO_ASSERT(it != map.end(),
                     "Interpreter backend doesn't implement evaluate method for OP ",
                     node->get_type_info().name);
-    res = it->second(node, tensor_outputs, tensor_inputs);
+    res = it->second(node, outputs, inputs);
     OPENVINO_ASSERT(res, "Running evaluate method for OP ", node->get_type_info().name, " failed!");
-    update_output_tensors(outputs, tensor_outputs);
     return res;
 }
 
diff --git a/src/plugins/template/backend/int_executable.hpp b/src/plugins/template/backend/int_executable.hpp
index 1be052349f3e9e..6a98dac4d992c6 100644
--- a/src/plugins/template/backend/int_executable.hpp
+++ b/src/plugins/template/backend/int_executable.hpp
@@ -72,11 +72,8 @@ class INTExecutable : public Executable {
         std::vector<float> scores_data;
         size_t out_shape_size;
         bool sort_result_descending;
-        ngraph::element::Type output_type;
+        ov::element::Type output_type;
     };
-
-    InfoForNMS5 get_info_for_nms5_eval(const ov::op::v5::NonMaxSuppression* nms5,
-                                       const std::vector<std::shared_ptr<HostTensor>>& inputs);
 };
 
 }  // namespace interpreter
diff --git a/src/plugins/template/backend/ops/abs.cpp b/src/plugins/template/backend/ops/abs.cpp
index b72163d1bb8f57..a23c6d91387e10 100644
--- a/src/plugins/template/backend/ops/abs.cpp
+++ b/src/plugins/template/backend/ops/abs.cpp
@@ -2,65 +2,59 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/abs.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Abs>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::abs<T>(inputs[0]->get_data_ptr<T>(),
-                          outputs[0]->get_data_ptr<T>(),
-                          ngraph::shape_size(inputs[0]->get_shape()));
+#include "evaluate_node.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Abs>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::abs<T>(inputs[0].data<T>(), outputs[0].data<T>(), ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Abs>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Abs>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Abs>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/adaptive_avg_pool.cpp b/src/plugins/template/backend/ops/adaptive_avg_pool.cpp
index 789460103b92b6..0bd4d1a6fddf8d 100644
--- a/src/plugins/template/backend/ops/adaptive_avg_pool.cpp
+++ b/src/plugins/template/backend/ops/adaptive_avg_pool.cpp
@@ -6,93 +6,60 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::AdaptiveAvgPool>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::adaptive_avg_pool(inputs[0]->get_data_ptr<T>(),
-                                     outputs[0]->get_data_ptr<T>(),
-                                     inputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v8::AdaptiveAvgPool>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::adaptive_avg_pool(inputs[0].data<T>(),
+                                     outputs[0].data<T>(),
+                                     inputs[0].get_shape(),
                                      op->get_output_shape(0));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::AdaptiveAvgPool>(std::shared_ptr<ngraph::Node> node,
-                                                    const ngraph::HostTensorVector& outputs,
-                                                    const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::AdaptiveAvgPool>(std::shared_ptr<ov::Node> node,
+                                                ov::TensorVector& outputs,
+                                                const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::AdaptiveAvgPool>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::AdaptiveAvgPool>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/adaptive_max_pool.cpp b/src/plugins/template/backend/ops/adaptive_max_pool.cpp
index e70fc9195a2d65..52aec1ea410556 100644
--- a/src/plugins/template/backend/ops/adaptive_max_pool.cpp
+++ b/src/plugins/template/backend/ops/adaptive_max_pool.cpp
@@ -2,108 +2,73 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
-#include "openvino/reference/adaptive_avg_pool.hpp"
 #include "openvino/reference/adaptive_max_pool.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::AdaptiveMaxPool>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    if (op->get_index_element_type() == ngraph::element::i32) {
-        ov::reference::adaptive_max_pool(inputs[0]->get_data_ptr<T>(),
-                                         outputs[0]->get_data_ptr<T>(),
-                                         outputs[1]->get_data_ptr<int32_t>(),
-                                         inputs[0]->get_shape(),
+#include "evaluate_node.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v8::AdaptiveMaxPool>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    if (op->get_index_element_type() == ov::element::i32) {
+        ov::reference::adaptive_max_pool(inputs[0].data<T>(),
+                                         outputs[0].data<T>(),
+                                         outputs[1].data<int32_t>(),
+                                         inputs[0].get_shape(),
                                          op->get_output_shape(0));
-    } else if (op->get_index_element_type() == ngraph::element::i64) {
-        ov::reference::adaptive_max_pool(inputs[0]->get_data_ptr<T>(),
-                                         outputs[0]->get_data_ptr<T>(),
-                                         outputs[1]->get_data_ptr<int64_t>(),
-                                         inputs[0]->get_shape(),
+    } else if (op->get_index_element_type() == ov::element::i64) {
+        ov::reference::adaptive_max_pool(inputs[0].data<T>(),
+                                         outputs[0].data<T>(),
+                                         outputs[1].data<int64_t>(),
+                                         inputs[0].get_shape(),
                                          op->get_output_shape(0));
     }
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::AdaptiveMaxPool>(std::shared_ptr<ngraph::Node> node,
-                                                    const ngraph::HostTensorVector& outputs,
-                                                    const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::AdaptiveMaxPool>(std::shared_ptr<ov::Node> node,
+                                                ov::TensorVector& outputs,
+                                                const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::AdaptiveMaxPool>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::AdaptiveMaxPool>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/assign.cpp b/src/plugins/template/backend/ops/assign.cpp
index 8cdef6c7677e9c..3f4b5f108d5662 100644
--- a/src/plugins/template/backend/ops/assign.cpp
+++ b/src/plugins/template/backend/ops/assign.cpp
@@ -4,61 +4,21 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::Assign>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    outputs[0]->set_unary(inputs[0]);
-    void* input = inputs[0]->get_data_ptr();
-    outputs[0]->write(input, outputs[0]->get_size_in_bytes());
+bool evaluate(const std::shared_ptr<ov::op::v3::Assign>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    outputs[0].set_shape(inputs[0].get_shape());
+    inputs[0].copy_to(outputs[0]);
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::Assign>(std::shared_ptr<ngraph::Node> node,
-                                           const ngraph::HostTensorVector& outputs,
-                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::Assign>(std::shared_ptr<ov::Node> node,
+                                       ov::TensorVector& outputs,
+                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
-    switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::Assign>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::Assign>(node), outputs, inputs);
-    default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
-    }
+    return evaluate(ov::as_type_ptr<ov::op::v3::Assign>(node), outputs, inputs);
 }
diff --git a/src/plugins/template/backend/ops/avg_pool.cpp b/src/plugins/template/backend/ops/avg_pool.cpp
index b6f3a6a9803eca..03d610fcd1ae70 100644
--- a/src/plugins/template/backend/ops/avg_pool.cpp
+++ b/src/plugins/template/backend/ops/avg_pool.cpp
@@ -6,14 +6,14 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::AvgPool>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::avg_pool<T>(inputs[0]->get_data_ptr<T>(),
-                               outputs[0]->get_data_ptr<T>(),
-                               inputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v1::AvgPool>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::avg_pool<T>(inputs[0].data<T>(),
+                               outputs[0].data<T>(),
+                               inputs[0].get_shape(),
                                op->get_output_shape(0),
                                op->get_kernel(),
                                op->get_strides(),
@@ -24,50 +24,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v1::AvgPool>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::AvgPool>(std::shared_ptr<ngraph::Node> node,
-                                            const ngraph::HostTensorVector& outputs,
-                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::AvgPool>(std::shared_ptr<ov::Node> node,
+                                        ov::TensorVector& outputs,
+                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::AvgPool>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/batch_norm.cpp b/src/plugins/template/backend/ops/batch_norm.cpp
index 012fc449186bf9..7a7821070818f6 100644
--- a/src/plugins/template/backend/ops/batch_norm.cpp
+++ b/src/plugins/template/backend/ops/batch_norm.cpp
@@ -6,192 +6,126 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::BatchNormInference>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::BatchNormInference>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
     ov::reference::batch_norm_inference<T>(static_cast<float>(op->get_eps_value()),
-                                           inputs[2]->get_data_ptr<T>(),
-                                           inputs[0]->get_data_ptr<T>(),
-                                           inputs[1]->get_data_ptr<T>(),
-                                           inputs[3]->get_data_ptr<T>(),
-                                           inputs[4]->get_data_ptr<T>(),
-                                           outputs[0]->get_data_ptr<T>(),
-                                           inputs[2]->get_shape());
+                                           inputs[2].data<T>(),
+                                           inputs[0].data<T>(),
+                                           inputs[1].data<T>(),
+                                           inputs[3].data<T>(),
+                                           inputs[4].data<T>(),
+                                           outputs[0].data<T>(),
+                                           inputs[2].get_shape());
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v5::BatchNormInference>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v5::BatchNormInference>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
     ov::reference::batch_norm_inference<T>(static_cast<float>(static_cast<float>(op->get_eps_value())),
-                                           inputs[0]->get_data_ptr<const T>(),
-                                           inputs[1]->get_data_ptr<const T>(),
-                                           inputs[2]->get_data_ptr<const T>(),
-                                           inputs[3]->get_data_ptr<const T>(),
-                                           inputs[4]->get_data_ptr<const T>(),
-                                           outputs[0]->get_data_ptr<T>(),
+                                           inputs[0].data<const T>(),
+                                           inputs[1].data<const T>(),
+                                           inputs[2].data<const T>(),
+                                           inputs[3].data<const T>(),
+                                           inputs[4].data<const T>(),
+                                           outputs[0].data<T>(),
                                            op->get_input_shape(0));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::BatchNormInference>(std::shared_ptr<ngraph::Node> node,
-                                                       const ngraph::HostTensorVector& outputs,
-                                                       const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::BatchNormInference>(std::shared_ptr<ov::Node> node,
+                                                   ov::TensorVector& outputs,
+                                                   const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::BatchNormInference>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v5::BatchNormInference>(std::shared_ptr<ngraph::Node> node,
-                                                       const ngraph::HostTensorVector& outputs,
-                                                       const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v5::BatchNormInference>(std::shared_ptr<ov::Node> node,
+                                                   ov::TensorVector& outputs,
+                                                   const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v5::BatchNormInference>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v5::BatchNormInference>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/binary_convolution.cpp b/src/plugins/template/backend/ops/binary_convolution.cpp
index 4b09df85a80bdd..1974c749d19826 100644
--- a/src/plugins/template/backend/ops/binary_convolution.cpp
+++ b/src/plugins/template/backend/ops/binary_convolution.cpp
@@ -7,19 +7,19 @@
 #include "evaluate_node.hpp"
 
 namespace bin_conv_v1 {
-template <ngraph::element::Type_t t_in, ngraph::element::Type_t t_f>
-inline void evaluate(const std::shared_ptr<ngraph::op::v1::BinaryConvolution>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T_IN = typename ngraph::element_type_traits<t_in>::value_type;
-    using T_F = typename ngraph::element_type_traits<t_f>::value_type;
+template <ov::element::Type_t t_in, ov::element::Type_t t_f>
+inline void evaluate(const std::shared_ptr<ov::op::v1::BinaryConvolution>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T_IN = typename ov::element_type_traits<t_in>::value_type;
+    using T_F = typename ov::element_type_traits<t_f>::value_type;
 
-    const auto in_data_ptr = inputs[0]->get_data_ptr<T_IN>();
-    const auto filter_data_ptr = inputs[1]->get_data_ptr<T_F>();
-    auto out_data_ptr = outputs[0]->get_data_ptr<T_IN>();
-    const auto in_shape = inputs[0]->get_shape();
-    const auto filter_shape = inputs[1]->get_shape();
-    const auto out_shape = outputs[0]->get_shape();
+    const auto in_data_ptr = static_cast<T_IN*>(inputs[0].data());
+    const auto filter_data_ptr = static_cast<T_F*>(inputs[1].data());
+    auto out_data_ptr = static_cast<T_IN*>(outputs[0].data());
+    const auto in_shape = inputs[0].get_shape();
+    const auto filter_shape = inputs[1].get_shape();
+    const auto out_shape = outputs[0].get_shape();
 
     ov::reference::binary_convolution<T_IN, T_F>(in_data_ptr,
                                                  filter_data_ptr,
@@ -35,96 +35,63 @@ inline void evaluate(const std::shared_ptr<ngraph::op::v1::BinaryConvolution>& o
 }
 }  // namespace bin_conv_v1
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::BinaryConvolution>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[1]->get_element_type()) {
-    case ngraph::element::Type_t::u1:
-        bin_conv_v1::evaluate<ET, ngraph::element::Type_t::u8>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v1::BinaryConvolution>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[1].get_element_type()) {
+    case ov::element::u1:
+        bin_conv_v1::evaluate<ET, ov::element::u8>(op, outputs, inputs);
         break;
     default:
-        throw std::runtime_error("BinaryConvolution supports only u1 element type for filters input");
+        OPENVINO_THROW("BinaryConvolution supports only u1 element type for filters input");
         break;
     }
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::BinaryConvolution>(std::shared_ptr<ngraph::Node> node,
-                                                      const ngraph::HostTensorVector& outputs,
-                                                      const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::BinaryConvolution>(std::shared_ptr<ov::Node> node,
+                                                  ov::TensorVector& outputs,
+                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::BinaryConvolution>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::BinaryConvolution>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/bucketize.cpp b/src/plugins/template/backend/ops/bucketize.cpp
index b55f7cda250a8f..ca9119fe19255a 100644
--- a/src/plugins/template/backend/ops/bucketize.cpp
+++ b/src/plugins/template/backend/ops/bucketize.cpp
@@ -7,139 +7,139 @@
 #include "evaluate_node.hpp"
 
 namespace bucketize_v3 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2, ngraph::element::Type_t t3>
-inline void evaluate(const std::shared_ptr<ngraph::op::v3::Bucketize>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    using T3 = typename ngraph::element_type_traits<t3>::value_type;
+template <ov::element::Type_t t1, ov::element::Type_t t2, ov::element::Type_t t3>
+inline void evaluate(const std::shared_ptr<ov::op::v3::Bucketize>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    using T3 = typename ov::element_type_traits<t3>::value_type;
 
-    ov::reference::bucketize<T1, T2, T3>(inputs[0]->get_data_ptr<T1>(),
-                                         inputs[1]->get_data_ptr<T2>(),
-                                         outputs[0]->get_data_ptr<T3>(),
+    ov::reference::bucketize<T1, T2, T3>(inputs[0].data<T1>(),
+                                         inputs[1].data<T2>(),
+                                         outputs[0].data<T3>(),
                                          op->get_input_shape(0),
                                          op->get_input_shape(1),
                                          op->get_with_right_bound());
 }
 
-static inline constexpr uint16_t getElementMask(ngraph::element::Type_t type1, ngraph::element::Type_t type2) {
+static inline constexpr uint16_t getElementMask(ov::element::Type_t type1, ov::element::Type_t type2) {
     return (static_cast<uint8_t>(type1)) | (static_cast<uint8_t>(type2) << 8);
 }
 }  // namespace bucketize_v3
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::Bucketize>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v3::Bucketize>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     switch (bucketize_v3::getElementMask(op->get_input_element_type(0), op->get_input_element_type(1))) {
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f32, ngraph::element::Type_t::f32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f32, ngraph::element::Type_t::f32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f32, ov::element::f32):
+        bucketize_v3::evaluate<ov::element::f32, ov::element::f32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f32, ngraph::element::Type_t::f16):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f32, ngraph::element::Type_t::f16, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f32, ov::element::f16):
+        bucketize_v3::evaluate<ov::element::f32, ov::element::f16, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f32, ngraph::element::Type_t::i32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f32, ngraph::element::Type_t::i32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f32, ov::element::i32):
+        bucketize_v3::evaluate<ov::element::f32, ov::element::i32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f32, ngraph::element::Type_t::i64):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f32, ngraph::element::Type_t::i64, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f32, ov::element::i64):
+        bucketize_v3::evaluate<ov::element::f32, ov::element::i64, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f32, ngraph::element::Type_t::i8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f32, ngraph::element::Type_t::i8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f32, ov::element::i8):
+        bucketize_v3::evaluate<ov::element::f32, ov::element::i8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f32, ngraph::element::Type_t::u8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f32, ngraph::element::Type_t::u8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f32, ov::element::u8):
+        bucketize_v3::evaluate<ov::element::f32, ov::element::u8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f16, ngraph::element::Type_t::f32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f16, ngraph::element::Type_t::f32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f16, ov::element::f32):
+        bucketize_v3::evaluate<ov::element::f16, ov::element::f32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f16, ngraph::element::Type_t::f16):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f16, ngraph::element::Type_t::f16, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f16, ov::element::f16):
+        bucketize_v3::evaluate<ov::element::f16, ov::element::f16, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f16, ngraph::element::Type_t::i32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f16, ngraph::element::Type_t::i32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f16, ov::element::i32):
+        bucketize_v3::evaluate<ov::element::f16, ov::element::i32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f16, ngraph::element::Type_t::i64):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f16, ngraph::element::Type_t::i64, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f16, ov::element::i64):
+        bucketize_v3::evaluate<ov::element::f16, ov::element::i64, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f16, ngraph::element::Type_t::i8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f16, ngraph::element::Type_t::i8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f16, ov::element::i8):
+        bucketize_v3::evaluate<ov::element::f16, ov::element::i8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::f16, ngraph::element::Type_t::u8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::f16, ngraph::element::Type_t::u8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::f16, ov::element::u8):
+        bucketize_v3::evaluate<ov::element::f16, ov::element::u8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i32, ngraph::element::Type_t::f32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i32, ngraph::element::Type_t::f32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i32, ov::element::f32):
+        bucketize_v3::evaluate<ov::element::i32, ov::element::f32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i32, ngraph::element::Type_t::f16):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i32, ngraph::element::Type_t::f16, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i32, ov::element::f16):
+        bucketize_v3::evaluate<ov::element::i32, ov::element::f16, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i32, ngraph::element::Type_t::i32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i32, ngraph::element::Type_t::i32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i32, ov::element::i32):
+        bucketize_v3::evaluate<ov::element::i32, ov::element::i32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i32, ngraph::element::Type_t::i64):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i32, ngraph::element::Type_t::i64, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i32, ov::element::i64):
+        bucketize_v3::evaluate<ov::element::i32, ov::element::i64, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i32, ngraph::element::Type_t::i8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i32, ngraph::element::Type_t::i8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i32, ov::element::i8):
+        bucketize_v3::evaluate<ov::element::i32, ov::element::i8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i32, ngraph::element::Type_t::u8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i32, ngraph::element::Type_t::u8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i32, ov::element::u8):
+        bucketize_v3::evaluate<ov::element::i32, ov::element::u8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i64, ngraph::element::Type_t::f32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i64, ngraph::element::Type_t::f32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i64, ov::element::f32):
+        bucketize_v3::evaluate<ov::element::i64, ov::element::f32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i64, ngraph::element::Type_t::f16):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i64, ngraph::element::Type_t::f16, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i64, ov::element::f16):
+        bucketize_v3::evaluate<ov::element::i64, ov::element::f16, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i64, ngraph::element::Type_t::i32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i64, ngraph::element::Type_t::i32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i64, ov::element::i32):
+        bucketize_v3::evaluate<ov::element::i64, ov::element::i32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i64, ngraph::element::Type_t::i64):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i64, ngraph::element::Type_t::i64, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i64, ov::element::i64):
+        bucketize_v3::evaluate<ov::element::i64, ov::element::i64, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i64, ngraph::element::Type_t::i8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i64, ngraph::element::Type_t::i8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i64, ov::element::i8):
+        bucketize_v3::evaluate<ov::element::i64, ov::element::i8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i64, ngraph::element::Type_t::u8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i64, ngraph::element::Type_t::u8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i64, ov::element::u8):
+        bucketize_v3::evaluate<ov::element::i64, ov::element::u8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i8, ngraph::element::Type_t::f32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i8, ngraph::element::Type_t::f32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i8, ov::element::f32):
+        bucketize_v3::evaluate<ov::element::i8, ov::element::f32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i8, ngraph::element::Type_t::f16):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i8, ngraph::element::Type_t::f16, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i8, ov::element::f16):
+        bucketize_v3::evaluate<ov::element::i8, ov::element::f16, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i8, ngraph::element::Type_t::i32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i8, ngraph::element::Type_t::i32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i8, ov::element::i32):
+        bucketize_v3::evaluate<ov::element::i8, ov::element::i32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i8, ngraph::element::Type_t::i64):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i8, ngraph::element::Type_t::i64, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i8, ov::element::i64):
+        bucketize_v3::evaluate<ov::element::i8, ov::element::i64, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i8, ngraph::element::Type_t::i8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i8, ngraph::element::Type_t::i8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i8, ov::element::i8):
+        bucketize_v3::evaluate<ov::element::i8, ov::element::i8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::i8, ngraph::element::Type_t::u8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::i8, ngraph::element::Type_t::u8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::i8, ov::element::u8):
+        bucketize_v3::evaluate<ov::element::i8, ov::element::u8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::u8, ngraph::element::Type_t::f32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::u8, ngraph::element::Type_t::f32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::u8, ov::element::f32):
+        bucketize_v3::evaluate<ov::element::u8, ov::element::f32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::u8, ngraph::element::Type_t::f16):
-        bucketize_v3::evaluate<ngraph::element::Type_t::u8, ngraph::element::Type_t::f16, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::u8, ov::element::f16):
+        bucketize_v3::evaluate<ov::element::u8, ov::element::f16, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::u8, ngraph::element::Type_t::i32):
-        bucketize_v3::evaluate<ngraph::element::Type_t::u8, ngraph::element::Type_t::i32, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::u8, ov::element::i32):
+        bucketize_v3::evaluate<ov::element::u8, ov::element::i32, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::u8, ngraph::element::Type_t::i64):
-        bucketize_v3::evaluate<ngraph::element::Type_t::u8, ngraph::element::Type_t::i64, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::u8, ov::element::i64):
+        bucketize_v3::evaluate<ov::element::u8, ov::element::i64, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::u8, ngraph::element::Type_t::i8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::u8, ngraph::element::Type_t::i8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::u8, ov::element::i8):
+        bucketize_v3::evaluate<ov::element::u8, ov::element::i8, ET>(op, outputs, inputs);
         break;
-    case bucketize_v3::getElementMask(ngraph::element::Type_t::u8, ngraph::element::Type_t::u8):
-        bucketize_v3::evaluate<ngraph::element::Type_t::u8, ngraph::element::Type_t::u8, ET>(op, outputs, inputs);
+    case bucketize_v3::getElementMask(ov::element::u8, ov::element::u8):
+        bucketize_v3::evaluate<ov::element::u8, ov::element::u8, ET>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -148,70 +148,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v3::Bucketize>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::Bucketize>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::Bucketize>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::Bucketize>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v3::Bucketize>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/ceiling.cpp b/src/plugins/template/backend/ops/ceiling.cpp
index 19c3127a43c523..3278219a3e6b6b 100644
--- a/src/plugins/template/backend/ops/ceiling.cpp
+++ b/src/plugins/template/backend/ops/ceiling.cpp
@@ -6,62 +6,57 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Ceiling>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::ceiling<T>(inputs[0]->get_data_ptr<T>(),
-                              outputs[0]->get_data_ptr<T>(),
-                              ngraph::shape_size(inputs[0]->get_shape()));
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Ceiling>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::ceiling<T>(inputs[0].data<T>(), outputs[0].data<T>(), ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Ceiling>(std::shared_ptr<ngraph::Node> node,
-                                            const ngraph::HostTensorVector& outputs,
-                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Ceiling>(std::shared_ptr<ov::Node> node,
+                                        ov::TensorVector& outputs,
+                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Ceiling>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/convert.cpp b/src/plugins/template/backend/ops/convert.cpp
index 319818a5727854..71f6f3cc87a152 100644
--- a/src/plugins/template/backend/ops/convert.cpp
+++ b/src/plugins/template/backend/ops/convert.cpp
@@ -7,79 +7,76 @@
 #include "evaluate_node.hpp"
 
 namespace convert_like_v1 {
-template <ngraph::element::Type_t ti, ngraph::element::Type_t to>
-inline void evaluate(const std::shared_ptr<ngraph::op::v1::ConvertLike>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    outputs[0]->set_shape(inputs[0]->get_shape());
-    size_t element_count = ngraph::shape_size(outputs[0]->get_shape());
+template <ov::element::Type_t ti, ov::element::Type_t to>
+inline void evaluate(const std::shared_ptr<ov::op::v1::ConvertLike>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T_I = typename ov::element_type_traits<ti>::value_type;
+    using T_O = typename ov::element_type_traits<to>::value_type;
+    outputs[0].set_shape(inputs[0].get_shape());
+    size_t element_count = ov::shape_size(outputs[0].get_shape());
 
-    if (((ti == ngraph::element::u1) || (to == ngraph::element::u1)) ||
-        ((ti == ngraph::element::u4) || (to == ngraph::element::u4)) ||
-        ((ti == ngraph::element::i4) || (to == ngraph::element::i4))) {
-        ov::reference::detail::lp_convert(inputs[0]->get_data_ptr<ti>(),
-                                          outputs[0]->get_data_ptr<to>(),
-                                          element_count,
-                                          ti,
-                                          to);
+    if (((ti == ov::element::u1) || (to == ov::element::u1)) || ((ti == ov::element::u4) || (to == ov::element::u4)) ||
+        ((ti == ov::element::i4) || (to == ov::element::i4))) {
+        ov::reference::detail::lp_convert(inputs[0].data<T_I>(), outputs[0].data<T_O>(), element_count, ti, to);
     } else {
-        ov::reference::convert(inputs[0]->get_data_ptr<ti>(), outputs[0]->get_data_ptr<to>(), element_count);
+        ov::reference::convert(inputs[0].data<T_I>(), outputs[0].data<T_O>(), element_count);
     }
 }
 }  // namespace convert_like_v1
 
-template <ngraph::element::Type_t OUT_ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::ConvertLike>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[0]->get_element_type()) {
-    case ngraph::element::Type_t::boolean:
-        convert_like_v1::evaluate<ngraph::element::Type_t::boolean, OUT_ET>(op, outputs, inputs);
+template <ov::element::Type_t OUT_ET>
+bool evaluate(const std::shared_ptr<ov::op::v1::ConvertLike>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[0].get_element_type()) {
+    case ov::element::boolean:
+        convert_like_v1::evaluate<ov::element::boolean, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u1:
-        convert_like_v1::evaluate<ngraph::element::Type_t::u1, OUT_ET>(op, outputs, inputs);
+    case ov::element::u1:
+        convert_like_v1::evaluate<ov::element::u1, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u4:
-        convert_like_v1::evaluate<ngraph::element::Type_t::u4, OUT_ET>(op, outputs, inputs);
+    case ov::element::u4:
+        convert_like_v1::evaluate<ov::element::u4, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u8:
-        convert_like_v1::evaluate<ngraph::element::Type_t::u8, OUT_ET>(op, outputs, inputs);
+    case ov::element::u8:
+        convert_like_v1::evaluate<ov::element::u8, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u16:
-        convert_like_v1::evaluate<ngraph::element::Type_t::u16, OUT_ET>(op, outputs, inputs);
+    case ov::element::u16:
+        convert_like_v1::evaluate<ov::element::u16, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u32:
-        convert_like_v1::evaluate<ngraph::element::Type_t::u32, OUT_ET>(op, outputs, inputs);
+    case ov::element::u32:
+        convert_like_v1::evaluate<ov::element::u32, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u64:
-        convert_like_v1::evaluate<ngraph::element::Type_t::u64, OUT_ET>(op, outputs, inputs);
+    case ov::element::u64:
+        convert_like_v1::evaluate<ov::element::u64, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i4:
-        convert_like_v1::evaluate<ngraph::element::Type_t::i4, OUT_ET>(op, outputs, inputs);
+    case ov::element::i4:
+        convert_like_v1::evaluate<ov::element::i4, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i8:
-        convert_like_v1::evaluate<ngraph::element::Type_t::i8, OUT_ET>(op, outputs, inputs);
+    case ov::element::i8:
+        convert_like_v1::evaluate<ov::element::i8, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i16:
-        convert_like_v1::evaluate<ngraph::element::Type_t::i16, OUT_ET>(op, outputs, inputs);
+    case ov::element::i16:
+        convert_like_v1::evaluate<ov::element::i16, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i32:
-        convert_like_v1::evaluate<ngraph::element::Type_t::i32, OUT_ET>(op, outputs, inputs);
+    case ov::element::i32:
+        convert_like_v1::evaluate<ov::element::i32, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i64:
-        convert_like_v1::evaluate<ngraph::element::Type_t::i64, OUT_ET>(op, outputs, inputs);
+    case ov::element::i64:
+        convert_like_v1::evaluate<ov::element::i64, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::bf16:
-        convert_like_v1::evaluate<ngraph::element::Type_t::bf16, OUT_ET>(op, outputs, inputs);
+    case ov::element::bf16:
+        convert_like_v1::evaluate<ov::element::bf16, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::f16:
-        convert_like_v1::evaluate<ngraph::element::Type_t::f16, OUT_ET>(op, outputs, inputs);
+    case ov::element::f16:
+        convert_like_v1::evaluate<ov::element::f16, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::f32:
-        convert_like_v1::evaluate<ngraph::element::Type_t::f32, OUT_ET>(op, outputs, inputs);
+    case ov::element::f32:
+        convert_like_v1::evaluate<ov::element::f32, OUT_ET>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::f64:
-        convert_like_v1::evaluate<ngraph::element::Type_t::f64, OUT_ET>(op, outputs, inputs);
+    case ov::element::f64:
+        convert_like_v1::evaluate<ov::element::f64, OUT_ET>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -88,80 +85,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v1::ConvertLike>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::ConvertLike>(std::shared_ptr<ngraph::Node> node,
-                                                const ngraph::HostTensorVector& outputs,
-                                                const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::ConvertLike>(std::shared_ptr<ov::Node> node,
+                                            ov::TensorVector& outputs,
+                                            const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::ConvertLike>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::ConvertLike>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/convert_color_nv12.cpp b/src/plugins/template/backend/ops/convert_color_nv12.cpp
index 3b9996da285192..f2b571f73cacfb 100644
--- a/src/plugins/template/backend/ops/convert_color_nv12.cpp
+++ b/src/plugins/template/backend/ops/convert_color_nv12.cpp
@@ -7,9 +7,9 @@
 #include "evaluate_node.hpp"
 
 template <ov::element::Type_t ET>
-inline bool evaluate(const std::shared_ptr<ngraph::op::v8::NV12toRGB>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
+inline bool evaluate(const std::shared_ptr<ov::op::v8::NV12toRGB>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
     return ov::reference::color_convert_nv12<ET>(op,
                                                  outputs,
                                                  inputs,
@@ -17,9 +17,9 @@ inline bool evaluate(const std::shared_ptr<ngraph::op::v8::NV12toRGB>& op,
 }
 
 template <ov::element::Type_t ET>
-inline bool evaluate(const std::shared_ptr<ngraph::op::v8::NV12toBGR>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
+inline bool evaluate(const std::shared_ptr<ov::op::v8::NV12toBGR>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
     return ov::reference::color_convert_nv12<ET>(op,
                                                  outputs,
                                                  inputs,
@@ -27,9 +27,9 @@ inline bool evaluate(const std::shared_ptr<ngraph::op::v8::NV12toBGR>& op,
 }
 
 template <ov::element::Type_t ET>
-inline bool evaluate(const std::shared_ptr<ngraph::op::v8::I420toRGB>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
+inline bool evaluate(const std::shared_ptr<ov::op::v8::I420toRGB>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
     return ov::reference::color_convert_i420<ET>(op,
                                                  outputs,
                                                  inputs,
@@ -37,9 +37,9 @@ inline bool evaluate(const std::shared_ptr<ngraph::op::v8::I420toRGB>& op,
 }
 
 template <ov::element::Type_t ET>
-inline bool evaluate(const std::shared_ptr<ngraph::op::v8::I420toBGR>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
+inline bool evaluate(const std::shared_ptr<ov::op::v8::I420toBGR>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
     return ov::reference::color_convert_i420<ET>(op,
                                                  outputs,
                                                  inputs,
@@ -47,68 +47,46 @@ inline bool evaluate(const std::shared_ptr<ngraph::op::v8::I420toBGR>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::NV12toRGB>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::NV12toRGB>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::NV12toRGB>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::NV12toRGB>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -116,68 +94,46 @@ bool evaluate_node<ngraph::op::v8::NV12toRGB>(std::shared_ptr<ngraph::Node> node
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::NV12toBGR>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::NV12toBGR>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::NV12toBGR>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::NV12toBGR>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -185,68 +141,46 @@ bool evaluate_node<ngraph::op::v8::NV12toBGR>(std::shared_ptr<ngraph::Node> node
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::I420toRGB>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::I420toRGB>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::I420toRGB>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::I420toRGB>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -254,70 +188,47 @@ bool evaluate_node<ngraph::op::v8::I420toRGB>(std::shared_ptr<ngraph::Node> node
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::I420toBGR>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::I420toBGR>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::I420toBGR>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::I420toBGR>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/convolution.cpp b/src/plugins/template/backend/ops/convolution.cpp
index 1af7805495022f..ea7e7ba20c1675 100644
--- a/src/plugins/template/backend/ops/convolution.cpp
+++ b/src/plugins/template/backend/ops/convolution.cpp
@@ -6,104 +6,72 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::Convolution>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto filter_data = inputs[1]->get_data_ptr<ET>();
-    auto out_data_ptr = outputs[0]->get_data_ptr<ET>();
-    const auto in_data_ptr = inputs[0]->get_data_ptr<ET>();
-    const auto& out_shape = outputs[0]->get_shape();
-    const auto& in_shape = inputs[0]->get_shape();
-    const auto& filter_shape = inputs[1]->get_shape();
-    ov::reference::convolution<typename ngraph::element_type_traits<ET>::value_type>(in_data_ptr,
-                                                                                     filter_data,
-                                                                                     out_data_ptr,
-                                                                                     in_shape,
-                                                                                     filter_shape,
-                                                                                     out_shape,
-                                                                                     op->get_strides(),
-                                                                                     op->get_dilations(),
-                                                                                     op->get_pads_begin(),
-                                                                                     op->get_pads_end());
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v1::Convolution>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    const auto filter_data = inputs[1].data<ET>();
+    auto out_data_ptr = outputs[0].data<ET>();
+    const auto in_data_ptr = inputs[0].data<ET>();
+    const auto& out_shape = outputs[0].get_shape();
+    const auto& in_shape = inputs[0].get_shape();
+    const auto& filter_shape = inputs[1].get_shape();
+    ov::reference::convolution<ET>(in_data_ptr,
+                                   filter_data,
+                                   out_data_ptr,
+                                   in_shape,
+                                   filter_shape,
+                                   out_shape,
+                                   op->get_strides(),
+                                   op->get_dilations(),
+                                   op->get_pads_begin(),
+                                   op->get_pads_end());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::Convolution>(std::shared_ptr<ngraph::Node> node,
-                                                const ngraph::HostTensorVector& outputs,
-                                                const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::Convolution>(std::shared_ptr<ov::Node> node,
+                                            ov::TensorVector& outputs,
+                                            const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::Convolution>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::Convolution>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/convolution_backprop_data.cpp b/src/plugins/template/backend/ops/convolution_backprop_data.cpp
index e0d7d7aafcb650..a9d8ebb6ef30e9 100644
--- a/src/plugins/template/backend/ops/convolution_backprop_data.cpp
+++ b/src/plugins/template/backend/ops/convolution_backprop_data.cpp
@@ -6,110 +6,78 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::ConvolutionBackpropData>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto filter_data = inputs[1]->get_data_ptr<ET>();
-    auto out_data_ptr = outputs[0]->get_data_ptr<ET>();
-    const auto in_data_ptr = inputs[0]->get_data_ptr<ET>();
-    const auto& out_shape = outputs[0]->get_shape();
-    const auto& in_shape = inputs[0]->get_shape();
-    const auto& filter_shape = inputs[1]->get_shape();
-    ngraph::Strides in_dilation(std::vector<size_t>(in_shape.size() - 2));
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v1::ConvolutionBackpropData>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    const auto filter_data = inputs[1].data<ET>();
+    auto out_data_ptr = outputs[0].data<ET>();
+    const auto in_data_ptr = inputs[0].data<ET>();
+    const auto& out_shape = outputs[0].get_shape();
+    const auto& in_shape = inputs[0].get_shape();
+    const auto& filter_shape = inputs[1].get_shape();
+    ov::Strides in_dilation(std::vector<size_t>(in_shape.size() - 2));
     std::fill(in_dilation.begin(), in_dilation.end(), 1);
-    ov::reference::convolution_backprop_in<typename ngraph::element_type_traits<ET>::value_type>(
-        in_data_ptr,
-        filter_data,
-        out_data_ptr,
-        in_shape,
-        filter_shape,
-        out_shape,
-        in_dilation,
-        op->get_dilations(),
-        op->get_pads_begin(),
-        op->get_pads_end(),
-        op->get_strides(),
-        op->get_output_padding());
+    ov::reference::convolution_backprop_in<ET>(in_data_ptr,
+                                               filter_data,
+                                               out_data_ptr,
+                                               in_shape,
+                                               filter_shape,
+                                               out_shape,
+                                               in_dilation,
+                                               op->get_dilations(),
+                                               op->get_pads_begin(),
+                                               op->get_pads_end(),
+                                               op->get_strides(),
+                                               op->get_output_padding());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::ConvolutionBackpropData>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::ConvolutionBackpropData>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(
-            ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::ConvolutionBackpropData>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::ConvolutionBackpropData>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/ctc_greedy_decoder.cpp b/src/plugins/template/backend/ops/ctc_greedy_decoder.cpp
index b0bbeffd5a0e18..de6f162ab44b3b 100644
--- a/src/plugins/template/backend/ops/ctc_greedy_decoder.cpp
+++ b/src/plugins/template/backend/ops/ctc_greedy_decoder.cpp
@@ -6,96 +6,63 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::CTCGreedyDecoder>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::ctc_greedy_decoder<T>(inputs[0]->get_data_ptr<const T>(),
-                                         inputs[1]->get_data_ptr<const T>(),
-                                         outputs[0]->get_data_ptr<T>(),
-                                         inputs[0]->get_shape(),
-                                         inputs[1]->get_shape(),
-                                         outputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::CTCGreedyDecoder>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::ctc_greedy_decoder<T>(inputs[0].data<const T>(),
+                                         inputs[1].data<const T>(),
+                                         outputs[0].data<T>(),
+                                         inputs[0].get_shape(),
+                                         inputs[1].get_shape(),
+                                         outputs[0].get_shape(),
                                          op->get_ctc_merge_repeated());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::CTCGreedyDecoder>(std::shared_ptr<ngraph::Node> node,
-                                                     const ngraph::HostTensorVector& outputs,
-                                                     const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::CTCGreedyDecoder>(std::shared_ptr<ov::Node> node,
+                                                 ov::TensorVector& outputs,
+                                                 const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::CTCGreedyDecoder>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::CTCGreedyDecoder>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/ctc_greedy_decoder_seq_len.cpp b/src/plugins/template/backend/ops/ctc_greedy_decoder_seq_len.cpp
index 7cff484d99ef6c..b76c5459cdfc7c 100644
--- a/src/plugins/template/backend/ops/ctc_greedy_decoder_seq_len.cpp
+++ b/src/plugins/template/backend/ops/ctc_greedy_decoder_seq_len.cpp
@@ -7,69 +7,57 @@
 #include "evaluate_node.hpp"
 
 namespace ctc_greedy_decoder_v6 {
-template <ngraph::element::Type_t T1, ngraph::element::Type_t T2, ngraph::element::Type_t TOUT>
-inline void evaluate(const std::shared_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using TF = typename ngraph::element_type_traits<T1>::value_type;
-    using TI = typename ngraph::element_type_traits<T2>::value_type;
-    using TIND1 = typename ngraph::element_type_traits<TOUT>::value_type;
-    TI blank_index_val = static_cast<TI>(inputs[0]->get_shape().back() - 1);
+template <ov::element::Type_t T1, ov::element::Type_t T2, ov::element::Type_t TOUT>
+inline void evaluate(const std::shared_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using TF = typename ov::element_type_traits<T1>::value_type;
+    using TI = typename ov::element_type_traits<T2>::value_type;
+    using TIND1 = typename ov::element_type_traits<TOUT>::value_type;
+    TI blank_index_val = static_cast<TI>(inputs[0].get_shape().back() - 1);
     const TI* blank_index = &blank_index_val;
     if (inputs.size() == 3) {
-        blank_index = inputs[2]->get_data_ptr<const TI>();
+        blank_index = inputs[2].data<const TI>();
     }
-    if (op->get_sequence_length_type() == ngraph::element::i32) {
-        ov::reference::ctc_greedy_decoder_seq_len<TF>(inputs[0]->get_data_ptr<const TF>(),
-                                                      inputs[1]->get_data_ptr<const TI>(),
+    if (op->get_sequence_length_type() == ov::element::i32) {
+        ov::reference::ctc_greedy_decoder_seq_len<TF>(inputs[0].data<const TF>(),
+                                                      inputs[1].data<const TI>(),
                                                       blank_index,
-                                                      outputs[0]->get_data_ptr<TIND1>(),
-                                                      outputs[1]->get_data_ptr<int32_t>(),
-                                                      inputs[0]->get_shape(),
-                                                      outputs[0]->get_shape(),
+                                                      outputs[0].data<TIND1>(),
+                                                      outputs[1].data<int32_t>(),
+                                                      inputs[0].get_shape(),
+                                                      outputs[0].get_shape(),
                                                       op->get_merge_repeated());
-    } else if (op->get_sequence_length_type() == ngraph::element::i64) {
-        ov::reference::ctc_greedy_decoder_seq_len<TF>(inputs[0]->get_data_ptr<const TF>(),
-                                                      inputs[1]->get_data_ptr<const TI>(),
+    } else if (op->get_sequence_length_type() == ov::element::i64) {
+        ov::reference::ctc_greedy_decoder_seq_len<TF>(inputs[0].data<const TF>(),
+                                                      inputs[1].data<const TI>(),
                                                       blank_index,
-                                                      outputs[0]->get_data_ptr<TIND1>(),
-                                                      outputs[1]->get_data_ptr<int64_t>(),
-                                                      inputs[0]->get_shape(),
-                                                      outputs[0]->get_shape(),
+                                                      outputs[0].data<TIND1>(),
+                                                      outputs[1].data<int64_t>(),
+                                                      inputs[0].get_shape(),
+                                                      outputs[0].get_shape(),
                                                       op->get_merge_repeated());
     }
 }
 }  // namespace ctc_greedy_decoder_v6
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto& dataType = inputs[0]->get_element_type();
-    const auto& seqLenType = inputs[1]->get_element_type();
-    if (dataType == ngraph::element::Type_t::f16 && seqLenType == ngraph::element::Type_t::i32) {
-        ctc_greedy_decoder_v6::evaluate<ngraph::element::Type_t::f16, ngraph::element::Type_t::i32, ET>(op,
-                                                                                                        outputs,
-                                                                                                        inputs);
-    } else if (dataType == ngraph::element::Type_t::f32 && seqLenType == ngraph::element::Type_t::i32) {
-        ctc_greedy_decoder_v6::evaluate<ngraph::element::Type_t::f32, ngraph::element::Type_t::i32, ET>(op,
-                                                                                                        outputs,
-                                                                                                        inputs);
-    } else if (dataType == ngraph::element::Type_t::f64 && seqLenType == ngraph::element::Type_t::i32) {
-        ctc_greedy_decoder_v6::evaluate<ngraph::element::Type_t::f64, ngraph::element::Type_t::i32, ET>(op,
-                                                                                                        outputs,
-                                                                                                        inputs);
-    } else if (dataType == ngraph::element::Type_t::f16 && seqLenType == ngraph::element::Type_t::i64) {
-        ctc_greedy_decoder_v6::evaluate<ngraph::element::Type_t::f16, ngraph::element::Type_t::i64, ET>(op,
-                                                                                                        outputs,
-                                                                                                        inputs);
-    } else if (dataType == ngraph::element::Type_t::f32 && seqLenType == ngraph::element::Type_t::i64) {
-        ctc_greedy_decoder_v6::evaluate<ngraph::element::Type_t::f32, ngraph::element::Type_t::i64, ET>(op,
-                                                                                                        outputs,
-                                                                                                        inputs);
-    } else if (dataType == ngraph::element::Type_t::f64 && seqLenType == ngraph::element::Type_t::i64) {
-        ctc_greedy_decoder_v6::evaluate<ngraph::element::Type_t::f64, ngraph::element::Type_t::i64, ET>(op,
-                                                                                                        outputs,
-                                                                                                        inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    const auto& dataType = inputs[0].get_element_type();
+    const auto& seqLenType = inputs[1].get_element_type();
+    if (dataType == ov::element::f16 && seqLenType == ov::element::i32) {
+        ctc_greedy_decoder_v6::evaluate<ov::element::f16, ov::element::i32, ET>(op, outputs, inputs);
+    } else if (dataType == ov::element::f32 && seqLenType == ov::element::i32) {
+        ctc_greedy_decoder_v6::evaluate<ov::element::f32, ov::element::i32, ET>(op, outputs, inputs);
+    } else if (dataType == ov::element::f64 && seqLenType == ov::element::i32) {
+        ctc_greedy_decoder_v6::evaluate<ov::element::f64, ov::element::i32, ET>(op, outputs, inputs);
+    } else if (dataType == ov::element::f16 && seqLenType == ov::element::i64) {
+        ctc_greedy_decoder_v6::evaluate<ov::element::f16, ov::element::i64, ET>(op, outputs, inputs);
+    } else if (dataType == ov::element::f32 && seqLenType == ov::element::i64) {
+        ctc_greedy_decoder_v6::evaluate<ov::element::f32, ov::element::i64, ET>(op, outputs, inputs);
+    } else if (dataType == ov::element::f64 && seqLenType == ov::element::i64) {
+        ctc_greedy_decoder_v6::evaluate<ov::element::f64, ov::element::i64, ET>(op, outputs, inputs);
     } else {
         return false;
     }
@@ -77,80 +65,49 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v6::CTCGreedyDecoderSeqLen>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v6::CTCGreedyDecoderSeqLen>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v6::CTCGreedyDecoderSeqLen>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v6::CTCGreedyDecoderSeqLen>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/ctc_loss.cpp b/src/plugins/template/backend/ops/ctc_loss.cpp
index 41b009be635185..215f4e661a08e6 100644
--- a/src/plugins/template/backend/ops/ctc_loss.cpp
+++ b/src/plugins/template/backend/ops/ctc_loss.cpp
@@ -2,62 +2,59 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/ctc_loss.hpp"
-// clang-format on
+
+#include "evaluate_node.hpp"
 
 namespace ctc_loss_v4 {
-template <ngraph::element::Type_t t1,
-          ngraph::element::Type_t t2,
-          typename std::enable_if<
-              !std::is_floating_point<typename ngraph::element_type_traits<t1>::value_type>::value &&
-                  !std::is_same<typename ngraph::element_type_traits<t1>::value_type, ngraph::bfloat16>::value &&
-                  !std::is_same<typename ngraph::element_type_traits<t1>::value_type, ngraph::float16>::value,
-              bool>::type = true>
-inline void evaluate(const std::shared_ptr<ngraph::op::v4::CTCLoss>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    OPENVINO_ASSERT(false,
-                    "The data type for logits is expected to be a floating point type. Got:",
-                    ngraph::element::Type(t1));
+template <
+    ov::element::Type_t ET1,
+    ov::element::Type_t ET2,
+    typename std::enable_if<!std::is_floating_point<typename ov::element_type_traits<ET1>::value_type>::value &&
+                                !std::is_same<typename ov::element_type_traits<ET1>::value_type, ov::bfloat16>::value &&
+                                !std::is_same<typename ov::element_type_traits<ET1>::value_type, ov::float16>::value,
+                            bool>::type = true>
+inline void evaluate(const std::shared_ptr<ov::op::v4::CTCLoss>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    OPENVINO_THROW("The data type for logits is expected to be a floating point type. Got:", ov::element::Type(ET1));
 }
 
-template <ngraph::element::Type_t t1,
-          ngraph::element::Type_t t2,
-          typename std::enable_if<
-              std::is_floating_point<typename ngraph::element_type_traits<t1>::value_type>::value ||
-                  std::is_same<typename ngraph::element_type_traits<t1>::value_type, ngraph::bfloat16>::value ||
-                  std::is_same<typename ngraph::element_type_traits<t1>::value_type, ngraph::float16>::value,
-              bool>::type = true>
-inline void evaluate(const std::shared_ptr<ngraph::op::v4::CTCLoss>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::CTCLoss<T1, T2>(inputs[0]->get_data_ptr<T1>(),
-                                   inputs[0]->get_shape(),
-                                   inputs[1]->get_data_ptr<T2>(),
-                                   inputs[2]->get_data_ptr<T2>(),
-                                   inputs[3]->get_data_ptr<T2>(),
-                                   inputs[4]->get_data_ptr<T2>(),
+template <
+    ov::element::Type_t ET1,
+    ov::element::Type_t ET2,
+    typename std::enable_if<std::is_floating_point<typename ov::element_type_traits<ET1>::value_type>::value ||
+                                std::is_same<typename ov::element_type_traits<ET1>::value_type, ov::bfloat16>::value ||
+                                std::is_same<typename ov::element_type_traits<ET1>::value_type, ov::float16>::value,
+                            bool>::type = true>
+inline void evaluate(const std::shared_ptr<ov::op::v4::CTCLoss>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<ET1>::value_type;
+    using T2 = typename ov::element_type_traits<ET2>::value_type;
+    ov::reference::CTCLoss<T1, T2>(static_cast<T1*>(inputs[0].data()),
+                                   inputs[0].get_shape(),
+                                   static_cast<T2*>(inputs[1].data()),
+                                   static_cast<T2*>(inputs[2].data()),
+                                   static_cast<T2*>(inputs[3].data()),
+                                   static_cast<T2*>(inputs[4].data()),
                                    op->get_preprocess_collapse_repeated(),
                                    op->get_ctc_merge_repeated(),
                                    op->get_unique(),
-                                   outputs[0]->get_data_ptr<T1>());
+                                   static_cast<T1*>(outputs[0].data()));
 }
 }  // namespace ctc_loss_v4
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v4::CTCLoss>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[1]->get_element_type()) {
-    case ngraph::element::Type_t::i32:
-        ctc_loss_v4::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v4::CTCLoss>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[1].get_element_type()) {
+    case ov::element::i32:
+        ctc_loss_v4::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i64:
-        ctc_loss_v4::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+    case ov::element::i64:
+        ctc_loss_v4::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -66,50 +63,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v4::CTCLoss>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v4::CTCLoss>(std::shared_ptr<ngraph::Node> node,
-                                            const ngraph::HostTensorVector& outputs,
-                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v4::CTCLoss>(std::shared_ptr<ov::Node> node,
+                                        ov::TensorVector& outputs,
+                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v4::CTCLoss>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/cum_sum.cpp b/src/plugins/template/backend/ops/cum_sum.cpp
index a0d23e50563996..06dc952b233fe7 100644
--- a/src/plugins/template/backend/ops/cum_sum.cpp
+++ b/src/plugins/template/backend/ops/cum_sum.cpp
@@ -8,81 +8,78 @@
 // clang-format on
 
 namespace cum_sum_v0 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v0::CumSum>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::cumsum<T1, T2>(inputs[0]->get_data_ptr<T1>(),
-                                  inputs[1]->get_data_ptr<T2>(),
-                                  outputs[0]->get_data_ptr<T1>(),
-                                  inputs[0]->get_shape(),
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v0::CumSum>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::cumsum<T1, T2>(inputs[0].data<T1>(),
+                                  inputs[1].data<T2>(),
+                                  outputs[0].data<T1>(),
+                                  inputs[0].get_shape(),
                                   op->is_exclusive(),
                                   op->is_reverse());
 }
 }  // namespace cum_sum_v0
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::CumSum>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[1]->get_element_type()) {
-    case ngraph::element::Type_t::i64:
-        cum_sum_v0::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::CumSum>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[1].get_element_type()) {
+    case ov::element::i64:
+        cum_sum_v0::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
     default:
-        cum_sum_v0::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+        cum_sum_v0::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
     }
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::CumSum>(std::shared_ptr<ngraph::Node> node,
-                                           const ngraph::HostTensorVector& outputs,
-                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::CumSum>(std::shared_ptr<ov::Node> node,
+                                       ov::TensorVector& outputs,
+                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::CumSum>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/deformable_convolution.cpp b/src/plugins/template/backend/ops/deformable_convolution.cpp
index d4b96062b842f8..ea9eeb2ac13aed 100644
--- a/src/plugins/template/backend/ops/deformable_convolution.cpp
+++ b/src/plugins/template/backend/ops/deformable_convolution.cpp
@@ -6,244 +6,181 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::DeformableConvolution>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto in_data_ptr = inputs[0]->get_data_ptr<ET>();
-    const auto offset_data_ptr = inputs[1]->get_data_ptr<ET>();
-    const auto filter_data_ptr = inputs[2]->get_data_ptr<ET>();
-    auto out_data_ptr = outputs[0]->get_data_ptr<ET>();
-    const auto& out_shape = outputs[0]->get_shape();
-    const auto& in_shape = inputs[0]->get_shape();
-    const auto& offset_shape = inputs[1]->get_shape();
-    const auto& filter_shape = inputs[2]->get_shape();
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v8::DeformableConvolution>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    const auto in_data_ptr = inputs[0].data<ET>();
+    const auto offset_data_ptr = inputs[1].data<ET>();
+    const auto filter_data_ptr = inputs[2].data<ET>();
+    auto out_data_ptr = outputs[0].data<ET>();
+    const auto& out_shape = outputs[0].get_shape();
+    const auto& in_shape = inputs[0].get_shape();
+    const auto& offset_shape = inputs[1].get_shape();
+    const auto& filter_shape = inputs[2].get_shape();
     if (inputs.size() == 3) {
-        ov::reference::deformable_convolution<typename ngraph::element_type_traits<ET>::value_type>(
-            in_data_ptr,
-            offset_data_ptr,
-            filter_data_ptr,
-            out_data_ptr,
-            in_shape,
-            offset_shape,
-            filter_shape,
-            out_shape,
-            op->get_strides(),
-            op->get_dilations(),
-            op->get_pads_begin(),
-            op->get_pads_end(),
-            op->get_group(),
-            op->get_deformable_group(),
-            op->get_bilinear_interpolation_pad());
+        ov::reference::deformable_convolution<ET>(in_data_ptr,
+                                                  offset_data_ptr,
+                                                  filter_data_ptr,
+                                                  out_data_ptr,
+                                                  in_shape,
+                                                  offset_shape,
+                                                  filter_shape,
+                                                  out_shape,
+                                                  op->get_strides(),
+                                                  op->get_dilations(),
+                                                  op->get_pads_begin(),
+                                                  op->get_pads_end(),
+                                                  op->get_group(),
+                                                  op->get_deformable_group(),
+                                                  op->get_bilinear_interpolation_pad());
     } else {
-        const auto mask_data_ptr = inputs[3]->get_data_ptr<ET>();
-        const auto& mask_shape = inputs[3]->get_shape();
-        ov::reference::deformable_convolution<typename ngraph::element_type_traits<ET>::value_type>(
-            in_data_ptr,
-            offset_data_ptr,
-            filter_data_ptr,
-            mask_data_ptr,
-            out_data_ptr,
-            in_shape,
-            offset_shape,
-            filter_shape,
-            mask_shape,
-            out_shape,
-            op->get_strides(),
-            op->get_dilations(),
-            op->get_pads_begin(),
-            op->get_pads_end(),
-            op->get_group(),
-            op->get_deformable_group(),
-            op->get_bilinear_interpolation_pad());
+        const auto mask_data_ptr = inputs[3].data<ET>();
+        const auto& mask_shape = inputs[3].get_shape();
+        ov::reference::deformable_convolution<ET>(in_data_ptr,
+                                                  offset_data_ptr,
+                                                  filter_data_ptr,
+                                                  mask_data_ptr,
+                                                  out_data_ptr,
+                                                  in_shape,
+                                                  offset_shape,
+                                                  filter_shape,
+                                                  mask_shape,
+                                                  out_shape,
+                                                  op->get_strides(),
+                                                  op->get_dilations(),
+                                                  op->get_pads_begin(),
+                                                  op->get_pads_end(),
+                                                  op->get_group(),
+                                                  op->get_deformable_group(),
+                                                  op->get_bilinear_interpolation_pad());
     }
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::DeformableConvolution>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto in_data_ptr = inputs[0]->get_data_ptr<ET>();
-    const auto offset_data_ptr = inputs[1]->get_data_ptr<ET>();
-    const auto filter_data_ptr = inputs[2]->get_data_ptr<ET>();
-    auto out_data_ptr = outputs[0]->get_data_ptr<ET>();
-    const auto& out_shape = outputs[0]->get_shape();
-    const auto& in_shape = inputs[0]->get_shape();
-    const auto& offset_shape = inputs[1]->get_shape();
-    const auto& filter_shape = inputs[2]->get_shape();
-    ov::reference::deformable_convolution<typename ngraph::element_type_traits<ET>::value_type>(
-        in_data_ptr,
-        offset_data_ptr,
-        filter_data_ptr,
-        out_data_ptr,
-        in_shape,
-        offset_shape,
-        filter_shape,
-        out_shape,
-        op->get_strides(),
-        op->get_dilations(),
-        op->get_pads_begin(),
-        op->get_pads_end(),
-        op->get_group(),
-        op->get_deformable_group());
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v1::DeformableConvolution>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    const auto in_data_ptr = inputs[0].data<ET>();
+    const auto offset_data_ptr = inputs[1].data<ET>();
+    const auto filter_data_ptr = inputs[2].data<ET>();
+    auto out_data_ptr = outputs[0].data<ET>();
+    const auto& out_shape = outputs[0].get_shape();
+    const auto& in_shape = inputs[0].get_shape();
+    const auto& offset_shape = inputs[1].get_shape();
+    const auto& filter_shape = inputs[2].get_shape();
+    ov::reference::deformable_convolution<ET>(in_data_ptr,
+                                              offset_data_ptr,
+                                              filter_data_ptr,
+                                              out_data_ptr,
+                                              in_shape,
+                                              offset_shape,
+                                              filter_shape,
+                                              out_shape,
+                                              op->get_strides(),
+                                              op->get_dilations(),
+                                              op->get_pads_begin(),
+                                              op->get_pads_end(),
+                                              op->get_group(),
+                                              op->get_deformable_group());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::DeformableConvolution>(std::shared_ptr<ngraph::Node> node,
-                                                          const ngraph::HostTensorVector& outputs,
-                                                          const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::DeformableConvolution>(std::shared_ptr<ov::Node> node,
+                                                      ov::TensorVector& outputs,
+                                                      const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::DeformableConvolution>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::DeformableConvolution>(std::shared_ptr<ngraph::Node> node,
-                                                          const ngraph::HostTensorVector& outputs,
-                                                          const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::DeformableConvolution>(std::shared_ptr<ov::Node> node,
+                                                      ov::TensorVector& outputs,
+                                                      const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::DeformableConvolution>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::DeformableConvolution>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/deformable_psroi_pooling.cpp b/src/plugins/template/backend/ops/deformable_psroi_pooling.cpp
index 78a0ed95612b9e..70c24918edd975 100644
--- a/src/plugins/template/backend/ops/deformable_psroi_pooling.cpp
+++ b/src/plugins/template/backend/ops/deformable_psroi_pooling.cpp
@@ -6,28 +6,28 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::DeformablePSROIPooling>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    NGRAPH_CHECK(inputs.size() > 1 && inputs[1]->get_shape().size() == 2,
-                 "2D tensor must be provided as second input. ");
-    outputs[0]->set_shape({inputs[1]->get_shape()[0],
-                           static_cast<size_t>(op->get_output_dim()),
-                           static_cast<size_t>(op->get_group_size()),
-                           static_cast<size_t>(op->get_group_size())});
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v1::DeformablePSROIPooling>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    OPENVINO_ASSERT(inputs.size() > 1 && inputs[1].get_shape().size() == 2,
+                    "2D tensor must be provided as second input. ");
+    outputs[0].set_shape({inputs[1].get_shape()[0],
+                          static_cast<size_t>(op->get_output_dim()),
+                          static_cast<size_t>(op->get_group_size()),
+                          static_cast<size_t>(op->get_group_size())});
 
     const bool has_offset_intput = inputs.size() == 3;
     if (has_offset_intput) {
-        ov::reference::deformable_psroi_pooling<T>(inputs[0]->get_data_ptr<T>(),
-                                                   inputs[0]->get_shape(),
-                                                   inputs[1]->get_data_ptr<T>(),
-                                                   inputs[1]->get_shape(),
-                                                   inputs[2]->get_data_ptr<T>(),
-                                                   inputs[2]->get_shape(),
-                                                   outputs[0]->get_data_ptr<T>(),
-                                                   outputs[0]->get_shape(),
+        ov::reference::deformable_psroi_pooling<T>(inputs[0].data<T>(),
+                                                   inputs[0].get_shape(),
+                                                   inputs[1].data<T>(),
+                                                   inputs[1].get_shape(),
+                                                   inputs[2].data<T>(),
+                                                   inputs[2].get_shape(),
+                                                   outputs[0].data<T>(),
+                                                   outputs[0].get_shape(),
                                                    op->get_mode(),
                                                    op->get_spatial_scale(),
                                                    op->get_spatial_bins_x(),
@@ -35,14 +35,14 @@ bool evaluate(const std::shared_ptr<ngraph::op::v1::DeformablePSROIPooling>& op,
                                                    op->get_trans_std(),
                                                    op->get_part_size());
     } else {
-        ov::reference::deformable_psroi_pooling<T>(inputs[0]->get_data_ptr<T>(),
-                                                   inputs[0]->get_shape(),
-                                                   inputs[1]->get_data_ptr<T>(),
-                                                   inputs[1]->get_shape(),
+        ov::reference::deformable_psroi_pooling<T>(inputs[0].data<T>(),
+                                                   inputs[0].get_shape(),
+                                                   inputs[1].data<T>(),
+                                                   inputs[1].get_shape(),
                                                    nullptr,
-                                                   ngraph::Shape(),
-                                                   outputs[0]->get_data_ptr<T>(),
-                                                   outputs[0]->get_shape(),
+                                                   ov::Shape(),
+                                                   outputs[0].data<T>(),
+                                                   outputs[0].get_shape(),
                                                    op->get_mode(),
                                                    op->get_spatial_scale(),
                                                    op->get_spatial_bins_x(),
@@ -54,80 +54,49 @@ bool evaluate(const std::shared_ptr<ngraph::op::v1::DeformablePSROIPooling>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::DeformablePSROIPooling>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::DeformablePSROIPooling>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::DeformablePSROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::DeformablePSROIPooling>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/detection_output.cpp b/src/plugins/template/backend/ops/detection_output.cpp
index 42ea79e14ab392..bc750cdffa339d 100644
--- a/src/plugins/template/backend/ops/detection_output.cpp
+++ b/src/plugins/template/backend/ops/detection_output.cpp
@@ -6,60 +6,60 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::DetectionOutput>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::DetectionOutput>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
     ov::reference::referenceDetectionOutput<T> refDetOut(op->get_attrs(),
                                                          op->get_input_shape(0),
                                                          op->get_input_shape(1),
                                                          op->get_input_shape(2),
                                                          op->get_output_shape(0));
     if (op->get_input_size() == 3) {
-        refDetOut.run(inputs[0]->get_data_ptr<const T>(),
-                      inputs[1]->get_data_ptr<const T>(),
-                      inputs[2]->get_data_ptr<const T>(),
+        refDetOut.run(inputs[0].data<const T>(),
+                      inputs[1].data<const T>(),
+                      inputs[2].data<const T>(),
                       nullptr,
                       nullptr,
-                      outputs[0]->get_data_ptr<T>());
+                      outputs[0].data<T>());
     } else if (op->get_input_size() == 5) {
-        refDetOut.run(inputs[0]->get_data_ptr<const T>(),
-                      inputs[1]->get_data_ptr<const T>(),
-                      inputs[2]->get_data_ptr<const T>(),
-                      inputs[3]->get_data_ptr<const T>(),
-                      inputs[4]->get_data_ptr<const T>(),
-                      outputs[0]->get_data_ptr<T>());
+        refDetOut.run(inputs[0].data<const T>(),
+                      inputs[1].data<const T>(),
+                      inputs[2].data<const T>(),
+                      inputs[3].data<const T>(),
+                      inputs[4].data<const T>(),
+                      outputs[0].data<T>());
     } else {
         OPENVINO_THROW("DetectionOutput layer supports only 3 or 5 inputs");
     }
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::DetectionOutput>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v8::DetectionOutput>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
     ov::reference::referenceDetectionOutput<T> refDetOut(op->get_attrs(),
                                                          op->get_input_shape(0),
                                                          op->get_input_shape(1),
                                                          op->get_input_shape(2),
                                                          op->get_output_shape(0));
     if (op->get_input_size() == 3) {
-        refDetOut.run(inputs[0]->get_data_ptr<const T>(),
-                      inputs[1]->get_data_ptr<const T>(),
-                      inputs[2]->get_data_ptr<const T>(),
+        refDetOut.run(inputs[0].data<const T>(),
+                      inputs[1].data<const T>(),
+                      inputs[2].data<const T>(),
                       nullptr,
                       nullptr,
-                      outputs[0]->get_data_ptr<T>());
+                      outputs[0].data<T>());
     } else if (op->get_input_size() == 5) {
-        refDetOut.run(inputs[0]->get_data_ptr<const T>(),
-                      inputs[1]->get_data_ptr<const T>(),
-                      inputs[2]->get_data_ptr<const T>(),
-                      inputs[3]->get_data_ptr<const T>(),
-                      inputs[4]->get_data_ptr<const T>(),
-                      outputs[0]->get_data_ptr<T>());
+        refDetOut.run(inputs[0].data<const T>(),
+                      inputs[1].data<const T>(),
+                      inputs[2].data<const T>(),
+                      inputs[3].data<const T>(),
+                      inputs[4].data<const T>(),
+                      outputs[0].data<T>());
     } else {
         OPENVINO_THROW("DetectionOutput layer supports only 3 or 5 inputs");
     }
@@ -67,159 +67,93 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::DetectionOutput>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::DetectionOutput>(std::shared_ptr<ngraph::Node> node,
-                                                    const ngraph::HostTensorVector& outputs,
-                                                    const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::DetectionOutput>(std::shared_ptr<ov::Node> node,
+                                                ov::TensorVector& outputs,
+                                                const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::DetectionOutput>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::DetectionOutput>(std::shared_ptr<ngraph::Node> node,
-                                                    const ngraph::HostTensorVector& outputs,
-                                                    const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::DetectionOutput>(std::shared_ptr<ov::Node> node,
+                                                ov::TensorVector& outputs,
+                                                const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::DetectionOutput>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::DetectionOutput>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/einsum.cpp b/src/plugins/template/backend/ops/einsum.cpp
index 70ac9c66be98a3..c744275de2778e 100644
--- a/src/plugins/template/backend/ops/einsum.cpp
+++ b/src/plugins/template/backend/ops/einsum.cpp
@@ -6,58 +6,56 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v7::Einsum>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v7::Einsum>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     const auto equation = op->get_equation();
     ov::reference::einsum(outputs, inputs, equation);
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v7::Einsum>(std::shared_ptr<ngraph::Node> node,
-                                           const ngraph::HostTensorVector& outputs,
-                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v7::Einsum>(std::shared_ptr<ov::Node> node,
+                                       ov::TensorVector& outputs,
+                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v7::Einsum>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
diff --git a/src/plugins/template/backend/ops/elu.cpp b/src/plugins/template/backend/ops/elu.cpp
index 3da9d8f83621fe..45b23f6ff579c5 100644
--- a/src/plugins/template/backend/ops/elu.cpp
+++ b/src/plugins/template/backend/ops/elu.cpp
@@ -6,61 +6,58 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Elu>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::elu<T>(inputs[0]->get_data_ptr<T>(),
-                          outputs[0]->get_data_ptr<T>(),
-                          ngraph::shape_size(inputs[0]->get_shape()),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Elu>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::elu<T>(inputs[0].data<T>(),
+                          outputs[0].data<T>(),
+                          ov::shape_size(inputs[0].get_shape()),
                           op->get_alpha());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Elu>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Elu>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Elu>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/embedding_bag_offsets_sum.cpp b/src/plugins/template/backend/ops/embedding_bag_offsets_sum.cpp
index a58340a56b112f..a391a502b8b885 100644
--- a/src/plugins/template/backend/ops/embedding_bag_offsets_sum.cpp
+++ b/src/plugins/template/backend/ops/embedding_bag_offsets_sum.cpp
@@ -7,33 +7,33 @@
 #include "evaluate_node.hpp"
 
 namespace embedding_bag_offsets_sum_v3 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::embeddingBagOffsetsSum<T1, T2>(inputs[0]->get_data_ptr<T1>(),
-                                                  inputs[1]->get_data_ptr<T2>(),
-                                                  inputs[2]->get_data_ptr<T2>(),
-                                                  inputs.size() > 3 ? inputs[3]->get_data_ptr<T2>() : nullptr,
-                                                  inputs.size() > 4 ? inputs[4]->get_data_ptr<T1>() : nullptr,
-                                                  outputs[0]->get_data_ptr<T1>(),
-                                                  ngraph::shape_size(inputs[1]->get_shape()),
-                                                  outputs[0]->get_shape());
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v3::EmbeddingBagOffsetsSum>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::embeddingBagOffsetsSum<T1, T2>(inputs[0].data<T1>(),
+                                                  inputs[1].data<T2>(),
+                                                  inputs[2].data<T2>(),
+                                                  inputs.size() > 3 ? inputs[3].data<T2>() : nullptr,
+                                                  inputs.size() > 4 ? inputs[4].data<T1>() : nullptr,
+                                                  outputs[0].data<T1>(),
+                                                  ov::shape_size(inputs[1].get_shape()),
+                                                  outputs[0].get_shape());
 }
 }  // namespace embedding_bag_offsets_sum_v3
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[1]->get_element_type()) {
-    case ngraph::element::Type_t::i32:
-        embedding_bag_offsets_sum_v3::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v3::EmbeddingBagOffsetsSum>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[1].get_element_type()) {
+    case ov::element::i32:
+        embedding_bag_offsets_sum_v3::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i64:
-        embedding_bag_offsets_sum_v3::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+    case ov::element::i64:
+        embedding_bag_offsets_sum_v3::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -42,80 +42,49 @@ bool evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::EmbeddingBagOffsetsSum>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::EmbeddingBagOffsetsSum>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagOffsetsSum>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v3::EmbeddingBagOffsetsSum>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/embedding_bag_packed_sum.cpp b/src/plugins/template/backend/ops/embedding_bag_packed_sum.cpp
index 4a9e764bc8d86d..8ff618230b8b54 100644
--- a/src/plugins/template/backend/ops/embedding_bag_packed_sum.cpp
+++ b/src/plugins/template/backend/ops/embedding_bag_packed_sum.cpp
@@ -2,37 +2,36 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/embedding_bag_packed_sum.hpp"
-// clang-format on
+
+#include "evaluate_node.hpp"
 
 namespace embedding_bag_packed_sum_v3 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingBagPackedSum>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::embeddingBagPackedSum<T1, T2>(inputs[0]->get_data_ptr<T1>(),
-                                                 inputs[1]->get_data_ptr<T2>(),
-                                                 inputs.size() > 2 ? inputs[2]->get_data_ptr<T1>() : nullptr,
-                                                 outputs[0]->get_data_ptr<T1>(),
-                                                 inputs[1]->get_shape(),
-                                                 outputs[0]->get_shape());
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v3::EmbeddingBagPackedSum>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::embeddingBagPackedSum<T1, T2>(inputs[0].data<T1>(),
+                                                 inputs[1].data<T2>(),
+                                                 inputs.size() > 2 ? inputs[2].data<T1>() : nullptr,
+                                                 outputs[0].data<T1>(),
+                                                 inputs[1].get_shape(),
+                                                 outputs[0].get_shape());
 }
 }  // namespace embedding_bag_packed_sum_v3
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingBagPackedSum>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[1]->get_element_type()) {
-    case ngraph::element::Type_t::i32:
-        embedding_bag_packed_sum_v3::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v3::EmbeddingBagPackedSum>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[1].get_element_type()) {
+    case ov::element::i32:
+        embedding_bag_packed_sum_v3::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i64:
-        embedding_bag_packed_sum_v3::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+    case ov::element::i64:
+        embedding_bag_packed_sum_v3::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -42,80 +41,49 @@ bool evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingBagPackedSum>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::EmbeddingBagPackedSum>(std::shared_ptr<ngraph::Node> node,
-                                                          const ngraph::HostTensorVector& outputs,
-                                                          const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::EmbeddingBagPackedSum>(std::shared_ptr<ov::Node> node,
+                                                      ov::TensorVector& outputs,
+                                                      const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingBagPackedSum>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v3::EmbeddingBagPackedSum>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/embedding_segments_sum.cpp b/src/plugins/template/backend/ops/embedding_segments_sum.cpp
index 1d67090fd9c8f5..8307406e7b5373 100644
--- a/src/plugins/template/backend/ops/embedding_segments_sum.cpp
+++ b/src/plugins/template/backend/ops/embedding_segments_sum.cpp
@@ -7,34 +7,34 @@
 #include "evaluate_node.hpp"
 
 namespace embedding_offsets_sum_v3 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingSegmentsSum>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::embeddingSegmentsSum<T1, T2>(inputs[0]->get_data_ptr<T1>(),
-                                                inputs[1]->get_data_ptr<T2>(),
-                                                inputs[2]->get_data_ptr<T2>(),
-                                                inputs.size() > 4 ? inputs[4]->get_data_ptr<T2>() : nullptr,
-                                                inputs.size() > 5 ? inputs[5]->get_data_ptr<T1>() : nullptr,
-                                                outputs[0]->get_data_ptr<T1>(),
-                                                inputs[0]->get_shape(),
-                                                inputs[1]->get_shape(),
-                                                outputs[0]->get_shape());
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v3::EmbeddingSegmentsSum>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::embeddingSegmentsSum<T1, T2>(inputs[0].data<T1>(),
+                                                inputs[1].data<T2>(),
+                                                inputs[2].data<T2>(),
+                                                inputs.size() > 4 ? inputs[4].data<T2>() : nullptr,
+                                                inputs.size() > 5 ? inputs[5].data<T1>() : nullptr,
+                                                outputs[0].data<T1>(),
+                                                inputs[0].get_shape(),
+                                                inputs[1].get_shape(),
+                                                outputs[0].get_shape());
 }
 }  // namespace embedding_offsets_sum_v3
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingSegmentsSum>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[1]->get_element_type()) {
-    case ngraph::element::Type_t::i32:
-        embedding_offsets_sum_v3::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v3::EmbeddingSegmentsSum>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[1].get_element_type()) {
+    case ov::element::i32:
+        embedding_offsets_sum_v3::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i64:
-        embedding_offsets_sum_v3::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+    case ov::element::i64:
+        embedding_offsets_sum_v3::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -43,80 +43,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v3::EmbeddingSegmentsSum>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::EmbeddingSegmentsSum>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::EmbeddingSegmentsSum>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::EmbeddingSegmentsSum>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v3::EmbeddingSegmentsSum>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/equal.cpp b/src/plugins/template/backend/ops/equal.cpp
index a6773c15c8a072..70402f9feb8c7a 100644
--- a/src/plugins/template/backend/ops/equal.cpp
+++ b/src/plugins/template/backend/ops/equal.cpp
@@ -5,73 +5,64 @@
 #include "openvino/reference/equal.hpp"
 
 #include "evaluate_node.hpp"
+#include "openvino/core/type/element_type.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::Equal>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto in0_data_ptr = inputs[0]->get_data_ptr<ET>();
-    const auto in1_data_ptr = inputs[1]->get_data_ptr<ET>();
-    const auto out_data_ptr = outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>();
-    const auto in0_shape = inputs[0]->get_shape();
-    const auto in1_shape = inputs[1]->get_shape();
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v1::Equal>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    using BT = typename ov::element_type_traits<ov::element::boolean>::value_type;
+    const auto in0_data_ptr = inputs[0].data<ET>();
+    const auto in1_data_ptr = inputs[1].data<ET>();
+    const auto out_data_ptr = outputs[0].data<BT>();
+    const auto in0_shape = inputs[0].get_shape();
+    const auto in1_shape = inputs[1].get_shape();
     const auto broadcast_spec = op->get_autob();
-    ov::reference::equal<typename ngraph::element_type_traits<ET>::value_type,
-                         typename ngraph::element_type_traits<ngraph::element::Type_t::boolean>::value_type>(
-        in0_data_ptr,
-        in1_data_ptr,
-        out_data_ptr,
-        in0_shape,
-        in1_shape,
-        broadcast_spec);
+    ov::reference::equal<ET, BT>(in0_data_ptr, in1_data_ptr, out_data_ptr, in0_shape, in1_shape, broadcast_spec);
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::Equal>(std::shared_ptr<ngraph::Node> node,
-                                          const ngraph::HostTensorVector& outputs,
-                                          const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::Equal>(std::shared_ptr<ov::Node> node,
+                                      ov::TensorVector& outputs,
+                                      const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::Equal>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::Equal>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/evaluate_node.hpp b/src/plugins/template/backend/ops/evaluate_node.hpp
index 8f5ac4892be458..58484f0a389de0 100644
--- a/src/plugins/template/backend/ops/evaluate_node.hpp
+++ b/src/plugins/template/backend/ops/evaluate_node.hpp
@@ -3,60 +3,56 @@
 //
 
 #pragma once
-#include "ngraph/ops.hpp"
+
 #include "openvino/core/except.hpp"
 #include "openvino/op/ops.hpp"
+#include "openvino/runtime/tensor.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(std::shared_ptr<ngraph::Node> op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(std::shared_ptr<ov::Node> op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
     return false;
 }
 
 template <typename T>
-bool evaluate_node(std::shared_ptr<ngraph::Node> node,
-                   const ngraph::HostTensorVector& outputs,
-                   const ngraph::HostTensorVector& inputs) {
+bool evaluate_node(std::shared_ptr<ov::Node> node, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<T>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::boolean:
+        return evaluate<ov::element::Type_t::boolean>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::bf16:
+        return evaluate<ov::element::Type_t::bf16>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::f16:
+        return evaluate<ov::element::Type_t::f16>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::f64:
+        return evaluate<ov::element::Type_t::f64>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::f32:
+        return evaluate<ov::element::Type_t::f32>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::i4:
+        return evaluate<ov::element::Type_t::i4>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::i8:
+        return evaluate<ov::element::Type_t::i8>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::i16:
+        return evaluate<ov::element::Type_t::i16>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::i32:
+        return evaluate<ov::element::Type_t::i32>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::i64:
+        return evaluate<ov::element::Type_t::i64>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::u1:
+        return evaluate<ov::element::Type_t::u1>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::u4:
+        return evaluate<ov::element::Type_t::u4>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::u8:
+        return evaluate<ov::element::Type_t::u8>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::u16:
+        return evaluate<ov::element::Type_t::u16>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::u32:
+        return evaluate<ov::element::Type_t::u32>(ov::as_type_ptr<T>(node), outputs, inputs);
+    case ov::element::Type_t::u64:
+        return evaluate<ov::element::Type_t::u64>(ov::as_type_ptr<T>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/exp.cpp b/src/plugins/template/backend/ops/exp.cpp
index 4d3fd3402b5d18..1f78c498ee1b84 100644
--- a/src/plugins/template/backend/ops/exp.cpp
+++ b/src/plugins/template/backend/ops/exp.cpp
@@ -6,60 +6,55 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Exp>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::exp<T>(inputs[0]->get_data_ptr<T>(),
-                          outputs[0]->get_data_ptr<T>(),
-                          ngraph::shape_size(inputs[0]->get_shape()));
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Exp>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::exp<T>(inputs[0].data<T>(), outputs[0].data<T>(), ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Exp>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Exp>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Exp>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/experimental_detectron_detection_output.cpp b/src/plugins/template/backend/ops/experimental_detectron_detection_output.cpp
index 9c6199637c8208..4eafe3f5cdd4b4 100644
--- a/src/plugins/template/backend/ops/experimental_detectron_detection_output.cpp
+++ b/src/plugins/template/backend/ops/experimental_detectron_detection_output.cpp
@@ -7,34 +7,31 @@
 #include "evaluate_node.hpp"
 #include "evaluates_map.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     const auto attrs = op->get_attrs();
     size_t rois_num = attrs.max_detections_per_image;
 
-    const ngraph::Shape output_boxes_shape = ngraph::Shape{rois_num, 4};
-    const ngraph::Shape output_classes_shape = ngraph::Shape{rois_num};
-    const ngraph::Shape output_scores_shape = ngraph::Shape{rois_num};
+    const ov::Shape output_boxes_shape = ov::Shape{rois_num, 4};
+    const ov::Shape output_classes_shape = ov::Shape{rois_num};
+    const ov::Shape output_scores_shape = ov::Shape{rois_num};
 
     const auto output_type = op->get_input_element_type(0);
 
-    const auto boxes_data = get_floats(inputs[0], inputs[0]->get_shape());
-    const auto input_deltas_data = get_floats(inputs[1], inputs[1]->get_shape());
-    const auto input_scores_data = get_floats(inputs[2], inputs[2]->get_shape());
-    const auto input_im_info_data = get_floats(inputs[3], inputs[3]->get_shape());
+    const auto boxes_data = get_floats(inputs[0], inputs[0].get_shape());
+    const auto input_deltas_data = get_floats(inputs[1], inputs[1].get_shape());
+    const auto input_scores_data = get_floats(inputs[2], inputs[2].get_shape());
+    const auto input_im_info_data = get_floats(inputs[3], inputs[3].get_shape());
 
-    std::vector<float> output_boxes(ngraph::shape_size(output_boxes_shape));
-    std::vector<int32_t> output_classes(ngraph::shape_size(output_classes_shape));
-    std::vector<float> output_scores(ngraph::shape_size(output_scores_shape));
+    std::vector<float> output_boxes(ov::shape_size(output_boxes_shape));
+    std::vector<int32_t> output_classes(ov::shape_size(output_classes_shape));
+    std::vector<float> output_scores(ov::shape_size(output_scores_shape));
 
-    outputs[0]->set_element_type(output_type);
-    outputs[0]->set_shape(output_boxes_shape);
-    outputs[1]->set_element_type(ngraph::element::Type_t::i32);
-    outputs[1]->set_shape(output_classes_shape);
-    outputs[2]->set_element_type(output_type);
-    outputs[2]->set_shape(output_scores_shape);
+    outputs[0].set_shape(output_boxes_shape);
+    outputs[1].set_shape(output_classes_shape);
+    outputs[2].set_shape(output_scores_shape);
 
     ov::reference::experimental_detectron_detection_output(boxes_data.data(),
                                                            input_deltas_data.data(),
@@ -45,9 +42,9 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronDetecti
                                                            output_scores.data(),
                                                            output_classes.data());
 
-    ov::reference::experimental_detectron_detection_output_postprocessing(outputs[0]->get_data_ptr(),
-                                                                          outputs[1]->get_data_ptr(),
-                                                                          outputs[2]->get_data_ptr(),
+    ov::reference::experimental_detectron_detection_output_postprocessing(outputs[0].data(),
+                                                                          outputs[1].data(),
+                                                                          outputs[2].data(),
                                                                           output_type,
                                                                           output_boxes,
                                                                           output_classes,
@@ -60,96 +57,79 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronDetecti
 }
 
 template <>
-bool evaluate_node<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(std::shared_ptr<ngraph::Node> node,
-                                                                         const ngraph::HostTensorVector& outputs,
-                                                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v6::ExperimentalDetectronDetectionOutput>(std::shared_ptr<ov::Node> node,
+                                                                     ov::TensorVector& outputs,
+                                                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(node),
-            outputs,
-            inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                           outputs,
+                                           inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronDetectionOutput>(node),
+                                          outputs,
+                                          inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/experimental_detectron_prior_grid_generator.cpp b/src/plugins/template/backend/ops/experimental_detectron_prior_grid_generator.cpp
index cff1eb493222bc..6fa9c91c5ae106 100644
--- a/src/plugins/template/backend/ops/experimental_detectron_prior_grid_generator.cpp
+++ b/src/plugins/template/backend/ops/experimental_detectron_prior_grid_generator.cpp
@@ -8,7 +8,7 @@
 
 namespace experimental_prior_grid {
 struct InfoForEDPriorGrid {
-    ngraph::Shape output_shape;
+    ov::Shape output_shape;
     int64_t grid_h;
     int64_t grid_w;
     float stride_h;
@@ -18,20 +18,17 @@ struct InfoForEDPriorGrid {
 constexpr size_t priors_port = 0;
 constexpr size_t feature_map_port = 1;
 
-ngraph::PartialShape infer_output_shape(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs, bool flatten) {
-    ngraph::PartialShape out_shape = {ngraph::Dimension::dynamic(),
-                                      ngraph::Dimension::dynamic(),
-                                      ngraph::Dimension::dynamic(),
-                                      4};
+ov::PartialShape infer_output_shape(const ov::TensorVector& inputs, bool flatten) {
+    ov::PartialShape out_shape = {ov::Dimension::dynamic(), ov::Dimension::dynamic(), ov::Dimension::dynamic(), 4};
 
     if (flatten) {
-        out_shape = ngraph::PartialShape{ngraph::Dimension::dynamic(), 4};
+        out_shape = ov::PartialShape{ov::Dimension::dynamic(), 4};
     }
 
-    const auto priors_shape = inputs[priors_port]->get_partial_shape();
-    const auto feature_map_shape = inputs[feature_map_port]->get_partial_shape();
+    const auto priors_shape = inputs[priors_port].get_shape();
+    const auto feature_map_shape = inputs[feature_map_port].get_shape();
 
-    if (priors_shape.rank().is_dynamic() || feature_map_shape.rank().is_dynamic()) {
+    if (!ov::shape_size(priors_shape) || !ov::shape_size(feature_map_shape)) {
         return out_shape;
     }
 
@@ -40,17 +37,21 @@ ngraph::PartialShape infer_output_shape(const std::vector<std::shared_ptr<ngraph
     auto featmap_width = feature_map_shape[3];
 
     if (flatten) {
-        out_shape = ngraph::PartialShape{featmap_height * featmap_width * num_priors, 4};
+        out_shape =
+            ov::PartialShape{ov::Dimension(static_cast<int64_t>(featmap_height * featmap_width * num_priors)), 4};
     } else {
-        out_shape = ngraph::PartialShape{featmap_height, featmap_width, num_priors, 4};
+        out_shape = ov::PartialShape{ov::Dimension(static_cast<int64_t>(featmap_height)),
+                                     ov::Dimension(static_cast<int64_t>(featmap_width)),
+                                     ov::Dimension(static_cast<int64_t>(num_priors)),
+                                     4};
     }
 
     return out_shape;
 }
 
 InfoForEDPriorGrid get_info_for_ed_prior_grid_eval(
-    const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>& prior_grid,
-    const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+    const std::shared_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>& prior_grid,
+    const ov::TensorVector& inputs) {
     InfoForEDPriorGrid result;
 
     auto attrs = prior_grid->get_attrs();
@@ -67,19 +68,19 @@ InfoForEDPriorGrid get_info_for_ed_prior_grid_eval(
 }
 }  // namespace experimental_prior_grid
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = experimental_prior_grid::get_info_for_ed_prior_grid_eval(op, inputs);
 
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    outputs[0]->set_shape(info.output_shape);
-    ov::reference::experimental_detectron_prior_grid_generator<T>(inputs[0]->get_data_ptr<const T>(),
-                                                                  inputs[0]->get_shape(),
-                                                                  inputs[1]->get_shape(),
-                                                                  inputs[2]->get_shape(),
-                                                                  outputs[0]->get_data_ptr<T>(),
+    using T = typename ov::element_type_traits<ET>::value_type;
+    outputs[0].set_shape(info.output_shape);
+    ov::reference::experimental_detectron_prior_grid_generator<T>(inputs[0].data<const T>(),
+                                                                  inputs[0].get_shape(),
+                                                                  inputs[1].get_shape(),
+                                                                  inputs[2].get_shape(),
+                                                                  outputs[0].data<T>(),
                                                                   info.grid_h,
                                                                   info.grid_w,
                                                                   info.stride_h,
@@ -89,96 +90,80 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronPriorGr
 }
 
 template <>
-bool evaluate_node<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(std::shared_ptr<ngraph::Node> node,
-                                                                            const ngraph::HostTensorVector& outputs,
-                                                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(std::shared_ptr<ov::Node> node,
+                                                                        ov::TensorVector& outputs,
+                                                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
-            outputs,
-            inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+            outputs,
+            inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                           outputs,
+                                           inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(node),
+                                          outputs,
+                                          inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/experimental_detectron_proposal_single_image.cpp b/src/plugins/template/backend/ops/experimental_detectron_proposal_single_image.cpp
index df064504a28126..9a933181ec7a90 100644
--- a/src/plugins/template/backend/ops/experimental_detectron_proposal_single_image.cpp
+++ b/src/plugins/template/backend/ops/experimental_detectron_proposal_single_image.cpp
@@ -7,10 +7,10 @@
 #include "evaluate_node.hpp"
 #include "evaluates_map.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     const auto attrs = op->get_attrs();
 
     size_t post_nms_count = 0;
@@ -22,28 +22,26 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronGenerat
         post_nms_count = static_cast<size_t>(attrs.post_nms_count);
     }
 
-    const ngraph::Shape output_rois_shape = ngraph::Shape{post_nms_count, 4};
-    const ngraph::Shape output_scores_shape = ngraph::Shape{post_nms_count};
+    const ov::Shape output_rois_shape = ov::Shape{post_nms_count, 4};
+    const ov::Shape output_scores_shape = ov::Shape{post_nms_count};
 
     const auto output_type = op->get_input_element_type(0);
 
-    const auto im_info_shape = inputs[0]->get_shape();
-    const auto anchors_shape = inputs[1]->get_shape();
-    const auto deltas_shape = inputs[2]->get_shape();
-    const auto scores_shape = inputs[3]->get_shape();
+    const auto im_info_shape = inputs[0].get_shape();
+    const auto anchors_shape = inputs[1].get_shape();
+    const auto deltas_shape = inputs[2].get_shape();
+    const auto scores_shape = inputs[3].get_shape();
 
     const auto im_info_data = get_floats(inputs[0], im_info_shape);
     const auto anchors_data = get_floats(inputs[1], anchors_shape);
     const auto deltas_data = get_floats(inputs[2], deltas_shape);
     const auto scores_data = get_floats(inputs[3], scores_shape);
 
-    std::vector<float> output_rois(ngraph::shape_size(output_rois_shape));
-    std::vector<float> output_scores(ngraph::shape_size(output_scores_shape));
+    std::vector<float> output_rois(ov::shape_size(output_rois_shape));
+    std::vector<float> output_scores(ov::shape_size(output_scores_shape));
 
-    outputs[0]->set_element_type(output_type);
-    outputs[0]->set_shape(output_rois_shape);
-    outputs[1]->set_element_type(output_type);
-    outputs[1]->set_shape(output_scores_shape);
+    outputs[0].set_shape(output_rois_shape);
+    outputs[1].set_shape(output_scores_shape);
 
     ov::reference::experimental_detectron_proposals_single_image(im_info_data.data(),
                                                                  anchors_data.data(),
@@ -56,8 +54,8 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronGenerat
                                                                  scores_shape,
                                                                  output_rois.data(),
                                                                  output_scores.data());
-    ov::reference::experimental_detectron_proposals_single_image_postprocessing(outputs[0]->get_data_ptr(),
-                                                                                outputs[1]->get_data_ptr(),
+    ov::reference::experimental_detectron_proposals_single_image_postprocessing(outputs[0].data(),
+                                                                                outputs[1].data(),
                                                                                 output_type,
                                                                                 output_rois,
                                                                                 output_scores,
@@ -68,97 +66,95 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronGenerat
 }
 
 template <>
-bool evaluate_node<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(
-    std::shared_ptr<ngraph::Node> node,
-    const ngraph::HostTensorVector& outputs,
-    const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(std::shared_ptr<ov::Node> node,
+                                                                                  ov::TensorVector& outputs,
+                                                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(node),
             outputs,
             inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/experimental_detectron_roi_feature_extractor.cpp b/src/plugins/template/backend/ops/experimental_detectron_roi_feature_extractor.cpp
index 4aaac9f381522e..847eb7f62e8b89 100644
--- a/src/plugins/template/backend/ops/experimental_detectron_roi_feature_extractor.cpp
+++ b/src/plugins/template/backend/ops/experimental_detectron_roi_feature_extractor.cpp
@@ -2,26 +2,25 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluates_map.hpp"
-#include "evaluate_node.hpp"
 #include "openvino/reference/experimental_detectron_roi_feature_extractor.hpp"
-// clang-format on
+
+#include "evaluate_node.hpp"
+#include "evaluates_map.hpp"
 
 namespace experimental_roi_feature {
 struct InfoForEDROIFeature {
-    ngraph::Shape output_rois_features_shape;
-    ngraph::Shape output_rois_shape;
+    ov::Shape output_rois_features_shape;
+    ov::Shape output_rois_shape;
 };
 
 InfoForEDROIFeature get_info_for_ed_roi_feature(
-    const std::vector<ngraph::Shape> input_shapes,
-    const ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor::Attributes& attrs) {
+    const std::vector<ov::Shape> input_shapes,
+    const ov::op::v6::ExperimentalDetectronROIFeatureExtractor::Attributes& attrs) {
     InfoForEDROIFeature result;
 
     size_t output_size = static_cast<size_t>(attrs.output_size);
-    auto out_shape = ngraph::Shape{0, 0, output_size, output_size};
-    auto out_rois_shape = ngraph::Shape{0, 4};
+    auto out_shape = ov::Shape{0, 0, output_size, output_size};
+    auto out_rois_shape = ov::Shape{0, 4};
 
     auto rois_shape = input_shapes[0];
 
@@ -37,16 +36,16 @@ InfoForEDROIFeature get_info_for_ed_roi_feature(
 }
 }  // namespace experimental_roi_feature
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     const auto attrs = op->get_attrs();
 
     std::vector<std::vector<float>> input_data;
-    std::vector<ngraph::Shape> input_shapes;
+    std::vector<ov::Shape> input_shapes;
     for (const auto& input : inputs) {
-        const auto current_shape = input->get_shape();
+        const auto current_shape = input.get_shape();
         input_data.push_back(get_floats(input, current_shape));
         input_shapes.push_back(current_shape);
     }
@@ -57,13 +56,11 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronROIFeat
 
     const auto output_type = op->get_input_element_type(0);
 
-    outputs[0]->set_element_type(output_type);
-    outputs[0]->set_shape(output_rois_features_shape);
-    outputs[1]->set_element_type(output_type);
-    outputs[1]->set_shape(output_rois_shape);
+    outputs[0].set_shape(output_rois_features_shape);
+    outputs[1].set_shape(output_rois_shape);
 
-    std::vector<float> output_rois_features(ngraph::shape_size(output_rois_features_shape));
-    std::vector<float> output_rois(ngraph::shape_size(output_rois_shape));
+    std::vector<float> output_rois_features(ov::shape_size(output_rois_features_shape));
+    std::vector<float> output_rois(ov::shape_size(output_rois_shape));
 
     ov::reference::experimental_detectron_roi_feature_extractor(input_data,
                                                                 input_shapes,
@@ -71,8 +68,8 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronROIFeat
                                                                 output_rois_features.data(),
                                                                 output_rois.data());
 
-    ov::reference::experimental_detectron_roi_feature_extractor_postprocessing(outputs[0]->get_data_ptr(),
-                                                                               outputs[1]->get_data_ptr(),
+    ov::reference::experimental_detectron_roi_feature_extractor_postprocessing(outputs[0].data(),
+                                                                               outputs[1].data(),
                                                                                output_type,
                                                                                output_rois_features,
                                                                                output_rois,
@@ -83,96 +80,80 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronROIFeat
 }
 
 template <>
-bool evaluate_node<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(std::shared_ptr<ngraph::Node> node,
-                                                                             const ngraph::HostTensorVector& outputs,
-                                                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(std::shared_ptr<ov::Node> node,
+                                                                         ov::TensorVector& outputs,
+                                                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
-            outputs,
-            inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(
+            ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+            outputs,
+            inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                           outputs,
+                                           inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(node),
+                                          outputs,
+                                          inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/experimental_detectron_topk_rois.cpp b/src/plugins/template/backend/ops/experimental_detectron_topk_rois.cpp
index cd03df2f38ccb4..ea05aea182f117 100644
--- a/src/plugins/template/backend/ops/experimental_detectron_topk_rois.cpp
+++ b/src/plugins/template/backend/ops/experimental_detectron_topk_rois.cpp
@@ -6,113 +6,96 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
     size_t max_rois = op->get_max_rois();
-    outputs[0]->set_shape(ngraph::Shape{max_rois, 4});
-    ov::reference::experimental_detectron_topk_rois<T>(inputs[0]->get_data_ptr<const T>(),
-                                                       inputs[1]->get_data_ptr<const T>(),
-                                                       inputs[0]->get_shape(),
-                                                       inputs[1]->get_shape(),
+    outputs[0].set_shape(ov::Shape{max_rois, 4});
+    ov::reference::experimental_detectron_topk_rois<T>(inputs[0].data<const T>(),
+                                                       inputs[1].data<const T>(),
+                                                       inputs[0].get_shape(),
+                                                       inputs[1].get_shape(),
                                                        max_rois,
-                                                       outputs[0]->get_data_ptr<T>());
+                                                       outputs[0].data<T>());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v6::ExperimentalDetectronTopKROIs>(std::shared_ptr<ngraph::Node> node,
-                                                                  const ngraph::HostTensorVector& outputs,
-                                                                  const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v6::ExperimentalDetectronTopKROIs>(std::shared_ptr<ov::Node> node,
+                                                              ov::TensorVector& outputs,
+                                                              const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(
-            ov::as_type_ptr<ngraph::op::v6::ExperimentalDetectronTopKROIs>(node),
-            outputs,
-            inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                           outputs,
+                                           inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v6::ExperimentalDetectronTopKROIs>(node),
+                                          outputs,
+                                          inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/extract_image_patches.cpp b/src/plugins/template/backend/ops/extract_image_patches.cpp
index d78a21e984b3fb..f1b087e3c44147 100644
--- a/src/plugins/template/backend/ops/extract_image_patches.cpp
+++ b/src/plugins/template/backend/ops/extract_image_patches.cpp
@@ -6,94 +6,93 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::ExtractImagePatches>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v3::ExtractImagePatches>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
     ov::reference::extract_image_patches<T>(op,
-                                            inputs[0]->get_data_ptr<T>(),
-                                            outputs[0]->get_data_ptr<T>(),
-                                            inputs[0]->get_shape(),
-                                            outputs[0]->get_shape());
+                                            inputs[0].data<T>(),
+                                            outputs[0].data<T>(),
+                                            inputs[0].get_shape(),
+                                            outputs[0].get_shape());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::ExtractImagePatches>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::ExtractImagePatches>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::ExtractImagePatches>(node),
+    case ov::element::Type_t::boolean:
+        return evaluate<ov::element::Type_t::boolean>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
                                                       outputs,
                                                       inputs);
+    case ov::element::Type_t::bf16:
+        return evaluate<ov::element::Type_t::bf16>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                   outputs,
+                                                   inputs);
+    case ov::element::Type_t::f16:
+        return evaluate<ov::element::Type_t::f16>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
+    case ov::element::Type_t::f64:
+        return evaluate<ov::element::Type_t::f64>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
+    case ov::element::Type_t::f32:
+        return evaluate<ov::element::Type_t::f32>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
+    case ov::element::Type_t::i4:
+        return evaluate<ov::element::Type_t::i4>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                 outputs,
+                                                 inputs);
+    case ov::element::Type_t::i8:
+        return evaluate<ov::element::Type_t::i8>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                 outputs,
+                                                 inputs);
+    case ov::element::Type_t::i16:
+        return evaluate<ov::element::Type_t::i16>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
+    case ov::element::Type_t::i32:
+        return evaluate<ov::element::Type_t::i32>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
+    case ov::element::Type_t::i64:
+        return evaluate<ov::element::Type_t::i64>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
+    case ov::element::Type_t::u1:
+        return evaluate<ov::element::Type_t::u1>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                 outputs,
+                                                 inputs);
+    case ov::element::Type_t::u4:
+        return evaluate<ov::element::Type_t::u4>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                 outputs,
+                                                 inputs);
+    case ov::element::Type_t::u8:
+        return evaluate<ov::element::Type_t::u8>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                 outputs,
+                                                 inputs);
+    case ov::element::Type_t::u16:
+        return evaluate<ov::element::Type_t::u16>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
+    case ov::element::Type_t::u32:
+        return evaluate<ov::element::Type_t::u32>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
+    case ov::element::Type_t::u64:
+        return evaluate<ov::element::Type_t::u64>(ov::as_type_ptr<ov::op::v3::ExtractImagePatches>(node),
+                                                  outputs,
+                                                  inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/fft.cpp b/src/plugins/template/backend/ops/fft.cpp
index db4620270faaf9..6ee238c0b4cf14 100644
--- a/src/plugins/template/backend/ops/fft.cpp
+++ b/src/plugins/template/backend/ops/fft.cpp
@@ -11,16 +11,16 @@ namespace fft_v7 {
 struct InfoForFFT7 {
     std::vector<float> input_data;
     std::vector<int64_t> axes_data;
-    ngraph::Shape input_data_shape;
-    ngraph::Shape axes_data_shape;
-    ngraph::Shape output_shape;
+    ov::Shape input_data_shape;
+    ov::Shape axes_data_shape;
+    ov::Shape output_shape;
 };
 
-InfoForFFT7 get_info_for_fft7_eval(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForFFT7 get_info_for_fft7_eval(const ov::TensorVector& inputs) {
     InfoForFFT7 result;
 
-    result.input_data_shape = inputs[0]->get_shape();
-    result.axes_data_shape = inputs[1]->get_shape();
+    result.input_data_shape = inputs[0].get_shape();
+    result.axes_data_shape = inputs[1].get_shape();
     result.input_data = get_floats(inputs[0], result.input_data_shape);
     result.axes_data = get_integers(inputs[1], result.axes_data_shape);
 
@@ -48,14 +48,12 @@ InfoForFFT7 get_info_for_fft7_eval(const std::vector<std::shared_ptr<ngraph::Hos
 }
 }  // namespace fft_v7
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v7::DFT>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v7::DFT>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
     auto info = fft_v7::get_info_for_fft7_eval(inputs);
-    outputs[0]->set_shape(info.output_shape);
+    outputs[0].set_shape(info.output_shape);
 
-    std::vector<float> fft_result(ngraph::shape_size(info.output_shape), 0.0f);
+    std::vector<float> fft_result(ov::shape_size(info.output_shape), 0.0f);
     ov::reference::fft(info.input_data.data(),
                        info.input_data_shape,
                        info.axes_data.data(),
@@ -69,14 +67,12 @@ bool evaluate(const std::shared_ptr<ngraph::op::v7::DFT>& op,
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v7::IDFT>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v7::IDFT>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
     auto info = fft_v7::get_info_for_fft7_eval(inputs);
-    outputs[0]->set_shape(info.output_shape);
+    outputs[0].set_shape(info.output_shape);
 
-    std::vector<float> fft_result(ngraph::shape_size(info.output_shape), 0.0f);
+    std::vector<float> fft_result(ov::shape_size(info.output_shape), 0.0f);
     ov::reference::fft(info.input_data.data(),
                        info.input_data_shape,
                        info.axes_data.data(),
@@ -91,95 +87,93 @@ bool evaluate(const std::shared_ptr<ngraph::op::v7::IDFT>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v7::DFT>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v7::DFT>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v7::DFT>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v7::IDFT>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v7::IDFT>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v7::IDFT>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/gather.cpp b/src/plugins/template/backend/ops/gather.cpp
index 9bb9799dc0d664..027a6c8cca1df7 100644
--- a/src/plugins/template/backend/ops/gather.cpp
+++ b/src/plugins/template/backend/ops/gather.cpp
@@ -6,24 +6,24 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::Gather>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    if (op->get_input_element_type(1) == ngraph::element::i64) {
-        ov::reference::gather<T, int64_t>(inputs[0]->get_data_ptr<T>(),
-                                          inputs[1]->get_data_ptr<int64_t>(),
-                                          outputs[0]->get_data_ptr<T>(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v8::Gather>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    if (op->get_input_element_type(1) == ov::element::i64) {
+        ov::reference::gather<T, int64_t>(inputs[0].data<T>(),
+                                          inputs[1].data<int64_t>(),
+                                          outputs[0].data<T>(),
                                           op->get_input_shape(0),
                                           op->get_input_shape(1),
                                           op->get_output_shape(0),
                                           op->get_axis(),
                                           op->get_batch_dims());
-    } else if (op->get_input_element_type(1) == ngraph::element::i32) {
-        ov::reference::gather<T, int32_t>(inputs[0]->get_data_ptr<T>(),
-                                          inputs[1]->get_data_ptr<int32_t>(),
-                                          outputs[0]->get_data_ptr<T>(),
+    } else if (op->get_input_element_type(1) == ov::element::i32) {
+        ov::reference::gather<T, int32_t>(inputs[0].data<T>(),
+                                          inputs[1].data<int32_t>(),
+                                          outputs[0].data<T>(),
                                           op->get_input_shape(0),
                                           op->get_input_shape(1),
                                           op->get_output_shape(0),
@@ -36,50 +36,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::Gather>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::Gather>(std::shared_ptr<ngraph::Node> node,
-                                           const ngraph::HostTensorVector& outputs,
-                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::Gather>(std::shared_ptr<ov::Node> node,
+                                       ov::TensorVector& outputs,
+                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::Gather>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::Gather>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/gather_elements.cpp b/src/plugins/template/backend/ops/gather_elements.cpp
index 9c7ac6e892cfa4..e919dc14e166a0 100644
--- a/src/plugins/template/backend/ops/gather_elements.cpp
+++ b/src/plugins/template/backend/ops/gather_elements.cpp
@@ -6,31 +6,31 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v6::GatherElements>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ngraph::Shape params_shape = inputs[0]->get_shape();
-    ngraph::Shape indices_shape = inputs[1]->get_shape();
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v6::GatherElements>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::Shape params_shape = inputs[0].get_shape();
+    ov::Shape indices_shape = inputs[1].get_shape();
 
-    outputs[0]->set_shape(indices_shape);
+    outputs[0].set_shape(indices_shape);
 
-    if (inputs[1]->get_element_type() == ngraph::element::i64) {
-        ov::reference::gather_elements<T, int64_t>(inputs[0]->get_data_ptr<ET>(),
-                                                   inputs[1]->get_data_ptr<int64_t>(),
-                                                   outputs[0]->get_data_ptr<ET>(),
-                                                   inputs[0]->get_shape(),
-                                                   inputs[1]->get_shape(),
-                                                   outputs[0]->get_shape(),
+    if (inputs[1].get_element_type() == ov::element::i64) {
+        ov::reference::gather_elements<T, int64_t>(inputs[0].data<T>(),
+                                                   inputs[1].data<int64_t>(),
+                                                   outputs[0].data<T>(),
+                                                   inputs[0].get_shape(),
+                                                   inputs[1].get_shape(),
+                                                   outputs[0].get_shape(),
                                                    op->get_axis());
-    } else if (inputs[1]->get_element_type() == ngraph::element::i32) {
-        ov::reference::gather_elements<T, int32_t>(inputs[0]->get_data_ptr<ET>(),
-                                                   inputs[1]->get_data_ptr<int32_t>(),
-                                                   outputs[0]->get_data_ptr<ET>(),
-                                                   inputs[0]->get_shape(),
-                                                   inputs[1]->get_shape(),
-                                                   outputs[0]->get_shape(),
+    } else if (inputs[1].get_element_type() == ov::element::i32) {
+        ov::reference::gather_elements<T, int32_t>(inputs[0].data<T>(),
+                                                   inputs[1].data<int32_t>(),
+                                                   outputs[0].data<T>(),
+                                                   inputs[0].get_shape(),
+                                                   inputs[1].get_shape(),
+                                                   outputs[0].get_shape(),
                                                    op->get_axis());
     } else {
         OPENVINO_THROW("Unexpected indices type");
@@ -40,80 +40,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::GatherElements>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v6::GatherElements>(std::shared_ptr<ngraph::Node> node,
-                                                   const ngraph::HostTensorVector& outputs,
-                                                   const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v6::GatherElements>(std::shared_ptr<ov::Node> node,
+                                               ov::TensorVector& outputs,
+                                               const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v6::GatherElements>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v6::GatherElements>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/gather_nd.cpp b/src/plugins/template/backend/ops/gather_nd.cpp
index 97127a297d287d..373fb57eeb6074 100644
--- a/src/plugins/template/backend/ops/gather_nd.cpp
+++ b/src/plugins/template/backend/ops/gather_nd.cpp
@@ -6,26 +6,26 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v5::GatherND>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    if (op->get_input_element_type(1) == ngraph::element::i64) {
-        ov::reference::gather_nd<T, int64_t>(inputs[0]->get_data_ptr<T>(),
-                                             inputs[1]->get_data_ptr<int64_t>(),
-                                             outputs[0]->get_data_ptr<T>(),
-                                             inputs[0]->get_shape(),
-                                             inputs[1]->get_shape(),
-                                             outputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v5::GatherND>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    if (op->get_input_element_type(1) == ov::element::i64) {
+        ov::reference::gather_nd<T, int64_t>(inputs[0].data<T>(),
+                                             inputs[1].data<int64_t>(),
+                                             outputs[0].data<T>(),
+                                             inputs[0].get_shape(),
+                                             inputs[1].get_shape(),
+                                             outputs[0].get_shape(),
                                              static_cast<int>(op->get_batch_dims()));
-    } else if (op->get_input_element_type(1) == ngraph::element::i32) {
-        ov::reference::gather_nd<T, int32_t>(inputs[0]->get_data_ptr<T>(),
-                                             inputs[1]->get_data_ptr<int32_t>(),
-                                             outputs[0]->get_data_ptr<T>(),
-                                             inputs[0]->get_shape(),
-                                             inputs[1]->get_shape(),
-                                             outputs[0]->get_shape(),
+    } else if (op->get_input_element_type(1) == ov::element::i32) {
+        ov::reference::gather_nd<T, int32_t>(inputs[0].data<T>(),
+                                             inputs[1].data<int32_t>(),
+                                             outputs[0].data<T>(),
+                                             inputs[0].get_shape(),
+                                             inputs[1].get_shape(),
+                                             outputs[0].get_shape(),
                                              static_cast<int>(op->get_batch_dims()));
     } else {
         OPENVINO_THROW("Unexpected indices type for GatherND operation");
@@ -33,26 +33,26 @@ bool evaluate(const std::shared_ptr<ngraph::op::v5::GatherND>& op,
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::GatherND>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    if (op->get_input_element_type(1) == ngraph::element::i64) {
-        ov::reference::gather_nd<T, int64_t>(inputs[0]->get_data_ptr<T>(),
-                                             inputs[1]->get_data_ptr<int64_t>(),
-                                             outputs[0]->get_data_ptr<T>(),
-                                             inputs[0]->get_shape(),
-                                             inputs[1]->get_shape(),
-                                             outputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v8::GatherND>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    if (op->get_input_element_type(1) == ov::element::i64) {
+        ov::reference::gather_nd<T, int64_t>(inputs[0].data<T>(),
+                                             inputs[1].data<int64_t>(),
+                                             outputs[0].data<T>(),
+                                             inputs[0].get_shape(),
+                                             inputs[1].get_shape(),
+                                             outputs[0].get_shape(),
                                              static_cast<int>(op->get_batch_dims()));
-    } else if (op->get_input_element_type(1) == ngraph::element::i32) {
-        ov::reference::gather_nd<T, int32_t>(inputs[0]->get_data_ptr<T>(),
-                                             inputs[1]->get_data_ptr<int32_t>(),
-                                             outputs[0]->get_data_ptr<T>(),
-                                             inputs[0]->get_shape(),
-                                             inputs[1]->get_shape(),
-                                             outputs[0]->get_shape(),
+    } else if (op->get_input_element_type(1) == ov::element::i32) {
+        ov::reference::gather_nd<T, int32_t>(inputs[0].data<T>(),
+                                             inputs[1].data<int32_t>(),
+                                             outputs[0].data<T>(),
+                                             inputs[0].get_shape(),
+                                             inputs[1].get_shape(),
+                                             outputs[0].get_shape(),
                                              static_cast<int>(op->get_batch_dims()));
     } else {
         OPENVINO_THROW("Unexpected indices type for GatherND operation");
@@ -61,103 +61,93 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::GatherND>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v5::GatherND>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v5::GatherND>(std::shared_ptr<ov::Node> node,
+                                         ov::TensorVector& outputs,
+                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v5::GatherND>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::GatherND>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::GatherND>(std::shared_ptr<ov::Node> node,
+                                         ov::TensorVector& outputs,
+                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::GatherND>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/gather_tree.cpp b/src/plugins/template/backend/ops/gather_tree.cpp
index 1aec9368d7cd4f..1c06cec35d34f4 100644
--- a/src/plugins/template/backend/ops/gather_tree.cpp
+++ b/src/plugins/template/backend/ops/gather_tree.cpp
@@ -6,98 +6,29 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::GatherTree>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    ov::reference::gather_tree(inputs[0]->get_data_ptr<const char>(),
-                               inputs[1]->get_data_ptr<const char>(),
-                               inputs[2]->get_data_ptr<const char>(),
-                               inputs[3]->get_data_ptr<const char>(),
-                               outputs[0]->get_data_ptr<char>(),
+bool evaluate(const std::shared_ptr<ov::op::v1::GatherTree>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    ov::reference::gather_tree(static_cast<const char*>(inputs[0].data()),
+                               static_cast<const char*>(inputs[1].data()),
+                               static_cast<const char*>(inputs[2].data()),
+                               static_cast<const char*>(inputs[3].data()),
+                               static_cast<char*>(outputs[0].data()),
                                op->get_input_shape(0),
                                op->get_input_shape(1),
                                op->get_input_shape(2),
                                op->get_input_shape(3),
-                               inputs[1]->get_element_type());
+                               inputs[1].get_element_type());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::GatherTree>(std::shared_ptr<ngraph::Node> node,
-                                               const ngraph::HostTensorVector& outputs,
-                                               const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::GatherTree>(std::shared_ptr<ov::Node> node,
+                                           ov::TensorVector& outputs,
+                                           const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
-    switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::GatherTree>(node),
-                                                      outputs,
-                                                      inputs);
-    default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
-    }
+    return evaluate(ov::as_type_ptr<ov::op::v1::GatherTree>(node), outputs, inputs);
 }
diff --git a/src/plugins/template/backend/ops/gelu.cpp b/src/plugins/template/backend/ops/gelu.cpp
index 0b994fedca4536..dae4e32e967dae 100644
--- a/src/plugins/template/backend/ops/gelu.cpp
+++ b/src/plugins/template/backend/ops/gelu.cpp
@@ -6,120 +6,114 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Gelu>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::gelu<T>(inputs[0]->get_data_ptr<T>(),
-                           outputs[0]->get_data_ptr<T>(),
-                           ngraph::op::GeluApproximationMode::ERF,
-                           ngraph::shape_size(inputs[0]->get_shape()));
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Gelu>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::gelu<T>(inputs[0].data<T>(),
+                           outputs[0].data<T>(),
+                           ov::op::GeluApproximationMode::ERF,
+                           ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v7::Gelu>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::gelu<T>(inputs[0]->get_data_ptr<T>(),
-                           outputs[0]->get_data_ptr<T>(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v7::Gelu>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::gelu<T>(inputs[0].data<T>(),
+                           outputs[0].data<T>(),
                            op->get_approximation_mode(),
-                           ngraph::shape_size(inputs[0]->get_shape()));
+                           ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Gelu>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Gelu>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Gelu>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v7::Gelu>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v7::Gelu>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v7::Gelu>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/generate_proposal.cpp b/src/plugins/template/backend/ops/generate_proposal.cpp
index 53571e113e9b67..bbdb0a140c191d 100644
--- a/src/plugins/template/backend/ops/generate_proposal.cpp
+++ b/src/plugins/template/backend/ops/generate_proposal.cpp
@@ -7,10 +7,10 @@
 #include "evaluate_node.hpp"
 #include "evaluates_map.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v9::GenerateProposals>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v9::GenerateProposals>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     const auto& attrs = op->get_attrs();
 
     if (attrs.post_nms_count < 0) {
@@ -21,10 +21,10 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::GenerateProposals>& op,
 
     const auto& output_type = op->get_input_element_type(0);
 
-    const auto& im_info_shape = inputs[0]->get_shape();
-    const auto& anchors_shape = inputs[1]->get_shape();
-    const auto& deltas_shape = inputs[2]->get_shape();
-    const auto& scores_shape = inputs[3]->get_shape();
+    const auto& im_info_shape = inputs[0].get_shape();
+    const auto& anchors_shape = inputs[1].get_shape();
+    const auto& deltas_shape = inputs[2].get_shape();
+    const auto& scores_shape = inputs[3].get_shape();
 
     const auto im_info_data = get_floats(inputs[0], im_info_shape);
     const auto anchors_data = get_floats(inputs[1], anchors_shape);
@@ -50,22 +50,19 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::GenerateProposals>& op,
 
     size_t num_selected = static_cast<size_t>(std::accumulate(output_num.begin(), output_num.end(), 0));
 
-    ngraph::Shape output_rois_shape = ngraph::Shape{num_selected, 4};
-    ngraph::Shape output_scores_shape = ngraph::Shape{num_selected};
+    ov::Shape output_rois_shape = ov::Shape{num_selected, 4};
+    ov::Shape output_scores_shape = ov::Shape{num_selected};
 
-    outputs[0]->set_element_type(output_type);
-    outputs[0]->set_shape(output_rois_shape);
-    outputs[1]->set_element_type(output_type);
-    outputs[1]->set_shape(output_scores_shape);
+    outputs[0].set_shape(output_rois_shape);
+    outputs[1].set_shape(output_scores_shape);
 
     const auto& roi_num_type = op->get_output_element_type(2);
-    ngraph::Shape output_roi_num_shape = ngraph::Shape{im_info_shape[0]};
-    outputs[2]->set_element_type(roi_num_type);
-    outputs[2]->set_shape(output_roi_num_shape);
+    ov::Shape output_roi_num_shape = ov::Shape{im_info_shape[0]};
+    outputs[2].set_shape(output_roi_num_shape);
 
-    ov::reference::generate_proposals_postprocessing(outputs[0]->get_data_ptr(),
-                                                     outputs[1]->get_data_ptr(),
-                                                     outputs[2]->get_data_ptr(),
+    ov::reference::generate_proposals_postprocessing(outputs[0].data(),
+                                                     outputs[1].data(),
+                                                     outputs[2].data(),
                                                      output_type,
                                                      roi_num_type,
                                                      output_rois,
@@ -78,80 +75,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::GenerateProposals>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v9::GenerateProposals>(std::shared_ptr<ngraph::Node> node,
-                                                      const ngraph::HostTensorVector& outputs,
-                                                      const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v9::GenerateProposals>(std::shared_ptr<ov::Node> node,
+                                                  ov::TensorVector& outputs,
+                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v9::GenerateProposals>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v9::GenerateProposals>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/greater.cpp b/src/plugins/template/backend/ops/greater.cpp
index 6df8f4c73e372d..7f8d28389933f0 100644
--- a/src/plugins/template/backend/ops/greater.cpp
+++ b/src/plugins/template/backend/ops/greater.cpp
@@ -6,72 +6,64 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::Greater>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto in0_data_ptr = inputs[0]->get_data_ptr<ET>();
-    const auto in1_data_ptr = inputs[1]->get_data_ptr<ET>();
-    const auto out_data_ptr = outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>();
-    const auto in0_shape = inputs[0]->get_shape();
-    const auto in1_shape = inputs[1]->get_shape();
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v1::Greater>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    using BT = typename ov::element_type_traits<ov::element::boolean>::value_type;
+    const auto in0_data_ptr = inputs[0].data<ET>();
+    const auto in1_data_ptr = inputs[1].data<ET>();
+    const auto out_data_ptr = outputs[0].data<BT>();
+    const auto in0_shape = inputs[0].get_shape();
+    const auto in1_shape = inputs[1].get_shape();
     const auto broadcast_spec = op->get_autob();
-    ov::reference::greater<typename ngraph::element_type_traits<ET>::value_type,
-                           typename ngraph::element_type_traits<ngraph::element::Type_t::boolean>::value_type>(
-        in0_data_ptr,
-        in1_data_ptr,
-        out_data_ptr,
-        in0_shape,
-        in1_shape,
-        broadcast_spec);
+    ov::reference::greater<ET, BT>(in0_data_ptr, in1_data_ptr, out_data_ptr, in0_shape, in1_shape, broadcast_spec);
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::Greater>(std::shared_ptr<ngraph::Node> node,
-                                            const ngraph::HostTensorVector& outputs,
-                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::Greater>(std::shared_ptr<ov::Node> node,
+                                        ov::TensorVector& outputs,
+                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::Greater>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::Greater>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/grid_sample.cpp b/src/plugins/template/backend/ops/grid_sample.cpp
index 20e74f5699a642..f47dba333f3c4e 100644
--- a/src/plugins/template/backend/ops/grid_sample.cpp
+++ b/src/plugins/template/backend/ops/grid_sample.cpp
@@ -6,19 +6,20 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t DATA_ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v9::GridSample>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v9::GridSample>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
     const auto& attributes = op->get_attributes();
-    ngraph::element::Type grid_et = op->get_input_element_type(1);
+    ov::element::Type grid_et = op->get_input_element_type(1);
     switch (grid_et) {
-    case ngraph::element::Type_t::f32:
-        ov::reference::grid_sample(outputs[0]->get_data_ptr<DATA_ET>(),
-                                   inputs[0]->get_data_ptr<DATA_ET>(),
-                                   inputs[1]->get_data_ptr<ngraph::element::Type_t::f32>(),
-                                   inputs[0]->get_shape(),
-                                   inputs[1]->get_shape(),
+    case ov::element::f32:
+        ov::reference::grid_sample(outputs[0].data<ET>(),
+                                   inputs[0].data<ET>(),
+                                   inputs[1].data<float>(),
+                                   inputs[0].get_shape(),
+                                   inputs[1].get_shape(),
                                    attributes.align_corners,
                                    attributes.mode,
                                    attributes.padding_mode);
@@ -30,80 +31,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::GridSample>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v9::GridSample>(std::shared_ptr<ngraph::Node> node,
-                                               const ngraph::HostTensorVector& outputs,
-                                               const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v9::GridSample>(std::shared_ptr<ov::Node> node,
+                                           ov::TensorVector& outputs,
+                                           const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v9::GridSample>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v9::GridSample>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/grn.cpp b/src/plugins/template/backend/ops/grn.cpp
index 74a5fceaa23f09..4eb748373f5005 100644
--- a/src/plugins/template/backend/ops/grn.cpp
+++ b/src/plugins/template/backend/ops/grn.cpp
@@ -6,61 +6,55 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::GRN>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::grn<T>(inputs[0]->get_data_ptr<ET>(),
-                          outputs[0]->get_data_ptr<ET>(),
-                          op->get_bias(),
-                          inputs[0]->get_shape());
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v0::GRN>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    ov::reference::grn<ET>(inputs[0].data<ET>(), outputs[0].data<ET>(), op->get_bias(), inputs[0].get_shape());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::GRN>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::GRN>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::GRN>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/group_convolution.cpp b/src/plugins/template/backend/ops/group_convolution.cpp
index 6dc851171d2d5b..be1a6601dd2d3f 100644
--- a/src/plugins/template/backend/ops/group_convolution.cpp
+++ b/src/plugins/template/backend/ops/group_convolution.cpp
@@ -6,104 +6,72 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::GroupConvolution>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto filter_data = inputs[1]->get_data_ptr<ET>();
-    auto out_data_ptr = outputs[0]->get_data_ptr<ET>();
-    const auto in_data_ptr = inputs[0]->get_data_ptr<ET>();
-    const auto& out_shape = outputs[0]->get_shape();
-    const auto& in_shape = inputs[0]->get_shape();
-    const auto& filter_shape = inputs[1]->get_shape();
-    ov::reference::group_convolution<typename ngraph::element_type_traits<ET>::value_type>(in_data_ptr,
-                                                                                           filter_data,
-                                                                                           out_data_ptr,
-                                                                                           in_shape,
-                                                                                           filter_shape,
-                                                                                           out_shape,
-                                                                                           op->get_strides(),
-                                                                                           op->get_dilations(),
-                                                                                           op->get_pads_begin(),
-                                                                                           op->get_pads_end());
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v1::GroupConvolution>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    const auto filter_data = inputs[1].data<ET>();
+    auto out_data_ptr = outputs[0].data<ET>();
+    const auto in_data_ptr = inputs[0].data<ET>();
+    const auto& out_shape = outputs[0].get_shape();
+    const auto& in_shape = inputs[0].get_shape();
+    const auto& filter_shape = inputs[1].get_shape();
+    ov::reference::group_convolution<ET>(in_data_ptr,
+                                         filter_data,
+                                         out_data_ptr,
+                                         in_shape,
+                                         filter_shape,
+                                         out_shape,
+                                         op->get_strides(),
+                                         op->get_dilations(),
+                                         op->get_pads_begin(),
+                                         op->get_pads_end());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::GroupConvolution>(std::shared_ptr<ngraph::Node> node,
-                                                     const ngraph::HostTensorVector& outputs,
-                                                     const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::GroupConvolution>(std::shared_ptr<ov::Node> node,
+                                                 ov::TensorVector& outputs,
+                                                 const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::GroupConvolution>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::GroupConvolution>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/group_convolution_backprop_data.cpp b/src/plugins/template/backend/ops/group_convolution_backprop_data.cpp
index ec58d1efdb83e7..26f1c44e57f9c6 100644
--- a/src/plugins/template/backend/ops/group_convolution_backprop_data.cpp
+++ b/src/plugins/template/backend/ops/group_convolution_backprop_data.cpp
@@ -6,122 +6,105 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::GroupConvolutionBackpropData>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto in_data_ptr = inputs[0]->get_data_ptr<ET>();
-    const auto filter_data_ptr = inputs[1]->get_data_ptr<ET>();
-    const auto out_data_ptr = outputs[0]->get_data_ptr<ET>();
-    const auto in_shape = inputs[0]->get_shape();
-    const auto filter_shape = inputs[1]->get_shape();
-    const auto out_shape = outputs[0]->get_shape();
-    ov::reference::group_convolution_backprop_data<typename ngraph::element_type_traits<ET>::value_type>(
-        in_data_ptr,
-        filter_data_ptr,
-        out_data_ptr,
-        in_shape,
-        filter_shape,
-        out_shape,
-        op->get_strides(),
-        op->get_dilations(),
-        op->get_pads_begin(),
-        op->get_pads_end(),
-        op->get_output_padding());
+template <ov::element::Type_t T>
+bool evaluate(const std::shared_ptr<ov::op::v1::GroupConvolutionBackpropData>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    const auto in_data_ptr = inputs[0].data<ET>();
+    const auto filter_data_ptr = inputs[1].data<ET>();
+    const auto out_data_ptr = outputs[0].data<ET>();
+    const auto in_shape = inputs[0].get_shape();
+    const auto filter_shape = inputs[1].get_shape();
+    const auto out_shape = outputs[0].get_shape();
+    ov::reference::group_convolution_backprop_data<ET>(in_data_ptr,
+                                                       filter_data_ptr,
+                                                       out_data_ptr,
+                                                       in_shape,
+                                                       filter_shape,
+                                                       out_shape,
+                                                       op->get_strides(),
+                                                       op->get_dilations(),
+                                                       op->get_pads_begin(),
+                                                       op->get_pads_end(),
+                                                       op->get_output_padding());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::GroupConvolutionBackpropData>(std::shared_ptr<ngraph::Node> node,
-                                                                 const ngraph::HostTensorVector& outputs,
-                                                                 const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::GroupConvolutionBackpropData>(std::shared_ptr<ov::Node> node,
+                                                             ov::TensorVector& outputs,
+                                                             const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(
-            ov::as_type_ptr<ngraph::op::v1::GroupConvolutionBackpropData>(node),
-            outputs,
-            inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                              outputs,
+                                              inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                           outputs,
+                                           inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                         outputs,
+                                         inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::GroupConvolutionBackpropData>(node),
+                                          outputs,
+                                          inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/group_normalization.cpp b/src/plugins/template/backend/ops/group_normalization.cpp
index 71481b560ac2c2..eb339388822f40 100644
--- a/src/plugins/template/backend/ops/group_normalization.cpp
+++ b/src/plugins/template/backend/ops/group_normalization.cpp
@@ -9,16 +9,17 @@
 
 using namespace ov;
 
-template <element::Type_t DATA_ET>
+template <element::Type_t T>
 bool evaluate(const std::shared_ptr<ov::op::v12::GroupNormalization>& node,
-              const ov::HostTensorVector& outputs,
-              const ov::HostTensorVector& inputs) {
-    outputs[0]->set_shape(inputs[0]->get_shape());
-    ov::reference::group_normalization(inputs[0]->get_data_ptr<DATA_ET>(),
-                                       inputs[1]->get_data_ptr<DATA_ET>(),
-                                       inputs[2]->get_data_ptr<DATA_ET>(),
-                                       outputs[0]->get_data_ptr<DATA_ET>(),
-                                       inputs[0]->get_shape(),
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using ET = typename ov::element_type_traits<T>::value_type;
+    outputs[0].set_shape(inputs[0].get_shape());
+    ov::reference::group_normalization(inputs[0].data<ET>(),
+                                       inputs[1].data<ET>(),
+                                       inputs[2].data<ET>(),
+                                       outputs[0].data<ET>(),
+                                       inputs[0].get_shape(),
                                        static_cast<size_t>(node->get_num_groups()),
                                        node->get_epsilon());
     return true;
@@ -26,18 +27,18 @@ bool evaluate(const std::shared_ptr<ov::op::v12::GroupNormalization>& node,
 
 template <>
 bool evaluate_node<op::v12::GroupNormalization>(std::shared_ptr<ov::Node> node,
-                                                const ov::HostTensorVector& outputs,
-                                                const ov::HostTensorVector& inputs) {
+                                                ov::TensorVector& outputs,
+                                                const ov::TensorVector& inputs) {
     switch (node->get_input_element_type(0)) {
-    case element::Type_t::bf16:
-        return evaluate<element::Type_t::bf16>(as_type_ptr<op::v12::GroupNormalization>(node), outputs, inputs);
-    case element::Type_t::f16:
-        return evaluate<element::Type_t::f16>(as_type_ptr<op::v12::GroupNormalization>(node), outputs, inputs);
-    case element::Type_t::f64:
-        return evaluate<element::Type_t::f64>(as_type_ptr<op::v12::GroupNormalization>(node), outputs, inputs);
-    case element::Type_t::f32:
-        return evaluate<element::Type_t::f32>(as_type_ptr<op::v12::GroupNormalization>(node), outputs, inputs);
+    case element::bf16:
+        return evaluate<element::bf16>(as_type_ptr<op::v12::GroupNormalization>(node), outputs, inputs);
+    case element::f16:
+        return evaluate<element::f16>(as_type_ptr<op::v12::GroupNormalization>(node), outputs, inputs);
+    case element::f64:
+        return evaluate<element::f64>(as_type_ptr<op::v12::GroupNormalization>(node), outputs, inputs);
+    case element::f32:
+        return evaluate<element::f32>(as_type_ptr<op::v12::GroupNormalization>(node), outputs, inputs);
     default:
-        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), "in evaluate_node()");
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/gru_cell.cpp b/src/plugins/template/backend/ops/gru_cell.cpp
index b34b5ea945965c..cbd431121fb058 100644
--- a/src/plugins/template/backend/ops/gru_cell.cpp
+++ b/src/plugins/template/backend/ops/gru_cell.cpp
@@ -7,22 +7,22 @@
 #include "evaluate_node.hpp"
 #include "ov_ops/augru_cell.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::GRUCell>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::gru_cell<T>(inputs[0]->get_data_ptr<ET>(),
-                               inputs[0]->get_shape(),
-                               inputs[1]->get_data_ptr<ET>(),
-                               inputs[1]->get_shape(),
-                               inputs[2]->get_data_ptr<ET>(),
-                               inputs[2]->get_shape(),
-                               inputs[3]->get_data_ptr<ET>(),
-                               inputs[3]->get_shape(),
-                               inputs[4]->get_data_ptr<ET>(),
-                               inputs[4]->get_shape(),
-                               outputs[0]->get_data_ptr<ET>(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v3::GRUCell>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::gru_cell<T>(inputs[0].data<T>(),
+                               inputs[0].get_shape(),
+                               inputs[1].data<T>(),
+                               inputs[1].get_shape(),
+                               inputs[2].data<T>(),
+                               inputs[2].get_shape(),
+                               inputs[3].data<T>(),
+                               inputs[3].get_shape(),
+                               inputs[4].data<T>(),
+                               inputs[4].get_shape(),
+                               outputs[0].data<T>(),
                                op->get_activations()[0],
                                op->get_activations()[1],
                                op->get_clip(),
@@ -30,154 +30,118 @@ bool evaluate(const std::shared_ptr<ngraph::op::v3::GRUCell>& op,
     return true;
 }
 
-template <ngraph::element::Type_t ET>
+template <ov::element::Type_t ET>
 bool evaluate(const std::shared_ptr<ov::op::internal::AUGRUCell>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::gru_cell<T>(inputs[0]->get_data_ptr<ET>(),
-                               inputs[0]->get_shape(),
-                               inputs[1]->get_data_ptr<ET>(),
-                               inputs[1]->get_shape(),
-                               inputs[2]->get_data_ptr<ET>(),
-                               inputs[2]->get_shape(),
-                               inputs[3]->get_data_ptr<ET>(),
-                               inputs[3]->get_shape(),
-                               inputs[4]->get_data_ptr<ET>(),
-                               inputs[4]->get_shape(),
-                               outputs[0]->get_data_ptr<ET>(),
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::gru_cell<T>(inputs[0].data<T>(),
+                               inputs[0].get_shape(),
+                               inputs[1].data<T>(),
+                               inputs[1].get_shape(),
+                               inputs[2].data<T>(),
+                               inputs[2].get_shape(),
+                               inputs[3].data<T>(),
+                               inputs[3].get_shape(),
+                               inputs[4].data<T>(),
+                               inputs[4].get_shape(),
+                               outputs[0].data<T>(),
                                op->get_activations()[0],
                                op->get_activations()[1],
                                op->get_clip(),
                                op->get_linear_before_reset(),
-                               inputs[5]->get_data_ptr<ET>());
+                               inputs[5].data<T>());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::GRUCell>(std::shared_ptr<ngraph::Node> node,
-                                            const ngraph::HostTensorVector& outputs,
-                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::GRUCell>(std::shared_ptr<ov::Node> node,
+                                        ov::TensorVector& outputs,
+                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v3::GRUCell>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ov::op::internal::AUGRUCell>(std::shared_ptr<ngraph::Node> node,
-                                                const ngraph::HostTensorVector& outputs,
-                                                const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::internal::AUGRUCell>(std::shared_ptr<ov::Node> node,
+                                                ov::TensorVector& outputs,
+                                                const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::internal::AUGRUCell>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/hard_sigmoid.cpp b/src/plugins/template/backend/ops/hard_sigmoid.cpp
index 9cf2a16f5dace1..9d3b9f56b53115 100644
--- a/src/plugins/template/backend/ops/hard_sigmoid.cpp
+++ b/src/plugins/template/backend/ops/hard_sigmoid.cpp
@@ -2,99 +2,65 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/hard_sigmoid.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::HardSigmoid>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::hard_sigmoid<T>(inputs[0]->get_data_ptr<T>(),
-                                   inputs[1]->get_data_ptr<const T>()[0],
-                                   inputs[2]->get_data_ptr<const T>()[0],
-                                   outputs[0]->get_data_ptr<T>(),
-                                   ngraph::shape_size(outputs[0]->get_shape()));
+#include "evaluate_node.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::HardSigmoid>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::hard_sigmoid<T>(inputs[0].data<T>(),
+                                   inputs[1].data<const T>()[0],
+                                   inputs[2].data<const T>()[0],
+                                   outputs[0].data<T>(),
+                                   ov::shape_size(outputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::HardSigmoid>(std::shared_ptr<ngraph::Node> node,
-                                                const ngraph::HostTensorVector& outputs,
-                                                const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::HardSigmoid>(std::shared_ptr<ov::Node> node,
+                                            ov::TensorVector& outputs,
+                                            const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::HardSigmoid>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::HardSigmoid>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/if.cpp b/src/plugins/template/backend/ops/if.cpp
index df93652d103bdb..8795d0bfa789b6 100644
--- a/src/plugins/template/backend/ops/if.cpp
+++ b/src/plugins/template/backend/ops/if.cpp
@@ -6,23 +6,24 @@
 
 #include "evaluate_node.hpp"
 #include "evaluates_map.hpp"
+#include "shape_util.hpp"
 
 namespace if_op {
-bool call(const ngraph::HostTensorVector& func_outputs,
-          const ngraph::HostTensorVector& func_inputs,
-          const std::shared_ptr<ngraph::Function>& function) {
-    // map function params -> ngraph::HostTensor
-    std::unordered_map<ngraph::descriptor::Tensor*, std::shared_ptr<ngraph::HostTensor>> tensor_map;
+bool call(ov::TensorVector& func_outputs,
+          const ov::TensorVector& func_inputs,
+          const std::shared_ptr<ov::Model>& function) {
+    // map function params -> ov::Tensor
+    std::unordered_map<ov::descriptor::Tensor*, ov::Tensor> tensor_map;
     size_t input_count = 0;
     for (const auto& param : function->get_parameters()) {
         for (size_t i = 0; i < param->get_output_size(); ++i) {
-            ngraph::descriptor::Tensor* tensor = &param->output(i).get_tensor();
+            ov::descriptor::Tensor* tensor = &param->output(i).get_tensor();
             tensor_map.insert({tensor, func_inputs[input_count++]});
         }
     }
 
-    std::unordered_map<std::shared_ptr<ngraph::Node>, size_t> results_map;
-    // map function outputs -> ngraph::HostTensor
+    std::unordered_map<std::shared_ptr<ov::Node>, size_t> results_map;
+    // map function outputs -> ov::HostTensor
     for (size_t output_count = 0; output_count < function->get_results().size(); ++output_count) {
         auto output = function->get_results()[output_count];
         results_map[output] = output_count;
@@ -30,27 +31,27 @@ bool call(const ngraph::HostTensorVector& func_outputs,
 
     // for each ordered op in the graph
     for (const auto& op : function->get_ordered_ops()) {
-        if (ngraph::op::is_parameter(op)) {
+        if (ov::op::util::is_parameter(op)) {
             continue;
         }
 
         // get op inputs from map
-        std::vector<std::shared_ptr<ngraph::HostTensor>> op_inputs;
+        std::vector<ov::Tensor> op_inputs;
         for (auto input : op->inputs()) {
-            ngraph::descriptor::Tensor* tensor = &input.get_tensor();
+            ov::descriptor::Tensor* tensor = &input.get_tensor();
             op_inputs.push_back(tensor_map.at(tensor));
         }
 
         // get op outputs from map or create
-        std::vector<std::shared_ptr<ngraph::HostTensor>> op_outputs;
+        std::vector<ov::Tensor> op_outputs;
         for (size_t i = 0; i < op->get_output_size(); ++i) {
-            ngraph::descriptor::Tensor* tensor = &op->output(i).get_tensor();
-            std::shared_ptr<ngraph::HostTensor> host_tensor;
+            ov::descriptor::Tensor* tensor = &op->output(i).get_tensor();
+            ov::Tensor host_tensor;
             auto it = tensor_map.find(tensor);
-            if (ngraph::op::is_output(op)) {
+            if (ov::op::util::is_output(op)) {
                 host_tensor = func_outputs[results_map[op]];
             } else if (it == tensor_map.end()) {
-                host_tensor = std::make_shared<ngraph::HostTensor>(op->output(i));
+                host_tensor = ov::Tensor(op->output(i));
                 tensor_map.insert({tensor, host_tensor});
             } else {
                 host_tensor = it->second;
@@ -58,22 +59,18 @@ bool call(const ngraph::HostTensorVector& func_outputs,
             op_outputs.push_back(host_tensor);
         }
         op->validate_and_infer_types();
-        OPENVINO_SUPPRESS_DEPRECATED_START
         if (!op->evaluate(op_outputs, op_inputs)) {
-            const auto& evaluates_map = ngraph::runtime::interpreter::get_evaluators_map();
+            const auto& evaluates_map = ov::runtime::interpreter::get_evaluators_map();
             auto it = evaluates_map.find(op->get_type_info());
             if (!it->second(op, op_outputs, op_inputs)) {
                 return false;
             }
         }
-        OPENVINO_SUPPRESS_DEPRECATED_END
     }
     return true;
 }
 
-void function(const std::shared_ptr<ngraph::Function>& function,
-              const ngraph::HostTensorVector& inputs,
-              ngraph::HostTensorVector& outputs) {
+void function(const std::shared_ptr<ov::Model>& function, const ov::TensorVector& inputs, ov::TensorVector& outputs) {
     const auto& parameters = function->get_parameters();
     const auto& parametersNumber = parameters.size();
     const auto& inputsNumber = inputs.size();
@@ -90,10 +87,10 @@ void function(const std::shared_ptr<ngraph::Function>& function,
         const auto& parameterIndex = function->get_parameter_index(parameter);
         const auto& parameterShape = parameter->get_shape();
         const auto& parameterType = parameter->get_element_type();
-        const auto& parameterSize = ngraph::shape_size(parameterShape) * parameterType.size();
+        const auto& parameterSize = ov::shape_size(parameterShape) * parameterType.size();
 
         const auto& input = inputs[parameterIndex];
-        const auto& inputSize = input->get_size_in_bytes();
+        const auto& inputSize = input.get_byte_size();
         NGRAPH_CHECK(parameterSize == inputSize,
                      "Got parameter (",
                      parameter->get_friendly_name(),
@@ -109,22 +106,26 @@ void function(const std::shared_ptr<ngraph::Function>& function,
     const auto& results = function->get_results();
     outputs.reserve(results.size());
     for (size_t i = 0; i < results.size(); ++i) {
-        outputs.push_back(std::make_shared<ngraph::HostTensor>());
+        OPENVINO_SUPPRESS_DEPRECATED_START
+        ov::Shape res_shape = results[i]->get_output_partial_shape(0).is_static() ? results[i]->get_output_shape(0)
+                                                                                  : ov::util::make_dynamic_shape();
+        OPENVINO_SUPPRESS_DEPRECATED_END
+        outputs.push_back(ov::Tensor(results[i]->get_element_type(), res_shape));
     }
     call(outputs, inputs, function);
 }
 
-void if_reference(const std::vector<std::shared_ptr<ngraph::Function>>& bodies,
-                  const std::vector<ngraph::op::util::MultiSubgraphOutputDescriptionVector>& out_descs,
-                  const std::vector<ngraph::op::util::MultiSubgraphInputDescriptionVector>& input_descs,
-                  const ngraph::HostTensorVector& out,
-                  const ngraph::HostTensorVector& args) {
+void if_reference(const std::vector<std::shared_ptr<ov::Model>>& bodies,
+                  const std::vector<ov::op::util::MultiSubGraphOp::MultiSubgraphOutputDescriptionVector>& out_descs,
+                  const std::vector<ov::op::util::MultiSubGraphOp::MultiSubgraphInputDescriptionVector>& input_descs,
+                  ov::TensorVector& out,
+                  const ov::TensorVector& args) {
     NGRAPH_CHECK(args.size() > 0, "If operation must have input condition value");
 
-    auto condition_value = args[0]->get_data_ptr<bool>()[0];
-    auto branch_index = (condition_value) ? ngraph::op::v8::If::THEN_BODY_INDEX : ngraph::op::v8::If::ELSE_BODY_INDEX;
-    ngraph::HostTensorVector inputs_to_body;
-    ngraph::HostTensorVector outs_from_body;
+    auto condition_value = args[0].data<bool>()[0];
+    auto branch_index = (condition_value) ? ov::op::v8::If::THEN_BODY_INDEX : ov::op::v8::If::ELSE_BODY_INDEX;
+    ov::TensorVector inputs_to_body;
+    ov::TensorVector outs_from_body;
     inputs_to_body.resize(input_descs[branch_index].size());
     auto inputs_size = args.size();
     auto output_size = out.size();
@@ -140,17 +141,16 @@ void if_reference(const std::vector<std::shared_ptr<ngraph::Function>>& bodies,
                      "Incorrect associating! If has not output with id ",
                      out_descr->m_output_index);
         auto res = outs_from_body[out_descr->m_body_value_index];
-        out[out_descr->m_output_index]->set_shape(res->get_shape());
-        out[out_descr->m_output_index]->write(res->get_data_ptr(), res->get_size_in_bytes());
+        out[out_descr->m_output_index].set_shape(res.get_shape());
+
+        res.copy_to(out[out_descr->m_output_index]);
     }
 }
 }  // namespace if_op
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::If>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    std::vector<std::shared_ptr<ngraph::Function>> bodies;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v8::If>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    std::vector<std::shared_ptr<ov::Model>> bodies;
     for (size_t i = 0; i < op->get_internal_subgraphs_size(); i++) {
         bodies.emplace_back(op->get_function(static_cast<int>(i)));
     }
@@ -171,46 +171,46 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::If>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::If>(std::shared_ptr<ngraph::Node> node,
-                                       const ngraph::HostTensorVector& outputs,
-                                       const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::If>(std::shared_ptr<ov::Node> node,
+                                   ov::TensorVector& outputs,
+                                   const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::If>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::If>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
diff --git a/src/plugins/template/backend/ops/interpolate.cpp b/src/plugins/template/backend/ops/interpolate.cpp
index c2f760c00524ba..16d3a425f5b486 100644
--- a/src/plugins/template/backend/ops/interpolate.cpp
+++ b/src/plugins/template/backend/ops/interpolate.cpp
@@ -7,39 +7,39 @@
 #include "evaluate_node.hpp"
 #include "interpolate_shape_inference.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Interpolate>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    ngraph::element::Type input_et = op->get_input_element_type(0);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Interpolate>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    ov::element::Type input_et = op->get_input_element_type(0);
     switch (input_et) {
-    case ngraph::element::Type_t::f64:
-        ov::reference::interpolate<double>(inputs[0]->get_data_ptr<double>(),
+    case ov::element::f64:
+        ov::reference::interpolate<double>(inputs[0].data<double>(),
                                            op->get_input_partial_shape(0),
-                                           outputs[0]->get_data_ptr<double>(),
+                                           outputs[0].data<double>(),
                                            op->get_output_shape(0),
                                            op->get_attrs());
         break;
-    case ngraph::element::Type_t::f32:
-        ov::reference::interpolate<float>(inputs[0]->get_data_ptr<float>(),
+    case ov::element::f32:
+        ov::reference::interpolate<float>(inputs[0].data<float>(),
                                           op->get_input_partial_shape(0),
-                                          outputs[0]->get_data_ptr<float>(),
+                                          outputs[0].data<float>(),
                                           op->get_output_shape(0),
                                           op->get_attrs());
         break;
-    case ngraph::element::Type_t::f16:
-        ov::reference::interpolate<ngraph::float16>(inputs[0]->get_data_ptr<ngraph::float16>(),
-                                                    op->get_input_partial_shape(0),
-                                                    outputs[0]->get_data_ptr<ngraph::float16>(),
-                                                    op->get_output_shape(0),
-                                                    op->get_attrs());
+    case ov::element::f16:
+        ov::reference::interpolate<ov::float16>(inputs[0].data<ov::float16>(),
+                                                op->get_input_partial_shape(0),
+                                                outputs[0].data<ov::float16>(),
+                                                op->get_output_shape(0),
+                                                op->get_attrs());
         break;
-    case ngraph::element::Type_t::bf16:
-        ov::reference::interpolate<ngraph::bfloat16>(inputs[0]->get_data_ptr<ngraph::bfloat16>(),
-                                                     op->get_input_partial_shape(0),
-                                                     outputs[0]->get_data_ptr<ngraph::bfloat16>(),
-                                                     op->get_output_shape(0),
-                                                     op->get_attrs());
+    case ov::element::bf16:
+        ov::reference::interpolate<ov::bfloat16>(inputs[0].data<ov::bfloat16>(),
+                                                 op->get_input_partial_shape(0),
+                                                 outputs[0].data<ov::bfloat16>(),
+                                                 op->get_output_shape(0),
+                                                 op->get_attrs());
         break;
     default:;
     }
@@ -47,78 +47,46 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::Interpolate>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Interpolate>(std::shared_ptr<ngraph::Node> node,
-                                                const ngraph::HostTensorVector& outputs,
-                                                const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Interpolate>(std::shared_ptr<ov::Node> node,
+                                            ov::TensorVector& outputs,
+                                            const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Interpolate>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -129,7 +97,7 @@ namespace eval {
 namespace interpolate {
 // The helpers below are similar to the internal utils used in evaluate method of v4::Intepolate core op
 // Those functions can be unified and moved to a common place
-std::vector<int64_t> get_axes_vector(const ngraph::HostTensorVector& args,
+std::vector<int64_t> get_axes_vector(const ov::TensorVector& args,
                                      size_t default_size,
                                      size_t axes_port,
                                      size_t max_num_of_ports) {
@@ -138,18 +106,18 @@ std::vector<int64_t> get_axes_vector(const ngraph::HostTensorVector& args,
 
     if (num_of_inputs == max_num_of_ports) {
         auto axes_arg = args[axes_port];
-        size_t num_of_axes = args[axes_port]->get_shape()[0];
+        size_t num_of_axes = args[axes_port].get_shape()[0];
         axes.reserve(num_of_axes);
 
-        if (axes_arg->get_element_type() == ov::element::i64) {
-            int64_t* axes_ptr = axes_arg->get_data_ptr<int64_t>();
+        if (axes_arg.get_element_type() == ov::element::i64) {
+            int64_t* axes_ptr = axes_arg.data<int64_t>();
             axes.insert(axes.end(), axes_ptr, axes_ptr + num_of_axes);
-        } else if (axes_arg->get_element_type() == ov::element::i32) {
-            int32_t* axes_ptr = axes_arg->get_data_ptr<int32_t>();
+        } else if (axes_arg.get_element_type() == ov::element::i32) {
+            int32_t* axes_ptr = axes_arg.data<int32_t>();
             for (size_t i = 0; i < num_of_axes; ++i)
                 axes.push_back(axes_ptr[i]);
         } else {
-            OPENVINO_ASSERT(false, "Failed to process ", axes_arg->get_element_type());
+            OPENVINO_THROW("Failed to process ", axes_arg.get_element_type());
         }
     } else {
         for (size_t i = 0; i < default_size; ++i) {
@@ -160,28 +128,28 @@ std::vector<int64_t> get_axes_vector(const ngraph::HostTensorVector& args,
     return axes;
 }
 
-std::vector<int64_t> get_target_shape_vector(const ngraph::HostTensorVector& args,
+std::vector<int64_t> get_target_shape_vector(const ov::TensorVector& args,
                                              size_t num_of_axes,
                                              size_t target_shape_port = 1) {
     std::vector<int64_t> target_shape;
     target_shape.reserve(num_of_axes);
 
     auto target_shape_arg = args[target_shape_port];
-    if (target_shape_arg->get_element_type() == ov::element::i64) {
-        int64_t* target_shape_ptr = target_shape_arg->get_data_ptr<int64_t>();
+    if (target_shape_arg.get_element_type() == ov::element::i64) {
+        int64_t* target_shape_ptr = target_shape_arg.data<int64_t>();
         target_shape.insert(target_shape.end(), target_shape_ptr, target_shape_ptr + num_of_axes);
-    } else if (target_shape_arg->get_element_type() == ov::element::i32) {
-        int32_t* target_shape_ptr = target_shape_arg->get_data_ptr<int32_t>();
+    } else if (target_shape_arg.get_element_type() == ov::element::i32) {
+        int32_t* target_shape_ptr = target_shape_arg.data<int32_t>();
         for (size_t i = 0; i < num_of_axes; ++i)
             target_shape.push_back(target_shape_ptr[i]);
     } else {
-        OPENVINO_ASSERT(false, "Failed to process ", target_shape_arg->get_element_type());
+        OPENVINO_THROW("Failed to process ", target_shape_arg.get_element_type());
     }
 
     return target_shape;
 }
 
-std::vector<float> get_scales_vector(const ngraph::HostTensorVector& args,
+std::vector<float> get_scales_vector(const ov::TensorVector& args,
                                      const ov::Shape& input_shape,
                                      const ov::op::util::InterpolateBase::InterpolateAttrs& attrs,
                                      std::vector<int64_t> axes,
@@ -189,7 +157,7 @@ std::vector<float> get_scales_vector(const ngraph::HostTensorVector& args,
     std::vector<float> scales;
     size_t num_of_axes = axes.size();
     if (attrs.shape_calculation_mode == ov::op::util::InterpolateBase::ShapeCalcMode::SCALES) {
-        float* scales_ptr = args[scales_port]->get_data_ptr<float>();
+        float* scales_ptr = args[scales_port].data<float>();
         scales.insert(scales.end(), scales_ptr, scales_ptr + num_of_axes);
     } else {
         auto target_shape = get_target_shape_vector(args, num_of_axes);
@@ -212,7 +180,7 @@ static void pad_input_data(const uint8_t* data_ptr,
     ov::CoordinateTransform input_transform(input_shape);
     ov::CoordinateTransform padded_transform(padded_input_shape);
 
-    for (const ngraph::Coordinate& input_coord : input_transform) {
+    for (const ov::Coordinate& input_coord : input_transform) {
         auto padded_coord = input_coord;
         size_t i = 0;
         for (size_t pad : pads_begin) {
@@ -228,8 +196,8 @@ static void pad_input_data(const uint8_t* data_ptr,
 
 namespace v11 {
 bool evaluate_interpolate(const std::shared_ptr<ov::op::v11::Interpolate>& op,
-                          const ngraph::HostTensorVector& outputs,
-                          const ngraph::HostTensorVector& inputs) {
+                          ov::TensorVector& outputs,
+                          const ov::TensorVector& inputs) {
     using namespace ov;
 
     constexpr size_t data_port = 0;
@@ -237,16 +205,16 @@ bool evaluate_interpolate(const std::shared_ptr<ov::op::v11::Interpolate>& op,
     constexpr size_t axes_port = 2;
     constexpr size_t max_num_of_ports = 3;
 
-    element::Type input_et = inputs[0]->get_element_type();
+    element::Type input_et = inputs[0].get_element_type();
     size_t type_size = input_et.size();
 
-    PartialShape input_shape{inputs[data_port]->get_shape()};
+    PartialShape input_shape{inputs[data_port].get_shape()};
     auto m_attrs = op->get_attrs();
 
     const auto ta = make_tensor_accessor(inputs);
     auto input_shapes = std::vector<PartialShape>();
-    std::transform(inputs.cbegin(), inputs.cend(), std::back_inserter(input_shapes), [](const HostTensorPtr& ht) {
-        return ht->get_shape();
+    std::transform(inputs.cbegin(), inputs.cend(), std::back_inserter(input_shapes), [](const ov::Tensor& ht) {
+        return ht.get_shape();
     });
     const auto output_shape =
         ov::op::v11::shape_infer(op.get(), input_shapes, m_attrs.pads_begin, m_attrs.pads_end, ta).front();
@@ -256,17 +224,16 @@ bool evaluate_interpolate(const std::shared_ptr<ov::op::v11::Interpolate>& op,
         padded_input_shape.emplace_back(m_attrs.pads_begin[i] + m_attrs.pads_end[i] + input_shape[i].get_length());
     }
 
-    auto axes = get_axes_vector(inputs, inputs[1]->get_shape()[0], axes_port, max_num_of_ports);
+    auto axes = get_axes_vector(inputs, inputs[1].get_shape()[0], axes_port, max_num_of_ports);
     auto scales = get_scales_vector(inputs, padded_input_shape, m_attrs, axes, scales_sizes_port);
 
     Shape out_shape = output_shape.to_shape();
-    outputs[0]->set_shape(out_shape);
-    outputs[0]->set_element_type(input_et);
+    outputs[0].set_shape(out_shape);
 
     size_t bytes_in_padded_input = shape_size(padded_input_shape) * type_size;
     std::vector<uint8_t> padded_input_data(bytes_in_padded_input, 0);
 
-    const uint8_t* data_ptr = inputs[0]->get_data_ptr<uint8_t>();
+    const uint8_t* data_ptr = static_cast<uint8_t*>(inputs[0].data());
     uint8_t* padded_data_ptr = padded_input_data.data();
 
     pad_input_data(data_ptr,
@@ -277,57 +244,57 @@ bool evaluate_interpolate(const std::shared_ptr<ov::op::v11::Interpolate>& op,
                    m_attrs.pads_begin);
 
     switch (input_et) {
-    case element::Type_t::f32:
+    case element::f32:
         ov::reference::interpolate<float>(reinterpret_cast<float*>(padded_data_ptr),
                                           padded_input_shape,
                                           scales,
                                           axes,
-                                          outputs[0]->get_data_ptr<float>(),
+                                          outputs[0].data<float>(),
                                           out_shape,
                                           m_attrs);
         break;
-    case element::Type_t::bf16:
+    case element::bf16:
         ov::reference::interpolate<bfloat16>(reinterpret_cast<bfloat16*>(padded_data_ptr),
                                              padded_input_shape,
                                              scales,
                                              axes,
-                                             outputs[0]->get_data_ptr<bfloat16>(),
+                                             outputs[0].data<bfloat16>(),
                                              out_shape,
                                              m_attrs);
         break;
-    case element::Type_t::f16:
+    case element::f16:
         ov::reference::interpolate<float16>(reinterpret_cast<float16*>(padded_data_ptr),
                                             padded_input_shape,
                                             scales,
                                             axes,
-                                            outputs[0]->get_data_ptr<float16>(),
+                                            outputs[0].data<float16>(),
                                             out_shape,
                                             m_attrs);
         break;
-    case element::Type_t::u8:
+    case element::u8:
         ov::reference::interpolate<uint8_t>(reinterpret_cast<uint8_t*>(padded_data_ptr),
                                             padded_input_shape,
                                             scales,
                                             axes,
-                                            outputs[0]->get_data_ptr<uint8_t>(),
+                                            outputs[0].data<uint8_t>(),
                                             out_shape,
                                             m_attrs);
         break;
-    case element::Type_t::i8:
+    case element::i8:
         ov::reference::interpolate<int8_t>(reinterpret_cast<int8_t*>(padded_data_ptr),
                                            padded_input_shape,
                                            scales,
                                            axes,
-                                           outputs[0]->get_data_ptr<int8_t>(),
+                                           outputs[0].data<int8_t>(),
                                            out_shape,
                                            m_attrs);
         break;
-    case element::Type_t::i32:
+    case element::i32:
         ov::reference::interpolate<int32_t>(reinterpret_cast<int32_t*>(padded_data_ptr),
                                             padded_input_shape,
                                             scales,
                                             axes,
-                                            outputs[0]->get_data_ptr<int32_t>(),
+                                            outputs[0].data<int32_t>(),
                                             out_shape,
                                             m_attrs);
         break;
@@ -340,88 +307,55 @@ bool evaluate_interpolate(const std::shared_ptr<ov::op::v11::Interpolate>& op,
 }  // namespace interpolate
 }  // namespace eval
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v11::Interpolate>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v11::Interpolate>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     return eval::interpolate::v11::evaluate_interpolate(op, outputs, inputs);
 }
 
 template <>
-bool evaluate_node<ngraph::op::v11::Interpolate>(std::shared_ptr<ngraph::Node> node,
-                                                 const ngraph::HostTensorVector& outputs,
-                                                 const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v11::Interpolate>(std::shared_ptr<ov::Node> node,
+                                             ov::TensorVector& outputs,
+                                             const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v11::Interpolate>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v11::Interpolate>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/irdft.cpp b/src/plugins/template/backend/ops/irdft.cpp
index 65a6093a2fda4e..4bf662d4e7b80c 100644
--- a/src/plugins/template/backend/ops/irdft.cpp
+++ b/src/plugins/template/backend/ops/irdft.cpp
@@ -12,18 +12,18 @@ namespace irfft_v9 {
 struct InfoForIRFFT9 {
     std::vector<float> input_data;
     std::vector<int64_t> axes_data;
-    ngraph::Shape input_data_shape;
-    ngraph::Shape axes_data_shape;
-    ngraph::Shape fft_output_shape;
-    ngraph::Shape output_shape;
+    ov::Shape input_data_shape;
+    ov::Shape axes_data_shape;
+    ov::Shape fft_output_shape;
+    ov::Shape output_shape;
     int64_t last_signal_size;
 };
 
-InfoForIRFFT9 get_info_for_irfft9_eval(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForIRFFT9 get_info_for_irfft9_eval(const ov::TensorVector& inputs) {
     InfoForIRFFT9 result;
 
-    result.input_data_shape = inputs[0]->get_shape();
-    result.axes_data_shape = inputs[1]->get_shape();
+    result.input_data_shape = inputs[0].get_shape();
+    result.axes_data_shape = inputs[1].get_shape();
     result.input_data = get_floats(inputs[0], result.input_data_shape);
     result.axes_data = get_integers(inputs[1], result.axes_data_shape);
 
@@ -64,14 +64,12 @@ InfoForIRFFT9 get_info_for_irfft9_eval(const std::vector<std::shared_ptr<ngraph:
 }
 }  // namespace irfft_v9
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v9::IRDFT>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v9::IRDFT>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
     auto info = irfft_v9::get_info_for_irfft9_eval(inputs);
-    outputs[0]->set_shape(info.output_shape);
+    outputs[0].set_shape(info.output_shape);
 
-    std::vector<float> irfft_result(ngraph::shape_size(info.output_shape), 0.0f);
+    std::vector<float> irfft_result(ov::shape_size(info.output_shape), 0.0f);
     ov::reference::irdft(info.input_data,
                          info.input_data_shape,
                          info.axes_data,
@@ -86,50 +84,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::IRDFT>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v9::IRDFT>(std::shared_ptr<ngraph::Node> node,
-                                          const ngraph::HostTensorVector& outputs,
-                                          const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v9::IRDFT>(std::shared_ptr<ov::Node> node,
+                                      ov::TensorVector& outputs,
+                                      const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v9::IRDFT>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/is_finite.cpp b/src/plugins/template/backend/ops/is_finite.cpp
index 2ec4826a50b7ac..3f081149cf0ea7 100644
--- a/src/plugins/template/backend/ops/is_finite.cpp
+++ b/src/plugins/template/backend/ops/is_finite.cpp
@@ -2,36 +2,37 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/is_finite.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v10::IsFinite>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    ngraph::element::Type input_et = op->get_input_element_type(0);
+#include "evaluate_node.hpp"
+#include "openvino/core/type/element_type.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v10::IsFinite>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using BT = typename ov::element_type_traits<ov::element::boolean>::value_type;
+    ov::element::Type input_et = op->get_input_element_type(0);
     switch (input_et) {
-    case ngraph::element::Type_t::f64:
-        ov::reference::is_finite<double>(inputs[0]->get_data_ptr<double>(),
-                                         outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                                         ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f64:
+        ov::reference::is_finite<double>(inputs[0].data<double>(),
+                                         outputs[0].data<BT>(),
+                                         ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::f32:
-        ov::reference::is_finite<float>(inputs[0]->get_data_ptr<float>(),
-                                        outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                                        ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f32:
+        ov::reference::is_finite<float>(inputs[0].data<float>(),
+                                        outputs[0].data<BT>(),
+                                        ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::f16:
-        ov::reference::is_finite<ngraph::float16>(inputs[0]->get_data_ptr<ngraph::float16>(),
-                                                  outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                                                  ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f16:
+        ov::reference::is_finite<ov::float16>(inputs[0].data<ov::float16>(),
+                                              outputs[0].data<BT>(),
+                                              ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::bf16:
-        ov::reference::is_finite<ngraph::bfloat16>(inputs[0]->get_data_ptr<ngraph::bfloat16>(),
-                                                   outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                                                   ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::bf16:
+        ov::reference::is_finite<ov::bfloat16>(inputs[0].data<ov::bfloat16>(),
+                                               outputs[0].data<BT>(),
+                                               ov::shape_size(inputs[0].get_shape()));
         break;
     default:
         return false;
@@ -40,70 +41,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v10::IsFinite>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v10::IsFinite>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v10::IsFinite>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v10::IsFinite>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v10::IsFinite>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/is_inf.cpp b/src/plugins/template/backend/ops/is_inf.cpp
index 4509ced254446d..40255efce351b8 100644
--- a/src/plugins/template/backend/ops/is_inf.cpp
+++ b/src/plugins/template/backend/ops/is_inf.cpp
@@ -2,39 +2,39 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/is_inf.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v10::IsInf>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    ngraph::element::Type input_et = op->get_input_element_type(0);
+#include "evaluate_node.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v10::IsInf>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using BT = typename ov::element_type_traits<ov::element::boolean>::value_type;
+    ov::element::Type input_et = op->get_input_element_type(0);
     switch (input_et) {
-    case ngraph::element::Type_t::f64:
-        ov::reference::is_inf(inputs[0]->get_data_ptr<double>(),
-                              outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                              ngraph::shape_size(inputs[0]->get_shape()),
+    case ov::element::f64:
+        ov::reference::is_inf(inputs[0].data<double>(),
+                              outputs[0].data<BT>(),
+                              ov::shape_size(inputs[0].get_shape()),
                               op->get_attributes());
         break;
-    case ngraph::element::Type_t::f32:
-        ov::reference::is_inf(inputs[0]->get_data_ptr<float>(),
-                              outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                              ngraph::shape_size(inputs[0]->get_shape()),
+    case ov::element::f32:
+        ov::reference::is_inf(inputs[0].data<float>(),
+                              outputs[0].data<BT>(),
+                              ov::shape_size(inputs[0].get_shape()),
                               op->get_attributes());
         break;
-    case ngraph::element::Type_t::f16:
-        ov::reference::is_inf(inputs[0]->get_data_ptr<ngraph::float16>(),
-                              outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                              ngraph::shape_size(inputs[0]->get_shape()),
+    case ov::element::f16:
+        ov::reference::is_inf(inputs[0].data<ov::float16>(),
+                              outputs[0].data<BT>(),
+                              ov::shape_size(inputs[0].get_shape()),
                               op->get_attributes());
         break;
-    case ngraph::element::Type_t::bf16:
-        ov::reference::is_inf(inputs[0]->get_data_ptr<ngraph::bfloat16>(),
-                              outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                              ngraph::shape_size(inputs[0]->get_shape()),
+    case ov::element::bf16:
+        ov::reference::is_inf(inputs[0].data<ov::bfloat16>(),
+                              outputs[0].data<BT>(),
+                              ov::shape_size(inputs[0].get_shape()),
                               op->get_attributes());
         break;
     default:
@@ -44,50 +44,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v10::IsInf>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v10::IsInf>(std::shared_ptr<ngraph::Node> node,
-                                           const ngraph::HostTensorVector& outputs,
-                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v10::IsInf>(std::shared_ptr<ov::Node> node,
+                                       ov::TensorVector& outputs,
+                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v10::IsInf>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/is_nan.cpp b/src/plugins/template/backend/ops/is_nan.cpp
index 87ba4c34328be4..c188256538e550 100644
--- a/src/plugins/template/backend/ops/is_nan.cpp
+++ b/src/plugins/template/backend/ops/is_nan.cpp
@@ -2,36 +2,32 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/is_nan.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v10::IsNaN>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    ngraph::element::Type input_et = op->get_input_element_type(0);
+#include "evaluate_node.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v10::IsNaN>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using BT = typename ov::element_type_traits<ov::element::boolean>::value_type;
+    ov::element::Type input_et = op->get_input_element_type(0);
     switch (input_et) {
-    case ngraph::element::Type_t::f64:
-        ov::reference::is_nan(inputs[0]->get_data_ptr<double>(),
-                              outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                              ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f64:
+        ov::reference::is_nan(inputs[0].data<double>(), outputs[0].data<BT>(), ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::f32:
-        ov::reference::is_nan(inputs[0]->get_data_ptr<float>(),
-                              outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                              ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f32:
+        ov::reference::is_nan(inputs[0].data<float>(), outputs[0].data<BT>(), ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::f16:
-        ov::reference::is_nan(inputs[0]->get_data_ptr<ngraph::float16>(),
-                              outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                              ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f16:
+        ov::reference::is_nan(inputs[0].data<ov::float16>(),
+                              outputs[0].data<BT>(),
+                              ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::bf16:
-        ov::reference::is_nan(inputs[0]->get_data_ptr<ngraph::bfloat16>(),
-                              outputs[0]->get_data_ptr<ngraph::element::Type_t::boolean>(),
-                              ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::bf16:
+        ov::reference::is_nan(inputs[0].data<ov::bfloat16>(),
+                              outputs[0].data<BT>(),
+                              ov::shape_size(inputs[0].get_shape()));
         break;
     default:
         return false;
@@ -40,50 +36,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v10::IsNaN>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v10::IsNaN>(std::shared_ptr<ngraph::Node> node,
-                                           const ngraph::HostTensorVector& outputs,
-                                           const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v10::IsNaN>(std::shared_ptr<ov::Node> node,
+                                       ov::TensorVector& outputs,
+                                       const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v10::IsNaN>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/log.cpp b/src/plugins/template/backend/ops/log.cpp
index c6b988dc66a16f..dea640a558443c 100644
--- a/src/plugins/template/backend/ops/log.cpp
+++ b/src/plugins/template/backend/ops/log.cpp
@@ -6,60 +6,55 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Log>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::log<T>(inputs[0]->get_data_ptr<T>(),
-                          outputs[0]->get_data_ptr<T>(),
-                          ngraph::shape_size(inputs[0]->get_shape()));
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Log>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::log<T>(inputs[0].data<T>(), outputs[0].data<T>(), ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Log>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Log>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Log>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Log>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/log_softmax.cpp b/src/plugins/template/backend/ops/log_softmax.cpp
index 415171d1db6caa..aa34a3905cb64c 100644
--- a/src/plugins/template/backend/ops/log_softmax.cpp
+++ b/src/plugins/template/backend/ops/log_softmax.cpp
@@ -6,97 +6,64 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v5::LogSoftmax>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v5::LogSoftmax>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
     int64_t i_axis = op->get_axis();
     if (i_axis < 0) {
-        i_axis += inputs[0]->get_partial_shape().rank().get_length();
+        i_axis += inputs[0].get_shape().size();
     }
-    ov::reference::log_softmax<T>(inputs[0]->get_data_ptr<const T>(),
-                                  outputs[0]->get_data_ptr<T>(),
+    ov::reference::log_softmax<T>(inputs[0].data<const T>(),
+                                  outputs[0].data<T>(),
                                   op->get_output_shape(0),
-                                  ngraph::AxisSet{(size_t)i_axis});
+                                  ov::AxisSet{(size_t)i_axis});
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v5::LogSoftmax>(std::shared_ptr<ngraph::Node> node,
-                                               const ngraph::HostTensorVector& outputs,
-                                               const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v5::LogSoftmax>(std::shared_ptr<ov::Node> node,
+                                           ov::TensorVector& outputs,
+                                           const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v5::LogSoftmax>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v5::LogSoftmax>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/lrn.cpp b/src/plugins/template/backend/ops/lrn.cpp
index 5522a695bea922..4c5aca69a5f0af 100644
--- a/src/plugins/template/backend/ops/lrn.cpp
+++ b/src/plugins/template/backend/ops/lrn.cpp
@@ -6,15 +6,13 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::LRN>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::lrn<T>(inputs[0]->get_data_ptr<ET>(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::LRN>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::lrn<T>(inputs[0].data<T>(),
                           op->get_reduction_axes(),
-                          outputs[0]->get_data_ptr<ET>(),
-                          inputs[0]->get_shape(),
+                          outputs[0].data<T>(),
+                          inputs[0].get_shape(),
                           op->get_alpha(),
                           op->get_beta(),
                           op->get_bias(),
@@ -23,48 +21,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::LRN>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::LRN>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::LRN>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::LRN>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/lstm_cell.cpp b/src/plugins/template/backend/ops/lstm_cell.cpp
index 12f81d29a26b13..1615c136cb3606 100644
--- a/src/plugins/template/backend/ops/lstm_cell.cpp
+++ b/src/plugins/template/backend/ops/lstm_cell.cpp
@@ -2,30 +2,29 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/lstm_cell.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v4::LSTMCell>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::lstm_cell<T>(inputs[0]->get_data_ptr<ET>(),
-                                inputs[0]->get_shape(),
-                                inputs[1]->get_data_ptr<ET>(),
-                                inputs[1]->get_shape(),
-                                inputs[2]->get_data_ptr<ET>(),
-                                inputs[2]->get_shape(),
-                                inputs[3]->get_data_ptr<ET>(),
-                                inputs[3]->get_shape(),
-                                inputs[4]->get_data_ptr<ET>(),
-                                inputs[4]->get_shape(),
-                                inputs[5]->get_data_ptr<ET>(),
-                                inputs[5]->get_shape(),
-                                outputs[0]->get_data_ptr<ET>(),
-                                outputs[1]->get_data_ptr<ET>(),
+#include "evaluate_node.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v4::LSTMCell>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::lstm_cell<T>(inputs[0].data<T>(),
+                                inputs[0].get_shape(),
+                                inputs[1].data<T>(),
+                                inputs[1].get_shape(),
+                                inputs[2].data<T>(),
+                                inputs[2].get_shape(),
+                                inputs[3].data<T>(),
+                                inputs[3].get_shape(),
+                                inputs[4].data<T>(),
+                                inputs[4].get_shape(),
+                                inputs[5].data<T>(),
+                                inputs[5].get_shape(),
+                                outputs[0].data<T>(),
+                                outputs[1].data<T>(),
                                 op->get_activations()[0],
                                 op->get_activations()[1],
                                 op->get_activations()[2],
@@ -33,27 +32,27 @@ bool evaluate(const std::shared_ptr<ngraph::op::v4::LSTMCell>& op,
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::LSTMCell>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::lstm_cell_v1<T>(inputs[0]->get_data_ptr<ET>(),
-                                   inputs[0]->get_shape(),
-                                   inputs[1]->get_data_ptr<ET>(),
-                                   inputs[1]->get_shape(),
-                                   inputs[2]->get_data_ptr<ET>(),
-                                   inputs[2]->get_shape(),
-                                   inputs[3]->get_data_ptr<ET>(),
-                                   inputs[3]->get_shape(),
-                                   inputs[4]->get_data_ptr<ET>(),
-                                   inputs[4]->get_shape(),
-                                   inputs[5]->get_data_ptr<ET>(),
-                                   inputs[5]->get_shape(),
-                                   inputs[6]->get_data_ptr<ET>(),
-                                   inputs[6]->get_shape(),
-                                   outputs[0]->get_data_ptr<ET>(),
-                                   outputs[1]->get_data_ptr<ET>(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::LSTMCell>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::lstm_cell_v1<T>(inputs[0].data<T>(),
+                                   inputs[0].get_shape(),
+                                   inputs[1].data<T>(),
+                                   inputs[1].get_shape(),
+                                   inputs[2].data<T>(),
+                                   inputs[2].get_shape(),
+                                   inputs[3].data<T>(),
+                                   inputs[3].get_shape(),
+                                   inputs[4].data<T>(),
+                                   inputs[4].get_shape(),
+                                   inputs[5].data<T>(),
+                                   inputs[5].get_shape(),
+                                   inputs[6].data<T>(),
+                                   inputs[6].get_shape(),
+                                   outputs[0].data<T>(),
+                                   outputs[1].data<T>(),
                                    op->get_activations()[0],
                                    op->get_activations()[1],
                                    op->get_activations()[2],
@@ -64,50 +63,46 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::LSTMCell>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v4::LSTMCell>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v4::LSTMCell>(std::shared_ptr<ov::Node> node,
+                                         ov::TensorVector& outputs,
+                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v4::LSTMCell>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -115,50 +110,46 @@ bool evaluate_node<ngraph::op::v4::LSTMCell>(std::shared_ptr<ngraph::Node> node,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::LSTMCell>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::LSTMCell>(std::shared_ptr<ov::Node> node,
+                                         ov::TensorVector& outputs,
+                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::LSTMCell>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
diff --git a/src/plugins/template/backend/ops/matrix_nms.cpp b/src/plugins/template/backend/ops/matrix_nms.cpp
index 3e13c542ec43b0..abf78dac65aa81 100644
--- a/src/plugins/template/backend/ops/matrix_nms.cpp
+++ b/src/plugins/template/backend/ops/matrix_nms.cpp
@@ -6,15 +6,17 @@
 
 #include "evaluate_node.hpp"
 #include "evaluates_map.hpp"
+#include "openvino/core/type/element_type.hpp"
 #include "openvino/reference/utils/nms_common.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 namespace matrix_nms_v8 {
-using SortResultType = ngraph::op::v8::MatrixNms::SortResultType;
+using SortResultType = ov::op::v8::MatrixNms::SortResultType;
 struct InfoForNMS {
-    ngraph::Shape selected_outputs_shape;
-    ngraph::Shape selected_indices_shape;
-    ngraph::Shape boxes_shape;
-    ngraph::Shape scores_shape;
+    ov::Shape selected_outputs_shape;
+    ov::Shape selected_indices_shape;
+    ov::Shape boxes_shape;
+    ov::Shape scores_shape;
     std::vector<float> boxes_data;
     std::vector<float> scores_data;
     size_t selected_outputs_shape_size;
@@ -24,50 +26,42 @@ struct InfoForNMS {
 constexpr size_t boxes_port = 0;
 constexpr size_t scores_port = 1;
 
-ngraph::PartialShape infer_selected_outputs_shape(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs,
-                                                  int nms_top_k,
-                                                  int keep_top_k) {
-    const auto boxes_ps = inputs[boxes_port]->get_partial_shape();
-    const auto scores_ps = inputs[scores_port]->get_partial_shape();
-
-    ngraph::PartialShape result = {ngraph::Dimension::dynamic(), 6};
-
-    if (boxes_ps.rank().is_static() && scores_ps.rank().is_static()) {
-        const auto num_boxes_boxes = boxes_ps[1];
-        if (num_boxes_boxes.is_static() && scores_ps[0].is_static() && scores_ps[1].is_static()) {
-            const auto num_boxes = num_boxes_boxes.get_length();
-            const auto num_classes = scores_ps[1].get_length();
-            int64_t max_output_boxes_per_class = 0;
-            if (nms_top_k >= 0)
-                max_output_boxes_per_class = std::min(num_boxes, (int64_t)nms_top_k);
-            else
-                max_output_boxes_per_class = num_boxes;
-
-            auto max_output_boxes_per_batch = max_output_boxes_per_class * num_classes;
-            if (keep_top_k >= 0)
-                max_output_boxes_per_batch = std::min(max_output_boxes_per_batch, (int64_t)keep_top_k);
-
-            result[0] = max_output_boxes_per_batch * scores_ps[0].get_length();
-        }
+ov::PartialShape infer_selected_outputs_shape(const ov::TensorVector& inputs, int nms_top_k, int keep_top_k) {
+    const auto boxes_ps = inputs[boxes_port].get_shape();
+    const auto scores_ps = inputs[scores_port].get_shape();
+
+    ov::PartialShape result = {ov::Dimension::dynamic(), 6};
+
+    if (ov::shape_size(boxes_ps) && ov::shape_size(scores_ps)) {
+        const auto num_boxes = boxes_ps[1];
+        const auto num_classes = scores_ps[1];
+        size_t max_output_boxes_per_class = 0;
+        if (nms_top_k >= 0)
+            max_output_boxes_per_class = std::min(num_boxes, (size_t)nms_top_k);
+        else
+            max_output_boxes_per_class = num_boxes;
+
+        auto max_output_boxes_per_batch = max_output_boxes_per_class * num_classes;
+        if (keep_top_k >= 0)
+            max_output_boxes_per_batch = std::min(max_output_boxes_per_batch, (size_t)keep_top_k);
+
+        result[0] = max_output_boxes_per_batch * scores_ps[0];
     }
 
     return result;
 }
 
-std::vector<float> prepare_boxes_data(const std::shared_ptr<ngraph::HostTensor>& boxes,
-                                      const ngraph::Shape& boxes_shape) {
+std::vector<float> prepare_boxes_data(const ov::Tensor& boxes, const ov::Shape& boxes_shape) {
     auto result = get_floats(boxes, boxes_shape);
     return result;
 }
 
-std::vector<float> prepare_scores_data(const std::shared_ptr<ngraph::HostTensor>& scores,
-                                       const ngraph::Shape& scores_shape) {
+std::vector<float> prepare_scores_data(const ov::Tensor& scores, const ov::Shape& scores_shape) {
     auto result = get_floats(scores, scores_shape);
     return result;
 }
 
-InfoForNMS get_info_for_nms_eval(const std::shared_ptr<ngraph::op::v8::MatrixNms>& nms,
-                                 const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForNMS get_info_for_nms_eval(const std::shared_ptr<ov::op::v8::MatrixNms>& nms, const ov::TensorVector& inputs) {
     InfoForNMS result;
     const auto& nms_attrs = nms->get_attrs();
     const auto nms_top_k = nms_attrs.nms_top_k;
@@ -77,23 +71,23 @@ InfoForNMS get_info_for_nms_eval(const std::shared_ptr<ngraph::op::v8::MatrixNms
     result.selected_outputs_shape = selected_outputs_shape.to_shape();
     result.selected_indices_shape = {result.selected_outputs_shape[0], 1};
 
-    result.boxes_shape = inputs[boxes_port]->get_shape();
-    result.scores_shape = inputs[scores_port]->get_shape();
+    result.boxes_shape = inputs[boxes_port].get_shape();
+    result.scores_shape = inputs[scores_port].get_shape();
 
     result.boxes_data = prepare_boxes_data(inputs[boxes_port], result.boxes_shape);
     result.scores_data = prepare_scores_data(inputs[scores_port], result.scores_shape);
 
-    result.selected_outputs_shape_size = ngraph::shape_size(result.selected_outputs_shape);
-    result.selected_indices_shape_size = ngraph::shape_size(result.selected_indices_shape);
+    result.selected_outputs_shape_size = ov::shape_size(result.selected_outputs_shape);
+    result.selected_indices_shape_size = ov::shape_size(result.selected_indices_shape);
 
     return result;
 }
 }  // namespace matrix_nms_v8
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::MatrixNms>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v8::MatrixNms>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = matrix_nms_v8::get_info_for_nms_eval(op, inputs);
 
     std::vector<float> selected_outputs(info.selected_outputs_shape_size);
@@ -116,15 +110,15 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::MatrixNms>& op,
     void* prois;
     size_t num_selected = static_cast<size_t>(std::accumulate(valid_outputs.begin(), valid_outputs.end(), size_t(0)));
 
-    outputs[0]->set_shape({num_selected, 6});
-    prois = outputs[0]->get_data_ptr();
+    outputs[0].set_shape({num_selected, 6});
+    prois = outputs[0].data();
 
     if (outputs.size() >= 2) {
-        outputs[1]->set_shape({num_selected, 1});
-        pscores = outputs[1]->get_data_ptr();
+        outputs[1].set_shape({num_selected, 1});
+        pscores = outputs[1].data();
     }
     if (outputs.size() >= 3) {
-        pselected_num = outputs[2]->get_data_ptr();
+        pselected_num = outputs[2].data();
     }
 
     ov::reference::nms_common::nms_common_postprocessing(prois,
@@ -139,70 +133,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::MatrixNms>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::MatrixNms>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::MatrixNms>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::MatrixNms>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::MatrixNms>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/mod.cpp b/src/plugins/template/backend/ops/mod.cpp
index a8e4ac1cbc44f7..b1668981a5b46b 100644
--- a/src/plugins/template/backend/ops/mod.cpp
+++ b/src/plugins/template/backend/ops/mod.cpp
@@ -6,63 +6,60 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::Mod>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::mod(inputs[0]->get_data_ptr<const T>(),
-                       inputs[1]->get_data_ptr<const T>(),
-                       outputs[0]->get_data_ptr<T>(),
-                       inputs[0]->get_shape(),
-                       inputs[1]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v1::Mod>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::mod(inputs[0].data<const T>(),
+                       inputs[1].data<const T>(),
+                       outputs[0].data<T>(),
+                       inputs[0].get_shape(),
+                       inputs[1].get_shape(),
                        op->get_autob());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::Mod>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::Mod>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::Mod>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/multiclass_nms.cpp b/src/plugins/template/backend/ops/multiclass_nms.cpp
index e4a3e7f1d5a71c..51d1d6e4cab2ff 100644
--- a/src/plugins/template/backend/ops/multiclass_nms.cpp
+++ b/src/plugins/template/backend/ops/multiclass_nms.cpp
@@ -8,6 +8,7 @@
 #include "evaluates_map.hpp"
 #include "multiclass_nms_shape_inference.hpp"
 #include "openvino/reference/utils/nms_common.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 namespace multiclass_nms {
 using namespace ov;
@@ -27,18 +28,17 @@ struct InfoForNMS {
     size_t selected_numrois_shape_size;
 };
 
-static std::vector<float> prepare_boxes_data(const std::shared_ptr<HostTensor>& boxes, const Shape& boxes_shape) {
+static std::vector<float> prepare_boxes_data(const ov::Tensor& boxes, const Shape& boxes_shape) {
     auto result = get_floats(boxes, boxes_shape);
     return result;
 }
 
-static std::vector<float> prepare_scores_data(const std::shared_ptr<HostTensor>& scores, const Shape& scores_shape) {
+static std::vector<float> prepare_scores_data(const ov::Tensor& scores, const Shape& scores_shape) {
     auto result = get_floats(scores, scores_shape);
     return result;
 }
 
-static std::vector<int64_t> prepare_roisnum_data(const std::shared_ptr<HostTensor>& roisnum,
-                                                 const Shape& roisnum_shape) {
+static std::vector<int64_t> prepare_roisnum_data(const ov::Tensor& roisnum, const Shape& roisnum_shape) {
     auto result = get_integers(roisnum, roisnum_shape);
     return result;
 }
@@ -48,14 +48,14 @@ constexpr size_t scores_port = 1;
 constexpr size_t roisnum_port = 2;
 
 InfoForNMS get_info_for_nms_eval(const std::shared_ptr<op::util::MulticlassNmsBase>& nms,
-                                 const std::vector<std::shared_ptr<HostTensor>>& inputs) {
+                                 const ov::TensorVector& inputs) {
     InfoForNMS result;
 
-    const auto boxes_ps = inputs[boxes_port]->get_partial_shape();
-    const auto scores_ps = inputs[scores_port]->get_partial_shape();
+    const auto boxes_ps = inputs[boxes_port].get_shape();
+    const auto scores_ps = inputs[scores_port].get_shape();
     std::vector<PartialShape> input_shapes = {boxes_ps, scores_ps};
     if (nms->get_input_size() == 3) {
-        const auto roisnum_ps = inputs[roisnum_port]->get_partial_shape();
+        const auto roisnum_ps = inputs[roisnum_port].get_shape();
         input_shapes.push_back(roisnum_ps);
     }
 
@@ -65,14 +65,14 @@ InfoForNMS get_info_for_nms_eval(const std::shared_ptr<op::util::MulticlassNmsBa
     result.selected_indices_shape = output_shapes[1].get_max_shape();
     result.selected_numrois_shape = output_shapes[2].to_shape();
 
-    result.boxes_shape = inputs[boxes_port]->get_shape();
-    result.scores_shape = inputs[scores_port]->get_shape();
+    result.boxes_shape = inputs[boxes_port].get_shape();
+    result.scores_shape = inputs[scores_port].get_shape();
 
     result.boxes_data = prepare_boxes_data(inputs[boxes_port], result.boxes_shape);
     result.scores_data = prepare_scores_data(inputs[scores_port], result.scores_shape);
 
     if (inputs.size() == 3) {
-        result.roisnum_shape = inputs[roisnum_port]->get_shape();
+        result.roisnum_shape = inputs[roisnum_port].get_shape();
         result.roisnum_data = prepare_roisnum_data(inputs[roisnum_port], result.roisnum_shape);
     }
 
@@ -84,10 +84,10 @@ InfoForNMS get_info_for_nms_eval(const std::shared_ptr<op::util::MulticlassNmsBa
 }
 }  // namespace multiclass_nms
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v8::MulticlassNms>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v8::MulticlassNms>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = multiclass_nms::get_info_for_nms_eval(op, inputs);
 
     std::vector<float> selected_outputs(info.selected_outputs_shape_size);
@@ -99,7 +99,7 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::MulticlassNms>& op,
                                   info.scores_data.data(),
                                   info.scores_shape,
                                   nullptr,
-                                  ngraph::Shape(),  // won't be used
+                                  ov::Shape(),  // won't be used
                                   op->get_attrs(),
                                   selected_outputs.data(),
                                   info.selected_outputs_shape,
@@ -112,15 +112,15 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::MulticlassNms>& op,
     void* prois;
     size_t num_selected = static_cast<size_t>(std::accumulate(valid_outputs.begin(), valid_outputs.end(), int64_t(0)));
 
-    outputs[0]->set_shape({num_selected, 6});
-    prois = outputs[0]->get_data_ptr();
+    outputs[0].set_shape({num_selected, 6});
+    prois = outputs[0].data();
 
     if (outputs.size() >= 2) {
-        outputs[1]->set_shape({num_selected, 1});
-        pscores = outputs[1]->get_data_ptr();
+        outputs[1].set_shape({num_selected, 1});
+        pscores = outputs[1].data();
     }
     if (outputs.size() >= 3) {
-        pselected_num = outputs[2]->get_data_ptr();
+        pselected_num = outputs[2].data();
     }
 
     ov::reference::nms_common::nms_common_postprocessing(prois,
@@ -135,10 +135,10 @@ bool evaluate(const std::shared_ptr<ngraph::op::v8::MulticlassNms>& op,
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v9::MulticlassNms>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v9::MulticlassNms>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = multiclass_nms::get_info_for_nms_eval(op, inputs);
 
     std::vector<float> selected_outputs(info.selected_outputs_shape_size);
@@ -163,15 +163,15 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::MulticlassNms>& op,
     void* prois;
     size_t num_selected = static_cast<size_t>(std::accumulate(valid_outputs.begin(), valid_outputs.end(), 0));
 
-    outputs[0]->set_shape({num_selected, 6});
-    prois = outputs[0]->get_data_ptr();
+    outputs[0].set_shape({num_selected, 6});
+    prois = outputs[0].data();
 
     if (outputs.size() >= 2) {
-        outputs[1]->set_shape({num_selected, 1});
-        pscores = outputs[1]->get_data_ptr();
+        outputs[1].set_shape({num_selected, 1});
+        pscores = outputs[1].data();
     }
     if (outputs.size() >= 3) {
-        pselected_num = outputs[2]->get_data_ptr();
+        pselected_num = outputs[2].data();
     }
 
     ov::reference::nms_common::nms_common_postprocessing(prois,
@@ -187,78 +187,46 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::MulticlassNms>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v8::MulticlassNms>(std::shared_ptr<ngraph::Node> node,
-                                                  const ngraph::HostTensorVector& outputs,
-                                                  const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v8::MulticlassNms>(std::shared_ptr<ov::Node> node,
+                                              ov::TensorVector& outputs,
+                                              const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v8::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v8::MulticlassNms>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -266,80 +234,47 @@ bool evaluate_node<ngraph::op::v8::MulticlassNms>(std::shared_ptr<ngraph::Node>
 }
 
 template <>
-bool evaluate_node<ngraph::op::v9::MulticlassNms>(std::shared_ptr<ngraph::Node> node,
-                                                  const ngraph::HostTensorVector& outputs,
-                                                  const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v9::MulticlassNms>(std::shared_ptr<ov::Node> node,
+                                              ov::TensorVector& outputs,
+                                              const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v9::MulticlassNms>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v9::MulticlassNms>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/mvn.cpp b/src/plugins/template/backend/ops/mvn.cpp
index 325016eef883ff..efd745ca25ee35 100644
--- a/src/plugins/template/backend/ops/mvn.cpp
+++ b/src/plugins/template/backend/ops/mvn.cpp
@@ -6,14 +6,12 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::MVN>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::mvn<T>(inputs[0]->get_data_ptr<ET>(),
-                          outputs[0]->get_data_ptr<ET>(),
-                          inputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::MVN>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::mvn<T>(inputs[0].data<T>(),
+                          outputs[0].data<T>(),
+                          inputs[0].get_shape(),
                           op->get_normalize_variance(),
                           op->get_reduction_axes(),
                           op->get_eps());
@@ -22,9 +20,9 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::MVN>& op,
 
 namespace mvn_6_axes {
 template <typename T>
-ngraph::AxisSet mvn_6_reduction_axes(const ngraph::HostTensorPtr& axes_input, size_t rank) {
-    T* a = axes_input->get_data_ptr<T>();
-    auto v = std::vector<T>(a, a + axes_input->get_shape()[0]);
+ov::AxisSet mvn_6_reduction_axes(const ov::Tensor& axes_input, size_t rank) {
+    T* a = axes_input.data<T>();
+    auto v = std::vector<T>(a, a + axes_input.get_shape()[0]);
     std::vector<size_t> axes(v.size(), 0);
     for (size_t i = 0; i < v.size(); i++) {
         if (v[i] < 0) {
@@ -36,27 +34,25 @@ ngraph::AxisSet mvn_6_reduction_axes(const ngraph::HostTensorPtr& axes_input, si
             axes[i] = (size_t)(v[i]);
         }
     }
-    return ngraph::AxisSet(axes);
+    return ov::AxisSet(axes);
 }
 }  // namespace mvn_6_axes
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v6::MVN>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ngraph::AxisSet reduction_axes;
-    auto rank = inputs[0]->get_shape().size();
-    if (inputs[1]->get_element_type() == ngraph::element::i64) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v6::MVN>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::AxisSet reduction_axes;
+    auto rank = inputs[0].get_shape().size();
+    if (inputs[1].get_element_type() == ov::element::i64) {
         reduction_axes = mvn_6_axes::mvn_6_reduction_axes<int64_t>(inputs[1], rank);
-    } else if (inputs[1]->get_element_type() == ngraph::element::i32) {
+    } else if (inputs[1].get_element_type() == ov::element::i32) {
         reduction_axes = mvn_6_axes::mvn_6_reduction_axes<int32_t>(inputs[1], rank);
     } else {
         OPENVINO_THROW("Unexpected indices type");
     }
-    ov::reference::mvn_6<T>(inputs[0]->get_data_ptr<ET>(),
-                            outputs[0]->get_data_ptr<ET>(),
-                            inputs[0]->get_shape(),
+    ov::reference::mvn_6<T>(inputs[0].data<T>(),
+                            outputs[0].data<T>(),
+                            inputs[0].get_shape(),
                             reduction_axes,
                             op->get_normalize_variance(),
                             op->get_eps(),
@@ -65,95 +61,93 @@ bool evaluate(const std::shared_ptr<ngraph::op::v6::MVN>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::MVN>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::MVN>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::MVN>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v6::MVN>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v6::MVN>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v6::MVN>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/non_max_suppression.cpp b/src/plugins/template/backend/ops/non_max_suppression.cpp
index e99f6d6c85ad88..c62b7a8187c148 100644
--- a/src/plugins/template/backend/ops/non_max_suppression.cpp
+++ b/src/plugins/template/backend/ops/non_max_suppression.cpp
@@ -2,56 +2,53 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluates_map.hpp"
-#include "evaluate_node.hpp"
 #include "openvino/reference/non_max_suppression.hpp"
-// clang-format on
+
+#include "evaluate_node.hpp"
+#include "evaluates_map.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 namespace nms_v9 {
-using V9BoxEncoding = ngraph::op::v9::NonMaxSuppression::BoxEncodingType;
+using V9BoxEncoding = ov::op::v9::NonMaxSuppression::BoxEncodingType;
 
 struct InfoForNMS9 {
     int64_t max_output_boxes_per_class;
     float iou_threshold;
     float score_threshold;
     float soft_nms_sigma;
-    ngraph::Shape out_shape;
-    ngraph::Shape boxes_shape;
-    ngraph::Shape scores_shape;
+    ov::Shape out_shape;
+    ov::Shape boxes_shape;
+    ov::Shape scores_shape;
     std::vector<float> boxes_data;
     std::vector<float> scores_data;
     size_t out_shape_size;
     bool sort_result_descending;
-    ngraph::element::Type output_type;
+    ov::element::Type output_type;
 };
 
 constexpr size_t boxes_port = 0;
 constexpr size_t scores_port = 1;
 
-ngraph::PartialShape infer_selected_indices_shape(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs,
-                                                  int64_t max_output_boxes_per_class) {
-    const auto boxes_ps = inputs[boxes_port]->get_partial_shape();
-    const auto scores_ps = inputs[scores_port]->get_partial_shape();
+ov::PartialShape infer_selected_indices_shape(const ov::TensorVector& inputs, size_t max_output_boxes_per_class) {
+    const auto boxes_ps = inputs[boxes_port].get_shape();
+    const auto scores_ps = inputs[scores_port].get_shape();
 
     // NonMaxSuppression produces triplets
     // that have the following format: [batch_index, class_index, box_index]
-    ngraph::PartialShape result = {ngraph::Dimension::dynamic(), 3};
+    ov::PartialShape result = {ov::Dimension::dynamic(), 3};
 
-    if (boxes_ps.rank().is_static() && scores_ps.rank().is_static()) {
+    if (ov::shape_size(boxes_ps) && ov::shape_size(scores_ps)) {
         const auto num_boxes_boxes = boxes_ps[1];
-        if (num_boxes_boxes.is_static() && scores_ps[0].is_static() && scores_ps[1].is_static()) {
-            const auto num_boxes = num_boxes_boxes.get_length();
-            const auto num_classes = scores_ps[1].get_length();
+        const auto num_boxes = num_boxes_boxes;
+        const auto num_classes = scores_ps[1];
 
-            result[0] = std::min(num_boxes, max_output_boxes_per_class) * num_classes * scores_ps[0].get_length();
-        }
+        result[0] = std::min(num_boxes, max_output_boxes_per_class) * num_classes * scores_ps[0];
     }
     return result;
 }
 
-void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_corner(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -72,8 +69,8 @@ void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_center(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -94,7 +91,7 @@ void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, const V9BoxEncoding box_encoding) {
+void normalize_box_encoding(float* boxes, const ov::Shape& boxes_shape, const V9BoxEncoding box_encoding) {
     if (box_encoding == V9BoxEncoding::CORNER) {
         normalize_corner(boxes, boxes_shape);
     } else {
@@ -102,39 +99,38 @@ void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, cons
     }
 }
 
-std::vector<float> prepare_boxes_data(const std::shared_ptr<ngraph::HostTensor>& boxes,
-                                      const ngraph::Shape& boxes_shape,
+std::vector<float> prepare_boxes_data(const ov::Tensor& boxes,
+                                      const ov::Shape& boxes_shape,
                                       const V9BoxEncoding box_encoding) {
     auto result = get_floats(boxes, boxes_shape);
     normalize_box_encoding(result.data(), boxes_shape, box_encoding);
     return result;
 }
 
-std::vector<float> prepare_scores_data(const std::shared_ptr<ngraph::HostTensor>& scores,
-                                       const ngraph::Shape& scores_shape) {
+std::vector<float> prepare_scores_data(const ov::Tensor& scores, const ov::Shape& scores_shape) {
     auto result = get_floats(scores, scores_shape);
     return result;
 }
 
-InfoForNMS9 get_info_for_nms9_eval(const std::shared_ptr<ngraph::op::v9::NonMaxSuppression>& nms9,
-                                   const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForNMS9 get_info_for_nms9_eval(const std::shared_ptr<ov::op::v9::NonMaxSuppression>& nms9,
+                                   const ov::TensorVector& inputs) {
     InfoForNMS9 result;
 
-    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ngraph::Shape({}))[0] : 0;
-    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ngraph::Shape({}))[0] : 0.0f;
-    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ngraph::Shape({}))[0] : 0.0f;
-    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ngraph::Shape({}))[0] : 0.0f;
+    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ov::Shape({}))[0] : 0;
+    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ov::Shape({}))[0] : 0.0f;
+    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ov::Shape({}))[0] : 0.0f;
+    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ov::Shape({}))[0] : 0.0f;
 
     auto selected_indices_shape = infer_selected_indices_shape(inputs, result.max_output_boxes_per_class);
     result.out_shape = selected_indices_shape.to_shape();
 
-    result.boxes_shape = inputs[boxes_port]->get_shape();
-    result.scores_shape = inputs[scores_port]->get_shape();
+    result.boxes_shape = inputs[boxes_port].get_shape();
+    result.scores_shape = inputs[scores_port].get_shape();
 
     result.boxes_data = prepare_boxes_data(inputs[boxes_port], result.boxes_shape, nms9->get_box_encoding());
     result.scores_data = prepare_scores_data(inputs[scores_port], result.scores_shape);
 
-    result.out_shape_size = ngraph::shape_size(result.out_shape);
+    result.out_shape_size = ov::shape_size(result.out_shape);
 
     result.sort_result_descending = nms9->get_sort_result_descending();
 
@@ -144,10 +140,10 @@ InfoForNMS9 get_info_for_nms9_eval(const std::shared_ptr<ngraph::op::v9::NonMaxS
 }
 }  // namespace nms_v9
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v9::NonMaxSuppression>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v9::NonMaxSuppression>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = nms_v9::get_info_for_nms9_eval(op, inputs);
 
     std::vector<int64_t> selected_indices(info.out_shape_size);
@@ -169,7 +165,7 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::NonMaxSuppression>& op,
                                        &valid_outputs,
                                        info.sort_result_descending);
 
-    auto selected_scores_type = (outputs.size() < 3) ? ngraph::element::f32 : outputs[1]->get_element_type();
+    auto selected_scores_type = (outputs.size() < 3) ? ov::element::f32 : outputs[1].get_element_type();
 
     ov::reference::nms_postprocessing(outputs,
                                       info.output_type,
@@ -181,49 +177,46 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::NonMaxSuppression>& op,
 }
 
 namespace nms_v4 {
-using V4BoxEncoding = ngraph::op::v4::NonMaxSuppression::BoxEncodingType;
+using V4BoxEncoding = ov::op::v4::NonMaxSuppression::BoxEncodingType;
 
 struct InfoForNMS4 {
     int64_t max_output_boxes_per_class;
     float iou_threshold;
     float score_threshold;
     float soft_nms_sigma;
-    ngraph::Shape out_shape;
-    ngraph::Shape boxes_shape;
-    ngraph::Shape scores_shape;
+    ov::Shape out_shape;
+    ov::Shape boxes_shape;
+    ov::Shape scores_shape;
     std::vector<float> boxes_data;
     std::vector<float> scores_data;
     size_t out_shape_size;
     bool sort_result_descending;
-    ngraph::element::Type output_type;
+    ov::element::Type output_type;
 };
 
 constexpr size_t boxes_port = 0;
 constexpr size_t scores_port = 1;
 
-ngraph::PartialShape infer_selected_indices_shape(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs,
-                                                  int64_t max_output_boxes_per_class) {
-    const auto boxes_ps = inputs[boxes_port]->get_partial_shape();
-    const auto scores_ps = inputs[scores_port]->get_partial_shape();
+ov::PartialShape infer_selected_indices_shape(const ov::TensorVector& inputs, size_t max_output_boxes_per_class) {
+    const auto boxes_ps = inputs[boxes_port].get_shape();
+    const auto scores_ps = inputs[scores_port].get_shape();
 
     // NonMaxSuppression produces triplets
     // that have the following format: [batch_index, class_index, box_index]
-    ngraph::PartialShape result = {ngraph::Dimension::dynamic(), 3};
+    ov::PartialShape result = {ov::Dimension::dynamic(), 3};
 
-    if (boxes_ps.rank().is_static() && scores_ps.rank().is_static()) {
+    if (ov::shape_size(boxes_ps) && ov::shape_size(scores_ps)) {
         const auto num_boxes_boxes = boxes_ps[1];
-        if (num_boxes_boxes.is_static() && scores_ps[0].is_static() && scores_ps[1].is_static()) {
-            const auto num_boxes = num_boxes_boxes.get_length();
-            const auto num_classes = scores_ps[1].get_length();
+        const auto num_boxes = num_boxes_boxes;
+        const auto num_classes = scores_ps[1];
 
-            result[0] = std::min(num_boxes, max_output_boxes_per_class) * num_classes * scores_ps[0].get_length();
-        }
+        result[0] = std::min(num_boxes, max_output_boxes_per_class) * num_classes * scores_ps[0];
     }
     return result;
 }
 
-void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_corner(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -244,8 +237,8 @@ void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_center(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -266,7 +259,7 @@ void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, const V4BoxEncoding box_encoding) {
+void normalize_box_encoding(float* boxes, const ov::Shape& boxes_shape, const V4BoxEncoding box_encoding) {
     if (box_encoding == V4BoxEncoding::CORNER) {
         normalize_corner(boxes, boxes_shape);
     } else {
@@ -274,39 +267,38 @@ void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, cons
     }
 }
 
-std::vector<float> prepare_boxes_data(const std::shared_ptr<ngraph::HostTensor>& boxes,
-                                      const ngraph::Shape& boxes_shape,
+std::vector<float> prepare_boxes_data(const ov::Tensor& boxes,
+                                      const ov::Shape& boxes_shape,
                                       const V4BoxEncoding box_encoding) {
     auto result = get_floats(boxes, boxes_shape);
     normalize_box_encoding(result.data(), boxes_shape, box_encoding);
     return result;
 }
 
-std::vector<float> prepare_scores_data(const std::shared_ptr<ngraph::HostTensor>& scores,
-                                       const ngraph::Shape& scores_shape) {
+std::vector<float> prepare_scores_data(const ov::Tensor& scores, const ov::Shape& scores_shape) {
     auto result = get_floats(scores, scores_shape);
     return result;
 }
 
-InfoForNMS4 get_info_for_nms4_eval(const std::shared_ptr<ngraph::op::v4::NonMaxSuppression>& nms4,
-                                   const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForNMS4 get_info_for_nms4_eval(const std::shared_ptr<ov::op::v4::NonMaxSuppression>& nms4,
+                                   const ov::TensorVector& inputs) {
     InfoForNMS4 result;
 
-    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ngraph::Shape({}))[0] : 0;
-    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ngraph::Shape({}))[0] : 0.0f;
-    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ngraph::Shape({}))[0] : 0.0f;
-    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ngraph::Shape({}))[0] : 0.0f;
+    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ov::Shape({}))[0] : 0;
+    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ov::Shape({}))[0] : 0.0f;
+    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ov::Shape({}))[0] : 0.0f;
+    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ov::Shape({}))[0] : 0.0f;
 
     auto selected_indices_shape = infer_selected_indices_shape(inputs, result.max_output_boxes_per_class);
     result.out_shape = selected_indices_shape.to_shape();
 
-    result.boxes_shape = inputs[boxes_port]->get_shape();
-    result.scores_shape = inputs[scores_port]->get_shape();
+    result.boxes_shape = inputs[boxes_port].get_shape();
+    result.scores_shape = inputs[scores_port].get_shape();
 
     result.boxes_data = prepare_boxes_data(inputs[boxes_port], result.boxes_shape, nms4->get_box_encoding());
     result.scores_data = prepare_scores_data(inputs[scores_port], result.scores_shape);
 
-    result.out_shape_size = ngraph::shape_size(result.out_shape);
+    result.out_shape_size = ov::shape_size(result.out_shape);
 
     result.sort_result_descending = nms4->get_sort_result_descending();
 
@@ -316,10 +308,10 @@ InfoForNMS4 get_info_for_nms4_eval(const std::shared_ptr<ngraph::op::v4::NonMaxS
 }
 }  // namespace nms_v4
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v4::NonMaxSuppression>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v4::NonMaxSuppression>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = nms_v4::get_info_for_nms4_eval(op, inputs);
 
     std::vector<int64_t> selected_indices(info.out_shape_size);
@@ -341,7 +333,7 @@ bool evaluate(const std::shared_ptr<ngraph::op::v4::NonMaxSuppression>& op,
                                        &valid_outputs,
                                        info.sort_result_descending);
 
-    auto selected_scores_type = (inputs.size() < 4) ? ngraph::element::f32 : inputs[3]->get_element_type();
+    auto selected_scores_type = (inputs.size() < 4) ? ov::element::f32 : inputs[3].get_element_type();
 
     ov::reference::nms_postprocessing(outputs,
                                       info.output_type,
@@ -353,49 +345,46 @@ bool evaluate(const std::shared_ptr<ngraph::op::v4::NonMaxSuppression>& op,
 }
 
 namespace nms_v3 {
-using V3BoxEncoding = ngraph::op::v3::NonMaxSuppression::BoxEncodingType;
+using V3BoxEncoding = ov::op::v3::NonMaxSuppression::BoxEncodingType;
 
 struct InfoForNMS3 {
     int64_t max_output_boxes_per_class;
     float iou_threshold;
     float score_threshold;
     float soft_nms_sigma;
-    ngraph::Shape out_shape;
-    ngraph::Shape boxes_shape;
-    ngraph::Shape scores_shape;
+    ov::Shape out_shape;
+    ov::Shape boxes_shape;
+    ov::Shape scores_shape;
     std::vector<float> boxes_data;
     std::vector<float> scores_data;
     size_t out_shape_size;
     bool sort_result_descending;
-    ngraph::element::Type output_type;
+    ov::element::Type output_type;
 };
 
 constexpr size_t boxes_port = 0;
 constexpr size_t scores_port = 1;
 
-ngraph::PartialShape infer_selected_indices_shape(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs,
-                                                  int64_t max_output_boxes_per_class) {
-    const auto boxes_ps = inputs[boxes_port]->get_partial_shape();
-    const auto scores_ps = inputs[scores_port]->get_partial_shape();
+ov::PartialShape infer_selected_indices_shape(const ov::TensorVector& inputs, size_t max_output_boxes_per_class) {
+    const auto boxes_ps = inputs[boxes_port].get_shape();
+    const auto scores_ps = inputs[scores_port].get_shape();
 
     // NonMaxSuppression produces triplets
     // that have the following format: [batch_index, class_index, box_index]
-    ngraph::PartialShape result = {ngraph::Dimension::dynamic(), 3};
+    ov::PartialShape result = {ov::Dimension::dynamic(), 3};
 
-    if (boxes_ps.rank().is_static() && scores_ps.rank().is_static()) {
+    if (ov::shape_size(boxes_ps) && ov::shape_size(scores_ps)) {
         const auto num_boxes_boxes = boxes_ps[1];
-        if (num_boxes_boxes.is_static() && scores_ps[0].is_static() && scores_ps[1].is_static()) {
-            const auto num_boxes = num_boxes_boxes.get_length();
-            const auto num_classes = scores_ps[1].get_length();
+        const auto num_boxes = num_boxes_boxes;
+        const auto num_classes = scores_ps[1];
 
-            result[0] = std::min(num_boxes, max_output_boxes_per_class * num_classes);
-        }
+        result[0] = std::min(num_boxes, max_output_boxes_per_class * num_classes);
     }
     return result;
 }
 
-void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_corner(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -416,8 +405,8 @@ void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_center(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -438,7 +427,7 @@ void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, const V3BoxEncoding box_encoding) {
+void normalize_box_encoding(float* boxes, const ov::Shape& boxes_shape, const V3BoxEncoding box_encoding) {
     if (box_encoding == V3BoxEncoding::CORNER) {
         normalize_corner(boxes, boxes_shape);
     } else {
@@ -446,39 +435,38 @@ void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, cons
     }
 }
 
-std::vector<float> prepare_boxes_data(const std::shared_ptr<ngraph::HostTensor>& boxes,
-                                      const ngraph::Shape& boxes_shape,
+std::vector<float> prepare_boxes_data(const ov::Tensor& boxes,
+                                      const ov::Shape& boxes_shape,
                                       const V3BoxEncoding box_encoding) {
     auto result = get_floats(boxes, boxes_shape);
     normalize_box_encoding(result.data(), boxes_shape, box_encoding);
     return result;
 }
 
-std::vector<float> prepare_scores_data(const std::shared_ptr<ngraph::HostTensor>& scores,
-                                       const ngraph::Shape& scores_shape) {
+std::vector<float> prepare_scores_data(const ov::Tensor& scores, const ov::Shape& scores_shape) {
     auto result = get_floats(scores, scores_shape);
     return result;
 }
 
-InfoForNMS3 get_info_for_nms3_eval(const std::shared_ptr<ngraph::op::v3::NonMaxSuppression>& nms3,
-                                   const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForNMS3 get_info_for_nms3_eval(const std::shared_ptr<ov::op::v3::NonMaxSuppression>& nms3,
+                                   const ov::TensorVector& inputs) {
     InfoForNMS3 result;
 
-    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ngraph::Shape({}))[0] : 0;
-    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ngraph::Shape({}))[0] : 0.0f;
-    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ngraph::Shape({}))[0] : 0.0f;
-    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ngraph::Shape({}))[0] : 0.0f;
+    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ov::Shape({}))[0] : 0;
+    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ov::Shape({}))[0] : 0.0f;
+    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ov::Shape({}))[0] : 0.0f;
+    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ov::Shape({}))[0] : 0.0f;
 
     auto selected_indices_shape = infer_selected_indices_shape(inputs, result.max_output_boxes_per_class);
     result.out_shape = selected_indices_shape.to_shape();
 
-    result.boxes_shape = inputs[boxes_port]->get_shape();
-    result.scores_shape = inputs[scores_port]->get_shape();
+    result.boxes_shape = inputs[boxes_port].get_shape();
+    result.scores_shape = inputs[scores_port].get_shape();
 
     result.boxes_data = prepare_boxes_data(inputs[boxes_port], result.boxes_shape, nms3->get_box_encoding());
     result.scores_data = prepare_scores_data(inputs[scores_port], result.scores_shape);
 
-    result.out_shape_size = ngraph::shape_size(result.out_shape);
+    result.out_shape_size = ov::shape_size(result.out_shape);
 
     result.sort_result_descending = nms3->get_sort_result_descending();
 
@@ -488,10 +476,10 @@ InfoForNMS3 get_info_for_nms3_eval(const std::shared_ptr<ngraph::op::v3::NonMaxS
 }
 }  // namespace nms_v3
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::NonMaxSuppression>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v3::NonMaxSuppression>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = nms_v3::get_info_for_nms3_eval(op, inputs);
 
     std::vector<int64_t> selected_indices(info.out_shape_size);
@@ -513,7 +501,7 @@ bool evaluate(const std::shared_ptr<ngraph::op::v3::NonMaxSuppression>& op,
                                        &valid_outputs,
                                        info.sort_result_descending);
 
-    auto selected_scores_type = (inputs.size() < 4) ? ngraph::element::f32 : inputs[3]->get_element_type();
+    auto selected_scores_type = (inputs.size() < 4) ? ov::element::f32 : inputs[3].get_element_type();
 
     ov::reference::nms_postprocessing(outputs,
                                       info.output_type,
@@ -525,49 +513,46 @@ bool evaluate(const std::shared_ptr<ngraph::op::v3::NonMaxSuppression>& op,
 }
 
 namespace nms_v1 {
-using V1BoxEncoding = ngraph::op::v1::NonMaxSuppression::BoxEncodingType;
+using V1BoxEncoding = ov::op::v1::NonMaxSuppression::BoxEncodingType;
 
 struct InfoForNMS1 {
     int64_t max_output_boxes_per_class;
     float iou_threshold;
     float score_threshold;
     float soft_nms_sigma;
-    ngraph::Shape out_shape;
-    ngraph::Shape boxes_shape;
-    ngraph::Shape scores_shape;
+    ov::Shape out_shape;
+    ov::Shape boxes_shape;
+    ov::Shape scores_shape;
     std::vector<float> boxes_data;
     std::vector<float> scores_data;
     size_t out_shape_size;
     bool sort_result_descending;
-    ngraph::element::Type output_type;
+    ov::element::Type output_type;
 };
 
 constexpr size_t boxes_port = 0;
 constexpr size_t scores_port = 1;
 
-ngraph::PartialShape infer_selected_indices_shape(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs,
-                                                  int64_t max_output_boxes_per_class) {
-    const auto boxes_ps = inputs[boxes_port]->get_partial_shape();
-    const auto scores_ps = inputs[scores_port]->get_partial_shape();
+ov::PartialShape infer_selected_indices_shape(const ov::TensorVector& inputs, size_t max_output_boxes_per_class) {
+    const auto boxes_ps = inputs[boxes_port].get_shape();
+    const auto scores_ps = inputs[scores_port].get_shape();
 
     // NonMaxSuppression produces triplets
     // that have the following format: [batch_index, class_index, box_index]
-    ngraph::PartialShape result = {ngraph::Dimension::dynamic(), 3};
+    ov::PartialShape result = {ov::Dimension::dynamic(), 3};
 
-    if (boxes_ps.rank().is_static() && scores_ps.rank().is_static()) {
+    if (ov::shape_size(boxes_ps) && ov::shape_size(scores_ps)) {
         const auto num_boxes_boxes = boxes_ps[1];
-        if (num_boxes_boxes.is_static() && scores_ps[0].is_static() && scores_ps[1].is_static()) {
-            const auto num_boxes = num_boxes_boxes.get_length();
-            const auto num_classes = scores_ps[1].get_length();
+        const auto num_boxes = num_boxes_boxes;
+        const auto num_classes = scores_ps[1];
 
-            result[0] = std::min(num_boxes, max_output_boxes_per_class * num_classes);
-        }
+        result[0] = std::min(num_boxes, max_output_boxes_per_class * num_classes);
     }
     return result;
 }
 
-void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_corner(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -588,8 +573,8 @@ void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_center(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -610,7 +595,7 @@ void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, const V1BoxEncoding box_encoding) {
+void normalize_box_encoding(float* boxes, const ov::Shape& boxes_shape, const V1BoxEncoding box_encoding) {
     if (box_encoding == V1BoxEncoding::CORNER) {
         normalize_corner(boxes, boxes_shape);
     } else {
@@ -618,39 +603,38 @@ void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, cons
     }
 }
 
-std::vector<float> prepare_boxes_data(const std::shared_ptr<ngraph::HostTensor>& boxes,
-                                      const ngraph::Shape& boxes_shape,
+std::vector<float> prepare_boxes_data(const ov::Tensor& boxes,
+                                      const ov::Shape& boxes_shape,
                                       const V1BoxEncoding box_encoding) {
     auto result = get_floats(boxes, boxes_shape);
     normalize_box_encoding(result.data(), boxes_shape, box_encoding);
     return result;
 }
 
-std::vector<float> prepare_scores_data(const std::shared_ptr<ngraph::HostTensor>& scores,
-                                       const ngraph::Shape& scores_shape) {
+std::vector<float> prepare_scores_data(const ov::Tensor& scores, const ov::Shape& scores_shape) {
     auto result = get_floats(scores, scores_shape);
     return result;
 }
 
-InfoForNMS1 get_info_for_nms1_eval(const std::shared_ptr<ngraph::op::v1::NonMaxSuppression>& nms1,
-                                   const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForNMS1 get_info_for_nms1_eval(const std::shared_ptr<ov::op::v1::NonMaxSuppression>& nms1,
+                                   const ov::TensorVector& inputs) {
     InfoForNMS1 result;
 
-    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ngraph::Shape({}))[0] : 0;
-    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ngraph::Shape({}))[0] : 0.0f;
-    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ngraph::Shape({}))[0] : 0.0f;
-    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ngraph::Shape({}))[0] : 0.0f;
+    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ov::Shape({}))[0] : 0;
+    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ov::Shape({}))[0] : 0.0f;
+    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ov::Shape({}))[0] : 0.0f;
+    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ov::Shape({}))[0] : 0.0f;
 
     auto selected_indices_shape = infer_selected_indices_shape(inputs, result.max_output_boxes_per_class);
     result.out_shape = selected_indices_shape.to_shape();
 
-    result.boxes_shape = inputs[boxes_port]->get_shape();
-    result.scores_shape = inputs[scores_port]->get_shape();
+    result.boxes_shape = inputs[boxes_port].get_shape();
+    result.scores_shape = inputs[scores_port].get_shape();
 
     result.boxes_data = prepare_boxes_data(inputs[boxes_port], result.boxes_shape, nms1->get_box_encoding());
     result.scores_data = prepare_scores_data(inputs[scores_port], result.scores_shape);
 
-    result.out_shape_size = ngraph::shape_size(result.out_shape);
+    result.out_shape_size = ov::shape_size(result.out_shape);
 
     result.sort_result_descending = nms1->get_sort_result_descending();
 
@@ -660,10 +644,10 @@ InfoForNMS1 get_info_for_nms1_eval(const std::shared_ptr<ngraph::op::v1::NonMaxS
 }
 }  // namespace nms_v1
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::NonMaxSuppression>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v1::NonMaxSuppression>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = nms_v1::get_info_for_nms1_eval(op, inputs);
 
     std::vector<int64_t> selected_indices(info.out_shape_size);
@@ -685,7 +669,7 @@ bool evaluate(const std::shared_ptr<ngraph::op::v1::NonMaxSuppression>& op,
                                        &valid_outputs,
                                        info.sort_result_descending);
 
-    auto selected_scores_type = (inputs.size() < 4) ? ngraph::element::f32 : inputs[3]->get_element_type();
+    auto selected_scores_type = (inputs.size() < 4) ? ov::element::f32 : inputs[3].get_element_type();
 
     ov::reference::nms_postprocessing(outputs,
                                       info.output_type,
@@ -697,49 +681,46 @@ bool evaluate(const std::shared_ptr<ngraph::op::v1::NonMaxSuppression>& op,
 }
 
 namespace nms_v5 {
-using V5BoxEncoding = ngraph::op::v5::NonMaxSuppression::BoxEncodingType;
+using V5BoxEncoding = ov::op::v5::NonMaxSuppression::BoxEncodingType;
 
 struct InfoForNMS5 {
     int64_t max_output_boxes_per_class;
     float iou_threshold;
     float score_threshold;
     float soft_nms_sigma;
-    ngraph::Shape out_shape;
-    ngraph::Shape boxes_shape;
-    ngraph::Shape scores_shape;
+    ov::Shape out_shape;
+    ov::Shape boxes_shape;
+    ov::Shape scores_shape;
     std::vector<float> boxes_data;
     std::vector<float> scores_data;
     size_t out_shape_size;
     bool sort_result_descending;
-    ngraph::element::Type output_type;
+    ov::element::Type output_type;
 };
 
 constexpr size_t boxes_port = 0;
 constexpr size_t scores_port = 1;
 
-ngraph::PartialShape infer_selected_indices_shape(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs,
-                                                  int64_t max_output_boxes_per_class) {
-    const auto boxes_ps = inputs[boxes_port]->get_partial_shape();
-    const auto scores_ps = inputs[scores_port]->get_partial_shape();
+ov::PartialShape infer_selected_indices_shape(const ov::TensorVector& inputs, size_t max_output_boxes_per_class) {
+    const auto boxes_ps = inputs[boxes_port].get_shape();
+    const auto scores_ps = inputs[scores_port].get_shape();
 
     // NonMaxSuppression produces triplets
     // that have the following format: [batch_index, class_index, box_index]
-    ngraph::PartialShape result = {ngraph::Dimension::dynamic(), 3};
+    ov::PartialShape result = {ov::Dimension::dynamic(), 3};
 
-    if (boxes_ps.rank().is_static() && scores_ps.rank().is_static()) {
+    if (ov::shape_size(boxes_ps) && ov::shape_size(scores_ps)) {
         const auto num_boxes_boxes = boxes_ps[1];
-        if (num_boxes_boxes.is_static() && scores_ps[0].is_static() && scores_ps[1].is_static()) {
-            const auto num_boxes = num_boxes_boxes.get_length();
-            const auto num_classes = scores_ps[1].get_length();
+        const auto num_boxes = num_boxes_boxes;
+        const auto num_classes = scores_ps[1];
 
-            result[0] = std::min(num_boxes, max_output_boxes_per_class) * num_classes * scores_ps[0].get_length();
-        }
+        result[0] = std::min(num_boxes, max_output_boxes_per_class) * num_classes * scores_ps[0];
     }
     return result;
 }
 
-void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_corner(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -760,8 +741,8 @@ void normalize_corner(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
-    size_t total_num_of_boxes = ngraph::shape_size(boxes_shape) / 4;
+void normalize_center(float* boxes, const ov::Shape& boxes_shape) {
+    size_t total_num_of_boxes = ov::shape_size(boxes_shape) / 4;
     for (size_t i = 0; i < total_num_of_boxes; ++i) {
         float* current_box = boxes + 4 * i;
 
@@ -782,7 +763,7 @@ void normalize_center(float* boxes, const ngraph::Shape& boxes_shape) {
     }
 }
 
-void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, const V5BoxEncoding box_encoding) {
+void normalize_box_encoding(float* boxes, const ov::Shape& boxes_shape, const V5BoxEncoding box_encoding) {
     if (box_encoding == V5BoxEncoding::CORNER) {
         normalize_corner(boxes, boxes_shape);
     } else {
@@ -790,39 +771,38 @@ void normalize_box_encoding(float* boxes, const ngraph::Shape& boxes_shape, cons
     }
 }
 
-std::vector<float> prepare_boxes_data(const std::shared_ptr<ngraph::HostTensor>& boxes,
-                                      const ngraph::Shape& boxes_shape,
+std::vector<float> prepare_boxes_data(const ov::Tensor& boxes,
+                                      const ov::Shape& boxes_shape,
                                       const V5BoxEncoding box_encoding) {
     auto result = get_floats(boxes, boxes_shape);
     normalize_box_encoding(result.data(), boxes_shape, box_encoding);
     return result;
 }
 
-std::vector<float> prepare_scores_data(const std::shared_ptr<ngraph::HostTensor>& scores,
-                                       const ngraph::Shape& scores_shape) {
+std::vector<float> prepare_scores_data(const ov::Tensor& scores, const ov::Shape& scores_shape) {
     auto result = get_floats(scores, scores_shape);
     return result;
 }
 
-InfoForNMS5 get_info_for_nms5_eval(const std::shared_ptr<ngraph::op::v5::NonMaxSuppression>& nms5,
-                                   const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForNMS5 get_info_for_nms5_eval(const std::shared_ptr<ov::op::v5::NonMaxSuppression>& nms5,
+                                   const ov::TensorVector& inputs) {
     InfoForNMS5 result;
 
-    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ngraph::Shape({}))[0] : 0;
-    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ngraph::Shape({}))[0] : 0.0f;
-    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ngraph::Shape({}))[0] : 0.0f;
-    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ngraph::Shape({}))[0] : 0.0f;
+    result.max_output_boxes_per_class = inputs.size() > 2 ? get_integers(inputs[2], ov::Shape({}))[0] : 0;
+    result.iou_threshold = inputs.size() > 3 ? get_floats(inputs[3], ov::Shape({}))[0] : 0.0f;
+    result.score_threshold = inputs.size() > 4 ? get_floats(inputs[4], ov::Shape({}))[0] : 0.0f;
+    result.soft_nms_sigma = inputs.size() > 5 ? get_floats(inputs[5], ov::Shape({}))[0] : 0.0f;
 
     auto selected_indices_shape = infer_selected_indices_shape(inputs, result.max_output_boxes_per_class);
     result.out_shape = selected_indices_shape.to_shape();
 
-    result.boxes_shape = inputs[boxes_port]->get_shape();
-    result.scores_shape = inputs[scores_port]->get_shape();
+    result.boxes_shape = inputs[boxes_port].get_shape();
+    result.scores_shape = inputs[scores_port].get_shape();
 
     result.boxes_data = prepare_boxes_data(inputs[boxes_port], result.boxes_shape, nms5->get_box_encoding());
     result.scores_data = prepare_scores_data(inputs[scores_port], result.scores_shape);
 
-    result.out_shape_size = ngraph::shape_size(result.out_shape);
+    result.out_shape_size = ov::shape_size(result.out_shape);
 
     result.sort_result_descending = nms5->get_sort_result_descending();
 
@@ -832,10 +812,10 @@ InfoForNMS5 get_info_for_nms5_eval(const std::shared_ptr<ngraph::op::v5::NonMaxS
 }
 }  // namespace nms_v5
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v5::NonMaxSuppression>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v5::NonMaxSuppression>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     auto info = nms_v5::get_info_for_nms5_eval(op, inputs);
 
     std::vector<int64_t> selected_indices(info.out_shape_size);
@@ -857,7 +837,7 @@ bool evaluate(const std::shared_ptr<ngraph::op::v5::NonMaxSuppression>& op,
                                         &valid_outputs,
                                         info.sort_result_descending);
 
-    auto selected_scores_type = (outputs.size() < 3) ? ngraph::element::f32 : outputs[1]->get_element_type();
+    auto selected_scores_type = (outputs.size() < 3) ? ov::element::f32 : outputs[1].get_element_type();
 
     ov::reference::nms_postprocessing(outputs,
                                       info.output_type,
@@ -869,396 +849,231 @@ bool evaluate(const std::shared_ptr<ngraph::op::v5::NonMaxSuppression>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v5::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                      const ngraph::HostTensorVector& outputs,
-                                                      const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v5::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                  ov::TensorVector& outputs,
+                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v5::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v5::NonMaxSuppression>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                      const ngraph::HostTensorVector& outputs,
-                                                      const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                  ov::TensorVector& outputs,
+                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::NonMaxSuppression>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                      const ngraph::HostTensorVector& outputs,
-                                                      const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                  ov::TensorVector& outputs,
+                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v3::NonMaxSuppression>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v4::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                      const ngraph::HostTensorVector& outputs,
-                                                      const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v4::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                  ov::TensorVector& outputs,
+                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v4::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v4::NonMaxSuppression>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v9::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                      const ngraph::HostTensorVector& outputs,
-                                                      const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v9::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                  ov::TensorVector& outputs,
+                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v9::NonMaxSuppression>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v9::NonMaxSuppression>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/normalize_l2.cpp b/src/plugins/template/backend/ops/normalize_l2.cpp
index c2eb3691755ad9..2d2035640ba2da 100644
--- a/src/plugins/template/backend/ops/normalize_l2.cpp
+++ b/src/plugins/template/backend/ops/normalize_l2.cpp
@@ -6,13 +6,13 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::NormalizeL2>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::normalize_l2<T>(inputs[0]->get_data_ptr<const T>(),
-                                   outputs[0]->get_data_ptr<T>(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::NormalizeL2>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::normalize_l2<T>(inputs[0].data<const T>(),
+                                   outputs[0].data<T>(),
                                    op->get_input_shape(0),
                                    op->get_reduction_axes(),
                                    op->get_eps(),
@@ -21,80 +21,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::NormalizeL2>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::NormalizeL2>(std::shared_ptr<ngraph::Node> node,
-                                                const ngraph::HostTensorVector& outputs,
-                                                const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::NormalizeL2>(std::shared_ptr<ov::Node> node,
+                                            ov::TensorVector& outputs,
+                                            const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::NormalizeL2>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::NormalizeL2>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/ops_evaluates.hpp b/src/plugins/template/backend/ops/ops_evaluates.hpp
index 7b71cbaf844dbf..c3a316bea50aa5 100644
--- a/src/plugins/template/backend/ops/ops_evaluates.hpp
+++ b/src/plugins/template/backend/ops/ops_evaluates.hpp
@@ -7,452 +7,448 @@
 #include "ov_ops/augru_cell.hpp"
 #include "ov_ops/augru_sequence.hpp"
 
-extern template bool evaluate_node<ngraph::op::v0::Abs>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Abs>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::BatchNormInference>(std::shared_ptr<ngraph::Node> node,
-                                                                       const ngraph::HostTensorVector& outputs,
-                                                                       const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::BatchNormInference>(std::shared_ptr<ov::Node> node,
+                                                                   ov::TensorVector& outputs,
+                                                                   const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Ceiling>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Ceiling>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::CTCGreedyDecoder>(std::shared_ptr<ngraph::Node> node,
-                                                                     const ngraph::HostTensorVector& outputs,
-                                                                     const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::CTCGreedyDecoder>(std::shared_ptr<ov::Node> node,
+                                                                 ov::TensorVector& outputs,
+                                                                 const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::CumSum>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::CumSum>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::DetectionOutput>(std::shared_ptr<ngraph::Node> node,
-                                                                    const ngraph::HostTensorVector& outputs,
-                                                                    const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::DetectionOutput>(std::shared_ptr<ov::Node> node,
+                                                                ov::TensorVector& outputs,
+                                                                const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Elu>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Elu>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Gelu>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Gelu>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v7::Gelu>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v7::Gelu>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::GRN>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::GRN>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::HardSigmoid>(std::shared_ptr<ngraph::Node> node,
-                                                                const ngraph::HostTensorVector& outputs,
-                                                                const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::HardSigmoid>(std::shared_ptr<ov::Node> node,
+                                                            ov::TensorVector& outputs,
+                                                            const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Interpolate>(std::shared_ptr<ngraph::Node> node,
-                                                                const ngraph::HostTensorVector& outputs,
-                                                                const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Interpolate>(std::shared_ptr<ov::Node> node,
+                                                            ov::TensorVector& outputs,
+                                                            const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v11::Interpolate>(std::shared_ptr<ngraph::Node> node,
-                                                                 const ngraph::HostTensorVector& outputs,
-                                                                 const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v11::Interpolate>(std::shared_ptr<ov::Node> node,
+                                                             ov::TensorVector& outputs,
+                                                             const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::LRN>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::LRN>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::LSTMCell>(std::shared_ptr<ngraph::Node> node,
-                                                             const ngraph::HostTensorVector& outputs,
-                                                             const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::LSTMSequence>(std::shared_ptr<ngraph::Node> node,
-                                                                 const ngraph::HostTensorVector& outputs,
-                                                                 const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::MVN>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::NormalizeL2>(std::shared_ptr<ngraph::Node> node,
-                                                                const ngraph::HostTensorVector& outputs,
-                                                                const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::Proposal>(std::shared_ptr<ngraph::Node> node,
-                                                             const ngraph::HostTensorVector& outputs,
-                                                             const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::PSROIPooling>(std::shared_ptr<ngraph::Node> node,
-                                                                 const ngraph::HostTensorVector& outputs,
-                                                                 const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::RegionYolo>(std::shared_ptr<ngraph::Node> node,
-                                                               const ngraph::HostTensorVector& outputs,
-                                                               const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::Relu>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::ReorgYolo>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::ReverseSequence>(std::shared_ptr<ngraph::Node> node,
-                                                                    const ngraph::HostTensorVector& outputs,
-                                                                    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::RNNCell>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v0::Selu>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::LSTMCell>(std::shared_ptr<ov::Node> node,
+                                                         ov::TensorVector& outputs,
+                                                         const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Sign>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::LSTMSequence>(std::shared_ptr<ov::Node> node,
+                                                             ov::TensorVector& outputs,
+                                                             const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::SquaredDifference>(std::shared_ptr<ngraph::Node> node,
-                                                                      const ngraph::HostTensorVector& outputs,
-                                                                      const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::MVN>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::TensorIterator>(std::shared_ptr<ngraph::Node> node,
-                                                                   const ngraph::HostTensorVector& outputs,
-                                                                   const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::NormalizeL2>(std::shared_ptr<ov::Node> node,
+                                                            ov::TensorVector& outputs,
+                                                            const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::ROIPooling>(std::shared_ptr<ngraph::Node> node,
-                                                               const ngraph::HostTensorVector& outputs,
-                                                               const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Proposal>(std::shared_ptr<ov::Node> node,
+                                                         ov::TensorVector& outputs,
+                                                         const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::AvgPool>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::PSROIPooling>(std::shared_ptr<ov::Node> node,
+                                                             ov::TensorVector& outputs,
+                                                             const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::BinaryConvolution>(std::shared_ptr<ngraph::Node> node,
-                                                                      const ngraph::HostTensorVector& outputs,
-                                                                      const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::RegionYolo>(std::shared_ptr<ov::Node> node,
+                                                           ov::TensorVector& outputs,
+                                                           const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::ConvertLike>(std::shared_ptr<ngraph::Node> node,
-                                                                const ngraph::HostTensorVector& outputs,
-                                                                const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Relu>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::Convolution>(std::shared_ptr<ngraph::Node> node,
-                                                                const ngraph::HostTensorVector& outputs,
-                                                                const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::ReorgYolo>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::ConvolutionBackpropData>(std::shared_ptr<ngraph::Node> node,
-                                                                            const ngraph::HostTensorVector& outputs,
-                                                                            const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::ReverseSequence>(std::shared_ptr<ov::Node> node,
+                                                                ov::TensorVector& outputs,
+                                                                const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::DeformablePSROIPooling>(std::shared_ptr<ngraph::Node> node,
-                                                                           const ngraph::HostTensorVector& outputs,
-                                                                           const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::RNNCell>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::Equal>(std::shared_ptr<ngraph::Node> node,
-                                                          const ngraph::HostTensorVector& outputs,
-                                                          const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Selu>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::Greater>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::Sign>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::GroupConvolution>(std::shared_ptr<ngraph::Node> node,
-                                                                     const ngraph::HostTensorVector& outputs,
-                                                                     const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::SquaredDifference>(std::shared_ptr<ov::Node> node,
+                                                                  ov::TensorVector& outputs,
+                                                                  const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::GroupConvolutionBackpropData>(
-    std::shared_ptr<ngraph::Node> node,
-    const ngraph::HostTensorVector& outputs,
-    const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::TensorIterator>(std::shared_ptr<ov::Node> node,
+                                                               ov::TensorVector& outputs,
+                                                               const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::DeformableConvolution>(std::shared_ptr<ngraph::Node> node,
-                                                                          const ngraph::HostTensorVector& outputs,
-                                                                          const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v0::ROIPooling>(std::shared_ptr<ov::Node> node,
+                                                           ov::TensorVector& outputs,
+                                                           const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::Mod>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::AvgPool>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v1::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                                      const ngraph::HostTensorVector& outputs,
-                                                                      const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v1::Pad>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v1::GatherTree>(std::shared_ptr<ngraph::Node> node,
-                                                               const ngraph::HostTensorVector& outputs,
-                                                               const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::Assign>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::Bucketize>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::EmbeddingBagOffsetsSum>(std::shared_ptr<ngraph::Node> node,
-                                                                           const ngraph::HostTensorVector& outputs,
-                                                                           const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::EmbeddingBagPackedSum>(std::shared_ptr<ngraph::Node> node,
-                                                                          const ngraph::HostTensorVector& outputs,
-                                                                          const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::ExtractImagePatches>(std::shared_ptr<ngraph::Node> node,
-                                                                        const ngraph::HostTensorVector& outputs,
-                                                                        const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::EmbeddingSegmentsSum>(std::shared_ptr<ngraph::Node> node,
-                                                                         const ngraph::HostTensorVector& outputs,
-                                                                         const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::GRUCell>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                                      const ngraph::HostTensorVector& outputs,
-                                                                      const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::ReadValue>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v3::ScatterNDUpdate>(std::shared_ptr<ngraph::Node> node,
-                                                                    const ngraph::HostTensorVector& outputs,
-                                                                    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v4::CTCLoss>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v4::LSTMCell>(std::shared_ptr<ngraph::Node> node,
-                                                             const ngraph::HostTensorVector& outputs,
-                                                             const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v4::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                                      const ngraph::HostTensorVector& outputs,
-                                                                      const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v4::Proposal>(std::shared_ptr<ngraph::Node> node,
-                                                             const ngraph::HostTensorVector& outputs,
-                                                             const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v5::BatchNormInference>(std::shared_ptr<ngraph::Node> node,
-                                                                       const ngraph::HostTensorVector& outputs,
-                                                                       const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v5::GatherND>(std::shared_ptr<ngraph::Node> node,
-                                                             const ngraph::HostTensorVector& outputs,
-                                                             const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v5::GRUSequence>(std::shared_ptr<ngraph::Node> node,
-                                                                const ngraph::HostTensorVector& outputs,
-                                                                const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v5::LogSoftmax>(std::shared_ptr<ngraph::Node> node,
-                                                               const ngraph::HostTensorVector& outputs,
-                                                               const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v5::LSTMSequence>(std::shared_ptr<ngraph::Node> node,
-                                                                 const ngraph::HostTensorVector& outputs,
-                                                                 const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v5::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                                      const ngraph::HostTensorVector& outputs,
-                                                                      const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v5::RNNSequence>(std::shared_ptr<ngraph::Node> node,
-                                                                const ngraph::HostTensorVector& outputs,
-                                                                const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v6::CTCGreedyDecoderSeqLen>(std::shared_ptr<ngraph::Node> node,
-                                                                           const ngraph::HostTensorVector& outputs,
-                                                                           const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v6::ExperimentalDetectronDetectionOutput>(
-    std::shared_ptr<ngraph::Node> node,
-    const ngraph::HostTensorVector& outputs,
-    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(
-    std::shared_ptr<ngraph::Node> node,
-    const ngraph::HostTensorVector& outputs,
-    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v9::GenerateProposals>(std::shared_ptr<ngraph::Node> node,
-                                                                      const ngraph::HostTensorVector& outputs,
-                                                                      const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v6::ExperimentalDetectronPriorGridGenerator>(
-    std::shared_ptr<ngraph::Node> node,
-    const ngraph::HostTensorVector& outputs,
-    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v6::ExperimentalDetectronROIFeatureExtractor>(
-    std::shared_ptr<ngraph::Node> node,
-    const ngraph::HostTensorVector& outputs,
-    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v6::ExperimentalDetectronTopKROIs>(
-    std::shared_ptr<ngraph::Node> node,
-    const ngraph::HostTensorVector& outputs,
-    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v6::GatherElements>(std::shared_ptr<ngraph::Node> node,
-                                                                   const ngraph::HostTensorVector& outputs,
-                                                                   const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v6::MVN>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v7::DFT>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v7::Einsum>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v7::IDFT>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v7::Roll>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::AdaptiveAvgPool>(std::shared_ptr<ngraph::Node> node,
-                                                                    const ngraph::HostTensorVector& outputs,
-                                                                    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::AdaptiveMaxPool>(std::shared_ptr<ngraph::Node> node,
-                                                                    const ngraph::HostTensorVector& outputs,
-                                                                    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::Gather>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::MatrixNms>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::MulticlassNms>(std::shared_ptr<ngraph::Node> node,
-                                                                  const ngraph::HostTensorVector& outputs,
-                                                                  const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::DeformableConvolution>(std::shared_ptr<ngraph::Node> node,
-                                                                          const ngraph::HostTensorVector& outputs,
-                                                                          const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::If>(std::shared_ptr<ngraph::Node> node,
-                                                       const ngraph::HostTensorVector& outputs,
-                                                       const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::GatherND>(std::shared_ptr<ngraph::Node> node,
-                                                             const ngraph::HostTensorVector& outputs,
-                                                             const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::DetectionOutput>(std::shared_ptr<ngraph::Node> node,
-                                                                    const ngraph::HostTensorVector& outputs,
-                                                                    const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::NV12toRGB>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::NV12toBGR>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::I420toRGB>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
-
-extern template bool evaluate_node<ngraph::op::v8::I420toBGR>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::BinaryConvolution>(std::shared_ptr<ov::Node> node,
+                                                                  ov::TensorVector& outputs,
+                                                                  const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Sigmoid>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::ConvertLike>(std::shared_ptr<ov::Node> node,
+                                                            ov::TensorVector& outputs,
+                                                            const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Tanh>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::Convolution>(std::shared_ptr<ov::Node> node,
+                                                            ov::TensorVector& outputs,
+                                                            const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Exp>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::ConvolutionBackpropData>(std::shared_ptr<ov::Node> node,
+                                                                        ov::TensorVector& outputs,
+                                                                        const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::Log>(std::shared_ptr<ngraph::Node> node,
-                                                        const ngraph::HostTensorVector& outputs,
-                                                        const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::DeformablePSROIPooling>(std::shared_ptr<ov::Node> node,
+                                                                       ov::TensorVector& outputs,
+                                                                       const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v0::PRelu>(std::shared_ptr<ngraph::Node> node,
-                                                          const ngraph::HostTensorVector& outputs,
-                                                          const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::Equal>(std::shared_ptr<ov::Node> node,
+                                                      ov::TensorVector& outputs,
+                                                      const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v9::GridSample>(std::shared_ptr<ngraph::Node> node,
-                                                               const ngraph::HostTensorVector& outputs,
-                                                               const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::Greater>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v9::RDFT>(std::shared_ptr<ngraph::Node> node,
-                                                         const ngraph::HostTensorVector& outputs,
-                                                         const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::GroupConvolution>(std::shared_ptr<ov::Node> node,
+                                                                 ov::TensorVector& outputs,
+                                                                 const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v9::NonMaxSuppression>(std::shared_ptr<ngraph::Node> node,
-                                                                      const ngraph::HostTensorVector& outputs,
-                                                                      const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::GroupConvolutionBackpropData>(std::shared_ptr<ov::Node> node,
+                                                                             ov::TensorVector& outputs,
+                                                                             const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v9::IRDFT>(std::shared_ptr<ngraph::Node> node,
-                                                          const ngraph::HostTensorVector& outputs,
-                                                          const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::DeformableConvolution>(std::shared_ptr<ov::Node> node,
+                                                                      ov::TensorVector& outputs,
+                                                                      const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v9::ROIAlign>(std::shared_ptr<ngraph::Node> node,
-                                                             const ngraph::HostTensorVector& outputs,
-                                                             const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::Mod>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v9::SoftSign>(std::shared_ptr<ngraph::Node> node,
-                                                             const ngraph::HostTensorVector& outputs,
-                                                             const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                                  ov::TensorVector& outputs,
+                                                                  const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v9::MulticlassNms>(std::shared_ptr<ngraph::Node> node,
-                                                                  const ngraph::HostTensorVector& outputs,
-                                                                  const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::Pad>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v10::IsFinite>(std::shared_ptr<ngraph::Node> node,
-                                                              const ngraph::HostTensorVector& outputs,
-                                                              const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v1::GatherTree>(std::shared_ptr<ov::Node> node,
+                                                           ov::TensorVector& outputs,
+                                                           const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v10::IsInf>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v3::Assign>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v10::IsNaN>(std::shared_ptr<ngraph::Node> node,
-                                                           const ngraph::HostTensorVector& outputs,
-                                                           const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v3::Bucketize>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ngraph::op::v10::Unique>(std::shared_ptr<ngraph::Node> node,
-                                                            const ngraph::HostTensorVector& outputs,
-                                                            const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::v3::EmbeddingBagOffsetsSum>(std::shared_ptr<ov::Node> node,
+                                                                       ov::TensorVector& outputs,
+                                                                       const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v3::EmbeddingBagPackedSum>(std::shared_ptr<ov::Node> node,
+                                                                      ov::TensorVector& outputs,
+                                                                      const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v3::ExtractImagePatches>(std::shared_ptr<ov::Node> node,
+                                                                    ov::TensorVector& outputs,
+                                                                    const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v3::EmbeddingSegmentsSum>(std::shared_ptr<ov::Node> node,
+                                                                     ov::TensorVector& outputs,
+                                                                     const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v3::GRUCell>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v3::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                                  ov::TensorVector& outputs,
+                                                                  const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v3::ReadValue>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v3::ScatterNDUpdate>(std::shared_ptr<ov::Node> node,
+                                                                ov::TensorVector& outputs,
+                                                                const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v4::CTCLoss>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v4::LSTMCell>(std::shared_ptr<ov::Node> node,
+                                                         ov::TensorVector& outputs,
+                                                         const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v4::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                                  ov::TensorVector& outputs,
+                                                                  const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v4::Proposal>(std::shared_ptr<ov::Node> node,
+                                                         ov::TensorVector& outputs,
+                                                         const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v5::BatchNormInference>(std::shared_ptr<ov::Node> node,
+                                                                   ov::TensorVector& outputs,
+                                                                   const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v5::GatherND>(std::shared_ptr<ov::Node> node,
+                                                         ov::TensorVector& outputs,
+                                                         const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v5::GRUSequence>(std::shared_ptr<ov::Node> node,
+                                                            ov::TensorVector& outputs,
+                                                            const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v5::LogSoftmax>(std::shared_ptr<ov::Node> node,
+                                                           ov::TensorVector& outputs,
+                                                           const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v5::LSTMSequence>(std::shared_ptr<ov::Node> node,
+                                                             ov::TensorVector& outputs,
+                                                             const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v5::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                                  ov::TensorVector& outputs,
+                                                                  const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v5::RNNSequence>(std::shared_ptr<ov::Node> node,
+                                                            ov::TensorVector& outputs,
+                                                            const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v6::CTCGreedyDecoderSeqLen>(std::shared_ptr<ov::Node> node,
+                                                                       ov::TensorVector& outputs,
+                                                                       const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v6::ExperimentalDetectronDetectionOutput>(std::shared_ptr<ov::Node> node,
+                                                                                     ov::TensorVector& outputs,
+                                                                                     const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(
+    std::shared_ptr<ov::Node> node,
+    ov::TensorVector& outputs,
+    const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v9::GenerateProposals>(std::shared_ptr<ov::Node> node,
+                                                                  ov::TensorVector& outputs,
+                                                                  const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v6::ExperimentalDetectronPriorGridGenerator>(std::shared_ptr<ov::Node> node,
+                                                                                        ov::TensorVector& outputs,
+                                                                                        const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v6::ExperimentalDetectronROIFeatureExtractor>(
+    std::shared_ptr<ov::Node> node,
+    ov::TensorVector& outputs,
+    const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v6::ExperimentalDetectronTopKROIs>(std::shared_ptr<ov::Node> node,
+                                                                              ov::TensorVector& outputs,
+                                                                              const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v6::GatherElements>(std::shared_ptr<ov::Node> node,
+                                                               ov::TensorVector& outputs,
+                                                               const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v6::MVN>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v7::DFT>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v7::Einsum>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v7::IDFT>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v7::Roll>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::AdaptiveAvgPool>(std::shared_ptr<ov::Node> node,
+                                                                ov::TensorVector& outputs,
+                                                                const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::AdaptiveMaxPool>(std::shared_ptr<ov::Node> node,
+                                                                ov::TensorVector& outputs,
+                                                                const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::Gather>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::MatrixNms>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::MulticlassNms>(std::shared_ptr<ov::Node> node,
+                                                              ov::TensorVector& outputs,
+                                                              const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::DeformableConvolution>(std::shared_ptr<ov::Node> node,
+                                                                      ov::TensorVector& outputs,
+                                                                      const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::If>(std::shared_ptr<ov::Node> node,
+                                                   ov::TensorVector& outputs,
+                                                   const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::GatherND>(std::shared_ptr<ov::Node> node,
+                                                         ov::TensorVector& outputs,
+                                                         const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::DetectionOutput>(std::shared_ptr<ov::Node> node,
+                                                                ov::TensorVector& outputs,
+                                                                const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::NV12toRGB>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::NV12toBGR>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::I420toRGB>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v8::I420toBGR>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v0::Sigmoid>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v0::Tanh>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v0::Exp>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v0::Log>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v0::PRelu>(std::shared_ptr<ov::Node> node,
+                                                      ov::TensorVector& outputs,
+                                                      const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v9::GridSample>(std::shared_ptr<ov::Node> node,
+                                                           ov::TensorVector& outputs,
+                                                           const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v9::RDFT>(std::shared_ptr<ov::Node> node,
+                                                     ov::TensorVector& outputs,
+                                                     const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v9::NonMaxSuppression>(std::shared_ptr<ov::Node> node,
+                                                                  ov::TensorVector& outputs,
+                                                                  const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v9::IRDFT>(std::shared_ptr<ov::Node> node,
+                                                      ov::TensorVector& outputs,
+                                                      const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v9::ROIAlign>(std::shared_ptr<ov::Node> node,
+                                                         ov::TensorVector& outputs,
+                                                         const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v9::SoftSign>(std::shared_ptr<ov::Node> node,
+                                                         ov::TensorVector& outputs,
+                                                         const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v9::MulticlassNms>(std::shared_ptr<ov::Node> node,
+                                                              ov::TensorVector& outputs,
+                                                              const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v10::IsFinite>(std::shared_ptr<ov::Node> node,
+                                                          ov::TensorVector& outputs,
+                                                          const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v10::IsInf>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v10::IsNaN>(std::shared_ptr<ov::Node> node,
+                                                       ov::TensorVector& outputs,
+                                                       const ov::TensorVector& inputs);
+
+extern template bool evaluate_node<ov::op::v10::Unique>(std::shared_ptr<ov::Node> node,
+                                                        ov::TensorVector& outputs,
+                                                        const ov::TensorVector& inputs);
 
 extern template bool evaluate_node<ov::op::v12::GroupNormalization>(std::shared_ptr<ov::Node> node,
-                                                                    const ov::HostTensorVector& outputs,
-                                                                    const ov::HostTensorVector& inputs);
+                                                                    ov::TensorVector& outputs,
+                                                                    const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ov::op::internal::AUGRUCell>(std::shared_ptr<ngraph::Node> node,
-                                                                const ngraph::HostTensorVector& outputs,
-                                                                const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::internal::AUGRUCell>(std::shared_ptr<ov::Node> node,
+                                                                ov::TensorVector& outputs,
+                                                                const ov::TensorVector& inputs);
 
-extern template bool evaluate_node<ov::op::internal::AUGRUSequence>(std::shared_ptr<ngraph::Node> node,
-                                                                    const ngraph::HostTensorVector& outputs,
-                                                                    const ngraph::HostTensorVector& inputs);
+extern template bool evaluate_node<ov::op::internal::AUGRUSequence>(std::shared_ptr<ov::Node> node,
+                                                                    ov::TensorVector& outputs,
+                                                                    const ov::TensorVector& inputs);
diff --git a/src/plugins/template/backend/ops/pad.cpp b/src/plugins/template/backend/ops/pad.cpp
index e5fdee71c10cf3..9bc0f5935484c5 100644
--- a/src/plugins/template/backend/ops/pad.cpp
+++ b/src/plugins/template/backend/ops/pad.cpp
@@ -6,16 +6,14 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v1::Pad>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    ov::reference::pad(inputs[0]->get_data_ptr<char>(),
-                       inputs[1]->get_data_ptr<char>(),
-                       outputs[0]->get_data_ptr<char>(),
-                       ngraph::shape_size(inputs[0]->get_shape()),
-                       inputs[1]->get_shape(),
-                       outputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v1::Pad>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    ov::reference::pad(inputs[0].data<char>(),
+                       inputs[1].data<char>(),
+                       outputs[0].data<char>(),
+                       ov::shape_size(inputs[0].get_shape()),
+                       inputs[1].get_shape(),
+                       outputs[0].get_shape(),
                        op->get_pads_end(),
                        op->get_pads_begin(),
                        op->get_pad_mode());
@@ -23,48 +21,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v1::Pad>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v1::Pad>(std::shared_ptr<ngraph::Node> node,
-                                        const ngraph::HostTensorVector& outputs,
-                                        const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v1::Pad>(std::shared_ptr<ov::Node> node,
+                                    ov::TensorVector& outputs,
+                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v1::Pad>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/prelu.cpp b/src/plugins/template/backend/ops/prelu.cpp
index 914feb94f6ab8d..d60f90f9fd3f7c 100644
--- a/src/plugins/template/backend/ops/prelu.cpp
+++ b/src/plugins/template/backend/ops/prelu.cpp
@@ -6,64 +6,59 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::PRelu>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::prelu<T>(inputs[0]->get_data_ptr<T>(),
-                            inputs[1]->get_data_ptr<T>(),
-                            outputs[0]->get_data_ptr<T>(),
-                            inputs[0]->get_shape(),
-                            inputs[1]->get_shape());
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::PRelu>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::prelu<T>(inputs[0].data<T>(),
+                            inputs[1].data<T>(),
+                            outputs[0].data<T>(),
+                            inputs[0].get_shape(),
+                            inputs[1].get_shape());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::PRelu>(std::shared_ptr<ngraph::Node> node,
-                                          const ngraph::HostTensorVector& outputs,
-                                          const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::PRelu>(std::shared_ptr<ov::Node> node,
+                                      ov::TensorVector& outputs,
+                                      const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::PRelu>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/proposal.cpp b/src/plugins/template/backend/ops/proposal.cpp
index b94c06379a1c2c..4cc40aae3b872f 100644
--- a/src/plugins/template/backend/ops/proposal.cpp
+++ b/src/plugins/template/backend/ops/proposal.cpp
@@ -6,140 +6,130 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Proposal>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::proposal_v0<T>(inputs[0]->get_data_ptr<T>(),
-                                  inputs[1]->get_data_ptr<T>(),
-                                  inputs[2]->get_data_ptr<T>(),
-                                  outputs[0]->get_data_ptr<T>(),
-                                  inputs[0]->get_shape(),
-                                  inputs[1]->get_shape(),
-                                  inputs[2]->get_shape(),
-                                  outputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Proposal>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::proposal_v0<T>(inputs[0].data<T>(),
+                                  inputs[1].data<T>(),
+                                  inputs[2].data<T>(),
+                                  outputs[0].data<T>(),
+                                  inputs[0].get_shape(),
+                                  inputs[1].get_shape(),
+                                  inputs[2].get_shape(),
+                                  outputs[0].get_shape(),
                                   op.get()->get_attrs());
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v4::Proposal>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::proposal_v4<T>(inputs[0]->get_data_ptr<T>(),
-                                  inputs[1]->get_data_ptr<T>(),
-                                  inputs[2]->get_data_ptr<T>(),
-                                  outputs[0]->get_data_ptr<T>(),
-                                  outputs[1]->get_data_ptr<T>(),
-                                  inputs[0]->get_shape(),
-                                  inputs[1]->get_shape(),
-                                  inputs[2]->get_shape(),
-                                  outputs[0]->get_shape(),
-                                  outputs[1]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v4::Proposal>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::proposal_v4<T>(inputs[0].data<T>(),
+                                  inputs[1].data<T>(),
+                                  inputs[2].data<T>(),
+                                  outputs[0].data<T>(),
+                                  outputs[1].data<T>(),
+                                  inputs[0].get_shape(),
+                                  inputs[1].get_shape(),
+                                  inputs[2].get_shape(),
+                                  outputs[0].get_shape(),
+                                  outputs[1].get_shape(),
                                   op.get()->get_attrs());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Proposal>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Proposal>(std::shared_ptr<ov::Node> node,
+                                         ov::TensorVector& outputs,
+                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Proposal>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
 
 template <>
-bool evaluate_node<ngraph::op::v4::Proposal>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v4::Proposal>(std::shared_ptr<ov::Node> node,
+                                         ov::TensorVector& outputs,
+                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v4::Proposal>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/psroi_pooling.cpp b/src/plugins/template/backend/ops/psroi_pooling.cpp
index c2bf72bcb624fe..beabc3d01a98b4 100644
--- a/src/plugins/template/backend/ops/psroi_pooling.cpp
+++ b/src/plugins/template/backend/ops/psroi_pooling.cpp
@@ -6,17 +6,17 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::PSROIPooling>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::psroi_pooling<T>(inputs[0]->get_data_ptr<T>(),
-                                    inputs[0]->get_shape(),
-                                    inputs[1]->get_data_ptr<T>(),
-                                    inputs[1]->get_shape(),
-                                    outputs[0]->get_data_ptr<T>(),
-                                    outputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::PSROIPooling>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::psroi_pooling<T>(inputs[0].data<T>(),
+                                    inputs[0].get_shape(),
+                                    inputs[1].data<T>(),
+                                    inputs[1].get_shape(),
+                                    outputs[0].data<T>(),
+                                    outputs[0].get_shape(),
                                     op->get_mode(),
                                     op->get_spatial_scale(),
                                     op->get_spatial_bins_x(),
@@ -26,52 +26,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::PSROIPooling>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::PSROIPooling>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::PSROIPooling>(std::shared_ptr<ov::Node> node,
+                                             ov::TensorVector& outputs,
+                                             const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::PSROIPooling>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::PSROIPooling>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/rdft.cpp b/src/plugins/template/backend/ops/rdft.cpp
index 0f3623876e9387..f2f53a5cfdeca2 100644
--- a/src/plugins/template/backend/ops/rdft.cpp
+++ b/src/plugins/template/backend/ops/rdft.cpp
@@ -7,22 +7,23 @@
 #include "evaluate_node.hpp"
 #include "evaluates_map.hpp"
 #include "openvino/reference/fft.hpp"
+#include "openvino/runtime/tensor.hpp"
 
 namespace rfft_v9 {
 struct InfoForRFFT9 {
     std::vector<float> input_data;
     std::vector<int64_t> axes_data;
-    ngraph::Shape input_data_shape;
-    ngraph::Shape axes_data_shape;
-    ngraph::Shape fft_output_shape;
-    ngraph::Shape output_shape;
+    ov::Shape input_data_shape;
+    ov::Shape axes_data_shape;
+    ov::Shape fft_output_shape;
+    ov::Shape output_shape;
 };
 
-InfoForRFFT9 get_info_for_rfft9_eval(const std::vector<std::shared_ptr<ngraph::HostTensor>>& inputs) {
+InfoForRFFT9 get_info_for_rfft9_eval(const ov::TensorVector& inputs) {
     InfoForRFFT9 result;
 
-    result.input_data_shape = inputs[0]->get_shape();
-    result.axes_data_shape = inputs[1]->get_shape();
+    result.input_data_shape = inputs[0].get_shape();
+    result.axes_data_shape = inputs[1].get_shape();
     result.input_data = get_floats(inputs[0], result.input_data_shape);
     result.axes_data = get_integers(inputs[1], result.axes_data_shape);
 
@@ -58,14 +59,12 @@ InfoForRFFT9 get_info_for_rfft9_eval(const std::vector<std::shared_ptr<ngraph::H
 }
 }  // namespace rfft_v9
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v9::RDFT>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v9::RDFT>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
     auto info = rfft_v9::get_info_for_rfft9_eval(inputs);
-    outputs[0]->set_shape(info.output_shape);
+    outputs[0].set_shape(info.output_shape);
 
-    std::vector<float> rfft_result(ngraph::shape_size(info.output_shape), 0.0f);
+    std::vector<float> rfft_result(ov::shape_size(info.output_shape), 0.0f);
     ov::reference::rdft(info.input_data,
                         info.input_data_shape,
                         info.axes_data,
@@ -78,48 +77,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::RDFT>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v9::RDFT>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v9::RDFT>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v9::RDFT>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/read_value.cpp b/src/plugins/template/backend/ops/read_value.cpp
index 4a1926568d4f32..39d06f29c9ba80 100644
--- a/src/plugins/template/backend/ops/read_value.cpp
+++ b/src/plugins/template/backend/ops/read_value.cpp
@@ -4,81 +4,21 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::ReadValue>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    outputs[0]->set_unary(inputs[0]);
-    void* input = inputs[0]->get_data_ptr();
-    outputs[0]->write(input, outputs[0]->get_size_in_bytes());
+bool evaluate(const std::shared_ptr<ov::op::v3::ReadValue>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    outputs[0].set_shape(inputs[0].get_shape());
+    inputs[0].copy_to(outputs[0]);
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::ReadValue>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::ReadValue>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
-    switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::ReadValue>(node),
-                                                      outputs,
-                                                      inputs);
-    default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
-    }
+    return evaluate(ov::as_type_ptr<ov::op::v3::ReadValue>(node), outputs, inputs);
 }
diff --git a/src/plugins/template/backend/ops/region_yolo.cpp b/src/plugins/template/backend/ops/region_yolo.cpp
index 7d3ae5971945ff..51038d036dabb1 100644
--- a/src/plugins/template/backend/ops/region_yolo.cpp
+++ b/src/plugins/template/backend/ops/region_yolo.cpp
@@ -6,14 +6,14 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::RegionYolo>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::region_yolo<T>(inputs[0]->get_data_ptr<const T>(),
-                                  outputs[0]->get_data_ptr<T>(),
-                                  inputs[0]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::RegionYolo>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::region_yolo<T>(inputs[0].data<const T>(),
+                                  outputs[0].data<T>(),
+                                  inputs[0].get_shape(),
                                   static_cast<int>(op->get_num_coords()),
                                   static_cast<int>(op->get_num_classes()),
                                   static_cast<int>(op->get_num_regions()),
@@ -23,80 +23,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::RegionYolo>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::RegionYolo>(std::shared_ptr<ngraph::Node> node,
-                                               const ngraph::HostTensorVector& outputs,
-                                               const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::RegionYolo>(std::shared_ptr<ov::Node> node,
+                                           ov::TensorVector& outputs,
+                                           const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::RegionYolo>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::RegionYolo>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/relu.cpp b/src/plugins/template/backend/ops/relu.cpp
index ce570e1a65c63e..dd2b4131d7847a 100644
--- a/src/plugins/template/backend/ops/relu.cpp
+++ b/src/plugins/template/backend/ops/relu.cpp
@@ -6,60 +6,55 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Relu>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::relu<T>(inputs[0]->get_data_ptr<T>(),
-                           outputs[0]->get_data_ptr<T>(),
-                           ngraph::shape_size(inputs[0]->get_shape()));
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Relu>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::relu<T>(inputs[0].data<T>(), outputs[0].data<T>(), ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Relu>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Relu>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Relu>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/reorg_yolo.cpp b/src/plugins/template/backend/ops/reorg_yolo.cpp
index 05730f4279d64f..d54e661958582b 100644
--- a/src/plugins/template/backend/ops/reorg_yolo.cpp
+++ b/src/plugins/template/backend/ops/reorg_yolo.cpp
@@ -6,83 +6,24 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::ReorgYolo>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    ov::reference::reorg_yolo(inputs[0]->get_data_ptr<char>(),
-                              outputs[0]->get_data_ptr<char>(),
-                              inputs[0]->get_shape(),
+bool evaluate(const std::shared_ptr<ov::op::v0::ReorgYolo>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    ov::reference::reorg_yolo(static_cast<char*>(inputs[0].data()),
+                              static_cast<char*>(outputs[0].data()),
+                              inputs[0].get_shape(),
                               op->get_strides().at(0),
-                              inputs[0]->get_element_type().size());
+                              inputs[0].get_element_type().size());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::ReorgYolo>(std::shared_ptr<ngraph::Node> node,
-                                              const ngraph::HostTensorVector& outputs,
-                                              const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::ReorgYolo>(std::shared_ptr<ov::Node> node,
+                                          ov::TensorVector& outputs,
+                                          const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
-    switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::ReorgYolo>(node),
-                                                      outputs,
-                                                      inputs);
-    default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
-    }
+    return evaluate(ov::as_type_ptr<ov::op::v0::ReorgYolo>(node), outputs, inputs);
 }
diff --git a/src/plugins/template/backend/ops/reverse_sequence.cpp b/src/plugins/template/backend/ops/reverse_sequence.cpp
index d00ba0b0fc2669..fa896ac13902b6 100644
--- a/src/plugins/template/backend/ops/reverse_sequence.cpp
+++ b/src/plugins/template/backend/ops/reverse_sequence.cpp
@@ -7,61 +7,61 @@
 #include "evaluate_node.hpp"
 
 namespace reverse_sequence_v0 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v0::ReverseSequence>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::reverse_sequence<T1, T2>(inputs[0]->get_data_ptr<T1>(),
-                                            outputs[0]->get_data_ptr<T1>(),
-                                            inputs[0]->get_shape(),
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v0::ReverseSequence>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::reverse_sequence<T1, T2>(inputs[0].data<T1>(),
+                                            outputs[0].data<T1>(),
+                                            inputs[0].get_shape(),
                                             op->get_batch_axis(),
                                             op->get_sequence_axis(),
-                                            inputs[1]->get_data_ptr<T2>());
+                                            inputs[1].data<T2>());
 }
 }  // namespace reverse_sequence_v0
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::ReverseSequence>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[1]->get_element_type()) {
-    case ngraph::element::Type_t::boolean:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::boolean>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::ReverseSequence>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[1].get_element_type()) {
+    case ov::element::boolean:
+        reverse_sequence_v0::evaluate<ET, ov::element::boolean>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i8:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::i8>(op, outputs, inputs);
+    case ov::element::i8:
+        reverse_sequence_v0::evaluate<ET, ov::element::i8>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i16:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::i16>(op, outputs, inputs);
+    case ov::element::i16:
+        reverse_sequence_v0::evaluate<ET, ov::element::i16>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i32:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+    case ov::element::i32:
+        reverse_sequence_v0::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i64:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+    case ov::element::i64:
+        reverse_sequence_v0::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u8:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::u8>(op, outputs, inputs);
+    case ov::element::u8:
+        reverse_sequence_v0::evaluate<ET, ov::element::u8>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u16:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::u16>(op, outputs, inputs);
+    case ov::element::u16:
+        reverse_sequence_v0::evaluate<ET, ov::element::u16>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u32:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::u32>(op, outputs, inputs);
+    case ov::element::u32:
+        reverse_sequence_v0::evaluate<ET, ov::element::u32>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::u64:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::u64>(op, outputs, inputs);
+    case ov::element::u64:
+        reverse_sequence_v0::evaluate<ET, ov::element::u64>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::f16:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::f16>(op, outputs, inputs);
+    case ov::element::f16:
+        reverse_sequence_v0::evaluate<ET, ov::element::f16>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::f32:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::f32>(op, outputs, inputs);
+    case ov::element::f32:
+        reverse_sequence_v0::evaluate<ET, ov::element::f32>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::f64:
-        reverse_sequence_v0::evaluate<ET, ngraph::element::Type_t::f64>(op, outputs, inputs);
+    case ov::element::f64:
+        reverse_sequence_v0::evaluate<ET, ov::element::f64>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -70,80 +70,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::ReverseSequence>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::ReverseSequence>(std::shared_ptr<ngraph::Node> node,
-                                                    const ngraph::HostTensorVector& outputs,
-                                                    const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::ReverseSequence>(std::shared_ptr<ov::Node> node,
+                                                ov::TensorVector& outputs,
+                                                const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::ReverseSequence>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::ReverseSequence>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/rnn_cell.cpp b/src/plugins/template/backend/ops/rnn_cell.cpp
index 8b52ff0275e2e5..6813b6eddde29a 100644
--- a/src/plugins/template/backend/ops/rnn_cell.cpp
+++ b/src/plugins/template/backend/ops/rnn_cell.cpp
@@ -6,72 +6,69 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::RNNCell>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::rnn_cell<T>(inputs[0]->get_data_ptr<ET>(),
-                               inputs[0]->get_shape(),
-                               inputs[1]->get_data_ptr<ET>(),
-                               inputs[1]->get_shape(),
-                               inputs[2]->get_data_ptr<ET>(),
-                               inputs[2]->get_shape(),
-                               inputs[3]->get_data_ptr<ET>(),
-                               inputs[3]->get_shape(),
-                               inputs[4]->get_data_ptr<ET>(),
-                               inputs[4]->get_shape(),
-                               outputs[0]->get_data_ptr<ET>(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::RNNCell>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::rnn_cell<T>(inputs[0].data<T>(),
+                               inputs[0].get_shape(),
+                               inputs[1].data<T>(),
+                               inputs[1].get_shape(),
+                               inputs[2].data<T>(),
+                               inputs[2].get_shape(),
+                               inputs[3].data<T>(),
+                               inputs[3].get_shape(),
+                               inputs[4].data<T>(),
+                               inputs[4].get_shape(),
+                               outputs[0].data<T>(),
                                op->get_activations().front(),
                                op->get_clip());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::RNNCell>(std::shared_ptr<ngraph::Node> node,
-                                            const ngraph::HostTensorVector& outputs,
-                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::RNNCell>(std::shared_ptr<ov::Node> node,
+                                        ov::TensorVector& outputs,
+                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::RNNCell>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/roi_align.cpp b/src/plugins/template/backend/ops/roi_align.cpp
index ae1fc3d9b83837..119c801cfe9fb8 100644
--- a/src/plugins/template/backend/ops/roi_align.cpp
+++ b/src/plugins/template/backend/ops/roi_align.cpp
@@ -5,31 +5,32 @@
 #include "openvino/reference/roi_align.hpp"
 
 #include "evaluate_node.hpp"
+#include "evaluates_map.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v9::ROIAlign>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    std::vector<int64_t> batch_indices_vec_scaled_up = host_tensor_2_vector<int64_t>(inputs[2]);
-    ngraph::op::v3::ROIAlign::PoolingMode m_mode_v3;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v9::ROIAlign>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    std::vector<int64_t> batch_indices_vec_scaled_up = get_integers(inputs[2], inputs[2].get_shape());
+    ov::op::v3::ROIAlign::PoolingMode m_mode_v3;
     switch (op->get_mode()) {
-    case ngraph::op::v9::ROIAlign::PoolingMode::AVG: {
-        m_mode_v3 = ngraph::op::v3::ROIAlign::PoolingMode::AVG;
+    case ov::op::v9::ROIAlign::PoolingMode::AVG: {
+        m_mode_v3 = ov::op::v3::ROIAlign::PoolingMode::AVG;
         break;
     }
-    case ngraph::op::v9::ROIAlign::PoolingMode::MAX: {
-        m_mode_v3 = ngraph::op::v3::ROIAlign::PoolingMode::MAX;
+    case ov::op::v9::ROIAlign::PoolingMode::MAX: {
+        m_mode_v3 = ov::op::v3::ROIAlign::PoolingMode::MAX;
         break;
     }
     default: {
         NGRAPH_CHECK(false, "unsupported PoolingMode ");
     }
     }
-    ov::reference::roi_align<T>(inputs[0]->get_data_ptr<const T>(),
-                                inputs[1]->get_data_ptr<const T>(),
+    ov::reference::roi_align<T>(inputs[0].data<const T>(),
+                                inputs[1].data<const T>(),
                                 batch_indices_vec_scaled_up.data(),
-                                outputs[0]->get_data_ptr<T>(),
+                                outputs[0].data<T>(),
                                 op->get_input_shape(0),
                                 op->get_input_shape(1),
                                 op->get_input_shape(2),
@@ -44,52 +45,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::ROIAlign>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v9::ROIAlign>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v9::ROIAlign>(std::shared_ptr<ov::Node> node,
+                                         ov::TensorVector& outputs,
+                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v9::ROIAlign>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/roi_pooling.cpp b/src/plugins/template/backend/ops/roi_pooling.cpp
index a10fe0b06ba8f0..bc115b114a2051 100644
--- a/src/plugins/template/backend/ops/roi_pooling.cpp
+++ b/src/plugins/template/backend/ops/roi_pooling.cpp
@@ -2,19 +2,18 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/roi_pooling.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::ROIPooling>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::roi_pooling<T>(inputs[0]->get_data_ptr<const T>(),
-                                  inputs[1]->get_data_ptr<const T>(),
-                                  outputs[0]->get_data_ptr<T>(),
+#include "evaluate_node.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::ROIPooling>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::roi_pooling<T>(inputs[0].data<const T>(),
+                                  inputs[1].data<const T>(),
+                                  outputs[0].data<T>(),
                                   op->get_input_shape(0),
                                   op->get_input_shape(1),
                                   op->get_output_shape(0),
@@ -24,80 +23,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::ROIPooling>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::ROIPooling>(std::shared_ptr<ngraph::Node> node,
-                                               const ngraph::HostTensorVector& outputs,
-                                               const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::ROIPooling>(std::shared_ptr<ov::Node> node,
+                                           ov::TensorVector& outputs,
+                                           const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::ROIPooling>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::ROIPooling>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/roll.cpp b/src/plugins/template/backend/ops/roll.cpp
index 69caac63c73769..57a4f666ad3b8c 100644
--- a/src/plugins/template/backend/ops/roll.cpp
+++ b/src/plugins/template/backend/ops/roll.cpp
@@ -6,91 +6,47 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v7::Roll>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    const auto& shiftType = inputs[1]->get_element_type();
+bool evaluate(const std::shared_ptr<ov::op::v7::Roll>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    const auto& shiftType = inputs[1].get_element_type();
     std::vector<int64_t> shift_int64;
-    if (shiftType == ngraph::element::Type_t::i32) {
-        auto shift = inputs[1]->get_data_ptr<const int32_t>();
-        shift_int64.resize(ngraph::shape_size(inputs[1]->get_shape()));
+    if (shiftType == ov::element::i32) {
+        auto shift = inputs[1].data<const int32_t>();
+        shift_int64.resize(ov::shape_size(inputs[1].get_shape()));
         std::transform(shift,
-                       shift + ngraph::shape_size(inputs[1]->get_shape()),
+                       shift + ov::shape_size(inputs[1].get_shape()),
                        shift_int64.begin(),
                        [](const int32_t& elem) {
                            return static_cast<int64_t>(elem);
                        });
     }
-    const auto& axesType = inputs[2]->get_element_type();
+    const auto& axesType = inputs[2].get_element_type();
     std::vector<int64_t> axes_int64;
-    if (axesType == ngraph::element::Type_t::i32) {
-        auto axes = inputs[2]->get_data_ptr<const int32_t>();
-        axes_int64.resize(ngraph::shape_size(inputs[2]->get_shape()));
-        std::transform(axes,
-                       axes + ngraph::shape_size(inputs[2]->get_shape()),
-                       axes_int64.begin(),
-                       [](const int32_t& elem) {
-                           return static_cast<int64_t>(elem);
-                       });
+    if (axesType == ov::element::i32) {
+        auto axes = inputs[2].data<const int32_t>();
+        axes_int64.resize(ov::shape_size(inputs[2].get_shape()));
+        std::transform(axes, axes + ov::shape_size(inputs[2].get_shape()), axes_int64.begin(), [](const int32_t& elem) {
+            return static_cast<int64_t>(elem);
+        });
     }
     ov::reference::roll(
-        inputs[0]->get_data_ptr<const char>(),
-        inputs[1]->get_element_type() != ngraph::element::Type_t::i64 ? shift_int64.data()
-                                                                      : inputs[1]->get_data_ptr<const int64_t>(),
-        inputs[2]->get_element_type() != ngraph::element::Type_t::i64 ? axes_int64.data()
-                                                                      : inputs[2]->get_data_ptr<const int64_t>(),
-        outputs[0]->get_data_ptr<char>(),
-        inputs[0]->get_shape(),
-        inputs[1]->get_shape(),
-        inputs[2]->get_shape(),
-        inputs[0]->get_element_type().size());
+        static_cast<const char*>(inputs[0].data()),
+        inputs[1].get_element_type() != ov::element::i64 ? shift_int64.data() : inputs[1].data<const int64_t>(),
+        inputs[2].get_element_type() != ov::element::i64 ? axes_int64.data() : inputs[2].data<const int64_t>(),
+        static_cast<char*>(outputs[0].data()),
+        inputs[0].get_shape(),
+        inputs[1].get_shape(),
+        inputs[2].get_shape(),
+        inputs[0].get_element_type().size());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v7::Roll>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v7::Roll>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
-    switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v7::Roll>(node), outputs, inputs);
-    default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
-    }
+    return evaluate(ov::as_type_ptr<ov::op::v7::Roll>(node), outputs, inputs);
 }
diff --git a/src/plugins/template/backend/ops/scatter_nd_update.cpp b/src/plugins/template/backend/ops/scatter_nd_update.cpp
index d55cac83087035..8064535a1b62db 100644
--- a/src/plugins/template/backend/ops/scatter_nd_update.cpp
+++ b/src/plugins/template/backend/ops/scatter_nd_update.cpp
@@ -6,25 +6,25 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v3::ScatterNDUpdate>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v3::ScatterNDUpdate>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
     auto idxType = op->get_input_element_type(1);
-    if (idxType == ngraph::element::i32) {
-        ov::reference::scatterNdUpdate<T, int32_t>(inputs[0]->get_data_ptr<const T>(),
-                                                   inputs[1]->get_data_ptr<const int32_t>(),
-                                                   inputs[2]->get_data_ptr<const T>(),
-                                                   outputs[0]->get_data_ptr<T>(),
+    if (idxType == ov::element::i32) {
+        ov::reference::scatterNdUpdate<T, int32_t>(inputs[0].data<const T>(),
+                                                   inputs[1].data<const int32_t>(),
+                                                   inputs[2].data<const T>(),
+                                                   outputs[0].data<T>(),
                                                    op->get_input_shape(0),
                                                    op->get_input_shape(1),
                                                    op->get_input_shape(2));
-    } else if (idxType == ngraph::element::i64) {
-        ov::reference::scatterNdUpdate<T, int64_t>(inputs[0]->get_data_ptr<const T>(),
-                                                   inputs[1]->get_data_ptr<const int64_t>(),
-                                                   inputs[2]->get_data_ptr<const T>(),
-                                                   outputs[0]->get_data_ptr<T>(),
+    } else if (idxType == ov::element::i64) {
+        ov::reference::scatterNdUpdate<T, int64_t>(inputs[0].data<const T>(),
+                                                   inputs[1].data<const int64_t>(),
+                                                   inputs[2].data<const T>(),
+                                                   outputs[0].data<T>(),
                                                    op->get_input_shape(0),
                                                    op->get_input_shape(1),
                                                    op->get_input_shape(2));
@@ -35,80 +35,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v3::ScatterNDUpdate>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v3::ScatterNDUpdate>(std::shared_ptr<ngraph::Node> node,
-                                                    const ngraph::HostTensorVector& outputs,
-                                                    const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v3::ScatterNDUpdate>(std::shared_ptr<ov::Node> node,
+                                                ov::TensorVector& outputs,
+                                                const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v3::ScatterNDUpdate>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v3::ScatterNDUpdate>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/selu.cpp b/src/plugins/template/backend/ops/selu.cpp
index 0580bd7220020d..11e3659b790963 100644
--- a/src/plugins/template/backend/ops/selu.cpp
+++ b/src/plugins/template/backend/ops/selu.cpp
@@ -6,64 +6,61 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Selu>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::selu<T>(inputs[0]->get_data_ptr<T>(),
-                           inputs[1]->get_data_ptr<T>(),
-                           inputs[2]->get_data_ptr<T>(),
-                           outputs[0]->get_data_ptr<T>(),
-                           ngraph::shape_size(inputs[0]->get_shape()),
-                           ngraph::shape_size(inputs[1]->get_shape()),
-                           ngraph::shape_size(inputs[2]->get_shape()));
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Selu>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::selu<T>(inputs[0].data<T>(),
+                           inputs[1].data<T>(),
+                           inputs[2].data<T>(),
+                           outputs[0].data<T>(),
+                           ov::shape_size(inputs[0].get_shape()),
+                           ov::shape_size(inputs[1].get_shape()),
+                           ov::shape_size(inputs[2].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Selu>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Selu>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Selu>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/sequences.cpp b/src/plugins/template/backend/ops/sequences.cpp
index a8d0ddf49b1cb0..dd182836e7485b 100644
--- a/src/plugins/template/backend/ops/sequences.cpp
+++ b/src/plugins/template/backend/ops/sequences.cpp
@@ -9,44 +9,44 @@
 // clang-format on
 
 namespace rnn_seq_v5 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v5::RNNSequence>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::rnn_sequence<T1, T2>(inputs[0]->get_data_ptr<char>(),
-                                        inputs[0]->get_shape(),
-                                        inputs[1]->get_data_ptr<char>(),
-                                        inputs[1]->get_shape(),
-                                        inputs[2]->get_data_ptr<char>(),
-                                        inputs[2]->get_shape(),
-                                        inputs[3]->get_data_ptr<char>(),
-                                        inputs[3]->get_shape(),
-                                        inputs[4]->get_data_ptr<char>(),
-                                        inputs[4]->get_shape(),
-                                        inputs[5]->get_data_ptr<char>(),
-                                        inputs[5]->get_shape(),
-                                        outputs[0]->get_data_ptr<char>(),
-                                        outputs[1]->get_data_ptr<char>(),
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v5::RNNSequence>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::rnn_sequence<T1, T2>(static_cast<char*>(inputs[0].data()),
+                                        inputs[0].get_shape(),
+                                        static_cast<char*>(inputs[1].data()),
+                                        inputs[1].get_shape(),
+                                        static_cast<char*>(inputs[2].data()),
+                                        inputs[2].get_shape(),
+                                        static_cast<char*>(inputs[3].data()),
+                                        inputs[3].get_shape(),
+                                        static_cast<char*>(inputs[4].data()),
+                                        inputs[4].get_shape(),
+                                        static_cast<char*>(inputs[5].data()),
+                                        inputs[5].get_shape(),
+                                        static_cast<char*>(outputs[0].data()),
+                                        static_cast<char*>(outputs[1].data()),
                                         op->get_activations()[0],
                                         op->get_clip(),
                                         op->get_direction());
 }
 }  // namespace rnn_seq_v5
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v5::RNNSequence>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[2]->get_element_type()) {
-    case ngraph::element::Type_t::i64:
-    case ngraph::element::Type_t::u64:
-        rnn_seq_v5::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v5::RNNSequence>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[2].get_element_type()) {
+    case ov::element::i64:
+    case ov::element::u64:
+        rnn_seq_v5::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i32:
-    case ngraph::element::Type_t::u32:
-        rnn_seq_v5::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+    case ov::element::i32:
+    case ov::element::u32:
+        rnn_seq_v5::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -55,31 +55,31 @@ bool evaluate(const std::shared_ptr<ngraph::op::v5::RNNSequence>& op,
 }
 
 namespace lstm_seq_v1 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v0::LSTMSequence>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::lstm_sequence_v1<T1, T2>(inputs[0]->get_data_ptr<char>(),
-                                            inputs[0]->get_shape(),
-                                            inputs[1]->get_data_ptr<char>(),
-                                            inputs[1]->get_shape(),
-                                            inputs[2]->get_data_ptr<char>(),
-                                            inputs[2]->get_shape(),
-                                            inputs[3]->get_data_ptr<char>(),
-                                            inputs[3]->get_shape(),
-                                            inputs[4]->get_data_ptr<char>(),
-                                            inputs[4]->get_shape(),
-                                            inputs[5]->get_data_ptr<char>(),
-                                            inputs[5]->get_shape(),
-                                            inputs[6]->get_data_ptr<char>(),
-                                            inputs[6]->get_shape(),
-                                            inputs[7]->get_data_ptr<char>(),
-                                            inputs[7]->get_shape(),
-                                            outputs[0]->get_data_ptr<char>(),
-                                            outputs[1]->get_data_ptr<char>(),
-                                            outputs[2]->get_data_ptr<char>(),
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v0::LSTMSequence>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::lstm_sequence_v1<T1, T2>(static_cast<char*>(inputs[0].data()),
+                                            inputs[0].get_shape(),
+                                            static_cast<char*>(inputs[1].data()),
+                                            inputs[1].get_shape(),
+                                            static_cast<char*>(inputs[2].data()),
+                                            inputs[2].get_shape(),
+                                            static_cast<char*>(inputs[3].data()),
+                                            inputs[3].get_shape(),
+                                            static_cast<char*>(inputs[4].data()),
+                                            inputs[4].get_shape(),
+                                            static_cast<char*>(inputs[5].data()),
+                                            inputs[5].get_shape(),
+                                            static_cast<char*>(inputs[6].data()),
+                                            inputs[6].get_shape(),
+                                            static_cast<char*>(inputs[7].data()),
+                                            inputs[7].get_shape(),
+                                            static_cast<char*>(outputs[0].data()),
+                                            static_cast<char*>(outputs[1].data()),
+                                            static_cast<char*>(outputs[2].data()),
                                             op->get_activations()[0],
                                             op->get_activations()[1],
                                             op->get_activations()[2],
@@ -91,29 +91,29 @@ inline void evaluate(const std::shared_ptr<ngraph::op::v0::LSTMSequence>& op,
 }  // namespace lstm_seq_v1
 
 namespace lstm_seq_v5 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v5::LSTMSequence>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::lstm_sequence<T1, T2>(inputs[0]->get_data_ptr<char>(),
-                                         inputs[0]->get_shape(),
-                                         inputs[1]->get_data_ptr<char>(),
-                                         inputs[1]->get_shape(),
-                                         inputs[2]->get_data_ptr<char>(),
-                                         inputs[2]->get_shape(),
-                                         inputs[3]->get_data_ptr<char>(),
-                                         inputs[3]->get_shape(),
-                                         inputs[4]->get_data_ptr<char>(),
-                                         inputs[4]->get_shape(),
-                                         inputs[5]->get_data_ptr<char>(),
-                                         inputs[5]->get_shape(),
-                                         inputs[6]->get_data_ptr<char>(),
-                                         inputs[6]->get_shape(),
-                                         outputs[0]->get_data_ptr<char>(),
-                                         outputs[1]->get_data_ptr<char>(),
-                                         outputs[2]->get_data_ptr<char>(),
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v5::LSTMSequence>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::lstm_sequence<T1, T2>(static_cast<char*>(inputs[0].data()),
+                                         inputs[0].get_shape(),
+                                         static_cast<char*>(inputs[1].data()),
+                                         inputs[1].get_shape(),
+                                         static_cast<char*>(inputs[2].data()),
+                                         inputs[2].get_shape(),
+                                         static_cast<char*>(inputs[3].data()),
+                                         inputs[3].get_shape(),
+                                         static_cast<char*>(inputs[4].data()),
+                                         inputs[4].get_shape(),
+                                         static_cast<char*>(inputs[5].data()),
+                                         inputs[5].get_shape(),
+                                         static_cast<char*>(inputs[6].data()),
+                                         inputs[6].get_shape(),
+                                         static_cast<char*>(outputs[0].data()),
+                                         static_cast<char*>(outputs[1].data()),
+                                         static_cast<char*>(outputs[2].data()),
                                          op->get_activations()[0],
                                          op->get_activations()[1],
                                          op->get_activations()[2],
@@ -122,18 +122,18 @@ inline void evaluate(const std::shared_ptr<ngraph::op::v5::LSTMSequence>& op,
 }
 }  // namespace lstm_seq_v5
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::LSTMSequence>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[3]->get_element_type()) {
-    case ngraph::element::Type_t::i64:
-    case ngraph::element::Type_t::u64:
-        lstm_seq_v1::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::LSTMSequence>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[3].get_element_type()) {
+    case ov::element::i64:
+    case ov::element::u64:
+        lstm_seq_v1::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i32:
-    case ngraph::element::Type_t::u32:
-        lstm_seq_v1::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+    case ov::element::i32:
+    case ov::element::u32:
+        lstm_seq_v1::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -141,18 +141,18 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::LSTMSequence>& op,
     return true;
 }
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v5::LSTMSequence>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[3]->get_element_type()) {
-    case ngraph::element::Type_t::i64:
-    case ngraph::element::Type_t::u64:
-        lstm_seq_v5::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v5::LSTMSequence>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[3].get_element_type()) {
+    case ov::element::i64:
+    case ov::element::u64:
+        lstm_seq_v5::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i32:
-    case ngraph::element::Type_t::u32:
-        lstm_seq_v5::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+    case ov::element::i32:
+    case ov::element::u32:
+        lstm_seq_v5::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -161,26 +161,26 @@ bool evaluate(const std::shared_ptr<ngraph::op::v5::LSTMSequence>& op,
 }
 
 namespace gru_seq_v5 {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
-inline void evaluate(const std::shared_ptr<ngraph::op::v5::GRUSequence>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::gru_sequence<T1, T2>(inputs[0]->get_data_ptr<char>(),
-                                        inputs[0]->get_shape(),
-                                        inputs[1]->get_data_ptr<char>(),
-                                        inputs[1]->get_shape(),
-                                        inputs[2]->get_data_ptr<char>(),
-                                        inputs[2]->get_shape(),
-                                        inputs[3]->get_data_ptr<char>(),
-                                        inputs[3]->get_shape(),
-                                        inputs[4]->get_data_ptr<char>(),
-                                        inputs[4]->get_shape(),
-                                        inputs[5]->get_data_ptr<char>(),
-                                        inputs[5]->get_shape(),
-                                        outputs[0]->get_data_ptr<char>(),
-                                        outputs[1]->get_data_ptr<char>(),
+template <ov::element::Type_t t1, ov::element::Type_t t2>
+inline void evaluate(const std::shared_ptr<ov::op::v5::GRUSequence>& op,
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::gru_sequence<T1, T2>(static_cast<char*>(inputs[0].data()),
+                                        inputs[0].get_shape(),
+                                        static_cast<char*>(inputs[1].data()),
+                                        inputs[1].get_shape(),
+                                        static_cast<char*>(inputs[2].data()),
+                                        inputs[2].get_shape(),
+                                        static_cast<char*>(inputs[3].data()),
+                                        inputs[3].get_shape(),
+                                        static_cast<char*>(inputs[4].data()),
+                                        inputs[4].get_shape(),
+                                        static_cast<char*>(inputs[5].data()),
+                                        inputs[5].get_shape(),
+                                        static_cast<char*>(outputs[0].data()),
+                                        static_cast<char*>(outputs[1].data()),
                                         op->get_activations()[0],
                                         op->get_activations()[1],
                                         op->get_clip(),
@@ -189,18 +189,18 @@ inline void evaluate(const std::shared_ptr<ngraph::op::v5::GRUSequence>& op,
 }
 }  // namespace gru_seq_v5
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v5::GRUSequence>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[2]->get_element_type()) {
-    case ngraph::element::Type_t::i64:
-    case ngraph::element::Type_t::u64:
-        gru_seq_v5::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v5::GRUSequence>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[2].get_element_type()) {
+    case ov::element::i64:
+    case ov::element::u64:
+        gru_seq_v5::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i32:
-    case ngraph::element::Type_t::u32:
-        gru_seq_v5::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+    case ov::element::i32:
+    case ov::element::u32:
+        gru_seq_v5::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -209,47 +209,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v5::GRUSequence>& op,
 }
 
 namespace augru_seq {
-template <ngraph::element::Type_t t1, ngraph::element::Type_t t2>
+template <ov::element::Type_t t1, ov::element::Type_t t2>
 inline void evaluate(const std::shared_ptr<ov::op::internal::AUGRUSequence>& op,
-                     const ngraph::HostTensorVector& outputs,
-                     const ngraph::HostTensorVector& inputs) {
-    using T1 = typename ngraph::element_type_traits<t1>::value_type;
-    using T2 = typename ngraph::element_type_traits<t2>::value_type;
-    ov::reference::gru_sequence<T1, T2>(inputs[0]->get_data_ptr<char>(),
-                                        inputs[0]->get_shape(),
-                                        inputs[1]->get_data_ptr<char>(),
-                                        inputs[1]->get_shape(),
-                                        inputs[2]->get_data_ptr<char>(),
-                                        inputs[2]->get_shape(),
-                                        inputs[3]->get_data_ptr<char>(),
-                                        inputs[3]->get_shape(),
-                                        inputs[4]->get_data_ptr<char>(),
-                                        inputs[4]->get_shape(),
-                                        inputs[5]->get_data_ptr<char>(),
-                                        inputs[5]->get_shape(),
-                                        outputs[0]->get_data_ptr<char>(),
-                                        outputs[1]->get_data_ptr<char>(),
+                     ov::TensorVector& outputs,
+                     const ov::TensorVector& inputs) {
+    using T1 = typename ov::element_type_traits<t1>::value_type;
+    using T2 = typename ov::element_type_traits<t2>::value_type;
+    ov::reference::gru_sequence<T1, T2>(static_cast<char*>(inputs[0].data()),
+                                        inputs[0].get_shape(),
+                                        static_cast<char*>(inputs[1].data()),
+                                        inputs[1].get_shape(),
+                                        static_cast<char*>(inputs[2].data()),
+                                        inputs[2].get_shape(),
+                                        static_cast<char*>(inputs[3].data()),
+                                        inputs[3].get_shape(),
+                                        static_cast<char*>(inputs[4].data()),
+                                        inputs[4].get_shape(),
+                                        static_cast<char*>(inputs[5].data()),
+                                        inputs[5].get_shape(),
+                                        static_cast<char*>(outputs[0].data()),
+                                        static_cast<char*>(outputs[1].data()),
                                         op->get_activations()[0],
                                         op->get_activations()[1],
                                         op->get_clip(),
                                         op->get_direction(),
                                         op->get_linear_before_reset(),
-                                        inputs[6]->get_data_ptr<char>());
+                                        static_cast<char*>(inputs[6].data()));
 }
 }  // namespace augru_seq
 
-template <ngraph::element::Type_t ET>
+template <ov::element::Type_t ET>
 bool evaluate(const std::shared_ptr<ov::op::internal::AUGRUSequence>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    switch (inputs[2]->get_element_type()) {
-    case ngraph::element::Type_t::i64:
-    case ngraph::element::Type_t::u64:
-        augru_seq::evaluate<ET, ngraph::element::Type_t::i64>(op, outputs, inputs);
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    switch (inputs[2].get_element_type()) {
+    case ov::element::i64:
+    case ov::element::u64:
+        augru_seq::evaluate<ET, ov::element::i64>(op, outputs, inputs);
         break;
-    case ngraph::element::Type_t::i32:
-    case ngraph::element::Type_t::u32:
-        augru_seq::evaluate<ET, ngraph::element::Type_t::i32>(op, outputs, inputs);
+    case ov::element::i32:
+    case ov::element::u32:
+        augru_seq::evaluate<ET, ov::element::i32>(op, outputs, inputs);
         break;
     default:
         return false;
@@ -258,78 +258,46 @@ bool evaluate(const std::shared_ptr<ov::op::internal::AUGRUSequence>& op,
 }
 
 template <>
-bool evaluate_node<ov::op::internal::AUGRUSequence>(std::shared_ptr<ngraph::Node> node,
-                                                    const ngraph::HostTensorVector& outputs,
-                                                    const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::internal::AUGRUSequence>(std::shared_ptr<ov::Node> node,
+                                                    ov::TensorVector& outputs,
+                                                    const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::internal::AUGRUSequence>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -337,78 +305,46 @@ bool evaluate_node<ov::op::internal::AUGRUSequence>(std::shared_ptr<ngraph::Node
 }
 
 template <>
-bool evaluate_node<ngraph::op::v5::GRUSequence>(std::shared_ptr<ngraph::Node> node,
-                                                const ngraph::HostTensorVector& outputs,
-                                                const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v5::GRUSequence>(std::shared_ptr<ov::Node> node,
+                                            ov::TensorVector& outputs,
+                                            const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v5::GRUSequence>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v5::GRUSequence>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -416,78 +352,46 @@ bool evaluate_node<ngraph::op::v5::GRUSequence>(std::shared_ptr<ngraph::Node> no
 }
 
 template <>
-bool evaluate_node<ngraph::op::v5::LSTMSequence>(std::shared_ptr<ngraph::Node> node,
-                                                 const ngraph::HostTensorVector& outputs,
-                                                 const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v5::LSTMSequence>(std::shared_ptr<ov::Node> node,
+                                             ov::TensorVector& outputs,
+                                             const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v5::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v5::LSTMSequence>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -495,78 +399,46 @@ bool evaluate_node<ngraph::op::v5::LSTMSequence>(std::shared_ptr<ngraph::Node> n
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::LSTMSequence>(std::shared_ptr<ngraph::Node> node,
-                                                 const ngraph::HostTensorVector& outputs,
-                                                 const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::LSTMSequence>(std::shared_ptr<ov::Node> node,
+                                             ov::TensorVector& outputs,
+                                             const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::LSTMSequence>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::LSTMSequence>(node), outputs, inputs);
     default:
         OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
                        std::string("in evaluate_node()"));
@@ -574,80 +446,47 @@ bool evaluate_node<ngraph::op::v0::LSTMSequence>(std::shared_ptr<ngraph::Node> n
 }
 
 template <>
-bool evaluate_node<ngraph::op::v5::RNNSequence>(std::shared_ptr<ngraph::Node> node,
-                                                const ngraph::HostTensorVector& outputs,
-                                                const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v5::RNNSequence>(std::shared_ptr<ov::Node> node,
+                                            ov::TensorVector& outputs,
+                                            const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v5::RNNSequence>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v5::RNNSequence>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/sigmoid.cpp b/src/plugins/template/backend/ops/sigmoid.cpp
index 7123ac4cb72249..9b2307ad884528 100644
--- a/src/plugins/template/backend/ops/sigmoid.cpp
+++ b/src/plugins/template/backend/ops/sigmoid.cpp
@@ -6,62 +6,57 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Sigmoid>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::sigmoid<T>(inputs[0]->get_data_ptr<T>(),
-                              outputs[0]->get_data_ptr<T>(),
-                              ngraph::shape_size(inputs[0]->get_shape()));
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Sigmoid>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::sigmoid<T>(inputs[0].data<T>(), outputs[0].data<T>(), ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Sigmoid>(std::shared_ptr<ngraph::Node> node,
-                                            const ngraph::HostTensorVector& outputs,
-                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Sigmoid>(std::shared_ptr<ov::Node> node,
+                                        ov::TensorVector& outputs,
+                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Sigmoid>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/sign.cpp b/src/plugins/template/backend/ops/sign.cpp
index 663a7a702be43b..c273c59afb5cc3 100644
--- a/src/plugins/template/backend/ops/sign.cpp
+++ b/src/plugins/template/backend/ops/sign.cpp
@@ -6,60 +6,55 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Sign>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::sign<T>(inputs[0]->get_data_ptr<T>(),
-                           outputs[0]->get_data_ptr<T>(),
-                           ngraph::shape_size(inputs[0]->get_shape()));
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Sign>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::sign<T>(inputs[0].data<T>(), outputs[0].data<T>(), ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Sign>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Sign>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Sign>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/softsign.cpp b/src/plugins/template/backend/ops/softsign.cpp
index 97885e733ee056..cd4c639bff8b6b 100644
--- a/src/plugins/template/backend/ops/softsign.cpp
+++ b/src/plugins/template/backend/ops/softsign.cpp
@@ -6,31 +6,31 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v9::SoftSign>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    ngraph::element::Type input_et = op->get_input_element_type(0);
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v9::SoftSign>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    ov::element::Type input_et = op->get_input_element_type(0);
     switch (input_et) {
-    case ngraph::element::Type_t::f64:
-        ov::reference::softsign<double>(inputs[0]->get_data_ptr<double>(),
-                                        outputs[0]->get_data_ptr<double>(),
-                                        ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f64:
+        ov::reference::softsign<double>(inputs[0].data<double>(),
+                                        outputs[0].data<double>(),
+                                        ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::f32:
-        ov::reference::softsign<float>(inputs[0]->get_data_ptr<float>(),
-                                       outputs[0]->get_data_ptr<float>(),
-                                       ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f32:
+        ov::reference::softsign<float>(inputs[0].data<float>(),
+                                       outputs[0].data<float>(),
+                                       ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::f16:
-        ov::reference::softsign<ngraph::float16>(inputs[0]->get_data_ptr<ngraph::float16>(),
-                                                 outputs[0]->get_data_ptr<ngraph::float16>(),
-                                                 ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::f16:
+        ov::reference::softsign<ov::float16>(inputs[0].data<ov::float16>(),
+                                             outputs[0].data<ov::float16>(),
+                                             ov::shape_size(inputs[0].get_shape()));
         break;
-    case ngraph::element::Type_t::bf16:
-        ov::reference::softsign<ngraph::bfloat16>(inputs[0]->get_data_ptr<ngraph::bfloat16>(),
-                                                  outputs[0]->get_data_ptr<ngraph::bfloat16>(),
-                                                  ngraph::shape_size(inputs[0]->get_shape()));
+    case ov::element::bf16:
+        ov::reference::softsign<ov::bfloat16>(inputs[0].data<ov::bfloat16>(),
+                                              outputs[0].data<ov::bfloat16>(),
+                                              ov::shape_size(inputs[0].get_shape()));
         break;
     default:
         return false;
@@ -39,52 +39,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v9::SoftSign>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v9::SoftSign>(std::shared_ptr<ngraph::Node> node,
-                                             const ngraph::HostTensorVector& outputs,
-                                             const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v9::SoftSign>(std::shared_ptr<ov::Node> node,
+                                         ov::TensorVector& outputs,
+                                         const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v9::SoftSign>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/squared_difference.cpp b/src/plugins/template/backend/ops/squared_difference.cpp
index 9f8c385e6b6bd0..f861cd2fe62cbe 100644
--- a/src/plugins/template/backend/ops/squared_difference.cpp
+++ b/src/plugins/template/backend/ops/squared_difference.cpp
@@ -6,95 +6,62 @@
 
 #include "evaluate_node.hpp"
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::SquaredDifference>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::squared_difference<T>(inputs[0]->get_data_ptr<const T>(),
-                                         inputs[1]->get_data_ptr<const T>(),
-                                         outputs[0]->get_data_ptr<T>(),
-                                         inputs[0]->get_shape(),
-                                         inputs[1]->get_shape(),
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::SquaredDifference>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::squared_difference<T>(inputs[0].data<const T>(),
+                                         inputs[1].data<const T>(),
+                                         outputs[0].data<T>(),
+                                         inputs[0].get_shape(),
+                                         inputs[1].get_shape(),
                                          op->get_autob());
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::SquaredDifference>(std::shared_ptr<ngraph::Node> node,
-                                                      const ngraph::HostTensorVector& outputs,
-                                                      const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::SquaredDifference>(std::shared_ptr<ov::Node> node,
+                                                  ov::TensorVector& outputs,
+                                                  const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::SquaredDifference>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::SquaredDifference>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/tanh.cpp b/src/plugins/template/backend/ops/tanh.cpp
index c85c5827a95fab..cb0c35246f09a9 100644
--- a/src/plugins/template/backend/ops/tanh.cpp
+++ b/src/plugins/template/backend/ops/tanh.cpp
@@ -2,65 +2,59 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-// clang-format off
-#include "evaluate_node.hpp"
 #include "openvino/reference/tanh.hpp"
-// clang-format on
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::Tanh>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using T = typename ngraph::element_type_traits<ET>::value_type;
-    ov::reference::tanh<T>(inputs[0]->get_data_ptr<T>(),
-                           outputs[0]->get_data_ptr<T>(),
-                           ngraph::shape_size(inputs[0]->get_shape()));
+#include "evaluate_node.hpp"
+
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::Tanh>& op, ov::TensorVector& outputs, const ov::TensorVector& inputs) {
+    using T = typename ov::element_type_traits<ET>::value_type;
+    ov::reference::tanh<T>(inputs[0].data<T>(), outputs[0].data<T>(), ov::shape_size(inputs[0].get_shape()));
     return true;
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::Tanh>(std::shared_ptr<ngraph::Node> node,
-                                         const ngraph::HostTensorVector& outputs,
-                                         const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::Tanh>(std::shared_ptr<ov::Node> node,
+                                     ov::TensorVector& outputs,
+                                     const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::Tanh>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/tensor_iterator.cpp b/src/plugins/template/backend/ops/tensor_iterator.cpp
index 4266186b592315..8b3fbd62874b27 100644
--- a/src/plugins/template/backend/ops/tensor_iterator.cpp
+++ b/src/plugins/template/backend/ops/tensor_iterator.cpp
@@ -9,9 +9,8 @@
 #include "tensor_conversion_util.hpp"
 
 namespace ti_v0 {
-ov::reference::custom_evaluate_function evaluate = [](const std::shared_ptr<ngraph::Function>& function,
-                                                      const ngraph::HostTensorVector& inputs,
-                                                      ngraph::HostTensorVector& outputs) -> void {
+ov::reference::custom_evaluate_function evaluate =
+    [](const std::shared_ptr<ov::Model>& function, const ov::TensorVector& inputs, ov::TensorVector& outputs) -> void {
     const auto& parameters = function->get_parameters();
     const auto& parametersNumber = parameters.size();
     const auto& inputsNumber = inputs.size();
@@ -27,25 +26,19 @@ ov::reference::custom_evaluate_function evaluate = [](const std::shared_ptr<ngra
     const auto& results = function->get_results();
     outputs.reserve(results.size());
     for (size_t i = 0; i < results.size(); ++i) {
-        outputs.push_back(std::make_shared<ngraph::HostTensor>(results[i]->output(0)));
+        outputs.push_back(ov::Tensor(results[i]->output(0)));
     }
 
     auto backend = ov::runtime::Backend::create();
     auto handle = backend->compile(function);
-    OPENVINO_SUPPRESS_DEPRECATED_START
-    auto outputTensors = ov::util::wrap_tensors(outputs);
-    auto inputTensors = ov::util::wrap_tensors(inputs);
-    handle->call_with_validate(outputTensors, inputTensors);
-
-    ov::util::update_output_host_tensors(outputs, outputTensors);
-    OPENVINO_SUPPRESS_DEPRECATED_END
+    handle->call_with_validate(outputs, inputs);
 };
 }  // namespace ti_v0
 
-template <ngraph::element::Type_t ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v0::TensorIterator>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
+template <ov::element::Type_t ET>
+bool evaluate(const std::shared_ptr<ov::op::v0::TensorIterator>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
     ov::reference::tensor_iterator(op->get_num_iterations(),
                                    op->get_function(),
                                    op->get_output_descriptions(),
@@ -57,80 +50,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v0::TensorIterator>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v0::TensorIterator>(std::shared_ptr<ngraph::Node> node,
-                                                   const ngraph::HostTensorVector& outputs,
-                                                   const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v0::TensorIterator>(std::shared_ptr<ov::Node> node,
+                                               ov::TensorVector& outputs,
+                                               const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                       outputs,
-                                                       inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                     outputs,
-                                                     inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v0::TensorIterator>(node),
-                                                      outputs,
-                                                      inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v0::TensorIterator>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/ops/unique.cpp b/src/plugins/template/backend/ops/unique.cpp
index da1c0d09e54030..172d2299fa9034 100644
--- a/src/plugins/template/backend/ops/unique.cpp
+++ b/src/plugins/template/backend/ops/unique.cpp
@@ -7,63 +7,59 @@
 #include "evaluate_node.hpp"
 
 template <typename Data_t, typename Index_t, typename Count_t>
-void execute_unique(const ngraph::HostTensorVector& outputs,
-                    const ngraph::HostTensorVector& inputs,
-                    const std::shared_ptr<ngraph::op::v10::Unique>& op) {
+void execute_unique(ov::TensorVector& outputs,
+                    const ov::TensorVector& inputs,
+                    const std::shared_ptr<ov::op::v10::Unique>& op) {
     const auto maybe_extract_axis = [&op]() {
         std::unique_ptr<int64_t> axis;
         if (op->get_input_size() == 2 && ov::op::util::is_constant(op->input_value(1).get_node())) {
             const auto axis_constant =
-                std::dynamic_pointer_cast<ngraph::op::v0::Constant>(op->input_value(1).get_node_shared_ptr());
+                std::dynamic_pointer_cast<ov::op::v0::Constant>(op->input_value(1).get_node_shared_ptr());
             const auto axis_vec = axis_constant->cast_vector<int64_t>();
             axis = std::unique_ptr<int64_t>(new int64_t{axis_vec.at(0)});
         }
         return axis;
     };
 
-    const auto unique_elements =
-        ov::reference::find_unique_elements<Data_t, Index_t, Count_t>(inputs[0]->get_data_ptr<Data_t>(),
-                                                                      inputs[0]->get_shape(),
-                                                                      maybe_extract_axis(),
-                                                                      op->get_sorted());
+    const auto unique_elements = ov::reference::find_unique_elements<Data_t, Index_t, Count_t>(inputs[0].data<Data_t>(),
+                                                                                               inputs[0].get_shape(),
+                                                                                               maybe_extract_axis(),
+                                                                                               op->get_sorted());
     const auto tensor_shapes =
-        ov::reference::make_tensor_shapes(unique_elements, inputs[0]->get_shape(), maybe_extract_axis());
+        ov::reference::make_tensor_shapes(unique_elements, inputs[0].get_shape(), maybe_extract_axis());
 
     auto& out_unique_elements = outputs[0];
     auto& out_indices = outputs[1];
     auto& out_rev_indices = outputs[2];
     auto& out_counts = outputs[3];
 
-    out_unique_elements->set_shape(std::get<0>(tensor_shapes));
-    out_indices->set_shape(std::get<1>(tensor_shapes));
-    out_rev_indices->set_shape(std::get<2>(tensor_shapes));
-    out_counts->set_shape(std::get<1>(tensor_shapes));
+    out_unique_elements.set_shape(std::get<0>(tensor_shapes));
+    out_indices.set_shape(std::get<1>(tensor_shapes));
+    out_rev_indices.set_shape(std::get<2>(tensor_shapes));
+    out_counts.set_shape(std::get<1>(tensor_shapes));
 
-    ov::reference::unique(out_unique_elements->get_data_ptr<Data_t>(),
-                          out_indices->get_data_ptr<Index_t>(),
-                          out_rev_indices->get_data_ptr<Index_t>(),
-                          out_counts->get_data_ptr<Count_t>(),
-                          inputs[0]->get_data_ptr<Data_t>(),
-                          inputs[0]->get_shape(),
+    ov::reference::unique(out_unique_elements.data<Data_t>(),
+                          out_indices.data<Index_t>(),
+                          out_rev_indices.data<Index_t>(),
+                          out_counts.data<Count_t>(),
+                          inputs[0].data<Data_t>(),
+                          inputs[0].get_shape(),
                           std::get<0>(tensor_shapes),
                           unique_elements);
 }
 
-template <ngraph::element::Type_t Data_ET>
-bool evaluate(const std::shared_ptr<ngraph::op::v10::Unique>& op,
-              const ngraph::HostTensorVector& outputs,
-              const ngraph::HostTensorVector& inputs) {
-    using Data_t = typename ngraph::element_type_traits<Data_ET>::value_type;
-    if (op->get_index_element_type() == ngraph::element::i32 && op->get_count_element_type() == ngraph::element::i32) {
+template <ov::element::Type_t Data_ET>
+bool evaluate(const std::shared_ptr<ov::op::v10::Unique>& op,
+              ov::TensorVector& outputs,
+              const ov::TensorVector& inputs) {
+    using Data_t = typename ov::element_type_traits<Data_ET>::value_type;
+    if (op->get_index_element_type() == ov::element::i32 && op->get_count_element_type() == ov::element::i32) {
         execute_unique<Data_t, int32_t, int32_t>(outputs, inputs, op);
-    } else if (op->get_index_element_type() == ngraph::element::i64 &&
-               op->get_count_element_type() == ngraph::element::i64) {
+    } else if (op->get_index_element_type() == ov::element::i64 && op->get_count_element_type() == ov::element::i64) {
         execute_unique<Data_t, int64_t, int64_t>(outputs, inputs, op);
-    } else if (op->get_index_element_type() == ngraph::element::i32 &&
-               op->get_count_element_type() == ngraph::element::i64) {
+    } else if (op->get_index_element_type() == ov::element::i32 && op->get_count_element_type() == ov::element::i64) {
         execute_unique<Data_t, int32_t, int64_t>(outputs, inputs, op);
-    } else if (op->get_index_element_type() == ngraph::element::i64 &&
-               op->get_count_element_type() == ngraph::element::i32) {
+    } else if (op->get_index_element_type() == ov::element::i64 && op->get_count_element_type() == ov::element::i32) {
         execute_unique<Data_t, int64_t, int32_t>(outputs, inputs, op);
     } else {
         return false;
@@ -73,50 +69,47 @@ bool evaluate(const std::shared_ptr<ngraph::op::v10::Unique>& op,
 }
 
 template <>
-bool evaluate_node<ngraph::op::v10::Unique>(std::shared_ptr<ngraph::Node> node,
-                                            const ngraph::HostTensorVector& outputs,
-                                            const ngraph::HostTensorVector& inputs) {
+bool evaluate_node<ov::op::v10::Unique>(std::shared_ptr<ov::Node> node,
+                                        ov::TensorVector& outputs,
+                                        const ov::TensorVector& inputs) {
     auto element_type = node->get_output_element_type(0);
-    if (ov::is_type<ngraph::op::v1::Select>(node) || ov::is_type<ngraph::op::util::BinaryElementwiseComparison>(node))
+    if (ov::is_type<ov::op::v1::Select>(node) || ov::is_type<ov::op::util::BinaryElementwiseComparison>(node))
         element_type = node->get_input_element_type(1);
 
     switch (element_type) {
-    case ngraph::element::Type_t::boolean:
-        return evaluate<ngraph::element::Type_t::boolean>(ov::as_type_ptr<ngraph::op::v10::Unique>(node),
-                                                          outputs,
-                                                          inputs);
-    case ngraph::element::Type_t::bf16:
-        return evaluate<ngraph::element::Type_t::bf16>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::f16:
-        return evaluate<ngraph::element::Type_t::f16>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::f64:
-        return evaluate<ngraph::element::Type_t::f64>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::f32:
-        return evaluate<ngraph::element::Type_t::f32>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::i4:
-        return evaluate<ngraph::element::Type_t::i4>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::i8:
-        return evaluate<ngraph::element::Type_t::i8>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::i16:
-        return evaluate<ngraph::element::Type_t::i16>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::i32:
-        return evaluate<ngraph::element::Type_t::i32>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::i64:
-        return evaluate<ngraph::element::Type_t::i64>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::u1:
-        return evaluate<ngraph::element::Type_t::u1>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::u4:
-        return evaluate<ngraph::element::Type_t::u4>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::u8:
-        return evaluate<ngraph::element::Type_t::u8>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::u16:
-        return evaluate<ngraph::element::Type_t::u16>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::u32:
-        return evaluate<ngraph::element::Type_t::u32>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
-    case ngraph::element::Type_t::u64:
-        return evaluate<ngraph::element::Type_t::u64>(ov::as_type_ptr<ngraph::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::boolean:
+        return evaluate<ov::element::boolean>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::bf16:
+        return evaluate<ov::element::bf16>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::f16:
+        return evaluate<ov::element::f16>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::f64:
+        return evaluate<ov::element::f64>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::f32:
+        return evaluate<ov::element::f32>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::i4:
+        return evaluate<ov::element::i4>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::i8:
+        return evaluate<ov::element::i8>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::i16:
+        return evaluate<ov::element::i16>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::i32:
+        return evaluate<ov::element::i32>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::i64:
+        return evaluate<ov::element::i64>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::u1:
+        return evaluate<ov::element::u1>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::u4:
+        return evaluate<ov::element::u4>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::u8:
+        return evaluate<ov::element::u8>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::u16:
+        return evaluate<ov::element::u16>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::u32:
+        return evaluate<ov::element::u32>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
+    case ov::element::u64:
+        return evaluate<ov::element::u64>(ov::as_type_ptr<ov::op::v10::Unique>(node), outputs, inputs);
     default:
-        OPENVINO_THROW(std::string("Unhandled data type ") + node->get_element_type().get_type_name() +
-                       std::string("in evaluate_node()"));
+        OPENVINO_THROW("Unhandled data type ", node->get_element_type().get_type_name(), " in evaluate_node()");
     }
 }
diff --git a/src/plugins/template/backend/opset_int_tbl.hpp b/src/plugins/template/backend/opset_int_tbl.hpp
index f65bf093a800cb..c94db72de7728f 100644
--- a/src/plugins/template/backend/opset_int_tbl.hpp
+++ b/src/plugins/template/backend/opset_int_tbl.hpp
@@ -12,7 +12,7 @@ _OPENVINO_OP_REG(BatchNormInference, op::v0)
 _OPENVINO_OP_REG(Ceiling, op::v0)
 _OPENVINO_OP_REG(Convert, op::v0)
 _OPENVINO_OP_REG(CTCGreedyDecoder, op::v0)
-_OPENVINO_OP_REG(CumSum, ngraph::op::v0)
+_OPENVINO_OP_REG(CumSum, op::v0)
 _OPENVINO_OP_REG(DetectionOutput, op::v0)
 _OPENVINO_OP_REG(Elu, op::v0)
 _OPENVINO_OP_REG(FakeQuantize, op::v0)
@@ -20,13 +20,13 @@ _OPENVINO_OP_REG(Gelu, op::v0)
 _OPENVINO_OP_REG(GRN, op::v0)
 _OPENVINO_OP_REG(HardSigmoid, op::v0)
 _OPENVINO_OP_REG(Interpolate, op::v0)
-_OPENVINO_OP_REG(LRN, ngraph::op::v0)
+_OPENVINO_OP_REG(LRN, op::v0)
 _OPENVINO_OP_REG(LSTMCell, op::v0)
 _OPENVINO_OP_REG(LSTMSequence, op::v0)
-_OPENVINO_OP_REG(MVN, ngraph::op::v0)
+_OPENVINO_OP_REG(MVN, op::v0)
 _OPENVINO_OP_REG(NormalizeL2, op::v0)
-_OPENVINO_OP_REG(PriorBox, ngraph::op::v0)
-_OPENVINO_OP_REG(Proposal, ngraph::op::v0)
+_OPENVINO_OP_REG(PriorBox, op::v0)
+_OPENVINO_OP_REG(Proposal, op::v0)
 _OPENVINO_OP_REG(PSROIPooling, op::v0)
 _OPENVINO_OP_REG(RegionYolo, op::v0)
 _OPENVINO_OP_REG(Relu, op::v0)
@@ -40,16 +40,16 @@ _OPENVINO_OP_REG(TensorIterator, op::v0)
 _OPENVINO_OP_REG(ROIPooling, op::v0)
 
 _OPENVINO_OP_REG(AvgPool, op::v1)
-_OPENVINO_OP_REG(BinaryConvolution, ngraph::op::v1)
+_OPENVINO_OP_REG(BinaryConvolution, op::v1)
 _OPENVINO_OP_REG(ConvertLike, op::v1)
-_OPENVINO_OP_REG(Convolution, ngraph::op::v1)
-_OPENVINO_OP_REG(ConvolutionBackpropData, ngraph::op::v1)
-_OPENVINO_OP_REG(DeformablePSROIPooling, ngraph::op::v1)
-_OPENVINO_OP_REG(Equal, ngraph::op::v1)
-_OPENVINO_OP_REG(Greater, ngraph::op::v1)
-_OPENVINO_OP_REG(GroupConvolution, ngraph::op::v1)
-_OPENVINO_OP_REG(GroupConvolutionBackpropData, ngraph::op::v1)
-_OPENVINO_OP_REG(DeformableConvolution, ngraph::op::v1)
+_OPENVINO_OP_REG(Convolution, op::v1)
+_OPENVINO_OP_REG(ConvolutionBackpropData, op::v1)
+_OPENVINO_OP_REG(DeformablePSROIPooling, op::v1)
+_OPENVINO_OP_REG(Equal, op::v1)
+_OPENVINO_OP_REG(Greater, op::v1)
+_OPENVINO_OP_REG(GroupConvolution, op::v1)
+_OPENVINO_OP_REG(GroupConvolutionBackpropData, op::v1)
+_OPENVINO_OP_REG(DeformableConvolution, op::v1)
 _OPENVINO_OP_REG(LessEqual, op::v1)
 _OPENVINO_OP_REG(LogicalAnd, op::v1)
 _OPENVINO_OP_REG(LogicalOr, op::v1)
@@ -67,11 +67,11 @@ _OPENVINO_OP_REG(GatherTree, op::v1)
 
 _OPENVINO_OP_REG(Assign, op::v3)
 _OPENVINO_OP_REG(Bucketize, op::v3)
-_OPENVINO_OP_REG(EmbeddingBagOffsetsSum, ngraph::op::v3)
-_OPENVINO_OP_REG(EmbeddingBagPackedSum, ngraph::op::v3)
+_OPENVINO_OP_REG(EmbeddingBagOffsetsSum, op::v3)
+_OPENVINO_OP_REG(EmbeddingBagPackedSum, op::v3)
 _OPENVINO_OP_REG(ExtractImagePatches, op::v3)
-_OPENVINO_OP_REG(EmbeddingSegmentsSum, ngraph::op::v3)
-_OPENVINO_OP_REG(GRUCell, ngraph::op::v3)
+_OPENVINO_OP_REG(EmbeddingSegmentsSum, op::v3)
+_OPENVINO_OP_REG(GRUCell, op::v3)
 _OPENVINO_OP_REG(NonMaxSuppression, op::v3)
 _OPENVINO_OP_REG(NonZero, op::v3)
 _OPENVINO_OP_REG(ReadValue, op::v3)
@@ -94,7 +94,7 @@ _OPENVINO_OP_REG(NonMaxSuppression, op::v5)
 _OPENVINO_OP_REG(RNNSequence, op::v5)
 _OPENVINO_OP_REG(Round, op::v5)
 
-_OPENVINO_OP_REG(Assign, ngraph::op::v6)
+_OPENVINO_OP_REG(Assign, op::v6)
 _OPENVINO_OP_REG(CTCGreedyDecoderSeqLen, op::v6)
 _OPENVINO_OP_REG(ExperimentalDetectronDetectionOutput, op::v6)
 _OPENVINO_OP_REG(ExperimentalDetectronGenerateProposalsSingleImage, op::v6)
@@ -103,21 +103,21 @@ _OPENVINO_OP_REG(ExperimentalDetectronPriorGridGenerator, op::v6)
 _OPENVINO_OP_REG(ExperimentalDetectronROIFeatureExtractor, op::v6)
 _OPENVINO_OP_REG(ExperimentalDetectronTopKROIs, op::v6)
 _OPENVINO_OP_REG(GatherElements, op::v6)
-_OPENVINO_OP_REG(MVN, ngraph::op::v6)
-_OPENVINO_OP_REG(ReadValue, ngraph::op::v6)
+_OPENVINO_OP_REG(MVN, op::v6)
+_OPENVINO_OP_REG(ReadValue, op::v6)
 
 _OPENVINO_OP_REG(DFT, op::v7)
 _OPENVINO_OP_REG(Einsum, op::v7)
 _OPENVINO_OP_REG(IDFT, op::v7)
-_OPENVINO_OP_REG(Roll, ngraph::op::v7)
+_OPENVINO_OP_REG(Roll, op::v7)
 
-_OPENVINO_OP_REG(AdaptiveAvgPool, ngraph::op::v8)
-_OPENVINO_OP_REG(AdaptiveMaxPool, ngraph::op::v8)
+_OPENVINO_OP_REG(AdaptiveAvgPool, op::v8)
+_OPENVINO_OP_REG(AdaptiveMaxPool, op::v8)
 _OPENVINO_OP_REG(Gather, op::v8)
 _OPENVINO_OP_REG(MatrixNms, op::v8)
 _OPENVINO_OP_REG(MulticlassNms, op::v8)
-_OPENVINO_OP_REG(DeformableConvolution, ngraph::op::v8)
-_OPENVINO_OP_REG(If, ngraph::op::v8)
+_OPENVINO_OP_REG(DeformableConvolution, op::v8)
+_OPENVINO_OP_REG(If, op::v8)
 _OPENVINO_OP_REG(GatherND, op::v8)
 _OPENVINO_OP_REG(DetectionOutput, op::v8)
 _OPENVINO_OP_REG(NV12toRGB, op::v8)
@@ -129,7 +129,7 @@ _OPENVINO_OP_REG(Sigmoid, op::v0)
 _OPENVINO_OP_REG(Tanh, op::v0)
 _OPENVINO_OP_REG(Exp, op::v0)
 _OPENVINO_OP_REG(Log, op::v0)
-_OPENVINO_OP_REG(PriorBox, ngraph::op::v8)
+_OPENVINO_OP_REG(PriorBox, op::v8)
 _OPENVINO_OP_REG(PRelu, op::v0)
 
 _OPENVINO_OP_REG(GridSample, op::v9)

From 35d0d92ef7d665f238e835ed3ea3d760476dde76 Mon Sep 17 00:00:00 2001
From: Evgeny Kotov <evgeny.kotov@intel.com>
Date: Tue, 19 Sep 2023 11:55:43 +0200
Subject: [PATCH 19/46] fix TSGatherForward transformation (#19821)

* fix ts_gather_forward

* remove unneeded header
---
 .../transpose_sinking/ts_gather.cpp           | 10 ++++----
 .../transpose_sinking/ts_gather_test.cpp      | 25 +++++++++++++++++--
 .../tests/transpose_sinking/ts_test_utils.cpp | 13 ++++++++++
 .../tests/transpose_sinking/ts_test_utils.hpp |  3 +++
 4 files changed, 44 insertions(+), 7 deletions(-)

diff --git a/src/common/transformations/src/transformations/transpose_sinking/ts_gather.cpp b/src/common/transformations/src/transformations/transpose_sinking/ts_gather.cpp
index d7609c935f1d61..42fa6f85cc61cf 100644
--- a/src/common/transformations/src/transformations/transpose_sinking/ts_gather.cpp
+++ b/src/common/transformations/src/transformations/transpose_sinking/ts_gather.cpp
@@ -57,16 +57,17 @@ TSGatherForward::TSGatherForward() {
             }
         }
 
-        size_t axis;
+        size_t order_axis;
         if (axes[0] < 0) {
             auto data_rank = main_node->get_input_partial_shape(0).rank();
             if (data_rank.is_dynamic()) {
                 return false;
             }
-            axis = static_cast<size_t>(axes[0] + data_rank.get_length());
+            order_axis = static_cast<size_t>(axes[0] + data_rank.get_length());
         } else {
-            axis = static_cast<size_t>(axes[0]);
+            order_axis = static_cast<size_t>(axes[0]);
         }
+        const size_t axis = order_val[order_axis];
         /*
             https://docs.openvino.ai/2023.0/openvino_docs_ops_movement_Gather_8.html
             The Gather output shape has the same shape as the input,
@@ -136,8 +137,7 @@ TSGatherForward::TSGatherForward() {
         if (!success) {
             return false;
         }
-        auto new_axis =
-            ov::op::v0::Constant::create(gather_axis->get_element_type(), gather_axis->get_shape(), {order_val[axis]});
+        auto new_axis = ov::op::v0::Constant::create(gather_axis->get_element_type(), gather_axis->get_shape(), {axis});
         main_node->input(2).replace_source_output(new_axis);
         copy_runtime_info(gather_axis, new_axis);
 
diff --git a/src/common/transformations/tests/transpose_sinking/ts_gather_test.cpp b/src/common/transformations/tests/transpose_sinking/ts_gather_test.cpp
index 34586bcdd81178..2a410fb0181333 100644
--- a/src/common/transformations/tests/transpose_sinking/ts_gather_test.cpp
+++ b/src/common/transformations/tests/transpose_sinking/ts_gather_test.cpp
@@ -63,6 +63,7 @@ auto wrapper = [](const TestCase& test_case) {
 
 struct GatherForwardArguments {
     OutputVector inputs_to_main;
+    std::function<OutputVector(const vector<size_t>&, const OutputVector&)> create_input_transpose_to_main;
     Output<Node> new_Gather_first_input;
     AxisVector new_transpose_order;
 };
@@ -76,7 +77,7 @@ auto test_forward_gather = [](const GatherForwardArguments& test_arguments) {
     test_case.inputs_to_main = test_arguments.inputs_to_main;
 
     // Test model description:
-    test_case.model.preprocess_inputs_to_main = {{set_transpose_for}, {{0}}};
+    test_case.model.preprocess_inputs_to_main = {{test_arguments.create_input_transpose_to_main}, {{0}}};
     test_case.model.main_op = {CREATE_GATHER_FACTORY(Gather)};
     test_case.model.model_template = create_model;
 
@@ -104,24 +105,44 @@ auto test_forward_gather = [](const GatherForwardArguments& test_arguments) {
     return wrapper(test_case);
 };
 
+class SetTransposeWithOrder {
+public:
+    SetTransposeWithOrder(const AxisVector& order) : _order(order) {}
+    OutputVector operator()(const vector<size_t>& idxs, const OutputVector& out_vec) const {
+        return set_transpose_with_order(idxs, out_vec, _order);
+    }
+
+private:
+    const AxisVector _order;
+};
+
 vector<GatherForwardArguments> tests_arguments_fw{
     {{{parameter(f32, {3, 4, 5, 6}), constant<int>(i32, {2}, {0, 2}), constant<int>(i32, {1}, {2})}},
+     set_transpose_for,
      constant<int>(i32, {1}, {1}),
      AxisVector{3, 2, 1, 0}},
     {{parameter(f32, {2, 4}), constant<int>(i32, {}, {0}), constant<int>(i32, {1}, {1})},
+     set_transpose_for,
      constant<int>(i32, {1}, {0}),
      AxisVector{0}},
     {{parameter(f32, {2, 4}), constant<int>(i32, {1}, {0}), constant<int>(i32, {1}, {1})},
+     set_transpose_for,
      constant<int>(i32, {1}, {0}),
      AxisVector{1, 0}},
     {{parameter(f32, {2, 3, 4}), constant<int>(i32, {2, 3}, {0, 1, 0, 1, 0, 1}), constant<int>(i32, {1}, {1})},
+     set_transpose_for,
      constant<int>(i32, {1}, {1}),
-     AxisVector{3, 1, 2, 0}}};
+     AxisVector{3, 1, 2, 0}},
+    {{parameter(f32, {64, 49, 3, 3, 32}), constant<int>(i32, {}, {1}), constant<int>(i32, {}, {0})},
+     SetTransposeWithOrder(AxisVector{2, 0, 3, 1, 4}),
+     constant<int>(i32, {}, {2}),
+     AxisVector{0, 2, 1, 3}}};
 
 INSTANTIATE_TEST_SUITE_P(TSCommonGatherForward_0, TSTestFixture, test_forward_gather(tests_arguments_fw[0]));
 INSTANTIATE_TEST_SUITE_P(TSCommonGatherForward_1, TSTestFixture, test_forward_gather(tests_arguments_fw[1]));
 INSTANTIATE_TEST_SUITE_P(TSCommonGatherForward_2, TSTestFixture, test_forward_gather(tests_arguments_fw[2]));
 INSTANTIATE_TEST_SUITE_P(TSCommonGatherForward_3, TSTestFixture, test_forward_gather(tests_arguments_fw[3]));
+INSTANTIATE_TEST_SUITE_P(TSCommonGatherForward_4, TSTestFixture, test_forward_gather(tests_arguments_fw[4]));
 
 struct GatherBackwardArguments {
     OutputVector inputs_to_main;
diff --git a/src/common/transformations/tests/transpose_sinking/ts_test_utils.cpp b/src/common/transformations/tests/transpose_sinking/ts_test_utils.cpp
index d0a81c5dd404bf..31be099f03a868 100644
--- a/src/common/transformations/tests/transpose_sinking/ts_test_utils.cpp
+++ b/src/common/transformations/tests/transpose_sinking/ts_test_utils.cpp
@@ -52,6 +52,19 @@ OutputVector set_transpose_for(const vector<size_t>& idxs, const OutputVector& o
     return result;
 }
 
+OutputVector set_transpose_with_order(const vector<size_t>& idxs,
+                                      const OutputVector& out_vec,
+                                      const vector<size_t>& transpose_order_axes) {
+    OutputVector result = out_vec;
+    for (const auto& idx : idxs) {
+        const auto& out = out_vec[idx];
+        auto order = make_shared<Constant>(element::i32, Shape{transpose_order_axes.size()}, transpose_order_axes);
+        auto transpose = make_shared<Transpose>(out, order);
+        result[idx] = transpose;
+    }
+    return result;
+}
+
 OutputVector set_gather_for(const vector<size_t>& idxs, const OutputVector& out_vec) {
     OutputVector result = out_vec;
     for (const auto& idx : idxs) {
diff --git a/src/common/transformations/tests/transpose_sinking/ts_test_utils.hpp b/src/common/transformations/tests/transpose_sinking/ts_test_utils.hpp
index 826d75e0b1bcdb..cc8685c1d7e911 100644
--- a/src/common/transformations/tests/transpose_sinking/ts_test_utils.hpp
+++ b/src/common/transformations/tests/transpose_sinking/ts_test_utils.hpp
@@ -21,6 +21,9 @@ std::string to_string(const ov::Shape& shape);
 ov::ParameterVector filter_parameters(const ov::OutputVector& out_vec);
 
 ov::OutputVector set_transpose_for(const std::vector<size_t>& idxs, const ov::OutputVector& out_vec);
+ov::OutputVector set_transpose_with_order(const std::vector<size_t>& idxs,
+                                          const ov::OutputVector& out_vec,
+                                          const std::vector<size_t>& transpose_order_axes);
 ov::OutputVector set_gather_for(const std::vector<size_t>& idxs, const ov::OutputVector& out_vec);
 std::shared_ptr<ov::Node> create_main_node(const ov::OutputVector& inputs, size_t num_ops, const FactoryPtr& creator);
 

From 2de9df8832991874edf8191478bc39374df621ea Mon Sep 17 00:00:00 2001
From: Sofya Balandina <sofya.balandina@intel.com>
Date: Tue, 19 Sep 2023 11:00:14 +0100
Subject: [PATCH 20/46] [apiConformance] Remove bf16 precision as unsupported
 (#19761)

---
 .../behavior/ov_infer_request/io_tensor.cpp   | 19 ++++++++++++++++++-
 .../behavior/ov_infer_request/io_tensor.cpp   |  5 -----
 2 files changed, 18 insertions(+), 6 deletions(-)

diff --git a/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_infer_request/io_tensor.cpp b/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_infer_request/io_tensor.cpp
index e1858a17781514..5d741f5f8148e7 100644
--- a/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_infer_request/io_tensor.cpp
+++ b/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_infer_request/io_tensor.cpp
@@ -20,7 +20,6 @@ INSTANTIATE_TEST_SUITE_P(ov_infer_request_mandatory, OVInferRequestIOTensorTest,
 
 std::vector<ov::element::Type> ovIOTensorElemTypes = {
     ov::element::boolean,
-    ov::element::bf16,
     ov::element::f16,
     ov::element::f32,
     ov::element::f64,
@@ -47,4 +46,22 @@ INSTANTIATE_TEST_SUITE_P(ov_infer_request_mandatory, OVInferRequestCheckTensorPr
                                  ::testing::ValuesIn(return_all_possible_device_combination()),
                                  ::testing::Values(pluginConfig)),
                          OVInferRequestCheckTensorPrecision::getTestCaseName);
+
+std::vector<ov::element::Type> ovIOTensorElemTypesOptional = {
+     ov::element::bf16
+};
+
+INSTANTIATE_TEST_SUITE_P(ov_infer_request, OVInferRequestIOTensorSetPrecisionTest,
+                         ::testing::Combine(
+                                 ::testing::ValuesIn(ovIOTensorElemTypesOptional),
+                                 ::testing::ValuesIn(return_all_possible_device_combination()),
+                                 ::testing::Values(pluginConfig)),
+                         OVInferRequestIOTensorSetPrecisionTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(ov_infer_request, OVInferRequestCheckTensorPrecision,
+                         ::testing::Combine(
+                                 ::testing::ValuesIn(ovIOTensorElemTypesOptional),
+                                 ::testing::ValuesIn(return_all_possible_device_combination()),
+                                 ::testing::Values(pluginConfig)),
+                         OVInferRequestCheckTensorPrecision::getTestCaseName);
 }  // namespace
diff --git a/src/tests/functional/plugin/shared/src/behavior/ov_infer_request/io_tensor.cpp b/src/tests/functional/plugin/shared/src/behavior/ov_infer_request/io_tensor.cpp
index 59fbc9b10852d2..344f0e57daf5d0 100644
--- a/src/tests/functional/plugin/shared/src/behavior/ov_infer_request/io_tensor.cpp
+++ b/src/tests/functional/plugin/shared/src/behavior/ov_infer_request/io_tensor.cpp
@@ -325,11 +325,6 @@ void OVInferRequestCheckTensorPrecision::createInferRequest() {
     try {
         compModel = core->compile_model(model, target_device, config);
         request = compModel.create_infer_request();
-
-        if (std::count(precisions.begin(), precisions.end(), element_type) == 0) {
-            FAIL() << "Precision " << element_type.c_type_string()
-                    << " is marked as unsupported but the network was loaded successfully";
-        }
     } catch (std::runtime_error& e) {
         const std::string errorMsg = e.what();
         const auto expectedMsg = exp_error_str_;

From a139fb48b796bcefa4ff263cbee1d8293090a6eb Mon Sep 17 00:00:00 2001
From: Roman Kazantsev <roman.kazantsev@intel.com>
Date: Tue, 19 Sep 2023 14:00:54 +0400
Subject: [PATCH 21/46] [TF FE][JAX] Add upper bound for jax dependencies
 (#19943)

Signed-off-by: Kazantsev, Roman <roman.kazantsev@intel.com>
---
 tests/constraints.txt | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/tests/constraints.txt b/tests/constraints.txt
index aae862f09a37c7..3f5a718dff257a 100644
--- a/tests/constraints.txt
+++ b/tests/constraints.txt
@@ -20,3 +20,5 @@ pytest>=5.0,<7.5
 pytest-dependency==0.5.1
 pytest-html==3.2.0
 pytest-timeout==2.1.0
+jax<=0.4.14
+jaxlib<=0.4.14

From ca344aea541da2df0d3358a52a6a1b35e667a7cb Mon Sep 17 00:00:00 2001
From: Vitaliy Urusovskij <vitaliy.urusovskij@intel.com>
Date: Tue, 19 Sep 2023 15:46:13 +0400
Subject: [PATCH 22/46] `TensorIteratorTest` to API2.0 (#19869)

* `TensorIteratorTest` to API2.0

* Port `TensorIteratorBody` to ov::test::utils
---
 .../single_layer_tests/tensor_iterator.cpp    |  94 ++++---
 .../single_op_tests/tensor_iterator.hpp       |  15 ++
 .../single_op/tensor_iterator.hpp             |  39 +++
 .../src/single_op/tensor_iterator.cpp         | 238 ++++++++++++++++++
 .../ngraph_functions/utils/ngraph_helpers.hpp |  12 +-
 .../src/utils/ngraph_helpers.cpp              |  17 --
 .../include/common_test_utils/test_enums.hpp  |   9 +
 .../common_test_utils/src/test_enums.cpp      |  17 ++
 8 files changed, 365 insertions(+), 76 deletions(-)
 create mode 100644 src/tests/functional/plugin/shared/include/single_op_tests/tensor_iterator.hpp
 create mode 100644 src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/tensor_iterator.hpp
 create mode 100644 src/tests/functional/shared_test_classes/src/single_op/tensor_iterator.cpp

diff --git a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/tensor_iterator.cpp b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/tensor_iterator.cpp
index 75e8cfe94225dc..d0c0f7594c72bc 100644
--- a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/tensor_iterator.cpp
+++ b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/tensor_iterator.cpp
@@ -3,59 +3,57 @@
 //
 
 #include <vector>
-#include <ngraph/op/util/attr_types.hpp>
-#include "single_layer_tests/tensor_iterator.hpp"
+#include "single_op_tests/tensor_iterator.hpp"
 #include "common_test_utils/test_constants.hpp"
 
-using namespace LayerTestsDefinitions;
+using ov::test::TensorIteratorTest;
 
 namespace {
-    std::vector<bool> should_decompose = {true, false};
-    // output values increase rapidly without clip, so use only seq_lengths = 2
-    std::vector<size_t> seq_lengths_zero_clip{2};
-    std::vector<size_t> seq_lengths_clip_non_zero{20};
-    std::vector<size_t> batch{1, 10};
-    std::vector<size_t> hidden_size{1, 10};
-    // std::vector<size_t> input_size{10};
-    std::vector<size_t> sequence_axis{0, 1};
-    std::vector<ngraph::helpers::TensorIteratorBody> body_type
-        = {ngraph::helpers::TensorIteratorBody::LSTM, ngraph::helpers::TensorIteratorBody::RNN,
-           ngraph::helpers::TensorIteratorBody::GRU};
-    std::vector<float> clip{0.f};
-    std::vector<float> clip_non_zeros{0.7f};
-    std::vector<ngraph::op::RecurrentSequenceDirection> direction = {ngraph::op::RecurrentSequenceDirection::FORWARD,
-                                                           ngraph::op::RecurrentSequenceDirection::REVERSE};
-    std::vector<InferenceEngine::Precision> netPrecisions = {InferenceEngine::Precision::FP32,
-                                                             InferenceEngine::Precision::FP16};
+std::vector<bool> should_decompose = {true, false};
+// output values increase rapidly without clip, so use only seq_lengths = 2
+std::vector<size_t> seq_lengths_zero_clip{2};
+std::vector<size_t> seq_lengths_clip_non_zero{20};
+std::vector<size_t> batch{1, 10};
+std::vector<size_t> hidden_size{1, 10};
+// std::vector<size_t> input_size{10};
+std::vector<size_t> sequence_axis{0, 1};
+std::vector<ov::test::utils::TensorIteratorBody> body_type
+= {ov::test::utils::TensorIteratorBody::LSTM, ov::test::utils::TensorIteratorBody::RNN,
+        ov::test::utils::TensorIteratorBody::GRU};
+std::vector<float> clip{0.f};
+std::vector<float> clip_non_zeros{0.7f};
+std::vector<ov::op::RecurrentSequenceDirection> direction = {ov::op::RecurrentSequenceDirection::FORWARD,
+                                                                 ov::op::RecurrentSequenceDirection::REVERSE};
+std::vector<ov::element::Type> model_types = {ov::element::f32, ov::element::f16};
 
-    INSTANTIATE_TEST_SUITE_P(smoke_TensorIteratorCommon, TensorIteratorTest,
-                            ::testing::Combine(
-                                    ::testing::ValuesIn(should_decompose),
-                                    ::testing::ValuesIn(seq_lengths_zero_clip),
-                                    ::testing::ValuesIn(batch),
-                                    ::testing::ValuesIn(hidden_size),
-                                    //::testing::ValuesIn(input_size), // hardcoded to 10 due to Combine supports up to 10 args
-                                    ::testing::ValuesIn(sequence_axis),
-                                    ::testing::ValuesIn(clip),
-                                    ::testing::ValuesIn(body_type),
-                                    ::testing::ValuesIn(direction),
-                                    ::testing::ValuesIn(netPrecisions),
-                                    ::testing::Values(ov::test::utils::DEVICE_CPU)),
-                            TensorIteratorTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TensorIteratorCommon, TensorIteratorTest,
+                        ::testing::Combine(
+                                ::testing::ValuesIn(should_decompose),
+                                ::testing::ValuesIn(seq_lengths_zero_clip),
+                                ::testing::ValuesIn(batch),
+                                ::testing::ValuesIn(hidden_size),
+                                //::testing::ValuesIn(input_size), // hardcoded to 10 due to Combine supports up to 10 args
+                                ::testing::ValuesIn(sequence_axis),
+                                ::testing::ValuesIn(clip),
+                                ::testing::ValuesIn(body_type),
+                                ::testing::ValuesIn(direction),
+                                ::testing::ValuesIn(model_types),
+                                ::testing::Values(ov::test::utils::DEVICE_CPU)),
+                        TensorIteratorTest::getTestCaseName);
 
-    INSTANTIATE_TEST_SUITE_P(smoke_TensorIteratorCommonClip, TensorIteratorTest,
-                            ::testing::Combine(
-                                    ::testing::ValuesIn(should_decompose),
-                                    ::testing::ValuesIn(seq_lengths_clip_non_zero),
-                                    ::testing::ValuesIn(batch),
-                                    ::testing::ValuesIn(hidden_size),
-                                    //::testing::ValuesIn(input_size), // hardcoded to 10 due to Combine supports up to 10 args
-                                    ::testing::ValuesIn(sequence_axis),
-                                    ::testing::ValuesIn(clip_non_zeros),
-                                    ::testing::ValuesIn(body_type),
-                                    ::testing::ValuesIn(direction),
-                                    ::testing::ValuesIn(netPrecisions),
-                                    ::testing::Values(ov::test::utils::DEVICE_CPU)),
-                            TensorIteratorTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TensorIteratorCommonClip, TensorIteratorTest,
+                        ::testing::Combine(
+                                ::testing::ValuesIn(should_decompose),
+                                ::testing::ValuesIn(seq_lengths_clip_non_zero),
+                                ::testing::ValuesIn(batch),
+                                ::testing::ValuesIn(hidden_size),
+                                //::testing::ValuesIn(input_size), // hardcoded to 10 due to Combine supports up to 10 args
+                                ::testing::ValuesIn(sequence_axis),
+                                ::testing::ValuesIn(clip_non_zeros),
+                                ::testing::ValuesIn(body_type),
+                                ::testing::ValuesIn(direction),
+                                ::testing::ValuesIn(model_types),
+                                ::testing::Values(ov::test::utils::DEVICE_CPU)),
+                        TensorIteratorTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/tests/functional/plugin/shared/include/single_op_tests/tensor_iterator.hpp b/src/tests/functional/plugin/shared/include/single_op_tests/tensor_iterator.hpp
new file mode 100644
index 00000000000000..f2409efa0cdeb3
--- /dev/null
+++ b/src/tests/functional/plugin/shared/include/single_op_tests/tensor_iterator.hpp
@@ -0,0 +1,15 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/single_op/tensor_iterator.hpp"
+
+namespace ov {
+namespace test {
+TEST_P(TensorIteratorTest, Inference) {
+    run();
+};
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/tensor_iterator.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/tensor_iterator.hpp
new file mode 100644
index 00000000000000..27e8a4e420d5ec
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/tensor_iterator.hpp
@@ -0,0 +1,39 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <tuple>
+#include <string>
+#include <vector>
+#include <memory>
+#include "shared_test_classes/base/ov_subgraph.hpp"
+#include "common_test_utils/test_enums.hpp"
+
+namespace ov {
+namespace test {
+using TensorIteratorParams = typename std::tuple<
+        bool,                                     // using unroll tensor iterator transformation
+        size_t,                                   // seq_lengths
+        size_t,                                   // batch
+        size_t,                                   // hidden size
+        // todo: fix. input size hardcoded to 10 due to limitation (10 args) of gtests Combine() func.
+        //size_t,                                 // input size
+        size_t,                                   // sequence axis
+        float,                                    // clip
+        ov::test::utils::TensorIteratorBody,      // body type
+        ov::op::RecurrentSequenceDirection,       // direction
+        ov::element::Type,                        // Model type
+        ov::test::TargetDevice>;                  // Device name
+
+class TensorIteratorTest : public testing::WithParamInterface<TensorIteratorParams>,
+                           virtual public ov::test::SubgraphBaseTest {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<TensorIteratorParams> &obj);
+
+protected:
+    void SetUp() override;
+};
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/single_op/tensor_iterator.cpp b/src/tests/functional/shared_test_classes/src/single_op/tensor_iterator.cpp
new file mode 100644
index 00000000000000..7cf3bd44972846
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/src/single_op/tensor_iterator.cpp
@@ -0,0 +1,238 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/control_flow/unroll_tensor_iterator.hpp"
+#include "shared_test_classes/single_op/tensor_iterator.hpp"
+#include "openvino/pass/manager.hpp"
+#include "ngraph_functions/builders.hpp"
+
+namespace ov {
+namespace test {
+std::string TensorIteratorTest::getTestCaseName(const testing::TestParamInfo<TensorIteratorParams> &obj) {
+    bool should_decompose;
+    size_t seq_lengths;
+    size_t batch;
+    size_t hidden_size;
+    size_t input_size = 10;
+    size_t sequence_axis;
+    ov::test::utils::TensorIteratorBody ti_body;
+    float clip;
+    ov::op::RecurrentSequenceDirection direction;
+    ov::element::Type model_type;
+    std::string target_device;
+    std::tie(should_decompose, seq_lengths, batch, hidden_size, sequence_axis, clip, ti_body, direction, model_type,
+                target_device) = obj.param;
+    std::vector<ov::Shape> input_shapes = {};
+
+    switch (ti_body) {
+        case ov::test::utils::TensorIteratorBody::LSTM:
+            input_shapes = {
+                    {{batch, input_size}, {batch, hidden_size}, {batch, hidden_size}, {4 * hidden_size, input_size},
+                            {4 * hidden_size, hidden_size}, {4 * hidden_size}},
+            };
+            break;
+        case ov::test::utils::TensorIteratorBody::GRU:
+            input_shapes = {
+                    {{batch, input_size}, {batch, hidden_size}, {3 * hidden_size, input_size},
+                            {3 * hidden_size, hidden_size}, {3 * hidden_size}},
+            };
+            break;
+        case ov::test::utils::TensorIteratorBody::RNN:
+            input_shapes = {{batch, input_size}, {batch, hidden_size},
+                            {hidden_size, input_size}, {hidden_size, hidden_size}, {hidden_size}};
+            break;
+    }
+
+    std::ostringstream result;
+    result << "unrolling=" << should_decompose << "_";
+    result << "seq_len=" << seq_lengths << "_";
+    result << "seq_len_axis=" << sequence_axis << "_";
+    result << "batch=" << batch << "_";
+    result << "hidden_size=" << hidden_size << "_";
+    result << "input_size=" << input_size << "_";
+    result << "IS=" << ov::test::utils::vec2str(input_shapes) << "_";
+    result << "TensorIteratorBody=" << ti_body << "_";
+    result << "direction=" << direction << "_";
+    result << "clip=" << clip << "_";
+    result << "modelType=" << model_type.to_string() << "_";
+    result << "targetDevice=" << target_device << "_";
+    return result.str();
+}
+
+void TensorIteratorTest::SetUp() {
+    size_t seq_lengths;
+    bool should_decompose;
+    size_t batch;
+    size_t hidden_size;
+    size_t input_size = 10;
+    size_t sequence_axis;
+    ov::test::utils::TensorIteratorBody ti_body;
+    float clip;
+    ov::op::RecurrentSequenceDirection direction;
+    ov::element::Type model_type;
+    std::tie(should_decompose, seq_lengths, batch, hidden_size, sequence_axis, clip, ti_body, direction, model_type,
+                targetDevice) = this->GetParam();
+    std::vector<ov::Shape> input_shapes;
+    auto tensor_iterator = std::make_shared<ov::op::v0::TensorIterator>();
+
+    // Each case consist of 3 steps:
+    // 1. Create TensorIterator body.
+    // 2. Set PortMap
+    // 3. Create outer function
+    auto axis = std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{1},
+                                                       std::vector<int64_t>{static_cast<int64_t>(sequence_axis)});
+    switch (ti_body) {
+        case ov::test::utils::TensorIteratorBody::LSTM: {
+            input_shapes = {
+                    {{batch, seq_lengths, input_size}, {batch, hidden_size}, {batch, hidden_size}, {4 * hidden_size, input_size},
+                            {4 * hidden_size, hidden_size}, {4 * hidden_size}},
+            };
+            if (sequence_axis == 0) {
+                // swap batch and seq_lengths
+                std::swap(input_shapes[0][0], input_shapes[0][1]);
+            }
+            init_input_shapes(static_shapes_to_test_representation(input_shapes));
+            ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[0]),
+                                                std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[1]),
+                                                std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[2])};
+
+            // 1. Create TensorIterator body.
+            inputDynamicShapes[0][sequence_axis] = 1; // sliced dimension
+            ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[0]),
+                                            std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[1]),
+                                            std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[2])};
+
+            auto squeeze = std::make_shared<ov::op::v0::Squeeze>(body_params[0], axis);
+            std::vector<ov::Shape> WRB = {input_shapes[3], input_shapes[4], input_shapes[5]};
+            ov::OutputVector out_vector = {squeeze, body_params[1], body_params[2]};
+            auto lstm_cell = ngraph::builder::makeLSTM(out_vector, WRB, hidden_size, {"sigmoid", "tanh", "tanh"}, {}, {}, clip);
+            auto unsqueeze = std::make_shared<ov::op::v0::Unsqueeze>(lstm_cell->output(0), axis);
+            ov::ResultVector results{std::make_shared<ov::op::v0::Result>(unsqueeze),
+                                     std::make_shared<ov::op::v0::Result>(lstm_cell->output(0)),
+                                     std::make_shared<ov::op::v0::Result>(lstm_cell->output(1))};
+            auto body = std::make_shared<ov::Model>(results, body_params, "lstm_cell");
+            tensor_iterator->set_function(body);
+
+            // 2. Set PortMap
+            if (direction == ov::op::RecurrentSequenceDirection::FORWARD) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, sequence_axis);
+                tensor_iterator->get_concatenated_slices(results[0], 0, 1, 1, -1, sequence_axis);
+            } else if (direction == ov::op::RecurrentSequenceDirection::REVERSE) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, sequence_axis);
+                tensor_iterator->get_concatenated_slices(results[0], -1, -1, 1, 0, sequence_axis);
+            } else {
+                OPENVINO_THROW("Bidirectional case is not supported.");
+            }
+
+            tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[1]);
+            tensor_iterator->set_merged_input(body_params[2], outer_params[2], results[2]);
+            tensor_iterator->get_iter_value(results[1]);
+            tensor_iterator->get_iter_value(results[2]);
+
+            // 3. Outer model
+            function = std::make_shared<ov::Model>(tensor_iterator->outputs(), outer_params);
+            break;
+        }
+        case ov::test::utils::TensorIteratorBody::GRU: {
+            input_shapes = {
+                    {{batch, seq_lengths, input_size}, {batch, hidden_size}, {3 * hidden_size, input_size},
+                            {3 * hidden_size, hidden_size}, {3 * hidden_size}},
+            };
+            if (sequence_axis == 0) {
+                // swap batch and seq_lengths
+                std::swap(input_shapes[0][0], input_shapes[0][1]);
+            }
+            init_input_shapes(static_shapes_to_test_representation(input_shapes));
+            ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[0]),
+                                             std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[1])};
+
+            // 1. Create TensorIterator body.
+            inputDynamicShapes[0][sequence_axis] = 1; // sliced dimension
+            ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[0]),
+                                            std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[1])};
+
+            std::vector<ov::Shape> WRB = {input_shapes[2], input_shapes[3], input_shapes[4]};
+            auto squeeze = std::make_shared<ov::op::v0::Squeeze>(body_params[0], axis);
+            ov::OutputVector out_vector = {squeeze, body_params[1]};
+            auto gru_cell = ngraph::builder::makeGRU(out_vector, WRB, hidden_size, {"sigmoid", "tanh"},
+                                                     {}, {}, clip, false);
+            auto unsqueeze = std::make_shared<ov::op::v0::Unsqueeze>(gru_cell->output(0), axis);
+            ov::ResultVector results{std::make_shared<ov::op::v0::Result>(gru_cell->output(0)),
+                                     std::make_shared<ov::op::v0::Result>(unsqueeze)};
+            auto body = std::make_shared<ov::Model>(results, body_params, "gru_cell");
+            tensor_iterator->set_function(body);
+
+            // 2. Set PortMap
+            if (direction == ov::op::RecurrentSequenceDirection::FORWARD) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, sequence_axis);
+                tensor_iterator->get_concatenated_slices(results[1], 0, 1, 1, -1, sequence_axis);
+            } else if (direction == ov::op::RecurrentSequenceDirection::REVERSE) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, sequence_axis);
+                tensor_iterator->get_concatenated_slices(results[1], -1, -1, 1, 0, sequence_axis);
+            } else {
+                OPENVINO_THROW("Bidirectional case is not supported.");
+            }
+
+            tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[0]);
+            tensor_iterator->get_iter_value(results[0]);
+
+            // 3. Outer function
+            function = std::make_shared<ov::Model>(ov::OutputVector{tensor_iterator->output(0), tensor_iterator->output(1)}, outer_params);
+            break;
+        }
+        case ov::test::utils::TensorIteratorBody::RNN: {
+            input_shapes = {{batch, seq_lengths, input_size},
+                            {batch,       hidden_size},
+                            {hidden_size, input_size},
+                            {hidden_size, hidden_size},
+                            {hidden_size}};
+            if (sequence_axis == 0) {
+                // swap batch and seq_lengths
+                std::swap(input_shapes[0][0], input_shapes[0][1]);
+            }
+            init_input_shapes(static_shapes_to_test_representation(input_shapes));
+            ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[0]),
+                                             std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[1])};
+
+            // 1. Create TensorIterator body.
+            inputDynamicShapes[0][sequence_axis] = 1; // sliced dimension
+            ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[0]),
+                                            std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes[1])};
+            std::vector<ov::Shape> WRB = {input_shapes[2], input_shapes[3], input_shapes[4]};
+            auto squeeze = std::make_shared<ov::op::v0::Squeeze>(body_params[0], axis);
+            ov::OutputVector out_vector = {squeeze, body_params[1]};
+            auto rnn_cell = ngraph::builder::makeRNN(out_vector, WRB, hidden_size, {"tanh"}, {}, {}, clip);
+            auto unsqueeze = std::make_shared<ov::op::v0::Unsqueeze>(rnn_cell->output(0), axis);
+            ov::ResultVector results{std::make_shared<ov::op::v0::Result>(rnn_cell),
+                                     std::make_shared<ov::op::v0::Result>(unsqueeze)};
+            auto body = std::make_shared<ov::Model>(results, body_params, "rnn_cell");
+            tensor_iterator->set_function(body);
+
+            // 2. Set PortMap
+            if (direction == ov::op::RecurrentSequenceDirection::FORWARD) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, sequence_axis);
+                tensor_iterator->get_concatenated_slices(results[1], 0, 1, 1, -1, sequence_axis);
+            } else if (direction == ov::op::RecurrentSequenceDirection::REVERSE) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, sequence_axis);
+                tensor_iterator->get_concatenated_slices(results[1], -1, -1, 1, 0, sequence_axis);
+            } else {
+                OPENVINO_THROW("Bidirectional case is not supported.");
+            }
+
+            tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[0]);
+            tensor_iterator->get_iter_value(results[0]);
+
+            // 3. Outer function
+            function = std::make_shared<ov::Model>(ov::OutputVector{tensor_iterator->output(0), tensor_iterator->output(1)}, outer_params);
+            break;
+        }
+    }
+    if (should_decompose) {
+        ov::pass::Manager m;
+        m.register_pass<ov::pass::UnrollTensorIterator>();
+        m.run_passes(function);
+    }
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/ngraph_helpers/ngraph_functions/include/ngraph_functions/utils/ngraph_helpers.hpp b/src/tests/ngraph_helpers/ngraph_functions/include/ngraph_functions/utils/ngraph_helpers.hpp
index e8d16e0cfb783b..5d0f3cd4ac7d0b 100644
--- a/src/tests/ngraph_helpers/ngraph_functions/include/ngraph_functions/utils/ngraph_helpers.hpp
+++ b/src/tests/ngraph_helpers/ngraph_functions/include/ngraph_functions/utils/ngraph_helpers.hpp
@@ -85,19 +85,11 @@ enum QuantizationGranularity {
     Perchannel
 };
 
+using ov::test::utils::TensorIteratorBody;
 using ov::test::utils::ReductionType;
 using ov::test::utils::DFTOpType;
 using ov::test::utils::InputLayerType;
 using ov::test::utils::PadMode;
-
-
-enum class TensorIteratorBody {
-    RNN,
-    GRU,
-    LSTM,
-    // CNN todo: implement
-};
-
 using ov::test::utils::SequenceTestsMode;
 
 enum class MemoryTransformation {
@@ -169,8 +161,6 @@ std::vector<std::uint8_t> convertOutputPrecision(const std::vector<std::uint8_t>
                                                  const element::Type_t& toPrecision,
                                                  const size_t elementsCount);
 
-std::ostream& operator<<(std::ostream& os, TensorIteratorBody type);
-
 std::ostream& operator<<(std::ostream& os, MemoryTransformation type);
 
 void resize_function(std::shared_ptr<ov::Model> function, const std::vector<ov::Shape>& targetInputStaticShapes);
diff --git a/src/tests/ngraph_helpers/ngraph_functions/src/utils/ngraph_helpers.cpp b/src/tests/ngraph_helpers/ngraph_functions/src/utils/ngraph_helpers.cpp
index ff28247546f311..6237536c9436e8 100644
--- a/src/tests/ngraph_helpers/ngraph_functions/src/utils/ngraph_helpers.cpp
+++ b/src/tests/ngraph_helpers/ngraph_functions/src/utils/ngraph_helpers.cpp
@@ -650,23 +650,6 @@ std::vector<std::uint8_t> convertOutputPrecision(const std::vector<std::uint8_t>
     }
 }
 
-std::ostream& operator<<(std::ostream& os, TensorIteratorBody type) {
-    switch (type) {
-    case TensorIteratorBody::LSTM:
-        os << "LSTM";
-        break;
-    case TensorIteratorBody::RNN:
-        os << "RNN";
-        break;
-    case TensorIteratorBody::GRU:
-        os << "GRU";
-        break;
-    default:
-        throw std::runtime_error("NOT_SUPPORTED_OP_TYPE");
-    }
-    return os;
-}
-
 std::ostream& operator<<(std::ostream& os, MemoryTransformation type) {
     switch (type) {
     case MemoryTransformation::NONE:
diff --git a/src/tests/test_utils/common_test_utils/include/common_test_utils/test_enums.hpp b/src/tests/test_utils/common_test_utils/include/common_test_utils/test_enums.hpp
index 4311535df95697..6e73dd07a5adac 100644
--- a/src/tests/test_utils/common_test_utils/include/common_test_utils/test_enums.hpp
+++ b/src/tests/test_utils/common_test_utils/include/common_test_utils/test_enums.hpp
@@ -152,6 +152,13 @@ enum class DFTOpType {
     INVERSE
 };
 
+enum class TensorIteratorBody {
+    RNN,
+    GRU,
+    LSTM,
+    // CNN todo: implement
+};
+
 // clang-format on
 
 std::ostream& operator<<(std::ostream& os, const ReductionType& m);
@@ -182,6 +189,8 @@ std::ostream& operator<<(std::ostream& os, ov::op::v8::MatrixNms::SortResultType
 
 std::ostream& operator<<(std::ostream& os, ov::op::v8::MatrixNms::DecayFunction type);
 
+std::ostream& operator<<(std::ostream& os, TensorIteratorBody type);
+
 }  // namespace utils
 }  // namespace test
 }  // namespace ov
diff --git a/src/tests/test_utils/common_test_utils/src/test_enums.cpp b/src/tests/test_utils/common_test_utils/src/test_enums.cpp
index 446aae2cda769a..8bb1cff3ce77dc 100644
--- a/src/tests/test_utils/common_test_utils/src/test_enums.cpp
+++ b/src/tests/test_utils/common_test_utils/src/test_enums.cpp
@@ -322,6 +322,23 @@ std::ostream& operator<<(std::ostream& os, op::v8::MatrixNms::DecayFunction type
     return os;
 }
 
+std::ostream& operator<<(std::ostream& os, TensorIteratorBody type) {
+    switch (type) {
+    case TensorIteratorBody::LSTM:
+        os << "LSTM";
+        break;
+    case TensorIteratorBody::RNN:
+        os << "RNN";
+        break;
+    case TensorIteratorBody::GRU:
+        os << "GRU";
+        break;
+    default:
+        throw std::runtime_error("NOT_SUPPORTED_OP_TYPE");
+    }
+    return os;
+}
+
 }  // namespace utils
 }  // namespace test
 }  // namespace ov

From f926e0e3920e27d81355f007f3b5dcfb51342ad1 Mon Sep 17 00:00:00 2001
From: Maxim Vafin <maxim.vafin@intel.com>
Date: Tue, 19 Sep 2023 14:02:46 +0200
Subject: [PATCH 23/46] [PT FE] Simplify repeat operation (#19926)

---
 src/frontends/pytorch/src/op/repeat.cpp | 34 -------------------------
 src/frontends/pytorch/src/op_table.cpp  |  3 +--
 2 files changed, 1 insertion(+), 36 deletions(-)
 delete mode 100644 src/frontends/pytorch/src/op/repeat.cpp

diff --git a/src/frontends/pytorch/src/op/repeat.cpp b/src/frontends/pytorch/src/op/repeat.cpp
deleted file mode 100644
index 15dc03a466ec92..00000000000000
--- a/src/frontends/pytorch/src/op/repeat.cpp
+++ /dev/null
@@ -1,34 +0,0 @@
-// Copyright (C) 2018-2023 Intel Corporation
-// SPDX-License-Identifier: Apache-2.0
-//
-
-#include "openvino/frontend/pytorch/node_context.hpp"
-#include "openvino/op/broadcast.hpp"
-#include "openvino/op/constant.hpp"
-#include "openvino/op/shape_of.hpp"
-#include "openvino/op/tile.hpp"
-#include "utils.hpp"
-
-namespace ov {
-namespace frontend {
-namespace pytorch {
-namespace op {
-
-using namespace ov::op;
-
-OutputVector translate_repeat(const NodeContext& context) {
-    num_inputs_check(context, 2, 2);
-    auto x = context.get_input(0);
-    auto repeats = context.get_input(1);
-    auto one = context.mark_node(v0::Constant::create(element::i32, Shape{}, {1}));
-    auto sizes_shape = context.mark_node(std::make_shared<v3::ShapeOf>(repeats, element::i32));
-    auto expand_shape = context.mark_node(std::make_shared<v3::Broadcast>(one, sizes_shape));
-    auto expanded_input =
-        context.mark_node(std::make_shared<v3::Broadcast>(x, expand_shape, BroadcastType::BIDIRECTIONAL));
-    return {context.mark_node(std::make_shared<v0::Tile>(expanded_input, repeats))};
-};
-
-}  // namespace op
-}  // namespace pytorch
-}  // namespace frontend
-}  // namespace ov
\ No newline at end of file
diff --git a/src/frontends/pytorch/src/op_table.cpp b/src/frontends/pytorch/src/op_table.cpp
index 87358dd4d42ee3..4dd60e01b71d7f 100644
--- a/src/frontends/pytorch/src/op_table.cpp
+++ b/src/frontends/pytorch/src/op_table.cpp
@@ -134,7 +134,6 @@ OP_CONVERTER(translate_randn_like);
 OP_CONVERTER(translate_reciprocal);
 OP_CONVERTER(translate_relu6);
 OP_CONVERTER(translate_remainder);
-OP_CONVERTER(translate_repeat);
 OP_CONVERTER(translate_repeat_interleave);
 OP_CONVERTER(translate_reshape);
 OP_CONVERTER(translate_reshape_as);
@@ -393,7 +392,7 @@ const std::map<std::string, CreatorFunction> get_supported_ops_ts() {
         {"aten::relu_", op::inplace_op<op::translate_1to1_match_1_inputs<opset10::Relu>>},
         {"aten::relu6", op::translate_relu6},
         {"aten::remainder", op::translate_remainder},
-        {"aten::repeat", op::translate_repeat},
+        {"aten::repeat", op::inplace_op<op::translate_1to1_match_2_inputs<opset10::Tile>>},
         {"aten::repeat_interleave", op::translate_repeat_interleave},
         {"aten::reshape", op::translate_reshape},
         {"aten::reshape_as", op::translate_reshape_as},

From 57df7a44b7f24f98dd4d0066af5133da01206e68 Mon Sep 17 00:00:00 2001
From: Oleg Pipikin <oleg.pipikin@intel.com>
Date: Tue, 19 Sep 2023 15:03:06 +0200
Subject: [PATCH 24/46] Refactor  CTCGreedyDecoderSeqLenLayerTest,
 GreedyDecoderLayerTest,  CTCLossLayerTest (#19842)

* Refactor CTCGreedyDecoderSeqLenLayerTest

* Refactor usingGreedyDecoderLayerTest

* Refactor CTCLossLayerTest
---
 .../single_layer_tests/ctc_greedy_decoder.cpp |  39 +++---
 .../ctc_greedy_decoder_seq_len.cpp            |  31 +++--
 .../single_layer_tests/ctc_loss.cpp           |  29 ++--
 .../single_op_tests/ctc_greedy_decoder.hpp    |  15 +++
 .../ctc_greedy_decoder_seq_len.hpp            |  15 +++
 .../include/single_op_tests/ctc_loss.hpp      |  15 +++
 .../single_op/ctc_greedy_decoder.hpp          |  31 +++++
 .../single_op/ctc_greedy_decoder_seq_len.hpp  |  36 +++++
 .../single_op/ctc_loss.hpp                    |  43 ++++++
 .../src/single_op/ctc_greedy_decoder.cpp      |  75 +++++++++++
 .../single_op/ctc_greedy_decoder_seq_len.cpp  | 124 ++++++++++++++++++
 .../src/single_op/ctc_loss.cpp                |  92 +++++++++++++
 12 files changed, 495 insertions(+), 50 deletions(-)
 create mode 100644 src/tests/functional/plugin/shared/include/single_op_tests/ctc_greedy_decoder.hpp
 create mode 100644 src/tests/functional/plugin/shared/include/single_op_tests/ctc_greedy_decoder_seq_len.hpp
 create mode 100644 src/tests/functional/plugin/shared/include/single_op_tests/ctc_loss.hpp
 create mode 100644 src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_greedy_decoder.hpp
 create mode 100644 src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_greedy_decoder_seq_len.hpp
 create mode 100644 src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_loss.hpp
 create mode 100644 src/tests/functional/shared_test_classes/src/single_op/ctc_greedy_decoder.cpp
 create mode 100644 src/tests/functional/shared_test_classes/src/single_op/ctc_greedy_decoder_seq_len.cpp
 create mode 100644 src/tests/functional/shared_test_classes/src/single_op/ctc_loss.cpp

diff --git a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_greedy_decoder.cpp b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_greedy_decoder.cpp
index 3e6cc4ebf2f872..0149a60ba1cb23 100644
--- a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_greedy_decoder.cpp
+++ b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_greedy_decoder.cpp
@@ -2,35 +2,32 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-#include "single_layer_tests/ctc_greedy_decoder.hpp"
+#include "single_op_tests/ctc_greedy_decoder.hpp"
 #include "common_test_utils/test_constants.hpp"
 
-using namespace LayerTestsDefinitions;
-using namespace ngraph::helpers;
-
 namespace {
+using ov::test::CTCGreedyDecoderLayerTest;
+
 // Common params
-const std::vector<InferenceEngine::Precision> netPrecisions = {
-    InferenceEngine::Precision::FP32,
-    InferenceEngine::Precision::FP16
+const std::vector<ov::element::Type> model_type = {
+    ov::element::f32,
+    ov::element::f16
 };
 std::vector<bool> mergeRepeated{true, false};
 
+std::vector<std::vector<ov::Shape>> input_shapes_static = {
+    {{ 50, 3, 3 }},
+    {{ 50, 3, 7 }},
+    {{ 50, 3, 8 }},
+    {{ 50, 3, 16 }},
+    {{ 50, 3, 128 }},
+    {{ 50, 3, 49 }},
+    {{ 50, 3, 55 }},
+    {{ 1, 1, 16 }}};
+
 const auto basicCases = ::testing::Combine(
-    ::testing::ValuesIn(netPrecisions),
-    ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-    ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-    ::testing::Values(InferenceEngine::Layout::ANY),
-    ::testing::Values(InferenceEngine::Layout::ANY),
-    ::testing::Values(std::vector<size_t>({ 50, 3, 3 }),
-                      std::vector<size_t>({ 50, 3, 7 }),
-                      std::vector<size_t>({ 50, 3, 8 }),
-                      std::vector<size_t>({ 50, 3, 16 }),
-                      std::vector<size_t>({ 50, 3, 128 }),
-                      std::vector<size_t>({ 50, 3, 49 }),
-                      std::vector<size_t>({ 50, 3, 55 }),
-                      std::vector<size_t>({ 1, 1, 16 })),
+    ::testing::ValuesIn(model_type),
+    ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(input_shapes_static)),
     ::testing::ValuesIn(mergeRepeated),
     ::testing::Values(ov::test::utils::DEVICE_CPU));
 
diff --git a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_greedy_decoder_seq_len.cpp b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_greedy_decoder_seq_len.cpp
index 4b843fcb2c941a..bc83d623c8a6b2 100644
--- a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_greedy_decoder_seq_len.cpp
+++ b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_greedy_decoder_seq_len.cpp
@@ -2,30 +2,30 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-#include "single_layer_tests/ctc_greedy_decoder_seq_len.hpp"
+#include "single_op_tests/ctc_greedy_decoder_seq_len.hpp"
 #include "common_test_utils/test_constants.hpp"
 
-using namespace LayerTestsDefinitions;
-using namespace ngraph::helpers;
-
 namespace {
+using ov::test::CTCGreedyDecoderSeqLenLayerTest;
 
-std::vector<std::vector<size_t>> inputShape{{1, 1, 1}, {1, 6, 10}, {3, 3, 16}, {5, 3, 55}};
+std::vector<std::vector<ov::Shape>> shapes1 = {{{1, 1, 1}},
+                                               {{1, 6, 10}},
+                                               {{3, 3, 16}},
+                                               {{5, 3, 55}}};
 
-const std::vector<InferenceEngine::Precision> probPrecisions = {
-    InferenceEngine::Precision::FP32,
-    InferenceEngine::Precision::FP16
+const std::vector<ov::element::Type> probPrecisions = {
+    ov::element::f32,
+    ov::element::f16
 };
-const std::vector<InferenceEngine::Precision> idxPrecisions = {
-    InferenceEngine::Precision::I32,
-    InferenceEngine::Precision::I64
+const std::vector<ov::element::Type> idxPrecisions = {
+    ov::element::i32,
+    ov::element::i64
 };
 
 std::vector<bool> mergeRepeated{true, false};
 
 const auto basicCases = ::testing::Combine(
-    ::testing::ValuesIn(inputShape),
+    ::testing::ValuesIn(ov::test::static_shapes_to_test_representation({shapes1})),
     ::testing::Values(10),
     ::testing::ValuesIn(probPrecisions),
     ::testing::ValuesIn(idxPrecisions),
@@ -37,9 +37,12 @@ INSTANTIATE_TEST_SUITE_P(smoke_set1, CTCGreedyDecoderSeqLenLayerTest,
                         basicCases,
                         CTCGreedyDecoderSeqLenLayerTest::getTestCaseName);
 
+std::vector<std::vector<ov::Shape>> shapes2 = {{{2, 8, 11}},
+                                               {{4, 10, 55}}};
+
 INSTANTIATE_TEST_SUITE_P(smoke_set2, CTCGreedyDecoderSeqLenLayerTest,
         ::testing::Combine(
-                        ::testing::ValuesIn(std::vector<std::vector<size_t>>{{2, 8, 11}, {4, 10, 55}}),
+                        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation({shapes2})),
                         ::testing::ValuesIn(std::vector<int>{5, 100}),
                         ::testing::ValuesIn(probPrecisions),
                         ::testing::ValuesIn(idxPrecisions),
diff --git a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_loss.cpp b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_loss.cpp
index c5da048ce40bc1..45a341a39003d4 100644
--- a/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_loss.cpp
+++ b/src/plugins/intel_cpu/tests/functional/shared_tests_instances/single_layer_tests/ctc_loss.cpp
@@ -4,19 +4,18 @@
 
 #include <vector>
 
-#include "single_layer_tests/ctc_loss.hpp"
-
-using namespace LayerTestsDefinitions;
+#include "single_op_tests/ctc_loss.hpp"
 
 namespace {
+using ov::test::CTCLossLayerTest;
 
-const std::vector<InferenceEngine::Precision> fPrecisions = {
-        InferenceEngine::Precision::FP32,
-        InferenceEngine::Precision::FP16
+const std::vector<ov::element::Type> f_type = {
+        ov::element::f32,
+        ov::element::f16
 };
-const std::vector<InferenceEngine::Precision> iPrecisions = {
-        InferenceEngine::Precision::I32,
-        InferenceEngine::Precision::I64
+const std::vector<ov::element::Type> i_type = {
+        ov::element::i32,
+        ov::element::i64
 };
 
 const std::vector<bool> preprocessCollapseRepeated = {true, false};
@@ -24,7 +23,6 @@ const std::vector<bool> ctcMergeRepeated = {true, false};
 const std::vector<bool> unique = {true, false};
 
 const auto ctcLossArgsSubset1 = ::testing::Combine(
-        ::testing::Values(std::vector<size_t>({2, 3, 3})),                    // logits shape
         ::testing::ValuesIn(std::vector<std::vector<int>>({{2, 3}, {3, 3}})), // logits length
         ::testing::ValuesIn(std::vector<std::vector<std::vector<int>>>(
             {{{0, 1, 0}, {1, 0, 1}}, {{0, 1, 2}, {1, 1, 1}}})),               // labels
@@ -38,13 +36,13 @@ const auto ctcLossArgsSubset1 = ::testing::Combine(
 INSTANTIATE_TEST_SUITE_P(smoke_Set1, CTCLossLayerTest,
                         ::testing::Combine(
                             ctcLossArgsSubset1,
-                            ::testing::ValuesIn(fPrecisions),
-                            ::testing::ValuesIn(iPrecisions),
+                            ::testing::Values(ov::test::static_shapes_to_test_representation({{2, 3, 3}})),
+                            ::testing::ValuesIn(f_type),
+                            ::testing::ValuesIn(i_type),
                             ::testing::Values(ov::test::utils::DEVICE_CPU)),
                         CTCLossLayerTest::getTestCaseName);
 
 const auto ctcLossArgsSubset2 = ::testing::Combine(
-        ::testing::Values(std::vector<size_t>({3, 6, 8})),                          // logits shape
         ::testing::ValuesIn(std::vector<std::vector<int>>({{6, 5, 6}, {5, 5, 5}})), // logits length
         ::testing::ValuesIn(std::vector<std::vector<std::vector<int>>>(
             {{{4, 1, 2, 3, 4, 5}, {5, 4, 3, 0, 1, 0}, {2, 1, 3, 1, 3, 0}},
@@ -59,8 +57,9 @@ const auto ctcLossArgsSubset2 = ::testing::Combine(
 INSTANTIATE_TEST_SUITE_P(smoke_Set2, CTCLossLayerTest,
                         ::testing::Combine(
                             ctcLossArgsSubset2,
-                            ::testing::ValuesIn(fPrecisions),
-                            ::testing::ValuesIn(iPrecisions),
+                            ::testing::Values(ov::test::static_shapes_to_test_representation({{3, 6, 8}})),
+                            ::testing::ValuesIn(f_type),
+                            ::testing::ValuesIn(i_type),
                             ::testing::Values(ov::test::utils::DEVICE_CPU)),
                         CTCLossLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/tests/functional/plugin/shared/include/single_op_tests/ctc_greedy_decoder.hpp b/src/tests/functional/plugin/shared/include/single_op_tests/ctc_greedy_decoder.hpp
new file mode 100644
index 00000000000000..2a3785283f2c14
--- /dev/null
+++ b/src/tests/functional/plugin/shared/include/single_op_tests/ctc_greedy_decoder.hpp
@@ -0,0 +1,15 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/single_op/ctc_greedy_decoder.hpp"
+
+namespace ov {
+namespace test {
+TEST_P(CTCGreedyDecoderLayerTest, Inference) {
+    run();
+};
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/plugin/shared/include/single_op_tests/ctc_greedy_decoder_seq_len.hpp b/src/tests/functional/plugin/shared/include/single_op_tests/ctc_greedy_decoder_seq_len.hpp
new file mode 100644
index 00000000000000..edcb79b3e050f7
--- /dev/null
+++ b/src/tests/functional/plugin/shared/include/single_op_tests/ctc_greedy_decoder_seq_len.hpp
@@ -0,0 +1,15 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/single_op/ctc_greedy_decoder_seq_len.hpp"
+
+namespace ov {
+namespace test {
+TEST_P(CTCGreedyDecoderSeqLenLayerTest, Inference) {
+    run();
+};
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/plugin/shared/include/single_op_tests/ctc_loss.hpp b/src/tests/functional/plugin/shared/include/single_op_tests/ctc_loss.hpp
new file mode 100644
index 00000000000000..43c32bdda6ff80
--- /dev/null
+++ b/src/tests/functional/plugin/shared/include/single_op_tests/ctc_loss.hpp
@@ -0,0 +1,15 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include "shared_test_classes/single_op/ctc_loss.hpp"
+
+namespace ov {
+namespace test {
+TEST_P(CTCLossLayerTest, Inference) {
+    run();
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_greedy_decoder.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_greedy_decoder.hpp
new file mode 100644
index 00000000000000..d795bbea676169
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_greedy_decoder.hpp
@@ -0,0 +1,31 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <string>
+#include <tuple>
+#include <vector>
+
+#include "shared_test_classes/base/ov_subgraph.hpp"
+
+namespace ov {
+namespace test {
+typedef std::tuple<
+    ov::element::Type,          // Model type
+    std::vector<InputShape>,    // Input shapes
+    bool,                       // Merge repeated
+    std::string                 // Device name
+> ctcGreedyDecoderParams;
+
+class CTCGreedyDecoderLayerTest
+    :  public testing::WithParamInterface<ctcGreedyDecoderParams>,
+       virtual public ov::test::SubgraphBaseTest {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<ctcGreedyDecoderParams>& obj);
+protected:
+    void SetUp() override;
+};
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_greedy_decoder_seq_len.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_greedy_decoder_seq_len.hpp
new file mode 100644
index 00000000000000..46e85ad6fa9260
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_greedy_decoder_seq_len.hpp
@@ -0,0 +1,36 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <string>
+#include <tuple>
+#include <vector>
+
+#include "shared_test_classes/base/ov_subgraph.hpp"
+
+namespace ov {
+namespace test {
+typedef std::tuple<
+        std::vector<InputShape>,   // Input shape
+        int,                       // Sequence lengths
+        ov::element::Type,         // Probabilities precision
+        ov::element::Type,         // Indices precision
+        int,                       // Blank index
+        bool,                      // Merge repeated
+        std::string                // Device name
+    > ctcGreedyDecoderSeqLenParams;
+
+class CTCGreedyDecoderSeqLenLayerTest
+    :  public testing::WithParamInterface<ctcGreedyDecoderSeqLenParams>,
+       virtual public ov::test::SubgraphBaseTest {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<ctcGreedyDecoderSeqLenParams>& obj);
+
+protected:
+    void SetUp() override;
+};
+
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_loss.hpp b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_loss.hpp
new file mode 100644
index 00000000000000..91439cc2c894be
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/include/shared_test_classes/single_op/ctc_loss.hpp
@@ -0,0 +1,43 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <string>
+#include <tuple>
+#include <vector>
+
+#include "shared_test_classes/base/ov_subgraph.hpp"
+
+namespace ov {
+namespace test {
+typedef std::tuple<
+        std::vector<int>,                  // logits length
+        std::vector<std::vector<int>>,     // labels
+        std::vector<int>,                  // labels length
+        int,                               // blank index
+        bool,                              // preprocessCollapseRepeated
+        bool,                              // ctcMergeRepeated
+        bool                               // Unique
+> CTCLossParamsSubset;
+
+typedef std::tuple<
+        CTCLossParamsSubset,
+        std::vector<InputShape>,  // Input shapes
+        ov::element::Type,        // Float point precision
+        ov::element::Type,        // Integer precision
+        std::string               // Device name
+> CTCLossParams;
+
+class CTCLossLayerTest : public testing::WithParamInterface<CTCLossParams>,
+                        virtual public ov::test::SubgraphBaseTest {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<CTCLossParams> &obj);
+
+protected:
+    void SetUp() override;
+};
+
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/single_op/ctc_greedy_decoder.cpp b/src/tests/functional/shared_test_classes/src/single_op/ctc_greedy_decoder.cpp
new file mode 100644
index 00000000000000..a049952f180253
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/src/single_op/ctc_greedy_decoder.cpp
@@ -0,0 +1,75 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "shared_test_classes/single_op/ctc_greedy_decoder.hpp"
+
+#include <random>
+
+#include "openvino/op/parameter.hpp"
+#include "openvino/op/result.hpp"
+#include "openvino/op/constant.hpp"
+#include "openvino/op/ctc_greedy_decoder.hpp"
+
+namespace ov {
+namespace test {
+std::string CTCGreedyDecoderLayerTest::getTestCaseName(const testing::TestParamInfo<ctcGreedyDecoderParams>& obj) {
+    ov::element::Type model_type;
+    std::vector<InputShape> shapes;
+    std::string targetDevice;
+    bool merge_repeated;
+    std::tie(model_type, shapes, merge_repeated, targetDevice) = obj.param;
+
+    std::ostringstream result;
+    const char separator = '_';
+
+    result << "IS=(";
+    for (size_t i = 0lu; i < shapes.size(); i++) {
+        result << ov::test::utils::partialShape2str({shapes[i].first}) << (i < shapes.size() - 1lu ? "_" : "");
+    }
+    result << ")_TS=";
+    for (size_t i = 0lu; i < shapes.front().second.size(); i++) {
+        result << "{";
+        for (size_t j = 0lu; j < shapes.size(); j++) {
+            result << ov::test::utils::vec2str(shapes[j].second[i]) << (j < shapes.size() - 1lu ? "_" : "");
+        }
+        result << "}_";
+    }
+    result << "netPRC=" << model_type.get_type_name() << separator;
+    result << "merge_repeated=" << std::boolalpha << merge_repeated << separator;
+    result << "trgDev=" << targetDevice;
+
+    return result.str();
+}
+
+void CTCGreedyDecoderLayerTest::SetUp() {
+    ov::element::Type model_type;
+    std::vector<InputShape> shapes;
+    bool merge_repeated;
+    std::tie(model_type, shapes, merge_repeated, targetDevice) = GetParam();
+    init_input_shapes(shapes);
+
+    auto param = std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes.front());
+
+    size_t T = targetStaticShapes[0][0][0];
+    size_t B = targetStaticShapes[0][0][1];
+
+    std::mt19937 gen(1);
+    std::uniform_int_distribution<unsigned long> dist(1, T);
+
+    std::vector<int> sequence_mask_data(B * T, 0);
+    for (int b = 0; b < B; b++) {
+        int len = dist(gen);
+        for (int t = 0; t < len; t++) {
+            sequence_mask_data[t * B + b] = 1;
+        }
+    }
+    auto sequence_mask_node = std::make_shared<ov::op::v0::Constant>(model_type, ov::Shape{T, B}, sequence_mask_data);
+
+    auto ctc_greedy_decoder = std::make_shared<ov::op::v0::CTCGreedyDecoder>(param, sequence_mask_node, merge_repeated);
+
+    auto result = std::make_shared<ov::op::v0::Result>(ctc_greedy_decoder);
+    function = std::make_shared<ov::Model>(result, ov::ParameterVector{param}, "CTCGreedyDecoder");
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/single_op/ctc_greedy_decoder_seq_len.cpp b/src/tests/functional/shared_test_classes/src/single_op/ctc_greedy_decoder_seq_len.cpp
new file mode 100644
index 00000000000000..1770aff47aae49
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/src/single_op/ctc_greedy_decoder_seq_len.cpp
@@ -0,0 +1,124 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "shared_test_classes/single_op/ctc_greedy_decoder_seq_len.hpp"
+
+#include <string>
+#include <vector>
+#include <memory>
+#include <random>
+
+#include "common_test_utils/ov_tensor_utils.hpp"
+#include "openvino/op/parameter.hpp"
+#include "openvino/op/constant.hpp"
+#include "openvino/op/result.hpp"
+#include "openvino/op/ctc_greedy_decoder_seq_len.hpp"
+
+namespace ov {
+namespace test {
+std::string CTCGreedyDecoderSeqLenLayerTest::getTestCaseName(const testing::TestParamInfo<ctcGreedyDecoderSeqLenParams>& obj) {
+    std::vector<InputShape> shapes;
+    int sequenceLengths;
+    ov::element::Type dataPrecision, indicesPrecision;
+    int blankIndex;
+    bool mergeRepeated;
+    std::string targetDevice;
+    std::tie(shapes,
+             sequenceLengths,
+             dataPrecision,
+             indicesPrecision,
+             blankIndex,
+             mergeRepeated,
+             targetDevice) = obj.param;
+
+    std::ostringstream result;
+
+    result << "IS=(";
+    for (size_t i = 0lu; i < shapes.size(); i++) {
+        result << ov::test::utils::partialShape2str({shapes[i].first}) << (i < shapes.size() - 1lu ? "_" : "");
+    }
+    result << ")_TS=";
+    for (size_t i = 0lu; i < shapes.front().second.size(); i++) {
+        result << "{";
+        for (size_t j = 0lu; j < shapes.size(); j++) {
+            result << ov::test::utils::vec2str(shapes[j].second[i]) << (j < shapes.size() - 1lu ? "_" : "");
+        }
+        result << "}_";
+    }
+    result << "seqLen=" << sequenceLengths << '_';
+    result << "dataPRC=" << dataPrecision.get_type_name() << '_';
+    result << "idxPRC=" << indicesPrecision.get_type_name() << '_';
+    result << "BlankIdx=" << blankIndex << '_';
+    result << "mergeRepeated=" << std::boolalpha << mergeRepeated << '_';
+    result << "trgDev=" << targetDevice;
+
+    return result.str();
+}
+
+void CTCGreedyDecoderSeqLenLayerTest::SetUp() {
+    std::vector<InputShape> shapes;
+    int sequenceLengths;
+    ov::element::Type model_type, indices_type;
+    int blankIndex;
+    bool mergeRepeated;
+    std::tie(shapes,
+             sequenceLengths,
+             model_type,
+             indices_type,
+             blankIndex,
+             mergeRepeated,
+             targetDevice) = GetParam();
+    init_input_shapes(shapes);
+
+    ov::ParameterVector params {std::make_shared<ov::op::v0::Parameter>(model_type, inputDynamicShapes.front())};
+
+    const auto sequenceLenNode = [&] {
+        const size_t B = targetStaticShapes[0][0][0];
+        const size_t T = targetStaticShapes[0][0][1];
+
+        // Cap sequence length up to T
+        const int seqLen = std::min<int>(T, sequenceLengths);
+
+        std::mt19937 gen{42};
+        std::uniform_int_distribution<int> dist(1, seqLen);
+
+        std::vector<int> sequenceLenData(B);
+        for (int b = 0; b < B; b++) {
+            const int len = dist(gen);
+            sequenceLenData[b] = len;
+        }
+
+        return std::make_shared<ov::op::v0::Constant>(indices_type, ov::Shape{B}, sequenceLenData);
+    }();
+
+    // Cap blank index up to C - 1
+    int C = targetStaticShapes[0][0][2];
+    blankIndex = std::min(blankIndex, C - 1);
+
+    const auto blankIndexNode = [&] {
+        if (indices_type == element::i32) {
+            const auto blankIdxDataI32 = std::vector<int32_t>{blankIndex};
+            return std::make_shared<ov::op::v0::Constant>(indices_type, ov::Shape{1}, blankIdxDataI32);
+        } else if (indices_type == element::i64) {
+            const auto blankIdxDataI64 = std::vector<int64_t>{blankIndex};
+            return std::make_shared<ov::op::v0::Constant>(indices_type, ov::Shape{1}, blankIdxDataI64);
+        }
+        throw std::logic_error("Unsupported index precision");
+    }();
+
+    auto ctcGreedyDecoderSeqLen = std::make_shared<ov::op::v6::CTCGreedyDecoderSeqLen>(params[0],
+                                                                                       sequenceLenNode,
+                                                                                       blankIndexNode,
+                                                                                       mergeRepeated,
+                                                                                       indices_type,
+                                                                                       indices_type);
+
+    ov::OutputVector results;
+    for (int i = 0; i < ctcGreedyDecoderSeqLen->get_output_size(); i++) {
+        results.push_back(std::make_shared<ov::op::v0::Result>(ctcGreedyDecoderSeqLen->output(i)));
+    }
+    function = std::make_shared<ov::Model>(results, params, "CTCGreedyDecoderSeqLen");
+}
+}  // namespace test
+}  // namespace ov
diff --git a/src/tests/functional/shared_test_classes/src/single_op/ctc_loss.cpp b/src/tests/functional/shared_test_classes/src/single_op/ctc_loss.cpp
new file mode 100644
index 00000000000000..cc4cbbb2fe7eff
--- /dev/null
+++ b/src/tests/functional/shared_test_classes/src/single_op/ctc_loss.cpp
@@ -0,0 +1,92 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "shared_test_classes/single_op/ctc_loss.hpp"
+
+#include "openvino/op/parameter.hpp"
+#include "openvino/op/result.hpp"
+#include "openvino/op/constant.hpp"
+#include "openvino/op/ctc_loss.hpp"
+
+namespace ov {
+namespace test {
+std::string CTCLossLayerTest::getTestCaseName(const testing::TestParamInfo<CTCLossParams>& obj) {
+    std::vector<InputShape> shapes;
+    ov::element::Type fp_type, int_type;
+    bool preprocess_collapse_repeated, ctc_merge_repeated, unique;
+    std::vector<int> logits_length, labels_length;
+    std::vector<std::vector<int>> labels;
+    int blank_index;
+    std::string targetDevice;
+    CTCLossParamsSubset ctcLossArgsSubset;
+    std::tie(ctcLossArgsSubset, shapes, fp_type, int_type, targetDevice) = obj.param;
+    std::tie(logits_length, labels, labels_length, blank_index, preprocess_collapse_repeated, ctc_merge_repeated, unique) = ctcLossArgsSubset;
+
+    std::ostringstream result;
+    result << "IS=(";
+    for (size_t i = 0lu; i < shapes.size(); i++) {
+        result << ov::test::utils::partialShape2str({shapes[i].first}) << (i < shapes.size() - 1lu ? "_" : "");
+    }
+    result << ")_TS=";
+    for (size_t i = 0lu; i < shapes.front().second.size(); i++) {
+        result << "{";
+        for (size_t j = 0lu; j < shapes.size(); j++) {
+            result << ov::test::utils::vec2str(shapes[j].second[i]) << (j < shapes.size() - 1lu ? "_" : "");
+        }
+        result << "}_";
+    }
+    result << "LL=" << ov::test::utils::vec2str(logits_length) << "_";
+    result << "A=" << ov::test::utils::vec2str(labels) << "_";
+    result << "AL=" << ov::test::utils::vec2str(labels_length) << "_";
+    result << "BI=" << blank_index << "_";
+    result << "PCR=" << preprocess_collapse_repeated << "_";
+    result << "CMR=" << ctc_merge_repeated << "_";
+    result << "U=" << unique << "_";
+    result << "PF=" << fp_type.get_type_name() << "_";
+    result << "PI=" << int_type.get_type_name() << "_";
+    result << "targetDevice=" << targetDevice;
+    return result.str();
+}
+
+void CTCLossLayerTest::SetUp() {
+    std::vector<InputShape> shapes;
+    ov::element::Type fp_type, int_type;
+    bool preprocess_collapse_repeated, ctc_merge_repeated, unique;
+    std::vector<int> logits_length, labels_length;
+    std::vector<std::vector<int>> labels;
+    int blank_index;
+    CTCLossParamsSubset ctcLossArgsSubset;
+    std::tie(ctcLossArgsSubset, shapes, fp_type, int_type, targetDevice) = this->GetParam();
+    std::tie(logits_length, labels, labels_length, blank_index, preprocess_collapse_repeated,
+        ctc_merge_repeated, unique) = ctcLossArgsSubset;
+    init_input_shapes(shapes);
+
+    auto param = std::make_shared<ov::op::v0::Parameter>(fp_type, inputDynamicShapes.front());
+
+    size_t N = targetStaticShapes[0][0][0];
+    size_t T = targetStaticShapes[0][0][1];
+
+    std::vector<int> labelsOneD(N * T);
+    for (int i = 0; i < labels.size(); i++)
+        std::copy(labels[i].begin(), labels[i].end(), labelsOneD.data() + i * T);
+
+    auto logits_length_node = std::make_shared<ov::op::v0::Constant>(int_type, ov::Shape{N}, logits_length);
+    auto labels_node = std::make_shared<ov::op::v0::Constant>(int_type, ov::Shape{N, T}, labelsOneD);
+    auto labels_length_node = std::make_shared<ov::op::v0::Constant>(int_type, ov::Shape{N}, labels_length);
+    auto blank_index_node = std::make_shared<ov::op::v0::Constant>(int_type, ov::Shape{}, blank_index);
+
+    auto ctc_loss = std::make_shared<ov::op::v4::CTCLoss>(param,
+                                                          logits_length_node,
+                                                          labels_node,
+                                                          labels_length_node,
+                                                          blank_index_node,
+                                                          preprocess_collapse_repeated,
+                                                          ctc_merge_repeated,
+                                                          unique);
+
+    auto result = std::make_shared<ov::op::v0::Result>(ctc_loss);
+    function = std::make_shared<ov::Model>(result, ov::ParameterVector{param}, "CTCLoss");
+}
+}  // namespace test
+}  // namespace ov

From e5a3500174494c20e2caeaff308b4473475c7a14 Mon Sep 17 00:00:00 2001
From: Ilya Lavrenov <ilya.lavrenov@intel.com>
Date: Tue, 19 Sep 2023 17:14:28 +0400
Subject: [PATCH 25/46] Fixed compilation on macOS 14 with new core development
 tools (#19946)

---
 src/plugins/intel_cpu/src/nodes/mha.cpp | 1 +
 1 file changed, 1 insertion(+)

diff --git a/src/plugins/intel_cpu/src/nodes/mha.cpp b/src/plugins/intel_cpu/src/nodes/mha.cpp
index d4405be5d468d0..19cf63ac727cba 100644
--- a/src/plugins/intel_cpu/src/nodes/mha.cpp
+++ b/src/plugins/intel_cpu/src/nodes/mha.cpp
@@ -16,6 +16,7 @@
 #include "common/cpu_convert.h"
 #include "transformations/cpu_opset/x64/op/mha.hpp"
 #include "dnnl_extension_utils.h"
+#include "utils/bfloat16.hpp"
 #include <ie_ngraph_utils.hpp>
 
 using namespace InferenceEngine;

From 67a41b28ec43577b80465f3883940d4920f111f3 Mon Sep 17 00:00:00 2001
From: PiotrekCzajkowski <130136084+PiotrekCzajkowski@users.noreply.github.com>
Date: Tue, 19 Sep 2023 15:16:16 +0200
Subject: [PATCH 26/46] Add file via upload (#19605)

* Add files via upload

add new words to dict

* Add files via upload

Fix typos in words and new words to cspell.json file.
---
 cspell.json | 327 ++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 327 insertions(+)

diff --git a/cspell.json b/cspell.json
index cfbab3df891ec3..f59d00a6a052f6 100644
--- a/cspell.json
+++ b/cspell.json
@@ -4,80 +4,407 @@
     "dictionaryDefinitions": [],
     "dictionaries": [],
     "words": [
+        "aarch64",
+        "acdadcfa",
+        "acea",
+        "abmrd",
+        "acfb",
+        "acosh",
+        "Acosh",
+        "adfcd",
+        "addcmul",
+        "addif",
+        "addmm",
+        "aeaa",
+        "agem",
+        "agew",
+        "armeabi",
         "armhf",
+        "artefacts",
+        "ARTEFACTS",
+        "Asinh",
+        "asynch",
+        "Atanh",
+        "autodoc",
+        "Autograd",
+        "autoplugin",
+        "AUTOPLUGIN",
         "autoremove",
+        "autosummary",
+        "bace",
+        "Backprop",
         "bblayers",
+        "Beautif",
+        "Bilat",
+        "bindir",
         "bitbake",
+        "BFYX",
+        "BFXY",
+        "bkgr",
+        "brctl",
+        "Bucketize",
+        "BUILDDIR",
         "buildtools",
+        "buildsystems",
+        "BYXF",
+        "bvalue",
+        "bvlc",
         "caffe",
+        "caffemodel",
+        "camvid",
+        "cbba",
+        "cbcd",
+        "cdad",
+        "cdrom",
         "chrpath",
+        "classov",
+        "cldnn",
+        "clumber",
+        "codepath",
+        "codepaths",
+        "coeffs",
+        "concat",
+        "Concat",
+        "Conts",
+        "constexpr",
+        "consts",
+        "Consts",
+        "conv",
+        "Convolutional",
+        "CPPLINT",
+        "cpplint",
+        "crbegin",
+        "crend",
+        "ctest",
+        "ctput",
+        "CVAT",
+        "cython",
+        "dadb",
+        "DANDROID",
+        "DARM",
+        "Datumaro",
+        "datumaro",
+        "DBUILD",
+        "DCMAKE",
+        "ddepth",
+        "Depthwise",
+        "dearmor",
+        "devicesupport",
+        "dequantization",
+        "Dequantization",
+        "deeplabv",
+        "deeced",
+        "DENABLE",
+        "delif",
+        "denormal",
+        "DENORMAL",
+        "denormalized",
+        "Detectron",
+        "Dequantize",
         "devel",
         "devtoolset",
         "dgpu",
         "diffstat",
+        "dldt",
+        "dlstreamer",
+        "dkms",
         "Dockerfiles",
+        "DOPENVINO",
+        "downscript",
+        "doxid",
+        "doxygen",
+        "Doxygen",
+        "doxygensnippet",
+        "DTHREADING",
         "dpkg",
+        "DPYTHON",
+        "DSELECTIVE",
+        "dylib",
         "DWORD",
+        "efficientdet",
+        "Efficientdet",
+        "Einsum",
+        "Elems",
+        "Elementwise",
+        "elementwise",
+        "Eltwise",
         "endsphinxdirective",
+        "enumov",
+        "emcmake",
+        "emmake",
+        "emod",
+        "emom",
+        "emow",
+        "Emscripten",
+        "emscripten",
+        "emsdk",
         "epel",
         "ERRORLEVEL",
+        "evolutionally",
         "executionpolicy",
         "fafe",
+        "fdupes",
+        "flatbuffers",
+        "FLATBUFFERS",
+        "frontends",
+        "Frontends",
+        "FYXB",
+        "gaddb",
+        "GAPI",
+        "gapi",
+        "Gaussed",
+        "gcompoundkernel",
+        "gcomputation",
+        "GCPU",
+        "gcpukernel",
+        "Gelu",
+        "GELU",
+        "Geti",
+        "getitem",
+        "gimg",
+        "gitee",
+        "gflags",
         "globbing",
         "gmmlib",
         "GNAs",
+        "gmock",
+        "gnueabihf",
         "googlenet",
         "gpgcheck",
         "gpgkey",
+        "graphviz",
+        "Graphviz",
+        "groupov",
+        "gtest",
+        "hardtanh",
         "hashfile",
+        "HDDL",
         "HKLM",
         "HOSTTOOLS",
+        "Hotspots",
+        "hotspots",
+        "hostnet",
+        "hwloc",
+        "hwquote",
+        "idbf",
+        "IDFT",
         "iigd",
+        "ifdef",
+        "ifdown",
+        "ifup",
+        "imgproc",
+        "imshow",
+        "inet",
+        "INTEGRITYCHECK",
+        "ILSVRC",
+        "inferenced",
+        "Informations",
         "insmod",
         "intelocl",
+        "INTERPROCEDURAL",
+        "INSTALLDIR",
+        "IRDFT",
+        "jemalloc",
         "kaldi",
+        "Keras",
+        "keypress",
+        "keyrings",
         "Khronos",
+        "KROIs",
+        "Landm",
+        "landm",
+        "Latency",
+        "Lcov",
         "ldconfig",
+        "libc",
         "libopencl",
+        "libopencv",
         "libpython",
+        "libtbb",
+        "libtbbbind",
+        "libtpm",
+        "libvirtd",
         "linmac",
+        "Liskov",
+        "lowlatency",
         "LTSC",
+        "LSTM",
+        "makefiles",
+        "malloc",
+        "memleaks",
+        "manylinux",
         "maxdepth",
+        "miktext",
+        "Mish",
         "mklink",
+        "mmap",
+        "mobilenet",
+        "Mobilenet",
         "monodepth",
+        "mozallowfullscreen",
+        "msallowfullscreen",
+        "MSVC",
+        "msvc",
+        "Multiclass",
+        "muxed",
         "mxnet",
+        "namespaceov",
+        "NCHW",
+        "ncpu",
+        "netdev",
+        "netplan",
+        "ngraph",
+        "nireq",
+        "NNCF",
+        "nncf",
         "nocache",
         "noglob",
         "nohup",
+        "nlohmann",
         "norestart",
+        "noqueue",
+        "nproc",
+        "NUMA",
+        "numpy",
+        "Numpy",
+        "oallowfullscreen",
         "ocloc",
+        "OCSP",
+        "oneapi",
+        "onetbb",
         "onnx",
         "opencl",
         "openembedded",
         "openvino",
+        "Opset",
+        "opset",
+        "opsets",
+        "OVMS",
+        "ovms",
+        "ovsa",
+        "OVSA",
+        "ovsatool",
+        "OVTF",
         "PACKAGECONFIG",
+        "paddlepaddle",
+        "parameterizable",
+        "partitioner",
         "patchelf",
+        "passpattern",
+        "Pexels",
+        "pdmodel",
+        "PDPD",
         "pkgdata",
         "pkgs",
+        "pkill",
+        "polylines",
+        "postproc",
+        "postprocess",
+        "preprocess",
+        "Preprocess",
+        "protobuf",
+        "Protobuf",
+        "PROTOBUF",
+        "prototxt",
+        "PSROI",
+        "Pugi",
+        "pugixml",
+        "PUGIXML",
         "pypi",
+        "PYTHONPATH",
         "pzstd",
+        "qcow",
+        "qlen",
+        "QSPECTRE",
+        "Qspectre",
         "quantizer",
+        "Rects",
+        "Relu",
+        "relu",
+        "rcnn",
+        "RCNN",
+        "RDFT",
         "Redistributable",
         "remotesigned",
         "repolist",
+        "reproject",
+        "reshapable",
+        "Requantize",
+        "retval",
+        "RHODS",
         "rmmod",
+        "runtool",
+        "scons",
+        "SCONS",
+        "segm",
+        "Selu",
         "servercore",
+        "setuptools",
         "setupvars",
         "SETX",
+        "SIMD",
+        "Softmax",
         "skylake",
         "sphinxdirective",
+        "Strided",
+        "squeezenet",
+        "SWTPM",
+        "swtpm",
+        "TBBBIND",
+        "TBBROOT",
+        "Tensro",
+        "texlive",
+        "textrm",
+        "tflite",
+        "thirdparty",
+        "Thresholded",
         "toctree",
+        "toolset",
+        "Torchvision",
+        "tpmrm",
+        "tpmstate",
+        "tput",
+        "Tunables",
+        "unet",
         "Uninstallation",
+        "unixio",
+        "unsharp",
+        "Unsharp",
+        "Unsh",
+        "Unsqueeze",
+        "Usecase",
+        "usecases",
+        "USERPROFILE",
         "userspace",
+        "VAAPI",
+        "valgrind",
+        "vcpkg",
+        "vcvars",
         "venv",
+        "virbr",
+        "virsh",
+        "virt",
+        "virtio",
+        "VMHWM",
+        "VMRSS",
+        "VNNI",
+        "vtune",
+        "vtunesummary",
+        "vtunebottonup",
+        "WHOLEARCHIVE",
         "WDDM",
         "WORKDIR",
+        "WORKSIZE",
+        "xbyak",
+        "Xbyak",
+        "xdot",
+        "xvfz",
         "yocto",
+        "yolo",
+        "YOLO",
+        "yolov",
+        "Yolov",
+        "YXFB",
         "zstd"
     ],
     "ignoreWords": [],

From 233ae78ff4542f08eac242ff6a65ae96a9b83610 Mon Sep 17 00:00:00 2001
From: Andrey Kashchikhin <andrey.kashchikhin@intel.com>
Date: Tue, 19 Sep 2023 15:06:47 +0100
Subject: [PATCH 27/46] [CI] [GHA] Introduce GHA Linux ONNX Runtime Pipeline
 (#19883)

* add pipeline

* address comments

* rm triggers
---
 .github/workflows/linux_onnxruntime.yml | 182 ++++++++++++++++++++++++
 1 file changed, 182 insertions(+)
 create mode 100644 .github/workflows/linux_onnxruntime.yml

diff --git a/.github/workflows/linux_onnxruntime.yml b/.github/workflows/linux_onnxruntime.yml
new file mode 100644
index 00000000000000..5a96a821e92080
--- /dev/null
+++ b/.github/workflows/linux_onnxruntime.yml
@@ -0,0 +1,182 @@
+name: Linux ONNX Runtime (Ubuntu 20.04, Python 3.11)
+on:
+  workflow_dispatch:
+  schedule:
+    # run daily at 00:00
+    - cron: '0 0 * * *'
+#  pull_request:
+#    paths-ignore:
+#      - '**/docs/**'
+#      - 'docs/**'
+#      - '**/**.md'
+#      - '**.md'
+#      - '**/layer_tests_summary/**'
+#      - '**/conformance/**'
+#  push:
+#    paths-ignore:
+#      - '**/docs/**'
+#      - 'docs/**'
+#      - '**/**.md'
+#      - '**.md'
+#      - '**/layer_tests_summary/**'
+#      - '**/conformance/**'
+#    branches:
+#      - master
+
+concurrency:
+  group: ${{ github.head_ref || github.run_id }}-linux-onnx-runtime
+  cancel-in-progress: true
+
+jobs:
+  Build:
+    # TODO: remove. Temporary measure to prevent the workflow from scheduling on forks.
+    if: ${{ github.repository_owner == 'openvinotoolkit' }}
+    defaults:
+      run:
+        shell: bash
+    runs-on: ubuntu-20.04-8-cores
+    env:
+      CMAKE_BUILD_TYPE: 'Release'
+      CMAKE_GENERATOR: 'Ninja'
+      CMAKE_CXX_COMPILER_LAUNCHER: ccache
+      CMAKE_C_COMPILER_LAUNCHER: ccache
+      CMAKE_CXX_LINKER_LAUNCHER: ccache
+      CMAKE_C_LINKER_LAUNCHER: ccache
+      BUILD_TYPE: Release
+      OPENVINO_REPO: ${{ github.workspace }}/openvino
+      ONNX_RUNTIME_REPO: ${{ github.workspace }}/onnxruntime
+      ONNX_RUNTIME_UTILS: ${{ github.workspace }}/openvino/.ci/azure/ci_utils/onnxruntime
+      ONNX_RUNTIME_BUILD_DIR: ${{ github.workspace }}/onnxruntime/build
+      BUILD_DIR: ${{ github.workspace }}/build
+      INSTALL_DIR: ${{ github.workspace }}/install/openvino
+    steps:
+      - name: Clone OpenVINO
+        uses: actions/checkout@v3
+        with:
+          path: 'openvino'
+          submodules: 'true'
+
+      - name: Clone ONNX Runtime
+        run: |
+          branch=`tr -s '\n ' < ${{ env.ONNX_RUNTIME_UTILS }}/version`
+          git clone --branch $branch --single-branch --recursive https://github.com/microsoft/onnxruntime.git ${{ env.ONNX_RUNTIME_REPO }}
+
+      - name: Create Directories
+        run: |
+          mkdir -p ${{ env.BUILD_DIR }}
+          mkdir -p ${{ env.INSTALL_DIR }}
+
+      - name: Setup Python 3.11
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.11'
+
+      #
+      # Dependencies
+      #
+
+      - name: Install build dependencies
+        run: |
+          sudo -E ${{ env.OPENVINO_REPO }}/install_build_dependencies.sh
+
+      - name: Setup ccache
+        uses: hendrikmuhs/ccache-action@v1.2
+        with:
+          max-size: "2000M"
+          # Should save cache only if run in the master branch of the base repo
+          # github.ref_name is 'ref/PR_#' in case of the PR, and 'branch_name' when executed on push
+          save: ${{ github.ref_name == 'master' && 'true' || 'false'  }}
+          verbose: 2
+          key: ${{ github.job }}-linux-onnx-runtime
+          restore-keys: |
+            ${{ github.job }}-linux-onnx-runtime
+
+      #
+      # Build
+      #
+
+      - name: Get number of CPU cores
+        uses: SimenB/github-actions-cpu-cores@v1
+        id: cpu-cores
+
+      - name: CMake configure
+        run: |
+          cmake \
+            -GNinja \
+            -DCMAKE_BUILD_TYPE=${{ env.BUILD_TYPE }} \
+            -DCMAKE_COMPILE_WARNING_AS_ERROR=OFF \
+            -DENABLE_INTEL_GNA=OFF \
+            -DENABLE_INTEL_GPU=OFF \
+            -DENABLE_CPPLINT=OFF \
+            -DENABLE_PROFILING_ITT=OFF \
+            -DENABLE_SAMPLES=OFF \
+            -DENABLE_OV_TF_FRONTEND=OFF \
+            -DENABLE_OV_TF_LITE=OFF \
+            -DENABLE_OV_PADDLE_FRONTEND=OFF \
+            -DENABLE_OV_PYTORCH_FRONTEND=OFF \
+            -S ${{ env.OPENVINO_REPO }} \
+            -B ${{ env.BUILD_DIR }}
+
+      - name: Clean ccache stats
+        run: ccache --zero-stats --show-config
+
+      - name: Build
+        run: cmake --build ${{ env.BUILD_DIR }} --parallel ${{ steps.cpu-cores.outputs.count }} --config ${{ env.BUILD_TYPE }}
+
+      - name: Show ccache stats
+        run: ccache --show-stats
+
+      - name: Install OpenVINO
+        run: cmake -DCMAKE_INSTALL_PREFIX=${{ env.INSTALL_DIR }} -P ${{ env.BUILD_DIR }}/cmake_install.cmake
+
+      - name: Build Lin ONNX Runtime
+        run: |
+          source ${{ env.INSTALL_DIR }}/setupvars.sh
+          
+          ${{ env.ONNX_RUNTIME_REPO }}/build.sh \
+            --config RelWithDebInfo \
+            --use_openvino CPU_FP32 \
+            --build_shared_lib \
+            --parallel \
+            --skip_tests \
+            --compile_no_warning_as_error \
+            --build_dir ${{ env.ONNX_RUNTIME_BUILD_DIR }}
+        env:
+          CXXFLAGS: "-Wno-error=deprecated-declarations"
+
+      - name: Run onnxruntime_test_all
+        run: |
+          source ${{ env.INSTALL_DIR }}/setupvars.sh
+          skip_tests=$(tr -s '\n ' ':' < ${{ env.ONNX_RUNTIME_UTILS }}/skip_tests)
+          ./onnxruntime_test_all --gtest_filter=-$skip_tests
+        working-directory: ${{ env.ONNX_RUNTIME_BUILD_DIR }}/RelWithDebInfo
+
+      - name: Run onnxruntime_shared_lib_test
+        run: |
+          source ${{ env.INSTALL_DIR }}/setupvars.sh
+          ./onnxruntime_shared_lib_test --gtest_filter=-CApiTest.test_custom_op_openvino_wrapper_library
+        working-directory: ${{ env.ONNX_RUNTIME_BUILD_DIR }}/RelWithDebInfo
+
+      - name: Run onnxruntime_global_thread_pools_test
+        run: |
+          source ${{ env.INSTALL_DIR }}/setupvars.sh
+          ./onnxruntime_global_thread_pools_test
+        working-directory: ${{ env.ONNX_RUNTIME_BUILD_DIR }}/RelWithDebInfo
+
+      - name: Run onnxruntime_api_tests_without_env
+        run: |
+          source ${{ env.INSTALL_DIR }}/setupvars.sh
+          ./onnxruntime_api_tests_without_env
+        working-directory: ${{ env.ONNX_RUNTIME_BUILD_DIR }}/RelWithDebInfo
+
+      - name: Run pytorch-converted tests
+        run: |
+          source ${{ env.INSTALL_DIR }}/setupvars.sh
+          ./onnx_test_runner "${{ env.ONNX_RUNTIME_REPO }}/cmake/external/onnx/onnx/backend/test/data/pytorch-converted"
+        working-directory: ${{ env.ONNX_RUNTIME_BUILD_DIR }}/RelWithDebInfo
+
+      - name: Run pytorch-operator tests
+        run: |
+          source ${{ env.INSTALL_DIR }}/setupvars.sh
+          ./onnx_test_runner "${{ env.ONNX_RUNTIME_REPO }}/cmake/external/onnx/onnx/backend/test/data/pytorch-operator"
+        working-directory: ${{ env.ONNX_RUNTIME_BUILD_DIR }}/RelWithDebInfo

From 472ad39a9d57bfdc8ff38920bc8f3927c5cb745a Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Tue, 19 Sep 2023 18:18:42 +0400
Subject: [PATCH 28/46] Update numpy requirement from <1.26,>=1.16.6 to
 >=1.16.6,<1.27 in /tests (#19938)

Updates the requirements on [numpy](https://github.com/numpy/numpy) to permit the latest version.
- [Release notes](https://github.com/numpy/numpy/releases)
- [Changelog](https://github.com/numpy/numpy/blob/main/doc/RELEASE_WALKTHROUGH.rst)
- [Commits](https://github.com/numpy/numpy/compare/v1.16.6...v1.26.0)

---
updated-dependencies:
- dependency-name: numpy
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
---
 tests/constraints.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/constraints.txt b/tests/constraints.txt
index 3f5a718dff257a..97c88475f178f7 100644
--- a/tests/constraints.txt
+++ b/tests/constraints.txt
@@ -1,4 +1,4 @@
-numpy>=1.16.6,<1.26
+numpy>=1.16.6,<1.27
 attrs==23.1.0
 distro==1.8.0
 h5py>=3.1.0

From b6e0706961d6a522ba1c9379b8ed195794bc61a5 Mon Sep 17 00:00:00 2001
From: Ilya Churaev <ilya.churaev@intel.com>
Date: Tue, 19 Sep 2023 18:20:30 +0400
Subject: [PATCH 29/46] Enable clang format for template plugin tests (#19942)

---
 .../template/tests/functional/CMakeLists.txt  |     2 +-
 .../template/tests/functional/core_config.cpp |     4 +-
 .../tests/functional/op_reference/abs.cpp     |    55 +-
 .../tests/functional/op_reference/acos.cpp    |    80 +-
 .../tests/functional/op_reference/acosh.cpp   |    46 +-
 .../op_reference/adaptive_avg_pool.cpp        |   118 +-
 .../op_reference/adaptive_max_pool.cpp        |   141 +-
 .../tests/functional/op_reference/add.cpp     |    98 +-
 .../tests/functional/op_reference/asin.cpp    |    95 +-
 .../tests/functional/op_reference/asinh.cpp   |    93 +-
 .../tests/functional/op_reference/atan.cpp    |    62 +-
 .../functional/op_reference/augru_cell.cpp    |   268 +-
 .../op_reference/augru_sequence.cpp           |  1251 +-
 .../functional/op_reference/avg_pool.cpp      |    64 +-
 .../op_reference/base_reference_test.cpp      |   134 +-
 .../op_reference/base_reference_test.hpp      |     4 +-
 .../functional/op_reference/batch_norm.cpp    |    83 +-
 .../op_reference/batch_to_space.cpp           |   105 +-
 .../op_reference/binary_convolution.cpp       |   356 +-
 .../functional/op_reference/broadcast.cpp     |   322 +-
 .../functional/op_reference/bucketize.cpp     |    60 +-
 .../tests/functional/op_reference/ceiling.cpp |    87 +-
 .../tests/functional/op_reference/clamp.cpp   |   165 +-
 .../functional/op_reference/comparison.cpp    |     6 +-
 .../functional/op_reference/comparison.hpp    |    42 +-
 .../tests/functional/op_reference/concat.cpp  |   645 +-
 .../functional/op_reference/constant.cpp      |   138 +-
 .../functional/op_reference/conversion.cpp    |     6 +-
 .../functional/op_reference/conversion.hpp    |    35 +-
 .../tests/functional/op_reference/convert.cpp |  1617 +-
 .../op_reference/convert_color_i420.cpp       |    78 +-
 .../op_reference/convert_color_nv12.cpp       |    47 +-
 .../functional/op_reference/convert_like.cpp  |  1617 +-
 .../functional/op_reference/convolution.cpp   |    64 +-
 .../op_reference/convolution_backprop.cpp     |  5132 ++++--
 .../tests/functional/op_reference/cos.cpp     |    72 +-
 .../tests/functional/op_reference/cosh.cpp    |    92 +-
 .../op_reference/ctc_greedy_decoder.cpp       |    75 +-
 .../ctc_greedy_decoder_seq_len.cpp            |   106 +-
 .../functional/op_reference/ctc_loss.cpp      |   265 +-
 .../tests/functional/op_reference/cum_sum.cpp |   267 +-
 .../op_reference/deformable_convolution.cpp   | 13049 +++++++++-------
 .../op_reference/deformable_psroi_pooling.cpp |   698 +-
 .../op_reference/depth_to_space.cpp           |    87 +-
 .../op_reference/detection_output.cpp         |   869 +-
 .../tests/functional/op_reference/dft.cpp     |    28 +-
 .../tests/functional/op_reference/divide.cpp  |   244 +-
 .../tests/functional/op_reference/einsum.cpp  |    73 +-
 .../tests/functional/op_reference/elu.cpp     |   117 +-
 .../op_reference/embedding_segments_sum.cpp   |    19 +-
 .../op_reference/embeddingbag_offsetssum.cpp  |    17 +-
 .../op_reference/embeddingbag_packedsum.cpp   |    11 +-
 .../tests/functional/op_reference/equal.cpp   |   112 +-
 .../tests/functional/op_reference/erf.cpp     |    63 +-
 .../tests/functional/op_reference/exp.cpp     |   125 +-
 ...xperimental_detectron_detection_output.cpp |   154 +-
 ...imental_detectron_detection_prior_grid.cpp |   258 +-
 ...erimental_detectron_generate_proposals.cpp |   245 +-
 ...mental_detectron_roi_feature_extractor.cpp |   205 +-
 .../experimental_detectron_topkrois.cpp       |    53 +-
 .../op_reference/extract_image_patches.cpp    |   190 +-
 .../tests/functional/op_reference/eye.cpp     |   498 +-
 .../functional/op_reference/fake_quantize.cpp |   229 +-
 .../tests/functional/op_reference/floor.cpp   |    83 +-
 .../functional/op_reference/floor_mod.cpp     |    96 +-
 .../tests/functional/op_reference/gather.cpp  |  1032 +-
 .../op_reference/gather_elements.cpp          |   158 +-
 .../functional/op_reference/gather_nd.cpp     |   463 +-
 .../functional/op_reference/gather_tree.cpp   |   143 +-
 .../tests/functional/op_reference/gelu.cpp    |   124 +-
 .../op_reference/generate_proposals.cpp       |   399 +-
 .../tests/functional/op_reference/greater.cpp |    65 +-
 .../functional/op_reference/greater_equal.cpp |    64 +-
 .../tests/functional/op_reference/grn.cpp     |   151 +-
 .../op_reference/group_convolution.cpp        |   295 +-
 .../group_convolution_backprop.cpp            |   595 +-
 .../functional/op_reference/gru_cell.cpp      |   280 +-
 .../functional/op_reference/gru_sequence.cpp  |  2359 ++-
 .../functional/op_reference/hard_sigmoid.cpp  |    60 +-
 .../functional/op_reference/hsigmoid.cpp      |    41 +-
 .../tests/functional/op_reference/hswish.cpp  |    49 +-
 .../tests/functional/op_reference/idft.cpp    |    38 +-
 .../tests/functional/op_reference/if.cpp      |   214 +-
 .../tests/functional/op_reference/irdft.cpp   |  1127 +-
 .../functional/op_reference/is_finite.cpp     |    46 +-
 .../tests/functional/op_reference/is_inf.cpp  |   131 +-
 .../tests/functional/op_reference/is_nan.cpp  |    49 +-
 .../tests/functional/op_reference/less.cpp    |    65 +-
 .../tests/functional/op_reference/less_eq.cpp |    65 +-
 .../tests/functional/op_reference/log.cpp     |    61 +-
 .../functional/op_reference/log_softmax.cpp   |   348 +-
 .../tests/functional/op_reference/logical.hpp |    17 +-
 .../functional/op_reference/logical_and.cpp   |    39 +-
 .../functional/op_reference/logical_not.cpp   |    15 +-
 .../functional/op_reference/logical_or.cpp    |    39 +-
 .../functional/op_reference/logical_xor.cpp   |    40 +-
 .../tests/functional/op_reference/loop.cpp    |   321 +-
 .../tests/functional/op_reference/lrn.cpp     |    77 +-
 .../functional/op_reference/lstm_cell.cpp     |   762 +-
 .../functional/op_reference/lstm_sequence.cpp |  5891 +++----
 .../tests/functional/op_reference/matmul.cpp  |     3 +-
 .../functional/op_reference/matrix_nms.cpp    |   774 +-
 .../functional/op_reference/max_pool.cpp      |     3 +-
 .../tests/functional/op_reference/maximum.cpp |   135 +-
 .../tests/functional/op_reference/memory.cpp  |    26 +-
 .../tests/functional/op_reference/minimum.cpp |    98 +-
 .../tests/functional/op_reference/mish.cpp    |    44 +-
 .../tests/functional/op_reference/mod.cpp     |   168 +-
 .../op_reference/multiclass_nms.cpp           |   909 +-
 .../functional/op_reference/multiply.cpp      |    92 +-
 .../tests/functional/op_reference/mvn.cpp     |   254 +-
 .../functional/op_reference/negative.cpp      |    46 +-
 .../op_reference/non_max_suppression.cpp      |  1806 +--
 .../tests/functional/op_reference/nonzero.cpp |   395 +-
 .../functional/op_reference/normalize_l2.cpp  |   977 +-
 .../functional/op_reference/not_equal.cpp     |   106 +-
 .../tests/functional/op_reference/one_hot.cpp |   199 +-
 .../tests/functional/op_reference/pad.cpp     |  3009 ++--
 .../op_reference/parameter_as_output.cpp      |    26 +-
 .../tests/functional/op_reference/power.cpp   |    78 +-
 .../tests/functional/op_reference/prelu.cpp   |   474 +-
 .../op_reference/prior_box_clustered.cpp      |    89 +-
 .../functional/op_reference/proposal.cpp      |   645 +-
 .../functional/op_reference/psroi_pooling.cpp |   236 +-
 .../op_reference/random_uniform.cpp           |   133 +-
 .../tests/functional/op_reference/range.cpp   |   171 +-
 .../tests/functional/op_reference/rdft.cpp    |   548 +-
 .../functional/op_reference/reduce_l1.cpp     |    32 +-
 .../functional/op_reference/reduce_l2.cpp     |    53 +-
 .../functional/op_reference/reduce_max.cpp    |    98 +-
 .../functional/op_reference/reduce_mean.cpp   |    74 +-
 .../functional/op_reference/reduce_min.cpp    |    99 +-
 .../functional/op_reference/reduce_prod.cpp   |   144 +-
 .../functional/op_reference/reduce_sum.cpp    |   175 +-
 .../functional/op_reference/reduction.cpp     |     6 +-
 .../functional/op_reference/reduction.hpp     |    27 +-
 .../functional/op_reference/region_yolo.cpp   |    82 +-
 .../tests/functional/op_reference/relu.cpp    |    77 +-
 .../functional/op_reference/reorg_yolo.cpp    |    57 +-
 .../tests/functional/op_reference/reshape.cpp |   231 +-
 .../tests/functional/op_reference/result.cpp  |    56 +-
 .../tests/functional/op_reference/reverse.cpp |     1 -
 .../op_reference/reverse_sequence.cpp         |   175 +-
 .../functional/op_reference/rnn_cell.cpp      |   272 +-
 .../functional/op_reference/rnn_sequence.cpp  |  1820 +--
 .../functional/op_reference/roi_align.cpp     |   330 +-
 .../functional/op_reference/roi_pooling.cpp   |   388 +-
 .../tests/functional/op_reference/roll.cpp    |   210 +-
 .../tests/functional/op_reference/round.cpp   |   134 +-
 .../op_reference/scatter_elements_update.cpp  |    35 +-
 .../op_reference/scatter_nd_update.cpp        |   184 +-
 .../op_reference/scatter_update.cpp           |  1304 +-
 .../tests/functional/op_reference/select.cpp  |   142 +-
 .../tests/functional/op_reference/selu.cpp    |   100 +-
 .../functional/op_reference/shape_of.cpp      |   154 +-
 .../op_reference/shuffle_channels.cpp         |   190 +-
 .../tests/functional/op_reference/sigmoid.cpp |    82 +-
 .../tests/functional/op_reference/sign.cpp    |    73 +-
 .../tests/functional/op_reference/sin.cpp     |    92 +-
 .../tests/functional/op_reference/sinh.cpp    |    92 +-
 .../tests/functional/op_reference/slice.cpp   |   135 +-
 .../tests/functional/op_reference/softmax.cpp |   173 +-
 .../functional/op_reference/softplus.cpp      |    38 +-
 .../functional/op_reference/softsign.cpp      |    38 +-
 .../op_reference/space_to_batch.cpp           |   100 +-
 .../op_reference/space_to_depth.cpp           |   103 +-
 .../tests/functional/op_reference/split.cpp   |   153 +-
 .../op_reference/squared_difference.cpp       |   111 +-
 .../tests/functional/op_reference/squeeze.cpp |    22 +-
 .../functional/op_reference/strided_slice.cpp |   219 +-
 .../functional/op_reference/subtract.cpp      |    84 +-
 .../tests/functional/op_reference/swish.cpp   |    80 +-
 .../tests/functional/op_reference/tan.cpp     |    82 +-
 .../tests/functional/op_reference/tanh.cpp    |    92 +-
 .../op_reference/tensor_iterator.cpp          |  4156 ++---
 .../tests/functional/op_reference/tile.cpp    |   116 +-
 .../tests/functional/op_reference/topk.cpp    |  1930 ++-
 .../functional/op_reference/transpose.cpp     |   122 +-
 .../functional/op_reference/unsqueeze.cpp     |    78 +-
 .../op_reference/variadic_split.cpp           |   383 +-
 .../preprocessing/yuv_to_grey_tests.cpp       |     4 +-
 .../tests/functional/set_device_name.cpp      |    10 +-
 .../executable_network/exec_network_base.cpp  |    41 +-
 .../behavior/infer_request/callback.cpp       |    18 +-
 .../behavior/infer_request/config.cpp         |    18 +-
 .../behavior/infer_request/io_blob.cpp        |    18 +-
 .../behavior/infer_request/memory_states.cpp  |     1 -
 .../behavior/infer_request/multithreading.cpp |    18 +-
 .../behavior/infer_request/wait.cpp           |    18 +-
 .../exec_network_base.cpp                     |   107 +-
 .../ov_executable_network/get_metric.cpp      |     2 -
 .../ov_exec_net_import_export.cpp             |    62 +-
 .../ov_executable_network/properties.cpp      |    15 +-
 .../ov_infer_request/batched_tensors.cpp      |    17 +-
 .../behavior/ov_infer_request/callback.cpp    |    18 +-
 .../ov_infer_request/cancellation.cpp         |    12 +-
 .../infer_request_dynamic.cpp                 |    53 +-
 .../behavior/ov_infer_request/inference.cpp   |    12 +-
 .../ov_infer_request/inference_chaining.cpp   |    58 +-
 .../behavior/ov_infer_request/io_tensor.cpp   |    54 +-
 .../ov_infer_request/multithreading.cpp       |    18 +-
 .../behavior/ov_infer_request/wait.cpp        |    18 +-
 .../behavior/ov_plugin/life_time.cpp          |    14 +-
 .../behavior/ov_plugin/properties_tests.cpp   |     6 +-
 .../behavior/plugin/caching_tests.cpp         |    26 +-
 .../behavior/plugin/core_integration.cpp      |    96 +-
 .../behavior/plugin/life_time.cpp             |    38 +-
 .../behavior/plugin/preprocessing.cpp         |    51 +-
 .../behavior/plugin/set_preprocess.cpp        |    85 +-
 .../behavior/plugin/synthetic.cpp             |   150 +-
 .../behavior/plugin/version.cpp               |    11 +-
 .../single_layer_tests/convolution.cpp        |   191 +-
 .../single_layer_tests/eltwise.cpp            |   166 +-
 .../single_layer_tests/reshape.cpp            |    82 +-
 .../single_layer_tests/softmax.cpp            |   237 +-
 .../single_layer_tests/split.cpp              |    29 +-
 .../base_reference_cnn_test.cpp               |    20 +-
 .../subgraph_reference/preprocess.cpp         |   741 +-
 .../subgraph_reference/preprocess_legacy.cpp  |    12 +-
 .../subgraph_reference/preprocess_opencv.cpp  |   105 +-
 220 files changed, 42186 insertions(+), 34257 deletions(-)

diff --git a/src/plugins/template/tests/functional/CMakeLists.txt b/src/plugins/template/tests/functional/CMakeLists.txt
index 983ee2534a497c..aef4a4ecfa71a5 100644
--- a/src/plugins/template/tests/functional/CMakeLists.txt
+++ b/src/plugins/template/tests/functional/CMakeLists.txt
@@ -20,7 +20,7 @@ ov_add_test_target(
         INCLUDES
             "${TEMPLATE_PLUGIN_SOURCE_DIR}/include"
             "${CMAKE_CURRENT_SOURCE_DIR}/op_reference"
-        # ADD_CPPLINT
+        ADD_CLANG_FORMAT
         LABELS
             TEMPLATE
 )
diff --git a/src/plugins/template/tests/functional/core_config.cpp b/src/plugins/template/tests/functional/core_config.cpp
index 39c114e8eabab4..2c54a0d17b2f8d 100644
--- a/src/plugins/template/tests/functional/core_config.cpp
+++ b/src/plugins/template/tests/functional/core_config.cpp
@@ -3,10 +3,10 @@
 //
 
 #include "functional_test_utils/core_config.hpp"
+
 #include "shared_test_classes/base/ov_subgraph.hpp"
 
-void CoreConfiguration(LayerTestsUtils::LayerTestsCommon* test) {
-}
+void CoreConfiguration(LayerTestsUtils::LayerTestsCommon* test) {}
 
 namespace ov {
 namespace test {
diff --git a/src/plugins/template/tests/functional/op_reference/abs.cpp b/src/plugins/template/tests/functional/op_reference/abs.cpp
index 944886da90bdc2..099b614afa391e 100644
--- a/src/plugins/template/tests/functional/op_reference/abs.cpp
+++ b/src/plugins/template/tests/functional/op_reference/abs.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/abs.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/abs.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -50,8 +52,8 @@ class ReferenceAbsLayerTest : public testing::TestWithParam<AbsParams>, public C
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto log = std::make_shared<op::v0::Abs>(in);
         return std::make_shared<Model>(NodeVector{log}, ParameterVector{in});
@@ -66,12 +68,10 @@ template <element::Type_t IN_ET>
 std::vector<AbsParams> generateParamsForAbsFloat() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<AbsParams> params{
-        AbsParams(ov::PartialShape{4},
-                  IN_ET,
-                  std::vector<T>{1.f, -2.f, 0.f, -4.75f},
-                  std::vector<T>{1.f, 2.f, 0.f, 4.75f})
-    };
+    std::vector<AbsParams> params{AbsParams(ov::PartialShape{4},
+                                            IN_ET,
+                                            std::vector<T>{1.f, -2.f, 0.f, -4.75f},
+                                            std::vector<T>{1.f, 2.f, 0.f, 4.75f})};
     return params;
 }
 
@@ -80,11 +80,7 @@ std::vector<AbsParams> generateParamsForAbsInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     std::vector<AbsParams> params{
-        AbsParams(ov::PartialShape{4},
-                  IN_ET,
-                  std::vector<T>{1, -2, 0, -4},
-                  std::vector<T>{1, 2, 0, 4})
-    };
+        AbsParams(ov::PartialShape{4}, IN_ET, std::vector<T>{1, -2, 0, -4}, std::vector<T>{1, 2, 0, 4})};
     return params;
 }
 
@@ -93,24 +89,18 @@ std::vector<AbsParams> generateParamsForAbsUInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     std::vector<AbsParams> params{
-        AbsParams(ov::PartialShape{4},
-                  IN_ET,
-                  std::vector<T>{1, 2, 0, 4},
-                  std::vector<T>{1, 2, 0, 4})
-    };
+        AbsParams(ov::PartialShape{4}, IN_ET, std::vector<T>{1, 2, 0, 4}, std::vector<T>{1, 2, 0, 4})};
     return params;
 }
 
 std::vector<AbsParams> generateCombinedParamsForAbs() {
-    const std::vector<std::vector<AbsParams>> allTypeParams{
-        generateParamsForAbsFloat<element::Type_t::f32>(),
-        generateParamsForAbsFloat<element::Type_t::f16>(),
-        generateParamsForAbsFloat<element::Type_t::bf16>(),
-        generateParamsForAbsInt<element::Type_t::i64>(),
-        generateParamsForAbsInt<element::Type_t::i32>(),
-        generateParamsForAbsUInt<element::Type_t::u64>(),
-        generateParamsForAbsUInt<element::Type_t::u32>()
-    };
+    const std::vector<std::vector<AbsParams>> allTypeParams{generateParamsForAbsFloat<element::Type_t::f32>(),
+                                                            generateParamsForAbsFloat<element::Type_t::f16>(),
+                                                            generateParamsForAbsFloat<element::Type_t::bf16>(),
+                                                            generateParamsForAbsInt<element::Type_t::i64>(),
+                                                            generateParamsForAbsInt<element::Type_t::i32>(),
+                                                            generateParamsForAbsUInt<element::Type_t::u64>(),
+                                                            generateParamsForAbsUInt<element::Type_t::u32>()};
 
     std::vector<AbsParams> combinedParams;
 
@@ -121,10 +111,9 @@ std::vector<AbsParams> generateCombinedParamsForAbs() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Abs_With_Hardcoded_Refs,
-    ReferenceAbsLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForAbs()),
-    ReferenceAbsLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Abs_With_Hardcoded_Refs,
+                         ReferenceAbsLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForAbs()),
+                         ReferenceAbsLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/acos.cpp b/src/plugins/template/tests/functional/op_reference/acos.cpp
index 22402222df3782..7a661ee098ffb3 100644
--- a/src/plugins/template/tests/functional/op_reference/acos.cpp
+++ b/src/plugins/template/tests/functional/op_reference/acos.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/acos.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/acos.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -42,7 +43,7 @@ class ReferenceAcosLayerTest : public testing::TestWithParam<AcosParams>, public
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto acos = std::make_shared<op::v0::Acos>(in);
-        return std::make_shared<Model>(NodeVector {acos}, ParameterVector {in});
+        return std::make_shared<Model>(NodeVector{acos}, ParameterVector{in});
     }
 };
 
@@ -53,30 +54,55 @@ TEST_P(ReferenceAcosLayerTest, AcosWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Acos_With_Hardcoded_Refs, ReferenceAcosLayerTest,
-    ::testing::Values(Builder {}
-                          .input({{11}, element::f16, std::vector<ov::float16> {-1.f, -0.75f, -0.5f, -0.25f, -0.125f,
-                                                                                     0.f, 0.125f, 0.25f, 0.5f, 0.75f, 1.f}})
-                          .expected({{11}, element::f16, std::vector<ov::float16> {3.14159265f, 2.41885841f, 2.09439510f, 1.82347658f, 1.69612416f,
-                                                                                       1.57079633f, 1.44546850f, 1.31811607f, 1.04719755f, 0.72273425f,
-                                                                                       0.00000000f}}),
-                      Builder {}
-                          .input({{11}, element::f32, std::vector<float> {-1.f, -0.75f, -0.5f, -0.25f, -0.125f,
-                                                                                  0.f, 0.125f, 0.25f, 0.5f, 0.75f, 1.f}})
-                          .expected({{11}, element::f32, std::vector<float> {3.14159265f, 2.41885841f, 2.09439510f, 1.82347658f, 1.69612416f,
-                                                                                     1.57079633f, 1.44546850f, 1.31811607f, 1.04719755f, 0.72273425f,
-                                                                                     0.00000000f}}),
-                      Builder {}
-                          .input({{3}, element::i32, std::vector<int32_t> {-1, 0, 1}})
-                          .expected({{3}, element::i32, std::vector<int32_t> {3, 2, 0}}),
-                      Builder {}
-                          .input({{3}, element::i64, std::vector<int64_t> {-1, 0, 1}})
-                          .expected({{3}, element::i64, std::vector<int64_t> {3, 2, 0}}),
-                      Builder {}
-                          .input({{2}, element::u32, std::vector<uint32_t> {0, 1}})
-                          .expected({{2}, element::u32, std::vector<uint32_t> {2, 0}}),
-                      Builder {}
-                          .input({{2}, element::u64, std::vector<uint64_t> {0, 1}})
-                          .expected({{2}, element::u64, std::vector<uint64_t> {2, 0}})),
+    smoke_Acos_With_Hardcoded_Refs,
+    ReferenceAcosLayerTest,
+    ::testing::Values(
+        Builder{}
+            .input(
+                {{11},
+                 element::f16,
+                 std::vector<ov::float16>{-1.f, -0.75f, -0.5f, -0.25f, -0.125f, 0.f, 0.125f, 0.25f, 0.5f, 0.75f, 1.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{3.14159265f,
+                                                2.41885841f,
+                                                2.09439510f,
+                                                1.82347658f,
+                                                1.69612416f,
+                                                1.57079633f,
+                                                1.44546850f,
+                                                1.31811607f,
+                                                1.04719755f,
+                                                0.72273425f,
+                                                0.00000000f}}),
+        Builder{}
+            .input({{11},
+                    element::f32,
+                    std::vector<float>{-1.f, -0.75f, -0.5f, -0.25f, -0.125f, 0.f, 0.125f, 0.25f, 0.5f, 0.75f, 1.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{3.14159265f,
+                                          2.41885841f,
+                                          2.09439510f,
+                                          1.82347658f,
+                                          1.69612416f,
+                                          1.57079633f,
+                                          1.44546850f,
+                                          1.31811607f,
+                                          1.04719755f,
+                                          0.72273425f,
+                                          0.00000000f}}),
+        Builder{}
+            .input({{3}, element::i32, std::vector<int32_t>{-1, 0, 1}})
+            .expected({{3}, element::i32, std::vector<int32_t>{3, 2, 0}}),
+        Builder{}
+            .input({{3}, element::i64, std::vector<int64_t>{-1, 0, 1}})
+            .expected({{3}, element::i64, std::vector<int64_t>{3, 2, 0}}),
+        Builder{}
+            .input({{2}, element::u32, std::vector<uint32_t>{0, 1}})
+            .expected({{2}, element::u32, std::vector<uint32_t>{2, 0}}),
+        Builder{}
+            .input({{2}, element::u64, std::vector<uint64_t>{0, 1}})
+            .expected({{2}, element::u64, std::vector<uint64_t>{2, 0}})),
     ReferenceAcosLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/acosh.cpp b/src/plugins/template/tests/functional/op_reference/acosh.cpp
index 8e2f916655b541..a281cc3f28922d 100644
--- a/src/plugins/template/tests/functional/op_reference/acosh.cpp
+++ b/src/plugins/template/tests/functional/op_reference/acosh.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/acosh.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/acosh.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -42,7 +43,7 @@ class ReferenceAcoshLayerTest : public testing::TestWithParam<AcoshParams>, publ
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto acosh = std::make_shared<op::v3::Acosh>(in);
-        return std::make_shared<ov::Model>(NodeVector {acosh}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{acosh}, ParameterVector{in});
     }
 };
 
@@ -53,24 +54,27 @@ TEST_P(ReferenceAcoshLayerTest, AcoshWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Acosh_With_Hardcoded_Refs, ReferenceAcoshLayerTest,
-    ::testing::Values(Builder {}
-                          .input({{8}, element::f16, std::vector<ov::float16> {1.f, 2.f, 3.f, 4.f, 5.f, 10.f, 100.f, 1000.f}})
-                          .expected({{8}, element::f16, std::vector<ov::float16> {0., 1.317, 1.763, 2.063, 2.292, 2.993, 5.298, 7.6012}}),
-                      Builder {}
-                          .input({{8}, element::f32, std::vector<float> {1.f, 2.f, 3.f, 4.f, 5.f, 10.f, 100.f, 1000.f}})
-                          .expected({{8}, element::f32, std::vector<float> {0., 1.317, 1.763, 2.063, 2.292, 2.993, 5.298, 7.6012}}),
-                      Builder {}
-                          .input({{8}, element::i32, std::vector<int32_t> {1, 2, 3, 4, 5, 10, 100, 1000}})
-                          .expected({{8}, element::i32, std::vector<int32_t> {0, 1, 2, 2, 2, 3, 5, 8}}),
-                      Builder {}
-                          .input({{8}, element::i64, std::vector<int64_t> {1, 2, 3, 4, 5, 10, 100, 1000}})
-                          .expected({{8}, element::i64, std::vector<int64_t> {0, 1, 2, 2, 2, 3, 5, 8}}),
-                      Builder {}
-                          .input({{8}, element::u32, std::vector<uint32_t> {1, 2, 3, 4, 5, 10, 100, 1000}})
-                          .expected({{8}, element::u32, std::vector<uint32_t> {0, 1, 2, 2, 2, 3, 5, 8}}),
-                      Builder {}
-                          .input({{8}, element::u64, std::vector<uint64_t> {1, 2, 3, 4, 5, 10, 100, 1000}})
-                          .expected({{8}, element::u64, std::vector<uint64_t> {0, 1, 2, 2, 2, 3, 5, 8}})),
+    smoke_Acosh_With_Hardcoded_Refs,
+    ReferenceAcoshLayerTest,
+    ::testing::Values(
+        Builder{}
+            .input({{8}, element::f16, std::vector<ov::float16>{1.f, 2.f, 3.f, 4.f, 5.f, 10.f, 100.f, 1000.f}})
+            .expected(
+                {{8}, element::f16, std::vector<ov::float16>{0., 1.317, 1.763, 2.063, 2.292, 2.993, 5.298, 7.6012}}),
+        Builder{}
+            .input({{8}, element::f32, std::vector<float>{1.f, 2.f, 3.f, 4.f, 5.f, 10.f, 100.f, 1000.f}})
+            .expected({{8}, element::f32, std::vector<float>{0., 1.317, 1.763, 2.063, 2.292, 2.993, 5.298, 7.6012}}),
+        Builder{}
+            .input({{8}, element::i32, std::vector<int32_t>{1, 2, 3, 4, 5, 10, 100, 1000}})
+            .expected({{8}, element::i32, std::vector<int32_t>{0, 1, 2, 2, 2, 3, 5, 8}}),
+        Builder{}
+            .input({{8}, element::i64, std::vector<int64_t>{1, 2, 3, 4, 5, 10, 100, 1000}})
+            .expected({{8}, element::i64, std::vector<int64_t>{0, 1, 2, 2, 2, 3, 5, 8}}),
+        Builder{}
+            .input({{8}, element::u32, std::vector<uint32_t>{1, 2, 3, 4, 5, 10, 100, 1000}})
+            .expected({{8}, element::u32, std::vector<uint32_t>{0, 1, 2, 2, 2, 3, 5, 8}}),
+        Builder{}
+            .input({{8}, element::u64, std::vector<uint64_t>{1, 2, 3, 4, 5, 10, 100, 1000}})
+            .expected({{8}, element::u64, std::vector<uint64_t>{0, 1, 2, 2, 2, 3, 5, 8}})),
     ReferenceAcoshLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/adaptive_avg_pool.cpp b/src/plugins/template/tests/functional/op_reference/adaptive_avg_pool.cpp
index d73df2f853c75c..8467889b60c130 100644
--- a/src/plugins/template/tests/functional/op_reference/adaptive_avg_pool.cpp
+++ b/src/plugins/template/tests/functional/op_reference/adaptive_avg_pool.cpp
@@ -2,10 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/adaptive_avg_pool.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
-#include "openvino/op/adaptive_avg_pool.hpp"
 #include "openvino/op/constant.hpp"
 
 using namespace ov;
@@ -41,7 +42,8 @@ struct AdaptiveAvgPoolParams {
     std::vector<int64_t> m_adaptive_values;
 };
 
-class ReferenceAdaptiveAvgPoolLayerTest : public testing::TestWithParam<AdaptiveAvgPoolParams>, public CommonReferenceTest {
+class ReferenceAdaptiveAvgPoolLayerTest : public testing::TestWithParam<AdaptiveAvgPoolParams>,
+                                          public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -65,9 +67,9 @@ class ReferenceAdaptiveAvgPoolLayerTest : public testing::TestWithParam<Adaptive
 
 private:
     static std::shared_ptr<Model> CreateFunction(const Shape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const Shape& adaptive_shape,
-                                                    const std::vector<int64_t> adaptive_values) {
+                                                 const element::Type& input_type,
+                                                 const Shape& adaptive_shape,
+                                                 const std::vector<int64_t> adaptive_values) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto out = op::v0::Constant::create<int64_t>(element::Type_t::i64, adaptive_shape, adaptive_values);
         const auto adaptive_avg_pool = std::make_shared<op::v8::AdaptiveAvgPool>(in, out);
@@ -84,49 +86,51 @@ std::vector<AdaptiveAvgPoolParams> generateParamsForAdaptiveAvgPool() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     std::vector<AdaptiveAvgPoolParams> params{
-        AdaptiveAvgPoolParams(ov::Shape{2, 3, 7},
-                      ov::Shape{2, 3, 3},
-                      IN_ET,
-                      IN_ET,
-                      std::vector<T>{0,  4,  1, 3, -2, -5, -2, -2, 1, -3, 1,  -3, -4, 0,  -2, 1, -1, -2, 3, -1, -3,
-                                    -1, -2, 3, 4, -3, -4, 1,  2,  0, -4, -5, -2, -2, -3, 2,  3, 1,  -5, 2, -4, -2},
-                      std::vector<T>{1.66666663,
-                                     0.66666669,
-                                    -3.,
-                                    -1.33333337,
-                                    -1.66666663,
-                                    -2.33333325,
-                                    -0.66666669,
-                                     0.,
-                                    -0.33333334,
-
-                                     0.,
-                                     1.33333337,
-                                    -2.,
-                                    -0.66666669,
-                                    -3.66666675,
-                                    -2.33333325,
-                                     2.,
-                                    -0.66666669,
-                                    -1.33333337},
-                      ov::Shape{1},
-                      {3}),
+        AdaptiveAvgPoolParams(
+            ov::Shape{2, 3, 7},
+            ov::Shape{2, 3, 3},
+            IN_ET,
+            IN_ET,
+            std::vector<T>{0,  4,  1, 3, -2, -5, -2, -2, 1, -3, 1,  -3, -4, 0,  -2, 1, -1, -2, 3, -1, -3,
+                           -1, -2, 3, 4, -3, -4, 1,  2,  0, -4, -5, -2, -2, -3, 2,  3, 1,  -5, 2, -4, -2},
+            std::vector<T>{1.66666663,
+                           0.66666669,
+                           -3.,
+                           -1.33333337,
+                           -1.66666663,
+                           -2.33333325,
+                           -0.66666669,
+                           0.,
+                           -0.33333334,
+
+                           0.,
+                           1.33333337,
+                           -2.,
+                           -0.66666669,
+                           -3.66666675,
+                           -2.33333325,
+                           2.,
+                           -0.66666669,
+                           -1.33333337},
+            ov::Shape{1},
+            {3}),
         AdaptiveAvgPoolParams(
             ov::Shape{1, 3, 7, 10},
             ov::Shape{1, 3, 3, 3},
             IN_ET,
             IN_ET,
-            std::vector<T>{-2, -3, -4, 3,  -5, 4,  0,  -4, -2, -4, -5, 0,  -3, 0,  -2, 0,  0,  -5, -4, -1, 3,  -1, 0,  -1,
-                            0,  -2, 0,  4,  1,  4,  0,  -1, -4, 2,  -2, -5, -1, -1, -2, 1,  2,  -2, -1, 2,  0,  -1, 0,  -5,
-                            4,  4,  3,  0,  -4, -4, -4, -2, 0,  1,  -2, -1, 4,  -2, -4, 1,  -1, -3, -4, -1, 1,  -4,
-
-                           -2, -4, -5, 0,  -4, 3,  4,  -5, -4, -2, 0,  2,  -4, -3, 3,  -1, 1,  -4, -5, 4,  2,  -5, 2,  -3,
-                            0,  4,  3,  3,  1,  2,  -1, -4, 1,  -3, -3, -2, 3,  4,  -2, -5, 1,  4,  4,  -2, 2,  1,  -5, -2,
-                           -5, 1,  1,  -2, -3, -3, -1, -5, 1,  -3, -5, -3, -4, -1, 4,  -3, 4,  -1, 4,  3,  1,  4,
-
-                           -2, -4, -4, 4,  -3, 4,  2,  -3, -2, 4,  -3, 0,  1,  -4, 4,  4,  0,  3,  -1, 3,  3,  -5, 0,  3,
-                           -3, 1,  -2, 4,  -5, -5, 1,  0,  -1, 0,  -3, -2, 0,  -3, 3,  -2, -2, 0,  -3, 4,  -1, 2,  -2, 2,
-                           -3, -1, -4, -2, 0,  2,  0,  2,  0,  -3, 4,  3,  -5, -3, -5, 1,  -5, -3, -5, 4,  -3, 3},
+            std::vector<T>{
+                -2, -3, -4, 3,  -5, 4,  0,  -4, -2, -4, -5, 0,  -3, 0,  -2, 0,  0,  -5, -4, -1, 3,  -1, 0,  -1,
+                0,  -2, 0,  4,  1,  4,  0,  -1, -4, 2,  -2, -5, -1, -1, -2, 1,  2,  -2, -1, 2,  0,  -1, 0,  -5,
+                4,  4,  3,  0,  -4, -4, -4, -2, 0,  1,  -2, -1, 4,  -2, -4, 1,  -1, -3, -4, -1, 1,  -4,
+
+                -2, -4, -5, 0,  -4, 3,  4,  -5, -4, -2, 0,  2,  -4, -3, 3,  -1, 1,  -4, -5, 4,  2,  -5, 2,  -3,
+                0,  4,  3,  3,  1,  2,  -1, -4, 1,  -3, -3, -2, 3,  4,  -2, -5, 1,  4,  4,  -2, 2,  1,  -5, -2,
+                -5, 1,  1,  -2, -3, -3, -1, -5, 1,  -3, -5, -3, -4, -1, 4,  -3, 4,  -1, 4,  3,  1,  4,
+
+                -2, -4, -4, 4,  -3, 4,  2,  -3, -2, 4,  -3, 0,  1,  -4, 4,  4,  0,  3,  -1, 3,  3,  -5, 0,  3,
+                -3, 1,  -2, 4,  -5, -5, 1,  0,  -1, 0,  -3, -2, 0,  -3, 3,  -2, -2, 0,  -3, 4,  -1, 2,  -2, 2,
+                -3, -1, -4, -2, 0,  2,  0,  2,  0,  -3, 4,  3,  -5, -3, -5, 1,  -5, -3, -5, 4,  -3, 3},
             std::vector<T>{-1.08333337, -0.25000000, -0.91666669, -0.08333334, -0.66666669,
                            0.75000000,  -0.41666666, -1.33333337, -0.58333331,
 
@@ -142,14 +146,14 @@ std::vector<AdaptiveAvgPoolParams> generateParamsForAdaptiveAvgPool() {
             ov::Shape{2, 2, 2, 2, 2},
             IN_ET,
             IN_ET,
-            std::vector<T>{-5, 1,  -3, -4, 4,  -4, 3,  -3, -1, 0,  0,  -2, -4, 2, 0,  -4, -5, -2, -4, -4, 0,  -2, 3,  -3, 4,  -1, -4,
-                           -1, -1, -5, 4,  -1, -2, -3, 0,  4,  -1, -5, -4, 1,  1, 4,  -5, -5, -5, 4,  -3, -3, -3, 4,  0,  -3, -5, 1,
-                            4,  2,  1,  -5, -5, 1,  0,  -4, -1, 2,  -4, -2, 4,  3, 1,  -3, -3, -2, -4, -3, -3, 3,  -1, 1,  2,  2,  -4,
-                           -5, -4, 1,  3,  -4, -1, 2,  4,  -5, 0,  1,  -2, 0,  0, -2, 3,  -2, -5, -3, -5, -2, -1, 3,  -2, 4,  3,  -3},
-            std::vector<T>{-0.750, -0.250, -1.375, -1.125, -1.125, -0.500, -0.875, -1.250,
-                           -0.375, -1.625, -1.,    -0.500, -0.250, -0.750, -1.875, -0.625,
-                            0.125,  -0.375, -1.625, -1.250, 0.,     -1.,    0.875,  -0.375,
-                           -1.125, -1.375, 0.750,  -1.875, -0.625, -1.125, 1.250,  -1.},
+            std::vector<T>{-5, 1,  -3, -4, 4,  -4, 3,  -3, -1, 0,  0,  -2, -4, 2,  0,  -4, -5, -2, -4, -4, 0,  -2,
+                           3,  -3, 4,  -1, -4, -1, -1, -5, 4,  -1, -2, -3, 0,  4,  -1, -5, -4, 1,  1,  4,  -5, -5,
+                           -5, 4,  -3, -3, -3, 4,  0,  -3, -5, 1,  4,  2,  1,  -5, -5, 1,  0,  -4, -1, 2,  -4, -2,
+                           4,  3,  1,  -3, -3, -2, -4, -3, -3, 3,  -1, 1,  2,  2,  -4, -5, -4, 1,  3,  -4, -1, 2,
+                           4,  -5, 0,  1,  -2, 0,  0,  -2, 3,  -2, -5, -3, -5, -2, -1, 3,  -2, 4,  3,  -3},
+            std::vector<T>{-0.750, -0.250, -1.375, -1.125, -1.125, -0.500, -0.875, -1.250, -0.375, -1.625, -1.,
+                           -0.500, -0.250, -0.750, -1.875, -0.625, 0.125,  -0.375, -1.625, -1.250, 0.,     -1.,
+                           0.875,  -0.375, -1.125, -1.375, 0.750,  -1.875, -0.625, -1.125, 1.250,  -1.},
             ov::Shape{3},
             {2, 2, 2}),
     };
@@ -160,8 +164,7 @@ std::vector<AdaptiveAvgPoolParams> generateCombinedParamsForAdaptiveAvgPool() {
     const std::vector<std::vector<AdaptiveAvgPoolParams>> allTypeParams{
         generateParamsForAdaptiveAvgPool<element::Type_t::f32>(),
         generateParamsForAdaptiveAvgPool<element::Type_t::f16>(),
-        generateParamsForAdaptiveAvgPool<element::Type_t::bf16>()
-    };
+        generateParamsForAdaptiveAvgPool<element::Type_t::bf16>()};
 
     std::vector<AdaptiveAvgPoolParams> combinedParams;
 
@@ -172,10 +175,9 @@ std::vector<AdaptiveAvgPoolParams> generateCombinedParamsForAdaptiveAvgPool() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_AdaptiveAvgPool_With_Hardcoded_Refs,
-    ReferenceAdaptiveAvgPoolLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForAdaptiveAvgPool()),
-    ReferenceAdaptiveAvgPoolLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_AdaptiveAvgPool_With_Hardcoded_Refs,
+                         ReferenceAdaptiveAvgPoolLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForAdaptiveAvgPool()),
+                         ReferenceAdaptiveAvgPoolLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/adaptive_max_pool.cpp b/src/plugins/template/tests/functional/op_reference/adaptive_max_pool.cpp
index 0fc8fab948c51e..68ac723f0ae8e2 100644
--- a/src/plugins/template/tests/functional/op_reference/adaptive_max_pool.cpp
+++ b/src/plugins/template/tests/functional/op_reference/adaptive_max_pool.cpp
@@ -2,10 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/adaptive_max_pool.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
-#include "openvino/op/adaptive_max_pool.hpp"
 #include "openvino/op/constant.hpp"
 
 using namespace ov;
@@ -44,7 +45,8 @@ struct AdaptiveMaxPoolParams {
     std::vector<int64_t> m_adaptive_values;
 };
 
-class ReferenceAdaptiveMaxPoolLayerTest : public testing::TestWithParam<AdaptiveMaxPoolParams>, public CommonReferenceTest {
+class ReferenceAdaptiveMaxPoolLayerTest : public testing::TestWithParam<AdaptiveMaxPoolParams>,
+                                          public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -68,9 +70,9 @@ class ReferenceAdaptiveMaxPoolLayerTest : public testing::TestWithParam<Adaptive
 
 private:
     static std::shared_ptr<Model> CreateFunction(const Shape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const Shape& adaptive_shape,
-                                                    const std::vector<int64_t> adaptive_values) {
+                                                 const element::Type& input_type,
+                                                 const Shape& adaptive_shape,
+                                                 const std::vector<int64_t> adaptive_values) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto out = op::v0::Constant::create<int64_t>(element::Type_t::i64, adaptive_shape, adaptive_values);
         const auto adaptive_max_pool = std::make_shared<op::v8::AdaptiveMaxPool>(in, out);
@@ -93,7 +95,7 @@ std::vector<AdaptiveMaxPoolParams> generateParamsForAdaptiveMaxPoolWithExpectedR
             IN_ET,
             IN_ET,
             std::vector<T>{0,  4,  1, 3, -2, -5, -2, -2, 1, -3, 1,  -3, -4, 0,  -2, 1, -1, -2, 3, -1, -3,
-                          -1, -2, 3, 4, -3, -4, 1,  2,  0, -4, -5, -2, -2, -3, 2,  3, 1,  -5, 2, -4, -2},
+                           -1, -2, 3, 4, -3, -4, 1,  2,  0, -4, -5, -2, -2, -3, 2,  3, 1,  -5, 2, -4, -2},
             std::vector<T>{4,
                            3,
                            -2,
@@ -114,77 +116,69 @@ std::vector<AdaptiveMaxPoolParams> generateParamsForAdaptiveMaxPoolWithExpectedR
                            2,
                            2},
             std::vector<int64_t>{1,
-                           3,
-                           4,
-                           1,
-                           3,
-                           6,
-                           1,
-                           4,
-                           4,
-
-                           2,
-                           3,
-                           6,
-                           0,
-                           4,
-                           4,
-                           1,
-                           4,
-                           4},
-                      ov::Shape{1},
+                                 3,
+                                 4,
+                                 1,
+                                 3,
+                                 6,
+                                 1,
+                                 4,
+                                 4,
+
+                                 2,
+                                 3,
+                                 6,
+                                 0,
+                                 4,
+                                 4,
+                                 1,
+                                 4,
+                                 4},
+            ov::Shape{1},
             std::vector<int64_t>{3}),
         AdaptiveMaxPoolParams(
             ov::Shape{1, 3, 7, 10},
             ov::Shape{1, 3, 3, 3},
             IN_ET,
             IN_ET,
-            std::vector<T>{0,  -2, -5, -5, 2,  3,  2,  -3, 1,  -2, -4, -1, -1, -1, 2,  -4, 3,  -5, -1, -1, 1,  2,  4,  -2,
-                          -3, -2, 0,  -5, 2,  -4, -1, -4, 4,  2,  1,  -2, 2,  -3, 0,  1,  -3, 3,  -1, 4,  0,  2,  0,  3,
-                           4,  -4, 1,  4,  -1, -5, -2, 4,  -3, 3,  2,  1,  0,  4,  2,  -5, 2,  -5, -2, -1, 4,  2,
-
-                           0,  4,  -2, 0,  -5, -3, 4,  -4, -2, -2, 2,  1,  4,  3,  2,  -5, -4, -4, 0,  1,  4,  -4, -3, 3,
-                           3,  4,  -2, -3, -4, -2, 0,  1,  -1, 3,  -2, 2,  0,  -3, -1, -1, 0,  0,  2,  2,  -2, 1,  -3, 1,
-                           2,  4,  3,  -5, -4, 1,  -4, 2,  0,  -2, -5, 2,  -3, -2, -3, -4, 2,  -2, -4, 2,  -4, -3,
-
-                           1,  -5, -1, -5, 2,  1,  3,  4,  3,  0,  -5, 4,  -3, -4, -1, 2,  -4, 2,  0,  -5, -3, 0,  2,  -3,
-                          -5, 3,  -2, -1, -5, -4, -5, 0,  -5, -1, -3, 3,  3,  -4, -3, -4, -5, 4,  -1, 1,  -1, -4, 1,  -3,
-                          -4, -1, -2, -3, -5, 2,  2,  -5, 1,  1,  -5, -4, 0,  2,  4,  2,  0,  2,  4,  0,  -5, 2},
-            std::vector<T>{4, 3, 3, 4, 4, 4, 4, 4, 4,
-                           4, 4, 4, 4, 4, 4, 3, 2, 4,
-                           4, 3, 4, 4, 3, 3, 4, 4, 4},
-            std::vector<int64_t>{22, 5, 16, 22, 43, 48, 43, 43, 48,
-                                 1,  6, 6,  20, 25, 49, 50, 43, 49,
-                                 11, 6, 7,  41, 25, 36, 41, 66, 66},
+            std::vector<T>{
+                0,  -2, -5, -5, 2,  3,  2,  -3, 1,  -2, -4, -1, -1, -1, 2,  -4, 3,  -5, -1, -1, 1,  2,  4,  -2,
+                -3, -2, 0,  -5, 2,  -4, -1, -4, 4,  2,  1,  -2, 2,  -3, 0,  1,  -3, 3,  -1, 4,  0,  2,  0,  3,
+                4,  -4, 1,  4,  -1, -5, -2, 4,  -3, 3,  2,  1,  0,  4,  2,  -5, 2,  -5, -2, -1, 4,  2,
+
+                0,  4,  -2, 0,  -5, -3, 4,  -4, -2, -2, 2,  1,  4,  3,  2,  -5, -4, -4, 0,  1,  4,  -4, -3, 3,
+                3,  4,  -2, -3, -4, -2, 0,  1,  -1, 3,  -2, 2,  0,  -3, -1, -1, 0,  0,  2,  2,  -2, 1,  -3, 1,
+                2,  4,  3,  -5, -4, 1,  -4, 2,  0,  -2, -5, 2,  -3, -2, -3, -4, 2,  -2, -4, 2,  -4, -3,
+
+                1,  -5, -1, -5, 2,  1,  3,  4,  3,  0,  -5, 4,  -3, -4, -1, 2,  -4, 2,  0,  -5, -3, 0,  2,  -3,
+                -5, 3,  -2, -1, -5, -4, -5, 0,  -5, -1, -3, 3,  3,  -4, -3, -4, -5, 4,  -1, 1,  -1, -4, 1,  -3,
+                -4, -1, -2, -3, -5, 2,  2,  -5, 1,  1,  -5, -4, 0,  2,  4,  2,  0,  2,  4,  0,  -5, 2},
+            std::vector<T>{4, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 3, 2, 4, 4, 3, 4, 4, 3, 3, 4, 4, 4},
+            std::vector<int64_t>{22, 5,  16, 22, 43, 48, 43, 43, 48, 1,  6,  6,  20, 25,
+                                 49, 50, 43, 49, 11, 6,  7,  41, 25, 36, 41, 66, 66},
             ov::Shape{2},
             std::vector<int64_t>{3, 3}),
-        AdaptiveMaxPoolParams(
-            ov::Shape{2, 2, 3, 3, 3},
-            ov::Shape{2, 2, 2, 2, 2},
-            IN_ET,
-            IN_ET,
-            std::vector<T>{-5, 1,  -3, -4, 4,  -4, 3,  -3, -1, 0,  0,  -2, -4, 2,
-                            0,  -4, -5, -2, -4, -4, 0,  -2, 3,  -3, 4,  -1, -4,
-
-                           -1, -1, -5, 4,  -1, -2, -3, 0,  4,  -1, -5, -4, 1,  1,
-                            4,  -5, -5, -5, 4,  -3, -3, -3, 4,  0,  -3, -5, 1,
-
-                            4,  2,  1,  -5, -5, 1,  0,  -4, -1, 2,  -4, -2, 4,  3,
-                            1,  -3, -3, -2, -4, -3, -3, 3,  -1, 1,  2,  2,  -4,
-
-                           -5, -4, 1,  3,  -4, -1, 2,  4,  -5, 0,  1,  -2, 0,  0,
-                           -2, 3,  -2, -5, -3, -5, -2, -1, 3,  -2, 4,  3,  -3},
-            std::vector<T>{4, 4, 4, 4, 3, 3, 4, 3,
-                           4, 4, 4, 4, 4, 4, 4, 4,
-                           4, 3, 4, 3, 4, 3, 4, 3,
-                           3, 1, 4, 4, 3, 3, 4, 3},
-            std::vector<int64_t>{4, 4,  4,  4,  22, 22, 24, 22,
-                                 3, 14, 3,  8,  18, 14, 22, 14,
-                                 0, 13, 12, 13, 12, 13, 12, 13,
-                                 3, 2,  7,  7,  22, 22, 24, 22},
-            ov::Shape{3},
-            std::vector<int64_t>{2, 2, 2})
-    };
+        AdaptiveMaxPoolParams(ov::Shape{2, 2, 3, 3, 3},
+                              ov::Shape{2, 2, 2, 2, 2},
+                              IN_ET,
+                              IN_ET,
+                              std::vector<T>{-5, 1,  -3, -4, 4,  -4, 3,  -3, -1, 0,  0,  -2, -4, 2,
+                                             0,  -4, -5, -2, -4, -4, 0,  -2, 3,  -3, 4,  -1, -4,
+
+                                             -1, -1, -5, 4,  -1, -2, -3, 0,  4,  -1, -5, -4, 1,  1,
+                                             4,  -5, -5, -5, 4,  -3, -3, -3, 4,  0,  -3, -5, 1,
+
+                                             4,  2,  1,  -5, -5, 1,  0,  -4, -1, 2,  -4, -2, 4,  3,
+                                             1,  -3, -3, -2, -4, -3, -3, 3,  -1, 1,  2,  2,  -4,
+
+                                             -5, -4, 1,  3,  -4, -1, 2,  4,  -5, 0,  1,  -2, 0,  0,
+                                             -2, 3,  -2, -5, -3, -5, -2, -1, 3,  -2, 4,  3,  -3},
+                              std::vector<T>{4, 4, 4, 4, 3, 3, 4, 3, 4, 4, 4, 4, 4, 4, 4, 4,
+                                             4, 3, 4, 3, 4, 3, 4, 3, 3, 1, 4, 4, 3, 3, 4, 3},
+                              std::vector<int64_t>{4, 4,  4,  4,  22, 22, 24, 22, 3, 14, 3, 8, 18, 14, 22, 14,
+                                                   0, 13, 12, 13, 12, 13, 12, 13, 3, 2,  7, 7, 22, 22, 24, 22},
+                              ov::Shape{3},
+                              std::vector<int64_t>{2, 2, 2})};
     return params;
 }
 
@@ -208,10 +202,9 @@ std::vector<AdaptiveMaxPoolParams> generateCombinedParamsForAdaptiveMaxPool() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_AdaptiveMaxPool_With_Hardcoded_Refs,
-    ReferenceAdaptiveMaxPoolLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForAdaptiveMaxPool()),
-    ReferenceAdaptiveMaxPoolLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_AdaptiveMaxPool_With_Hardcoded_Refs,
+                         ReferenceAdaptiveMaxPoolLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForAdaptiveMaxPool()),
+                         ReferenceAdaptiveMaxPoolLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/add.cpp b/src/plugins/template/tests/functional/op_reference/add.cpp
index 7a5e99ba91d493..96a0091a949594 100644
--- a/src/plugins/template/tests/functional/op_reference/add.cpp
+++ b/src/plugins/template/tests/functional/op_reference/add.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/add.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/add.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -57,9 +59,9 @@ class ReferenceAddLayerTest : public testing::TestWithParam<AddParams>, public C
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto add = std::make_shared<op::v1::Add>(in1, in2);
@@ -88,9 +90,9 @@ class ReferenceAddInPlaceLayerTest : public testing::TestWithParam<AddParams>, p
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         auto add = std::make_shared<op::v1::Add>(in1, in2);
@@ -146,31 +148,27 @@ template <element::Type_t IN_ET>
 std::vector<AddParams> generateParamsForAddInPlace() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<AddParams> params{
-        AddParams(ov::PartialShape{2, 2},
-                  ov::PartialShape{2, 2},
-                  IN_ET,
-                  std::vector<T>{1, 2, 3, 4},
-                  std::vector<T>{5, 6, 7, 8},
-                  std::vector<T>{48, 64, 80, 96})
-    };
+    std::vector<AddParams> params{AddParams(ov::PartialShape{2, 2},
+                                            ov::PartialShape{2, 2},
+                                            IN_ET,
+                                            std::vector<T>{1, 2, 3, 4},
+                                            std::vector<T>{5, 6, 7, 8},
+                                            std::vector<T>{48, 64, 80, 96})};
     return params;
 }
 
 std::vector<AddParams> generateCombinedParamsForAdd() {
-    const std::vector<std::vector<AddParams>> allTypeParams{
-        generateParamsForAdd<element::Type_t::f32>(),
-        generateParamsForAdd<element::Type_t::f16>(),
-        generateParamsForAdd<element::Type_t::bf16>(),
-        generateParamsForAdd<element::Type_t::i64>(),
-        generateParamsForAdd<element::Type_t::i32>(),
-        generateParamsForAdd<element::Type_t::i16>(),
-        generateParamsForAdd<element::Type_t::i8>(),
-        generateParamsForAdd<element::Type_t::u64>(),
-        generateParamsForAdd<element::Type_t::u32>(),
-        generateParamsForAdd<element::Type_t::u16>(),
-        generateParamsForAdd<element::Type_t::u8>()
-    };
+    const std::vector<std::vector<AddParams>> allTypeParams{generateParamsForAdd<element::Type_t::f32>(),
+                                                            generateParamsForAdd<element::Type_t::f16>(),
+                                                            generateParamsForAdd<element::Type_t::bf16>(),
+                                                            generateParamsForAdd<element::Type_t::i64>(),
+                                                            generateParamsForAdd<element::Type_t::i32>(),
+                                                            generateParamsForAdd<element::Type_t::i16>(),
+                                                            generateParamsForAdd<element::Type_t::i8>(),
+                                                            generateParamsForAdd<element::Type_t::u64>(),
+                                                            generateParamsForAdd<element::Type_t::u32>(),
+                                                            generateParamsForAdd<element::Type_t::u16>(),
+                                                            generateParamsForAdd<element::Type_t::u8>()};
 
     std::vector<AddParams> combinedParams;
 
@@ -182,19 +180,17 @@ std::vector<AddParams> generateCombinedParamsForAdd() {
 }
 
 std::vector<AddParams> generateCombinedParamsForAddInPlace() {
-    const std::vector<std::vector<AddParams>> allTypeParams{
-        generateParamsForAddInPlace<element::Type_t::f32>(),
-        generateParamsForAddInPlace<element::Type_t::f16>(),
-        generateParamsForAddInPlace<element::Type_t::bf16>(),
-        generateParamsForAddInPlace<element::Type_t::i64>(),
-        generateParamsForAddInPlace<element::Type_t::i32>(),
-        generateParamsForAddInPlace<element::Type_t::i16>(),
-        generateParamsForAddInPlace<element::Type_t::i8>(),
-        generateParamsForAddInPlace<element::Type_t::u64>(),
-        generateParamsForAddInPlace<element::Type_t::u32>(),
-        generateParamsForAddInPlace<element::Type_t::u16>(),
-        generateParamsForAddInPlace<element::Type_t::u8>()
-    };
+    const std::vector<std::vector<AddParams>> allTypeParams{generateParamsForAddInPlace<element::Type_t::f32>(),
+                                                            generateParamsForAddInPlace<element::Type_t::f16>(),
+                                                            generateParamsForAddInPlace<element::Type_t::bf16>(),
+                                                            generateParamsForAddInPlace<element::Type_t::i64>(),
+                                                            generateParamsForAddInPlace<element::Type_t::i32>(),
+                                                            generateParamsForAddInPlace<element::Type_t::i16>(),
+                                                            generateParamsForAddInPlace<element::Type_t::i8>(),
+                                                            generateParamsForAddInPlace<element::Type_t::u64>(),
+                                                            generateParamsForAddInPlace<element::Type_t::u32>(),
+                                                            generateParamsForAddInPlace<element::Type_t::u16>(),
+                                                            generateParamsForAddInPlace<element::Type_t::u8>()};
 
     std::vector<AddParams> combinedParams;
 
@@ -205,16 +201,14 @@ std::vector<AddParams> generateCombinedParamsForAddInPlace() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Add_With_Hardcoded_Refs,
-    ReferenceAddLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForAdd()),
-    ReferenceAddLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Add_In_Place_With_Hardcoded_Refs,
-    ReferenceAddInPlaceLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForAddInPlace()),
-    ReferenceAddLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Add_With_Hardcoded_Refs,
+                         ReferenceAddLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForAdd()),
+                         ReferenceAddLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Add_In_Place_With_Hardcoded_Refs,
+                         ReferenceAddInPlaceLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForAddInPlace()),
+                         ReferenceAddLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/asin.cpp b/src/plugins/template/tests/functional/op_reference/asin.cpp
index 362b7fe6acc980..56dfd504d9d110 100644
--- a/src/plugins/template/tests/functional/op_reference/asin.cpp
+++ b/src/plugins/template/tests/functional/op_reference/asin.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/asin.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/asin.hpp"
-#include "shared_test_classes/base/layer_test_utils.hpp"
 #include "base_reference_test.hpp"
+#include "shared_test_classes/base/layer_test_utils.hpp"
 
 using namespace ov;
 
@@ -43,7 +44,7 @@ class ReferenceAsinLayerTest : public testing::TestWithParam<AsinParams>, public
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto Asin = std::make_shared<op::v0::Asin>(in);
-        return std::make_shared<ov::Model>(NodeVector {Asin}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Asin}, ParameterVector{in});
     }
 };
 
@@ -54,46 +55,56 @@ TEST_P(ReferenceAsinLayerTest, AsinWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Asin_With_Hardcoded_Refs, ReferenceAsinLayerTest,
+    smoke_Asin_With_Hardcoded_Refs,
+    ReferenceAsinLayerTest,
     ::testing::Values(
-        Builder {}
-            .input({{11}, element::f16, std::vector<ov::float16> {-1.f, -0.75f, -0.5f, -0.25f, -0.125f, 0.f, 0.125f, 0.25f, 0.5f, 0.75f, 1.f}})
-            .expected({{11}, element::f16, std::vector<ov::float16> {-1.57079633f,
-                            -0.84806208f,
-                            -0.52359878f,
-                            -0.25268026f,
-                            -0.12532783f,
-                            0.00000000f,
-                            0.12532783f,
-                            0.25268026f,
-                            0.52359878f,
-                            0.84806208f,
-                            1.57079633f}}),
-        Builder {}
-            .input({{11}, element::f32, std::vector<float> {-1.f, -0.75f, -0.5f, -0.25f, -0.125f, 0.f, 0.125f, 0.25f, 0.5f, 0.75f, 1.f}})
-            .expected({{11}, element::f32, std::vector<float> {-1.57079633f,
-                            -0.84806208f,
-                            -0.52359878f,
-                            -0.25268026f,
-                            -0.12532783f,
-                            0.00000000f,
-                            0.12532783f,
-                            0.25268026f,
-                            0.52359878f,
-                            0.84806208f,
-                            1.57079633f}}),
-        Builder {}
-            .input({{3}, element::i32, std::vector<int32_t> {-1, 0, 1}})
-            .expected({{3}, element::i32, std::vector<int32_t> {-1, 0, 1}}),
-        Builder {}
-            .input({{3}, element::i64, std::vector<int64_t> {-1, 0, 1}})
-            .expected({{3}, element::i64, std::vector<int64_t> {-1, 0, 1}}),
-        Builder {}
-            .input({{2}, element::u32, std::vector<uint32_t> {0, 1}})
-            .expected({{2}, element::u32, std::vector<uint32_t> {0, 1}}),
-        Builder {}
-            .input({{2}, element::u64, std::vector<uint64_t> {0, 1}})
-            .expected({{2}, element::u64, std::vector<uint64_t> {0, 1}})),
+        Builder{}
+            .input(
+                {{11},
+                 element::f16,
+                 std::vector<ov::float16>{-1.f, -0.75f, -0.5f, -0.25f, -0.125f, 0.f, 0.125f, 0.25f, 0.5f, 0.75f, 1.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{-1.57079633f,
+                                                -0.84806208f,
+                                                -0.52359878f,
+                                                -0.25268026f,
+                                                -0.12532783f,
+                                                0.00000000f,
+                                                0.12532783f,
+                                                0.25268026f,
+                                                0.52359878f,
+                                                0.84806208f,
+                                                1.57079633f}}),
+        Builder{}
+            .input({{11},
+                    element::f32,
+                    std::vector<float>{-1.f, -0.75f, -0.5f, -0.25f, -0.125f, 0.f, 0.125f, 0.25f, 0.5f, 0.75f, 1.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{-1.57079633f,
+                                          -0.84806208f,
+                                          -0.52359878f,
+                                          -0.25268026f,
+                                          -0.12532783f,
+                                          0.00000000f,
+                                          0.12532783f,
+                                          0.25268026f,
+                                          0.52359878f,
+                                          0.84806208f,
+                                          1.57079633f}}),
+        Builder{}
+            .input({{3}, element::i32, std::vector<int32_t>{-1, 0, 1}})
+            .expected({{3}, element::i32, std::vector<int32_t>{-1, 0, 1}}),
+        Builder{}
+            .input({{3}, element::i64, std::vector<int64_t>{-1, 0, 1}})
+            .expected({{3}, element::i64, std::vector<int64_t>{-1, 0, 1}}),
+        Builder{}
+            .input({{2}, element::u32, std::vector<uint32_t>{0, 1}})
+            .expected({{2}, element::u32, std::vector<uint32_t>{0, 1}}),
+        Builder{}
+            .input({{2}, element::u64, std::vector<uint64_t>{0, 1}})
+            .expected({{2}, element::u64, std::vector<uint64_t>{0, 1}})),
 
     ReferenceAsinLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/asinh.cpp b/src/plugins/template/tests/functional/op_reference/asinh.cpp
index 6691662c6df644..0fbd3f5783819e 100644
--- a/src/plugins/template/tests/functional/op_reference/asinh.cpp
+++ b/src/plugins/template/tests/functional/op_reference/asinh.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/asinh.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/asinh.hpp"
-#include "shared_test_classes/base/layer_test_utils.hpp"
 #include "base_reference_test.hpp"
+#include "shared_test_classes/base/layer_test_utils.hpp"
 
 using namespace ov;
 
@@ -43,7 +44,7 @@ class ReferenceAsinhLayerTest : public testing::TestWithParam<AsinhParams>, publ
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto Asinh = std::make_shared<op::v3::Asinh>(in);
-        return std::make_shared<ov::Model>(NodeVector {Asinh}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Asinh}, ParameterVector{in});
     }
 };
 
@@ -54,46 +55,54 @@ TEST_P(ReferenceAsinhLayerTest, AsinhWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Asinh_With_Hardcoded_Refs, ReferenceAsinhLayerTest,
+    smoke_Asinh_With_Hardcoded_Refs,
+    ReferenceAsinhLayerTest,
     ::testing::Values(
-        Builder {}
-            .input({{11}, element::f16, std::vector<ov::float16> {0.f, 1.f, -1.f, 2.f, -2.f, 3.f, -3.f, 4.f, 5.f, 10.f, 100.f}})
-            .expected({{11}, element::f16, std::vector<ov::float16> {0.00000000f,
-                            0.88137359f,
-                            -0.88137359f,
-                            1.44363548f,
-                            -1.44363548f,
-                            1.81844646f,
-                            -1.81844646f,
-                            2.09471255f,
-                            2.31243834f,
-                            2.99822295f,
-                            5.29834237f}}),
-        Builder {}
-            .input({{11}, element::f32, std::vector<float> {0.f, 1.f, -1.f, 2.f, -2.f, 3.f, -3.f, 4.f, 5.f, 10.f, 100.f}})
-            .expected({{11}, element::f32, std::vector<float> {0.00000000f,
-                            0.88137359f,
-                            -0.88137359f,
-                            1.44363548f,
-                            -1.44363548f,
-                            1.81844646f,
-                            -1.81844646f,
-                            2.09471255f,
-                            2.31243834f,
-                            2.99822295f,
-                            5.29834237f}}),
-        Builder {}
-            .input({{11}, element::i32, std::vector<int32_t> {-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5}})
-            .expected({{11}, element::i32, std::vector<int32_t> {-2, -2, -2, -1, -1, 0, 1, 1, 2, 2, 2}}),
-        Builder {}
-            .input({{11}, element::i64, std::vector<int64_t> {-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5}})
-            .expected({{11}, element::i64, std::vector<int64_t> {-2, -2, -2, -1, -1, 0, 1, 1, 2, 2, 2}}),
-        Builder {}
-            .input({{6}, element::u32, std::vector<uint32_t> {0, 1, 2, 3, 4, 5}})
-            .expected({{6}, element::u32, std::vector<uint32_t> {0, 1, 1, 2, 2, 2}}),
-        Builder {}
-            .input({{6}, element::u64, std::vector<uint64_t> {0, 1, 2, 3, 4, 5}})
-            .expected({{6}, element::u64, std::vector<uint64_t> {0, 1, 1, 2, 2, 2}})),
+        Builder{}
+            .input({{11},
+                    element::f16,
+                    std::vector<ov::float16>{0.f, 1.f, -1.f, 2.f, -2.f, 3.f, -3.f, 4.f, 5.f, 10.f, 100.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{0.00000000f,
+                                                0.88137359f,
+                                                -0.88137359f,
+                                                1.44363548f,
+                                                -1.44363548f,
+                                                1.81844646f,
+                                                -1.81844646f,
+                                                2.09471255f,
+                                                2.31243834f,
+                                                2.99822295f,
+                                                5.29834237f}}),
+        Builder{}
+            .input(
+                {{11}, element::f32, std::vector<float>{0.f, 1.f, -1.f, 2.f, -2.f, 3.f, -3.f, 4.f, 5.f, 10.f, 100.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{0.00000000f,
+                                          0.88137359f,
+                                          -0.88137359f,
+                                          1.44363548f,
+                                          -1.44363548f,
+                                          1.81844646f,
+                                          -1.81844646f,
+                                          2.09471255f,
+                                          2.31243834f,
+                                          2.99822295f,
+                                          5.29834237f}}),
+        Builder{}
+            .input({{11}, element::i32, std::vector<int32_t>{-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5}})
+            .expected({{11}, element::i32, std::vector<int32_t>{-2, -2, -2, -1, -1, 0, 1, 1, 2, 2, 2}}),
+        Builder{}
+            .input({{11}, element::i64, std::vector<int64_t>{-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5}})
+            .expected({{11}, element::i64, std::vector<int64_t>{-2, -2, -2, -1, -1, 0, 1, 1, 2, 2, 2}}),
+        Builder{}
+            .input({{6}, element::u32, std::vector<uint32_t>{0, 1, 2, 3, 4, 5}})
+            .expected({{6}, element::u32, std::vector<uint32_t>{0, 1, 1, 2, 2, 2}}),
+        Builder{}
+            .input({{6}, element::u64, std::vector<uint64_t>{0, 1, 2, 3, 4, 5}})
+            .expected({{6}, element::u64, std::vector<uint64_t>{0, 1, 1, 2, 2, 2}})),
 
     ReferenceAsinhLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/atan.cpp b/src/plugins/template/tests/functional/op_reference/atan.cpp
index 17e5ca343330de..99ff77e977e4ec 100644
--- a/src/plugins/template/tests/functional/op_reference/atan.cpp
+++ b/src/plugins/template/tests/functional/op_reference/atan.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/atan.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/atan.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -53,34 +54,43 @@ TEST_P(ReferenceAtanLayerTest, AtanWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Atan_With_Hardcoded_Refs, ReferenceAtanLayerTest,
+    smoke_Atan_With_Hardcoded_Refs,
+    ReferenceAtanLayerTest,
     ::testing::Values(
         Builder{}
-            .input({{11}, element::f16, std::vector<ov::float16>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
-            .expected({{11}, element::f16, std::vector<ov::float16>{-1.32581766f,
-                                                                       -1.10714872f,
-                                                                       -0.78539816f,
-                                                                       -0.46364761f,
-                                                                       -0.24497866f,
-                                                                        0.00000000f,
-                                                                        0.24497866f,
-                                                                        0.46364761f,
-                                                                        0.78539816f,
-                                                                        1.10714872f,
-                                                                        1.32581766f}}),
+            .input({{11},
+                    element::f16,
+                    std::vector<ov::float16>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{-1.32581766f,
+                                                -1.10714872f,
+                                                -0.78539816f,
+                                                -0.46364761f,
+                                                -0.24497866f,
+                                                0.00000000f,
+                                                0.24497866f,
+                                                0.46364761f,
+                                                0.78539816f,
+                                                1.10714872f,
+                                                1.32581766f}}),
         Builder{}
-            .input({{11}, element::f32, std::vector<float>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
-            .expected({{11}, element::f32, std::vector<float>{-1.32581766f,
-                                                             -1.10714872f,
-                                                             -0.78539816f,
-                                                             -0.46364761f,
-                                                             -0.24497866f,
-                                                              0.00000000f,
-                                                              0.24497866f,
-                                                              0.46364761f,
-                                                              0.78539816f,
-                                                              1.10714872f,
-                                                              1.32581766f}}),
+            .input({{11},
+                    element::f32,
+                    std::vector<float>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{-1.32581766f,
+                                          -1.10714872f,
+                                          -0.78539816f,
+                                          -0.46364761f,
+                                          -0.24497866f,
+                                          0.00000000f,
+                                          0.24497866f,
+                                          0.46364761f,
+                                          0.78539816f,
+                                          1.10714872f,
+                                          1.32581766f}}),
         Builder{}
             .input({{5}, element::i32, std::vector<int32_t>{-2, -1, 0, 1, 2}})
             .expected({{5}, element::i32, std::vector<int32_t>{-1, -1, 0, 1, 1}}),
diff --git a/src/plugins/template/tests/functional/op_reference/augru_cell.cpp b/src/plugins/template/tests/functional/op_reference/augru_cell.cpp
index 239dd84342ce4d..c72ad13aaeb6b4 100644
--- a/src/plugins/template/tests/functional/op_reference/augru_cell.cpp
+++ b/src/plugins/template/tests/functional/op_reference/augru_cell.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "ov_ops/augru_cell.hpp"
+
 #include <gtest/gtest.h>
 
-#include "ov_ops/augru_cell.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,12 +13,30 @@ using namespace ov;
 
 namespace {
 struct AUGRUCellParams {
-    AUGRUCellParams(
-        const int32_t batchSize, const int32_t inputSize, const int32_t hiddenSize, const int32_t gatesCount,
-        const reference_tests::Tensor& X, const reference_tests::Tensor& H_t, const reference_tests::Tensor& W, const reference_tests::Tensor& R, const reference_tests::Tensor& B, const reference_tests::Tensor& A,
-        const reference_tests::Tensor& Ho, const std::string& testcaseName = "") :
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize), gatesCount(gatesCount),
-        X(X), H_t(H_t), W(W), R(R), B(B), A(A), Ho(Ho), testcaseName(testcaseName) {}
+    AUGRUCellParams(const int32_t batchSize,
+                    const int32_t inputSize,
+                    const int32_t hiddenSize,
+                    const int32_t gatesCount,
+                    const reference_tests::Tensor& X,
+                    const reference_tests::Tensor& H_t,
+                    const reference_tests::Tensor& W,
+                    const reference_tests::Tensor& R,
+                    const reference_tests::Tensor& B,
+                    const reference_tests::Tensor& A,
+                    const reference_tests::Tensor& Ho,
+                    const std::string& testcaseName = "")
+        : batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          gatesCount(gatesCount),
+          X(X),
+          H_t(H_t),
+          W(W),
+          R(R),
+          B(B),
+          A(A),
+          Ho(Ho),
+          testcaseName(testcaseName) {}
 
     int32_t batchSize;
     int32_t inputSize;
@@ -76,13 +95,7 @@ class ReferenceAUGRUCellTest : public testing::TestWithParam<AUGRUCellParams>, p
         const auto B = std::make_shared<op::v0::Parameter>(params.B.type, params.B.shape);
         const auto A = std::make_shared<op::v0::Parameter>(params.A.type, params.A.shape);
 
-        const auto augru_cell = std::make_shared<ov::op::internal::AUGRUCell>(X,
-                                                                H_t,
-                                                                W,
-                                                                R,
-                                                                B,
-                                                                A,
-                                                                params.hiddenSize);
+        const auto augru_cell = std::make_shared<ov::op::internal::AUGRUCell>(X, H_t, W, R, B, A, params.hiddenSize);
 
         auto function = std::make_shared<Model>(NodeVector{augru_cell}, ParameterVector{X, H_t, W, R, B, A});
         return function;
@@ -96,107 +109,144 @@ TEST_P(ReferenceAUGRUCellTest, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<AUGRUCellParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<AUGRUCellParams> params {
+    std::vector<AUGRUCellParams> params{
         AUGRUCellParams(
-            2, 3, 3, 3,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.52421564f, 0.78845507f, 0.9372873f, 0.59783894f, 0.18278378f, 0.2084126f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.45738035f, 0.996877f, 0.82882977f, 0.47492632f, 0.88471466f, 0.57833236f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.5815369f, 0.16559383f, 0.08464007f, 0.843122f,   0.73968244f, 0.11359601f,
-                0.8295078f, 0.9240567f,  0.10007995f, 0.20573162f, 0.09002485f, 0.2839569f,
-                0.3096991f, 0.5638341f,  0.5787327f,  0.84552664f, 0.16263747f, 0.7243242f,
-                0.8049057f, 0.43966424f, 0.46294412f, 0.9833361f,  0.31369713f, 0.1719934f,
-                0.4937093f, 0.6353004f,  0.77982515f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.16510165f, 0.52435565f, 0.2788478f, 0.99427545f, 0.1623331f,  0.01389796f,
-                0.99669236f, 0.53901845f, 0.8737506f, 0.9254788f,  0.21172932f, 0.11634306f,
-                0.40111724f, 0.37497616f, 0.2903471f, 0.6796794f,  0.65131867f, 0.78163475f,
-                0.12058706f, 0.45591718f, 0.791677f,  0.76497287f, 0.9895242f,  0.7845312f,
-                0.51267904f, 0.49030215f, 0.08498167f}),
-            reference_tests::Tensor(ET, {3 * 3}, std::vector<T>{
-                0.8286678f + 0.9175602f,
-                0.9153158f + 0.14958014f,
-                0.9581612f + 0.49230585f,
-                0.6639213f + 0.63162816f,
-                0.84239805f + 0.4161903f,
-                0.5282445f + 0.22148274f,
-                0.14153397f + 0.50496656f,
-                0.22404431f + 0.34798595f,
-                0.6549655f + 0.6699164f}),
+            2,
+            3,
+            3,
+            3,
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.52421564f, 0.78845507f, 0.9372873f, 0.59783894f, 0.18278378f, 0.2084126f}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.45738035f, 0.996877f, 0.82882977f, 0.47492632f, 0.88471466f, 0.57833236f}),
+            reference_tests::Tensor(
+                ET,
+                {3 * 3, 3},
+                std::vector<T>{0.5815369f, 0.16559383f, 0.08464007f, 0.843122f,   0.73968244f, 0.11359601f, 0.8295078f,
+                               0.9240567f, 0.10007995f, 0.20573162f, 0.09002485f, 0.2839569f,  0.3096991f,  0.5638341f,
+                               0.5787327f, 0.84552664f, 0.16263747f, 0.7243242f,  0.8049057f,  0.43966424f, 0.46294412f,
+                               0.9833361f, 0.31369713f, 0.1719934f,  0.4937093f,  0.6353004f,  0.77982515f}),
+            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{0.16510165f, 0.52435565f, 0.2788478f,  0.99427545f,
+                                                                   0.1623331f,  0.01389796f, 0.99669236f, 0.53901845f,
+                                                                   0.8737506f,  0.9254788f,  0.21172932f, 0.11634306f,
+                                                                   0.40111724f, 0.37497616f, 0.2903471f,  0.6796794f,
+                                                                   0.65131867f, 0.78163475f, 0.12058706f, 0.45591718f,
+                                                                   0.791677f,   0.76497287f, 0.9895242f,  0.7845312f,
+                                                                   0.51267904f, 0.49030215f, 0.08498167f}),
+            reference_tests::Tensor(ET,
+                                    {3 * 3},
+                                    std::vector<T>{0.8286678f + 0.9175602f,
+                                                   0.9153158f + 0.14958014f,
+                                                   0.9581612f + 0.49230585f,
+                                                   0.6639213f + 0.63162816f,
+                                                   0.84239805f + 0.4161903f,
+                                                   0.5282445f + 0.22148274f,
+                                                   0.14153397f + 0.50496656f,
+                                                   0.22404431f + 0.34798595f,
+                                                   0.6549655f + 0.6699164f}),
             reference_tests::Tensor(ET, {2, 1}, std::vector<T>(2, 0)),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.480763f, 0.996927f, 0.830836f, 0.50231f, 0.894105f, 0.58932f}),
+            reference_tests::Tensor(ET,
+                                    {2, 3},
+                                    std::vector<T>{0.480763f, 0.996927f, 0.830836f, 0.50231f, 0.894105f, 0.58932f}),
             "augru_zero_attentional_gate"),
         AUGRUCellParams(
-            2, 3, 3, 3,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.52421564f, 0.78845507f, 0.9372873f, 0.59783894f, 0.18278378f, 0.2084126f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.45738035f, 0.996877f, 0.82882977f, 0.47492632f, 0.88471466f, 0.57833236f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.5815369f, 0.16559383f, 0.08464007f, 0.843122f,   0.73968244f, 0.11359601f,
-                0.8295078f, 0.9240567f,  0.10007995f, 0.20573162f, 0.09002485f, 0.2839569f,
-                0.3096991f, 0.5638341f,  0.5787327f,  0.84552664f, 0.16263747f, 0.7243242f,
-                0.8049057f, 0.43966424f, 0.46294412f, 0.9833361f,  0.31369713f, 0.1719934f,
-                0.4937093f, 0.6353004f,  0.77982515f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.16510165f, 0.52435565f, 0.2788478f, 0.99427545f, 0.1623331f,  0.01389796f,
-                0.99669236f, 0.53901845f, 0.8737506f, 0.9254788f,  0.21172932f, 0.11634306f,
-                0.40111724f, 0.37497616f, 0.2903471f, 0.6796794f,  0.65131867f, 0.78163475f,
-                0.12058706f, 0.45591718f, 0.791677f,  0.76497287f, 0.9895242f,  0.7845312f,
-                0.51267904f, 0.49030215f, 0.08498167f}),
-            reference_tests::Tensor(ET, {3 * 3}, std::vector<T>{
-                0.8286678f + 0.9175602f,
-                0.9153158f + 0.14958014f,
-                0.9581612f + 0.49230585f,
-                0.6639213f + 0.63162816f,
-                0.84239805f + 0.4161903f,
-                0.5282445f + 0.22148274f,
-                0.14153397f + 0.50496656f,
-                0.22404431f + 0.34798595f,
-                0.6549655f + 0.6699164f}),
+            2,
+            3,
+            3,
+            3,
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.52421564f, 0.78845507f, 0.9372873f, 0.59783894f, 0.18278378f, 0.2084126f}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.45738035f, 0.996877f, 0.82882977f, 0.47492632f, 0.88471466f, 0.57833236f}),
+            reference_tests::Tensor(
+                ET,
+                {3 * 3, 3},
+                std::vector<T>{0.5815369f, 0.16559383f, 0.08464007f, 0.843122f,   0.73968244f, 0.11359601f, 0.8295078f,
+                               0.9240567f, 0.10007995f, 0.20573162f, 0.09002485f, 0.2839569f,  0.3096991f,  0.5638341f,
+                               0.5787327f, 0.84552664f, 0.16263747f, 0.7243242f,  0.8049057f,  0.43966424f, 0.46294412f,
+                               0.9833361f, 0.31369713f, 0.1719934f,  0.4937093f,  0.6353004f,  0.77982515f}),
+            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{0.16510165f, 0.52435565f, 0.2788478f,  0.99427545f,
+                                                                   0.1623331f,  0.01389796f, 0.99669236f, 0.53901845f,
+                                                                   0.8737506f,  0.9254788f,  0.21172932f, 0.11634306f,
+                                                                   0.40111724f, 0.37497616f, 0.2903471f,  0.6796794f,
+                                                                   0.65131867f, 0.78163475f, 0.12058706f, 0.45591718f,
+                                                                   0.791677f,   0.76497287f, 0.9895242f,  0.7845312f,
+                                                                   0.51267904f, 0.49030215f, 0.08498167f}),
+            reference_tests::Tensor(ET,
+                                    {3 * 3},
+                                    std::vector<T>{0.8286678f + 0.9175602f,
+                                                   0.9153158f + 0.14958014f,
+                                                   0.9581612f + 0.49230585f,
+                                                   0.6639213f + 0.63162816f,
+                                                   0.84239805f + 0.4161903f,
+                                                   0.5282445f + 0.22148274f,
+                                                   0.14153397f + 0.50496656f,
+                                                   0.22404431f + 0.34798595f,
+                                                   0.6549655f + 0.6699164f}),
             reference_tests::Tensor(ET, {2, 1}, std::vector<T>{0.4f, 0.7f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.686381f, 0.997266f, 0.897868f, 0.832165f, 0.963144f, 0.868483f}),
-                "augru_attentional_gate_provided"),
-AUGRUCellParams(
-            2, 3, 4, 3,
-            reference_tests::Tensor(ET, {1, 3}, std::vector<T>{
-                0.64053001f,   0.84805253f,   0.84544252f}),
-            reference_tests::Tensor(ET, {1, 4}, std::vector<T>{
-                0.43200249f,   0.08097203f,   0.68151259f,   0.09095205f}),
-            reference_tests::Tensor(ET, {3 * 4, 3}, std::vector<T>{
-               0.23187583f,   0.66675389f,   0.01945467f,   0.60630121f,   0.18400699f,   0.16003634f,
-               0.04636866f,   0.75745989f,   0.96562912f,   0.56330529f,   0.20863093f,   0.93179716f,
-               0.99211225f,   0.73087621f,   0.21175275f,   0.03808638f,   0.63130526f,   0.76965886f,
-               0.67656870f,   0.57886251f,   0.94375534f,   0.88943972f,   0.96256618f,   0.38204562f,
-               0.76424904f,   0.30076485f,   0.60250044f,   0.40778284f,   0.70017757f,   0.00410288f,
-               0.97978094f,   0.73106175f,   0.22250106f,   0.44011834f,   0.11434720f,   0.62128995}),
-            reference_tests::Tensor(ET, {3 * 4, 4}, std::vector<T>{
-                0.60702709f,   0.47515485f,   0.26202747f,   0.53851601f,   0.73423241f,   0.11627945f,
-                0.04631785f,   0.43604361f,   0.12472080f,   0.47546322f,   0.23103632f,   0.36108585f,
-                0.45139418f,   0.79838954f,   0.28194170f,   0.76877929f,   0.28428253f,   0.13822001f,
-                0.51670576f,   0.80312243f,   0.11050813f,   0.19925340f,   0.29769184f,   0.78933459f,
-                0.79981487f,   0.55313454f,   0.04135296f,   0.50578146f,   0.76553680f,   0.44311704f,
-                0.30525652f,   0.26301583f,   0.41771479f,   0.18182059f,   0.11106816f,   0.67427757f,
-                0.59174944f,   0.13339960f,   0.33362533f,   0.78938375f,   0.99260256f,   0.86955733f,
-                0.24899024f,   0.87134874f,   0.02803802f,   0.61244129f,   0.40803782f,   0.90735816f,
-                0.51267904f, 0.49030215f, 0.08498167f}),
-            reference_tests::Tensor(ET, {3 * 4}, std::vector<T>{
-                0.61387895f,   0.56121052f,   0.89328753f,   0.15302506f,   0.90491122f,   0.78289335f,
-                0.97930211f,   0.75002178f,   0.92500923f,   0.18957983f,   0.07849785f,   0.76568159f}),
+            reference_tests::Tensor(ET,
+                                    {2, 3},
+                                    std::vector<T>{0.686381f, 0.997266f, 0.897868f, 0.832165f, 0.963144f, 0.868483f}),
+            "augru_attentional_gate_provided"),
+        AUGRUCellParams(
+            2,
+            3,
+            4,
+            3,
+            reference_tests::Tensor(ET, {1, 3}, std::vector<T>{0.64053001f, 0.84805253f, 0.84544252f}),
+            reference_tests::Tensor(ET, {1, 4}, std::vector<T>{0.43200249f, 0.08097203f, 0.68151259f, 0.09095205f}),
+            reference_tests::Tensor(
+                ET,
+                {3 * 4, 3},
+                std::vector<T>{0.23187583f, 0.66675389f, 0.01945467f, 0.60630121f, 0.18400699f, 0.16003634f,
+                               0.04636866f, 0.75745989f, 0.96562912f, 0.56330529f, 0.20863093f, 0.93179716f,
+                               0.99211225f, 0.73087621f, 0.21175275f, 0.03808638f, 0.63130526f, 0.76965886f,
+                               0.67656870f, 0.57886251f, 0.94375534f, 0.88943972f, 0.96256618f, 0.38204562f,
+                               0.76424904f, 0.30076485f, 0.60250044f, 0.40778284f, 0.70017757f, 0.00410288f,
+                               0.97978094f, 0.73106175f, 0.22250106f, 0.44011834f, 0.11434720f, 0.62128995}),
+            reference_tests::Tensor(
+                ET,
+                {3 * 4, 4},
+                std::vector<T>{0.60702709f, 0.47515485f, 0.26202747f, 0.53851601f, 0.73423241f, 0.11627945f,
+                               0.04631785f, 0.43604361f, 0.12472080f, 0.47546322f, 0.23103632f, 0.36108585f,
+                               0.45139418f, 0.79838954f, 0.28194170f, 0.76877929f, 0.28428253f, 0.13822001f,
+                               0.51670576f, 0.80312243f, 0.11050813f, 0.19925340f, 0.29769184f, 0.78933459f,
+                               0.79981487f, 0.55313454f, 0.04135296f, 0.50578146f, 0.76553680f, 0.44311704f,
+                               0.30525652f, 0.26301583f, 0.41771479f, 0.18182059f, 0.11106816f, 0.67427757f,
+                               0.59174944f, 0.13339960f, 0.33362533f, 0.78938375f, 0.99260256f, 0.86955733f,
+                               0.24899024f, 0.87134874f, 0.02803802f, 0.61244129f, 0.40803782f, 0.90735816f,
+                               0.51267904f, 0.49030215f, 0.08498167f}),
+            reference_tests::Tensor(ET,
+                                    {3 * 4},
+                                    std::vector<T>{0.61387895f,
+                                                   0.56121052f,
+                                                   0.89328753f,
+                                                   0.15302506f,
+                                                   0.90491122f,
+                                                   0.78289335f,
+                                                   0.97930211f,
+                                                   0.75002178f,
+                                                   0.92500923f,
+                                                   0.18957983f,
+                                                   0.07849785f,
+                                                   0.76568159f}),
             reference_tests::Tensor(ET, {1, 1}, std::vector<T>{0.3333f}),
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                0.666063f, 0.451451f, 0.792762f, 0.453281f}),
-                "augru_different_input_and_hidden_size"),
-     };
+            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{0.666063f, 0.451451f, 0.792762f, 0.453281f}),
+            "augru_different_input_and_hidden_size"),
+    };
     return params;
 }
 
 std::vector<AUGRUCellParams> generateCombinedParams() {
-    const std::vector<std::vector<AUGRUCellParams>> generatedParams {
+    const std::vector<std::vector<AUGRUCellParams>> generatedParams{
         generateParams<element::Type_t::bf16>(),
         generateParams<element::Type_t::f16>(),
         generateParams<element::Type_t::f32>(),
@@ -210,7 +260,9 @@ std::vector<AUGRUCellParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_AUGRUCell_With_Hardcoded_Refs, ReferenceAUGRUCellTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceAUGRUCellTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_AUGRUCell_With_Hardcoded_Refs,
+                         ReferenceAUGRUCellTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceAUGRUCellTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/augru_sequence.cpp b/src/plugins/template/tests/functional/op_reference/augru_sequence.cpp
index 27d5c48330bc05..c9d654da23367e 100644
--- a/src/plugins/template/tests/functional/op_reference/augru_sequence.cpp
+++ b/src/plugins/template/tests/functional/op_reference/augru_sequence.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "ov_ops/augru_sequence.hpp"
+
 #include <gtest/gtest.h>
 
-#include "ov_ops/augru_sequence.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,42 +14,53 @@ using namespace ov;
 namespace {
 struct AUGRUSequenceParams {
     template <class T>
-    AUGRUSequenceParams(
-        const size_t batchSize, const size_t inputSize, const size_t hiddenSize, const size_t seqLength,
-        const element::Type_t& iType,
-        const std::vector<T>& XValues, const std::vector<T>& H_tValues, const std::vector<int64_t>& seqLengthsValues,
-        const std::vector<T>& WValues, const std::vector<T>& RValues, const std::vector<T>& BValues, const std::vector<T>& AValues,
-        const std::vector<T>& YValues, const std::vector<T>& HoValues,
-        const std::string& testcaseName = "") :
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize), seqLength(seqLength),
-        iType(iType), oType(iType),
-        testcaseName(testcaseName) {
-            numDirections = 1;
+    AUGRUSequenceParams(const size_t batchSize,
+                        const size_t inputSize,
+                        const size_t hiddenSize,
+                        const size_t seqLength,
+                        const element::Type_t& iType,
+                        const std::vector<T>& XValues,
+                        const std::vector<T>& H_tValues,
+                        const std::vector<int64_t>& seqLengthsValues,
+                        const std::vector<T>& WValues,
+                        const std::vector<T>& RValues,
+                        const std::vector<T>& BValues,
+                        const std::vector<T>& AValues,
+                        const std::vector<T>& YValues,
+                        const std::vector<T>& HoValues,
+                        const std::string& testcaseName = "")
+        : batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          seqLength(seqLength),
+          iType(iType),
+          oType(iType),
+          testcaseName(testcaseName) {
+        numDirections = 1;
 
-            Shape XShape = Shape{batchSize, seqLength, inputSize};
-            Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape seqLengthsShape = Shape{batchSize};
-            Shape WShape = Shape{numDirections, 3 * hiddenSize, inputSize};
-            Shape RShape = Shape{numDirections, 3 * hiddenSize, hiddenSize};
-            Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
-            Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape XShape = Shape{batchSize, seqLength, inputSize};
+        Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape seqLengthsShape = Shape{batchSize};
+        Shape WShape = Shape{numDirections, 3 * hiddenSize, inputSize};
+        Shape RShape = Shape{numDirections, 3 * hiddenSize, hiddenSize};
+        Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
+        Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
 
-            X = reference_tests::Tensor(XShape, iType, XValues);
-            H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
-            sequence_lengths = reference_tests::Tensor(seqLengthsShape, element::Type_t::i64, seqLengthsValues);
-            W = reference_tests::Tensor(WShape, iType, WValues);
-            R = reference_tests::Tensor(RShape, iType, RValues);
+        X = reference_tests::Tensor(XShape, iType, XValues);
+        H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
+        sequence_lengths = reference_tests::Tensor(seqLengthsShape, element::Type_t::i64, seqLengthsValues);
+        W = reference_tests::Tensor(WShape, iType, WValues);
+        R = reference_tests::Tensor(RShape, iType, RValues);
 
-            Y = reference_tests::Tensor(YShape, oType, YValues);
-            Ho = reference_tests::Tensor(HoShape, oType, HoValues);
+        Y = reference_tests::Tensor(YShape, oType, YValues);
+        Ho = reference_tests::Tensor(HoShape, oType, HoValues);
 
-            Shape BShape = Shape{numDirections, 3 * hiddenSize};
-            B = reference_tests::Tensor(BShape, iType, BValues);
+        Shape BShape = Shape{numDirections, 3 * hiddenSize};
+        B = reference_tests::Tensor(BShape, iType, BValues);
 
-            Shape AShape = Shape{batchSize, seqLength, 1};
-            A = reference_tests::Tensor(AShape, iType, AValues);
-
-        }
+        Shape AShape = Shape{batchSize, seqLength, 1};
+        A = reference_tests::Tensor(AShape, iType, AValues);
+    }
 
     size_t batchSize;
     size_t inputSize;
@@ -75,7 +87,13 @@ class ReferenceAUGRUSequenceTest : public testing::TestWithParam<AUGRUSequencePa
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.X.data, params.H_t.data, params.sequence_lengths.data, params.W.data, params.R.data, params.B.data, params.A.data};
+        inputData = {params.X.data,
+                     params.H_t.data,
+                     params.sequence_lengths.data,
+                     params.W.data,
+                     params.R.data,
+                     params.B.data,
+                     params.A.data};
         refOutData = {params.Y.data, params.Ho.data};
     }
 
@@ -101,23 +119,18 @@ class ReferenceAUGRUSequenceTest : public testing::TestWithParam<AUGRUSequencePa
     static std::shared_ptr<Model> CreateFunction(const AUGRUSequenceParams& params) {
         const auto X = std::make_shared<op::v0::Parameter>(params.X.type, params.X.shape);
         const auto H_t = std::make_shared<op::v0::Parameter>(params.H_t.type, params.H_t.shape);
-        const auto sequence_lengths = std::make_shared<op::v0::Parameter>(params.sequence_lengths.type, params.sequence_lengths.shape);
+        const auto sequence_lengths =
+            std::make_shared<op::v0::Parameter>(params.sequence_lengths.type, params.sequence_lengths.shape);
         const auto W = std::make_shared<op::v0::Parameter>(params.W.type, params.W.shape);
         const auto R = std::make_shared<op::v0::Parameter>(params.R.type, params.R.shape);
         const auto B = std::make_shared<op::v0::Parameter>(params.B.type, params.B.shape);
         const auto A = std::make_shared<op::v0::Parameter>(params.A.type, params.A.shape);
 
         const auto augru_sequence =
-            std::make_shared<ov::op::internal::AUGRUSequence>(X,
-                                                  H_t,
-                                                  sequence_lengths,
-                                                  W,
-                                                  R,
-                                                  B,
-                                                  A,
-                                                  params.hiddenSize);
+            std::make_shared<ov::op::internal::AUGRUSequence>(X, H_t, sequence_lengths, W, R, B, A, params.hiddenSize);
 
-        auto function = std::make_shared<Model>(augru_sequence->outputs(), ParameterVector{X, H_t, sequence_lengths, W, R, B, A});
+        auto function =
+            std::make_shared<Model>(augru_sequence->outputs(), ParameterVector{X, H_t, sequence_lengths, W, R, B, A});
         return function;
     }
 };
@@ -130,504 +143,528 @@ template <element::Type_t ET>
 std::vector<AUGRUSequenceParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<AUGRUSequenceParams> params {
+    std::vector<AUGRUSequenceParams> params{
         AUGRUSequenceParams(
-            5, 10, 10, 10,
+            5,
+            10,
+            10,
+            10,
             ET,
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
-                1.82401, 6.1306, 4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686,
-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 4.59474,
-                6.19214, 8.80766, 8.07546, 3.29232, 1.74029, 2.4198, 2.88544, 4.75644, 4.12921, 7.29896,
-                7.27759, 1.67252, 1.32823, 8.1046, 9.10476, 1.04197, 3.37783, 5.2064, 4.23835, 3.16196,
-                1.20852, 5.78501, 2.17175, 6.05313, 2.51048, 4.78967, 7.16219, 3.4651, 1.09, 2.9788,
-                1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892, 5.86648, 8.73895, 2.66603, 1.75192,
-                1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565, 7.35114, 3.1439, 1.39976,
-                3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637, 8.6232, 8.54902,
-                2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225, 3.99956, 1.08021, 5.54918, 7.05833,
-                1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
-                5.59325, 9.89258, 2.30223, 1.4347, 9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909,
-                1.00912, 6.62167, 2.80244, 6.626, 3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902,
-                6.26823, 9.72608, 3.73491, 3.8238, 3.03815, 7.05101, 8.0103, 5.61396, 6.53738, 1.41095,
-                5.0149, 9.71211, 4.23604, 5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328, 8.2817,
-                5.12336, 8.98577, 5.80541, 6.19552, 9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817,
-                8.57269, 5.99975, 3.42893, 5.38068, 3.48261, 3.02851, 6.82079, 9.2902, 2.80427, 8.91868,
-                5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755, 2.49121, 5.52697, 8.08823, 9.13242,
-                2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457, 5.55154, 7.24966, 5.1128,
-                4.25147, 8.34407, 1.4123, 4.49045, 5.12671, 7.62159, 9.18673, 3.49665, 8.35992, 6.90684,
-                1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283, 9.88249, 4.48422,
-                8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155, 9.94928, 6.88321, 1.33685,
-                7.4718, 7.19305, 6.47932, 1.9559, 3.52616, 7.98593, 9.0115, 5.59539, 7.44137, 1.70001,
-                6.53774, 8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153,
-                5.4073, 9.00437, 8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473,
-                7.95084, 2.11852, 9.28916, 1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549,
-                3.75218, 8.98228, 8.98158, 5.63695, 3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035,
-                8.37644, 8.54954, 5.70516, 2.45744, 9.54079, 1.53504, 8.9785, 6.1691, 4.40962, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
+                1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 8.6168,
+                3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.0055,  7.44373,
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         AUGRUSequenceParams(
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+            10,
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             ET,
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-                3.75218, 8.98228, 8.98158, 5.63695, 3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035,
-                8.37644, 8.54954, 5.70516, 2.45744, 9.54079, 1.53504, 8.9785, 6.1691, 4.40962, 10},
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-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
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-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
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+                7.4718,  7.19305, 6.47932, 1.9559,  3.52616, 7.98593, 9.0115,  5.59539, 7.44137, 1.70001, 6.53774,
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+                1.53504, 8.9785,  6.1691,  4.40962, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
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-                1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565, 7.35114, 3.1439, 10},
-            std::vector<T>{
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+                7.35114, 3.1439,  10},
+            std::vector<T>{1,      9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168, 3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 10},
+            std::vector<T>{0.034518f, 0.673286f, 0.406714f, 0.252863f, 0.403579f, 0.985528f, 0.195026f, 0.102555f,
+                           0.862911f, 0.698157f, 0.159086f, 0.980120f, 0.821253f, 0.041956f, 0.297002f, 0.154800f,
+                           0.107107f, 0.457263f, 0.512179f, 0.372368f, 0.672125f, 0.078459f, 0.593353f, 0.800342f,
+                           0.245871f, 0.675492f, 0.799024f, 0.432696f, 0.095204f, 0.187363f, 0.715765f, 0.981477f,
+                           0.806237f, 0.544187f, 0.450795f, 0.717673f, 0.426730f, 0.601688f, 0.765923f, 0.675334f,
+                           0.341641f, 0.958286f, 0.137889f, 0.239074f, 0.015245f, 0.148769f, 0.793591f, 0.210904f,
+                           0.973056f, 0.646550f},
+            std::vector<T>{
+                1,       9.66487, 9.10331, 2.11332, 9.681,   3.05146, 4.44603, 4.37069, 6.81965, 9.12921, 1,
+                3.83094, 3.64746, 1.36374, 3.8362,  1.67024, 2.12587, 2.10125, 2.90136, 3.65593, 1,       2.67955,
+                2.5707,  1.2158,  2.68268, 1.39764, 1.66796, 1.65336, 2.12805, 2.57572, 1,       2.25486, 2.17353,
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+                1.00256, 1.00431, 1.00421, 1.00727, 1.01016, 1,       1.00872, 1.00815, 1.00112, 1.00874, 1.00206,
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+                1.00304, 1.00526, 1.00734, 1,       1.00107, 1.001,   1.00014, 1.00107, 1.00025, 1.00043, 1.00042,
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+                1.15808, 1.17724, 1.02049, 1.1144,  1.19098, 1.18306, 1.18316, 1.06029, 1.01308, 1.1296,  1.11921,
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+                1.00501, 1.028,   1.04674, 1.0448,  1.04482, 1.01475, 1.0032,  1.00845, 1.00777, 1.00872, 1.00101,
+                1.00563, 1.00939, 1.009,   1.00901, 1.00296, 1.00064, 1.0048,  1.00441, 1.00495, 1.00057, 1.00319,
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+                1.00376, 1.00124, 1.00027, 2.71529, 2.51713, 2.71817, 2.0534,  1.50536, 1.74091, 1.36356, 3.00381,
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+                1.00044, 1.00027, 1.00013, 1.00019, 1.00009, 1.00051, 1.00027, 1.00002, 1.00025, 1.00022, 1.00025,
+                1.00015, 1.00007, 1.00011, 1.00005, 1.00029, 1.00015, 1.00001, 1.0001,  1.00009, 1.0001,  1.00006,
+                1.00003, 1.00004, 1.00002, 1.00012, 1.00006, 1.00001, 1.00002, 1.00002, 1.00002, 1.00001, 1.00001,
+                1.00001, 1,       1.00003, 1.00001, 1,       1.00001, 1.00001, 1.00001, 1,       1,       1,
+                1,       1.00001, 1,       1,       4.69752, 4.91442, 2.76866, 3.64345, 2.31614, 1.4347,  3.78035,
+                1.56984, 6.35268, 6.92523, 1.15424, 1.16329, 1.07378, 1.11027, 1.0549,  1.01813, 1.11598, 1.02377,
+                1.22328, 1.24717, 1.13297, 1.14077, 1.0636,  1.09506, 1.04733, 1.01563, 1.09999, 1.02049, 1.19249,
+                1.21308, 1.10118, 1.10712, 1.0484,  1.07234, 1.03602, 1.0119,  1.07608, 1.01559, 1.14647, 1.16214,
+                1.09964, 1.10548, 1.04766, 1.07123, 1.03547, 1.01171, 1.07492, 1.01536, 1.14424, 1.15967, 1.08482,
+                1.08979, 1.04057, 1.06064, 1.03019, 1.00997, 1.06378, 1.01307, 1.12278, 1.13592, 1.01751, 1.01853,
+                1.00837, 1.01252, 1.00623, 1.00206, 1.01316, 1.0027,  1.02534, 1.02805, 1.01381, 1.01462, 1.00661,
+                1.00988, 1.00492, 1.00162, 1.01039, 1.00213, 1.02,    1.02214, 1.00037, 1.00039, 1.00018, 1.00027,
+                1.00013, 1.00004, 1.00028, 1.00006, 1.00054, 1.0006,  1.00013, 1.00014, 1.00006, 1.00009, 1.00005,
+                1.00002, 1.0001,  1.00002, 1.00019, 1.00021},
+            std::vector<T>{1,       1.00032, 1.0003,  1.00004, 1.00032, 1.00008, 1.00013, 1.00013, 1.00022, 1.0003,
+                           1.00192, 1.00071, 1.00119, 1.00101, 1.00052, 1.00121, 1.00208, 1.00104, 1.00098, 1.00213,
+                           1.00353, 1.00324, 1.00364, 1.00042, 1.00235, 1.00392, 1.00376, 1.00376, 1.00124, 1.00027,
+                           1.00001, 1.00001, 1.00001, 1,       1,       1,       1,       1.00001, 1,       1,
+                           1.00013, 1.00014, 1.00006, 1.00009, 1.00005, 1.00002, 1.0001,  1.00002, 1.00019, 1.00021},
+            "augru_sequence_attentional_gate_provided"),
         AUGRUSequenceParams(
-            3, 4, 5, 6,
+            3,
+            4,
+            5,
+            6,
             ET,
             std::vector<T>{
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-                8.754645f, 1.173500f, 19.354236f, 18.344900f, 16.889204f, 15.882624f,
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-                11.851100f, 4.481464f, 2.963150f, 18.103926f, 1.524719f, 6.200507f,
-                10.349086f, 1.085302f, 9.037059f, 8.240071f, 9.869549f, 13.749188f,
-                6.019619f, 7.583932f, 9.870675f, 5.238130f, 3.383805f, 6.283896f},
-            std::vector<T>{
-                17.012305f, 0.280625f, 4.584126f, 5.899313f, 17.788775f, 19.869320f,
-                17.561679f, 1.209108f, 2.772207f, 15.623852f, 0.212452f, 8.111215f,
-                5.552669f, 10.256264f, 0.026503f},
+                18.351103f, 13.520717f, 11.687705f, 16.378006f, 15.568568f, 2.611258f,  8.754645f,  1.173500f,
+                19.354236f, 18.344900f, 16.889204f, 15.882624f, 5.627136f,  18.532579f, 3.884619f,  5.119867f,
+                19.311458f, 13.728893f, 14.391294f, 14.994748f, 1.131725f,  7.582668f,  14.131282f, 19.547387f,
+                17.038887f, 9.964800f,  0.993434f,  11.316858f, 5.330938f,  17.378582f, 14.467881f, 4.232232f,
+                1.326875f,  5.338556f,  6.427002f,  7.961141f,  11.043235f, 13.890585f, 15.062217f, 11.441225f,
+                14.734964f, 17.898548f, 3.364136f,  12.155336f, 13.873233f, 5.822778f,  14.347963f, 3.387873f,
+                11.021886f, 15.638179f, 15.419064f, 3.743839f,  7.656481f,  9.581622f,  11.851100f, 4.481464f,
+                2.963150f,  18.103926f, 1.524719f,  6.200507f,  10.349086f, 1.085302f,  9.037059f,  8.240071f,
+                9.869549f,  13.749188f, 6.019619f,  7.583932f,  9.870675f,  5.238130f,  3.383805f,  6.283896f},
+            std::vector<T>{17.012305f,
+                           0.280625f,
+                           4.584126f,
+                           5.899313f,
+                           17.788775f,
+                           19.869320f,
+                           17.561679f,
+                           1.209108f,
+                           2.772207f,
+                           15.623852f,
+                           0.212452f,
+                           8.111215f,
+                           5.552669f,
+                           10.256264f,
+                           0.026503f},
             std::vector<int64_t>{6, 6, 6},
-            std::vector<T>{
-                2.599543f, 1.017497f, 2.188785f, 9.186879f, 19.503938f, 9.249134f,
-                1.613915f, 16.139065f, 16.139263f, 6.162586f, 3.584053f, 13.815329f,
-                3.166837f, 9.710348f, 13.262320f, 5.637648f, 7.555024f, 4.282188f,
-                0.890288f, 9.009603f, 6.672247f, 10.287107f, 3.250285f, 17.159962f,
-                12.805244f, 7.266579f, 6.671443f, 4.756829f, 14.331350f, 4.955475f,
-                15.988379f, 1.444935f, 8.917654f, 13.265950f, 14.192596f, 6.813692f,
-                6.118729f, 9.446750f, 6.676908f, 2.862558f, 7.298118f, 14.044843f,
-                4.047191f, 18.313578f, 14.433683f, 10.046828f, 6.272552f, 5.960752f,
-                7.687321f, 17.799588f, 17.974497f, 3.092019f, 17.537077f, 5.673742f,
-                7.945506f, 16.820461f, 3.382466f, 14.536867f, 10.431873f, 17.666089f},
-            std::vector<T>{
-                19.883110f, 3.627721f, 12.381158f, 8.494785f, 0.744855f, 2.083576f,
-                3.628426f, 13.435420f, 8.021385f, 16.324589f, 9.171570f, 5.194103f,
-                9.534415f, 3.747218f, 14.976561f, 15.450245f, 0.690866f, 14.611735f,
-                12.058640f, 12.255162f, 11.922434f, 5.324248f, 16.084200f, 11.910202f,
-                8.972001f, 8.331036f, 5.271550f, 3.376512f, 17.947813f, 11.445078f,
-                19.813407f, 7.357054f, 18.609516f, 1.641881f, 15.659794f, 12.757155f,
-                19.407852f, 15.042537f, 5.609916f, 5.240596f, 16.863105f, 2.939757f,
-                7.419171f, 17.463287f, 15.461648f, 3.089222f, 0.349571f, 17.916363f,
-                17.127918f, 9.218649f, 16.540375f, 19.735329f, 14.503906f, 2.743288f,
-                18.953856f, 7.761779f, 15.795299f, 4.491015f, 16.724311f, 10.091499f,
-                8.233435f, 7.727666f, 17.705235f, 10.873172f, 6.631204f, 4.461747f,
-                0.832513f, 7.237117f, 12.597311f, 13.430508f, 11.884650f, 3.903417f,
-                8.122048f, 14.688200f, 3.733118f},
-            std::vector<T>{
-                14.387985f, 12.398350f, 12.775042f, 11.106416f, 18.022651f, 2.087257f,
-                17.773750f, 15.364595f, 9.153267f, 14.613577f, 11.195361f, 15.070744f,
-                1.611076f, 11.896046f, 10.134009f},
-            std::vector<T>
-                {9.273749f, 12.871767f, 16.940379f, 9.644809f, 8.121616f, 12.174741f,
-                11.509982f, 10.122257f, 4.616639f, 13.560133f, 3.175609f, 5.129174f,
-                2.827964f, 9.646965f, 9.387886f, 1.972116f, 17.192705f, 6.235506f},
-            std::vector<T>{
-                -131.482, 6.95193, -28.6542, -39.5357, -137.906, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1, -197.316,
-                -173.063, -1.19772, -17.6259, -152.696, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1, 2.43961,
-                -11.999, -7.32212, -15.9201, 2.77952, 1, 94.1084, 72.961, 147.308, 1, 1,
-                -779.982, -602.601, -1226.21, 1, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1,},
-            std::vector<T>{
-                1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1},
-                "augru_sequence_different_input_size_and_hidden_size_and_seq_length"),
-AUGRUSequenceParams(
-            3, 4, 4, 4,
+            std::vector<T>{2.599543f,  1.017497f,  2.188785f,  9.186879f,  19.503938f, 9.249134f,  1.613915f,
+                           16.139065f, 16.139263f, 6.162586f,  3.584053f,  13.815329f, 3.166837f,  9.710348f,
+                           13.262320f, 5.637648f,  7.555024f,  4.282188f,  0.890288f,  9.009603f,  6.672247f,
+                           10.287107f, 3.250285f,  17.159962f, 12.805244f, 7.266579f,  6.671443f,  4.756829f,
+                           14.331350f, 4.955475f,  15.988379f, 1.444935f,  8.917654f,  13.265950f, 14.192596f,
+                           6.813692f,  6.118729f,  9.446750f,  6.676908f,  2.862558f,  7.298118f,  14.044843f,
+                           4.047191f,  18.313578f, 14.433683f, 10.046828f, 6.272552f,  5.960752f,  7.687321f,
+                           17.799588f, 17.974497f, 3.092019f,  17.537077f, 5.673742f,  7.945506f,  16.820461f,
+                           3.382466f,  14.536867f, 10.431873f, 17.666089f},
+            std::vector<T>{19.883110f, 3.627721f,  12.381158f, 8.494785f,  0.744855f,  2.083576f,  3.628426f,
+                           13.435420f, 8.021385f,  16.324589f, 9.171570f,  5.194103f,  9.534415f,  3.747218f,
+                           14.976561f, 15.450245f, 0.690866f,  14.611735f, 12.058640f, 12.255162f, 11.922434f,
+                           5.324248f,  16.084200f, 11.910202f, 8.972001f,  8.331036f,  5.271550f,  3.376512f,
+                           17.947813f, 11.445078f, 19.813407f, 7.357054f,  18.609516f, 1.641881f,  15.659794f,
+                           12.757155f, 19.407852f, 15.042537f, 5.609916f,  5.240596f,  16.863105f, 2.939757f,
+                           7.419171f,  17.463287f, 15.461648f, 3.089222f,  0.349571f,  17.916363f, 17.127918f,
+                           9.218649f,  16.540375f, 19.735329f, 14.503906f, 2.743288f,  18.953856f, 7.761779f,
+                           15.795299f, 4.491015f,  16.724311f, 10.091499f, 8.233435f,  7.727666f,  17.705235f,
+                           10.873172f, 6.631204f,  4.461747f,  0.832513f,  7.237117f,  12.597311f, 13.430508f,
+                           11.884650f, 3.903417f,  8.122048f,  14.688200f, 3.733118f},
+            std::vector<T>{14.387985f,
+                           12.398350f,
+                           12.775042f,
+                           11.106416f,
+                           18.022651f,
+                           2.087257f,
+                           17.773750f,
+                           15.364595f,
+                           9.153267f,
+                           14.613577f,
+                           11.195361f,
+                           15.070744f,
+                           1.611076f,
+                           11.896046f,
+                           10.134009f},
+            std::vector<T>{9.273749f,
+                           12.871767f,
+                           16.940379f,
+                           9.644809f,
+                           8.121616f,
+                           12.174741f,
+                           11.509982f,
+                           10.122257f,
+                           4.616639f,
+                           13.560133f,
+                           3.175609f,
+                           5.129174f,
+                           2.827964f,
+                           9.646965f,
+                           9.387886f,
+                           1.972116f,
+                           17.192705f,
+                           6.235506f},
+            std::vector<T>{
+                -131.482, 6.95193,  -28.6542, -39.5357, -137.906, 1, 1,       1,      1,       1,
+                1,        1,        1,        1,        1,        1, 1,       1,      1,       1,
+                1,        1,        1,        1,        1,        1, 1,       1,      1,       1,
+                -197.316, -173.063, -1.19772, -17.6259, -152.696, 1, 1,       1,      1,       1,
+                1,        1,        1,        1,        1,        1, 1,       1,      1,       1,
+                1,        1,        1,        1,        1,        1, 1,       1,      1,       1,
+                2.43961,  -11.999,  -7.32212, -15.9201, 2.77952,  1, 94.1084, 72.961, 147.308, 1,
+                1,        -779.982, -602.601, -1226.21, 1,        1, 1,       1,      1,       1,
+                1,        1,        1,        1,        1,        1, 1,       1,      1,       1,
+            },
+            std::vector<T>{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1},
+            "augru_sequence_different_input_size_and_hidden_size_and_seq_length"),
+        AUGRUSequenceParams(
+            3,
+            4,
+            4,
+            4,
             ET,
-            std::vector<T>{
-                6.333189f, 5.312533f, 3.092159f, 6.788004f, 6.543326f, 6.307378f,
-                7.487966f, 3.300125f, 5.563141f, 5.551623f, 3.812029f, 0.132248f,
-                6.767892f, 7.179934f, 4.832786f, 7.047989f, 7.439896f, 5.970488f,
-                4.878981f, 7.562621f, 7.069236f, 6.484528f, 3.208064f, 5.561788f,
-                3.716249f, 3.412311f, 2.414488f, 7.465214f, 6.444024f, 6.718469f,
-                1.158724f, 0.874442f, 3.319976f, 3.639372f, 5.725887f, 6.594659f,
-                2.427224f, 7.611652f, 4.804684f, 3.739928f, 1.892036f, 2.038615f,
-                1.297785f, 2.687379f, 7.228432f, 3.015881f, 1.658817f, 6.812868f},
-            std::vector<T>{
-                1.905747f, 1.157613f, 7.828747f, 0.730339f, 0.177484f, 6.356011f,
-                7.802150f, 0.351901f, 2.614103f, 5.295752f, 1.925256f, 5.925945f},
+            std::vector<T>{6.333189f, 5.312533f, 3.092159f, 6.788004f, 6.543326f, 6.307378f, 7.487966f, 3.300125f,
+                           5.563141f, 5.551623f, 3.812029f, 0.132248f, 6.767892f, 7.179934f, 4.832786f, 7.047989f,
+                           7.439896f, 5.970488f, 4.878981f, 7.562621f, 7.069236f, 6.484528f, 3.208064f, 5.561788f,
+                           3.716249f, 3.412311f, 2.414488f, 7.465214f, 6.444024f, 6.718469f, 1.158724f, 0.874442f,
+                           3.319976f, 3.639372f, 5.725887f, 6.594659f, 2.427224f, 7.611652f, 4.804684f, 3.739928f,
+                           1.892036f, 2.038615f, 1.297785f, 2.687379f, 7.228432f, 3.015881f, 1.658817f, 6.812868f},
+            std::vector<T>{1.905747f,
+                           1.157613f,
+                           7.828747f,
+                           0.730339f,
+                           0.177484f,
+                           6.356011f,
+                           7.802150f,
+                           0.351901f,
+                           2.614103f,
+                           5.295752f,
+                           1.925256f,
+                           5.925945f},
             std::vector<int64_t>{2, 4, 6},
-            std::vector<T>{
-                4.092708f, 3.566296f, 1.985790f, 6.146150f, 6.427968f, 7.096002f,
-                7.786629f, 1.156184f, 2.091389f, 3.677408f, 0.800674f, 2.707813f,
-                5.396107f, 5.135335f, 3.197786f, 2.983154f, 3.029478f, 1.616802f,
-                2.162019f, 6.922834f, 5.473023f, 4.648859f, 7.976208f, 0.100666f,
-                1.022222f, 6.531802f, 4.358081f, 2.619875f, 2.189079f, 4.086223f,
-                7.818407f, 1.802662f, 7.781939f, 7.542665f, 0.512391f, 6.402292f,
-                6.450581f, 5.147434f, 5.103659f, 0.894397f, 3.192224f, 3.798631f,
-                4.647818f, 3.119819f, 6.469874f, 1.386456f, 2.030223f, 6.888086f},
-            std::vector<T>{
-                5.094750f, 0.455363f, 4.989539f, 0.998320f, 6.369301f, 6.971411f,
-                1.183518f, 1.386444f, 7.572741f, 4.089349f, 0.116142f, 3.784642f,
-                7.925501f, 6.721643f, 3.293674f, 5.754296f, 0.642623f, 2.969238f,
-                3.536983f, 6.635469f, 1.634170f, 0.507635f, 0.205818f, 0.014995f,
-                4.528792f, 7.128315f, 2.403315f, 7.728932f, 4.206394f, 6.285463f,
-                5.314773f, 6.473219f, 2.506818f, 0.430820f, 3.337787f, 3.828441f,
-                2.620897f, 5.545934f, 2.593279f, 3.601373f, 2.595556f, 0.687849f,
-                5.277596f, 4.074282f, 1.844880f, 1.232070f, 4.970289f, 5.472321f},
-            std::vector<T>{
-                5.516398f, 5.621736f, 4.341954f, 6.820305f, 4.760572f, 7.643595f,
-                1.733547f, 3.100034f, 7.009072f, 3.027971f, 5.044797f, 0.534897f},
-            std::vector<T>
-                {5.472119f, 1.116471f, 4.916850f, 1.217513f, 5.672895f, 4.827186f,
-                 2.210116f, 3.160670f, 4.265747f, 3.949529f, 4.224079f, 3.049556f},
-            std::vector<T>{
-                -3.05061, 0.295136, -29.539, 2.20596, 1, 1.0821, 2.32396, -1.30623, 0, 0, 0,
-                0, 0, 0, 0, 0, 4.84353, -24.0281, -30.7857, 4.0285, 1,
-                -1, 122.647, 1, 1, 3.42023, -146.207, 1, 1, 1, 319.066,
-                1, -4.27125, -13.0288, -2.02165, -15.0869, 16.5477, 1, 1, 1, -49.1271,
-                1, 1, 1, 0.999999, -1, -1, 1},
-            std::vector<T>{
-                1, 1.0821, 2.32396, -1.30623, 1, 1, 319.066, 1, 0, 0, 0, 0},
-                "augru_sequence_different_sequence_len_in_each_batch"),
+            std::vector<T>{4.092708f, 3.566296f, 1.985790f, 6.146150f, 6.427968f, 7.096002f, 7.786629f, 1.156184f,
+                           2.091389f, 3.677408f, 0.800674f, 2.707813f, 5.396107f, 5.135335f, 3.197786f, 2.983154f,
+                           3.029478f, 1.616802f, 2.162019f, 6.922834f, 5.473023f, 4.648859f, 7.976208f, 0.100666f,
+                           1.022222f, 6.531802f, 4.358081f, 2.619875f, 2.189079f, 4.086223f, 7.818407f, 1.802662f,
+                           7.781939f, 7.542665f, 0.512391f, 6.402292f, 6.450581f, 5.147434f, 5.103659f, 0.894397f,
+                           3.192224f, 3.798631f, 4.647818f, 3.119819f, 6.469874f, 1.386456f, 2.030223f, 6.888086f},
+            std::vector<T>{5.094750f, 0.455363f, 4.989539f, 0.998320f, 6.369301f, 6.971411f, 1.183518f, 1.386444f,
+                           7.572741f, 4.089349f, 0.116142f, 3.784642f, 7.925501f, 6.721643f, 3.293674f, 5.754296f,
+                           0.642623f, 2.969238f, 3.536983f, 6.635469f, 1.634170f, 0.507635f, 0.205818f, 0.014995f,
+                           4.528792f, 7.128315f, 2.403315f, 7.728932f, 4.206394f, 6.285463f, 5.314773f, 6.473219f,
+                           2.506818f, 0.430820f, 3.337787f, 3.828441f, 2.620897f, 5.545934f, 2.593279f, 3.601373f,
+                           2.595556f, 0.687849f, 5.277596f, 4.074282f, 1.844880f, 1.232070f, 4.970289f, 5.472321f},
+            std::vector<T>{5.516398f,
+                           5.621736f,
+                           4.341954f,
+                           6.820305f,
+                           4.760572f,
+                           7.643595f,
+                           1.733547f,
+                           3.100034f,
+                           7.009072f,
+                           3.027971f,
+                           5.044797f,
+                           0.534897f},
+            std::vector<T>{5.472119f,
+                           1.116471f,
+                           4.916850f,
+                           1.217513f,
+                           5.672895f,
+                           4.827186f,
+                           2.210116f,
+                           3.160670f,
+                           4.265747f,
+                           3.949529f,
+                           4.224079f,
+                           3.049556f},
+            std::vector<T>{-3.05061, 0.295136, -29.539,  2.20596,  1,        1.0821, 2.32396, -1.30623,
+                           0,        0,        0,        0,        0,        0,      0,       0,
+                           4.84353,  -24.0281, -30.7857, 4.0285,   1,        -1,     122.647, 1,
+                           1,        3.42023,  -146.207, 1,        1,        1,      319.066, 1,
+                           -4.27125, -13.0288, -2.02165, -15.0869, 16.5477,  1,      1,       1,
+                           -49.1271, 1,        1,        1,        0.999999, -1,     -1,      1},
+            std::vector<T>{1, 1.0821, 2.32396, -1.30623, 1, 1, 319.066, 1, 0, 0, 0, 0},
+            "augru_sequence_different_sequence_len_in_each_batch"),
     };
     return params;
 }
@@ -635,80 +672,106 @@ AUGRUSequenceParams(
 template <element::Type_t ET>
 std::vector<AUGRUSequenceParams> generateParamsBF16() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<AUGRUSequenceParams> params {
+    std::vector<AUGRUSequenceParams> params{
         AUGRUSequenceParams(
-            3, 4, 5, 6,
+            3,
+            4,
+            5,
+            6,
             ET,
             std::vector<T>{
-                18.351103f, 13.520717f, 11.687705f, 16.378006f, 15.568568f, 2.611258f,
-                8.754645f, 1.173500f, 19.354236f, 18.344900f, 16.889204f, 15.882624f,
-                5.627136f, 18.532579f, 3.884619f, 5.119867f, 19.311458f, 13.728893f,
-                14.391294f, 14.994748f, 1.131725f, 7.582668f, 14.131282f, 19.547387f,
-                17.038887f, 9.964800f, 0.993434f, 11.316858f, 5.330938f, 17.378582f,
-                14.467881f, 4.232232f, 1.326875f, 5.338556f, 6.427002f, 7.961141f,
-                11.043235f, 13.890585f, 15.062217f, 11.441225f, 14.734964f, 17.898548f,
-                3.364136f, 12.155336f, 13.873233f, 5.822778f, 14.347963f, 3.387873f,
-                11.021886f, 15.638179f, 15.419064f, 3.743839f, 7.656481f, 9.581622f,
-                11.851100f, 4.481464f, 2.963150f, 18.103926f, 1.524719f, 6.200507f,
-                10.349086f, 1.085302f, 9.037059f, 8.240071f, 9.869549f, 13.749188f,
-                6.019619f, 7.583932f, 9.870675f, 5.238130f, 3.383805f, 6.283896f},
-            std::vector<T>{
-                17.012305f, 0.280625f, 4.584126f, 5.899313f, 17.788775f, 19.869320f,
-                17.561679f, 1.209108f, 2.772207f, 15.623852f, 0.212452f, 8.111215f,
-                5.552669f, 10.256264f, 0.026503f},
+                18.351103f, 13.520717f, 11.687705f, 16.378006f, 15.568568f, 2.611258f,  8.754645f,  1.173500f,
+                19.354236f, 18.344900f, 16.889204f, 15.882624f, 5.627136f,  18.532579f, 3.884619f,  5.119867f,
+                19.311458f, 13.728893f, 14.391294f, 14.994748f, 1.131725f,  7.582668f,  14.131282f, 19.547387f,
+                17.038887f, 9.964800f,  0.993434f,  11.316858f, 5.330938f,  17.378582f, 14.467881f, 4.232232f,
+                1.326875f,  5.338556f,  6.427002f,  7.961141f,  11.043235f, 13.890585f, 15.062217f, 11.441225f,
+                14.734964f, 17.898548f, 3.364136f,  12.155336f, 13.873233f, 5.822778f,  14.347963f, 3.387873f,
+                11.021886f, 15.638179f, 15.419064f, 3.743839f,  7.656481f,  9.581622f,  11.851100f, 4.481464f,
+                2.963150f,  18.103926f, 1.524719f,  6.200507f,  10.349086f, 1.085302f,  9.037059f,  8.240071f,
+                9.869549f,  13.749188f, 6.019619f,  7.583932f,  9.870675f,  5.238130f,  3.383805f,  6.283896f},
+            std::vector<T>{17.012305f,
+                           0.280625f,
+                           4.584126f,
+                           5.899313f,
+                           17.788775f,
+                           19.869320f,
+                           17.561679f,
+                           1.209108f,
+                           2.772207f,
+                           15.623852f,
+                           0.212452f,
+                           8.111215f,
+                           5.552669f,
+                           10.256264f,
+                           0.026503f},
             std::vector<int64_t>{6, 6, 6},
-            std::vector<T>{
-                2.599543f, 1.017497f, 2.188785f, 9.186879f, 19.503938f, 9.249134f,
-                1.613915f, 16.139065f, 16.139263f, 6.162586f, 3.584053f, 13.815329f,
-                3.166837f, 9.710348f, 13.262320f, 5.637648f, 7.555024f, 4.282188f,
-                0.890288f, 9.009603f, 6.672247f, 10.287107f, 3.250285f, 17.159962f,
-                12.805244f, 7.266579f, 6.671443f, 4.756829f, 14.331350f, 4.955475f,
-                15.988379f, 1.444935f, 8.917654f, 13.265950f, 14.192596f, 6.813692f,
-                6.118729f, 9.446750f, 6.676908f, 2.862558f, 7.298118f, 14.044843f,
-                4.047191f, 18.313578f, 14.433683f, 10.046828f, 6.272552f, 5.960752f,
-                7.687321f, 17.799588f, 17.974497f, 3.092019f, 17.537077f, 5.673742f,
-                7.945506f, 16.820461f, 3.382466f, 14.536867f, 10.431873f, 17.666089f},
-            std::vector<T>{
-                19.883110f, 3.627721f, 12.381158f, 8.494785f, 0.744855f, 2.083576f,
-                3.628426f, 13.435420f, 8.021385f, 16.324589f, 9.171570f, 5.194103f,
-                9.534415f, 3.747218f, 14.976561f, 15.450245f, 0.690866f, 14.611735f,
-                12.058640f, 12.255162f, 11.922434f, 5.324248f, 16.084200f, 11.910202f,
-                8.972001f, 8.331036f, 5.271550f, 3.376512f, 17.947813f, 11.445078f,
-                19.813407f, 7.357054f, 18.609516f, 1.641881f, 15.659794f, 12.757155f,
-                19.407852f, 15.042537f, 5.609916f, 5.240596f, 16.863105f, 2.939757f,
-                7.419171f, 17.463287f, 15.461648f, 3.089222f, 0.349571f, 17.916363f,
-                17.127918f, 9.218649f, 16.540375f, 19.735329f, 14.503906f, 2.743288f,
-                18.953856f, 7.761779f, 15.795299f, 4.491015f, 16.724311f, 10.091499f,
-                8.233435f, 7.727666f, 17.705235f, 10.873172f, 6.631204f, 4.461747f,
-                0.832513f, 7.237117f, 12.597311f, 13.430508f, 11.884650f, 3.903417f,
-                8.122048f, 14.688200f, 3.733118f},
-            std::vector<T>{
-                14.387985f, 12.398350f, 12.775042f, 11.106416f, 18.022651f, 2.087257f,
-                17.773750f, 15.364595f, 9.153267f, 14.613577f, 11.195361f, 15.070744f,
-                1.611076f, 11.896046f, 10.134009f},
-            std::vector<T>
-                {9.273749f, 12.871767f, 16.940379f, 9.644809f, 8.121616f, 12.174741f,
-                11.509982f, 10.122257f, 4.616639f, 13.560133f, 3.175609f, 5.129174f,
-                2.827964f, 9.646965f, 9.387886f, 1.972116f, 17.192705f, 6.235506f},
-            std::vector<T>{
-                -130, 6.9375, -28.25, -39.25, -136, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1, -196,
-                -172, -1.125, -17.5, -152, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1, 2.42188,
-                -11.9375, -7.25, -15.6875, 2.75, 1, 93, 72, 144, 1, 1,
-                -768, -592, -1184, 1, 1, 1, 1, 1, 1, 1,
-                1, 1, 1, 1, 1, 1, 1, 1, 1},
-            std::vector<T>{
-                1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1},
-                "augru_sequence_bfloat16"),
+            std::vector<T>{2.599543f,  1.017497f,  2.188785f,  9.186879f,  19.503938f, 9.249134f,  1.613915f,
+                           16.139065f, 16.139263f, 6.162586f,  3.584053f,  13.815329f, 3.166837f,  9.710348f,
+                           13.262320f, 5.637648f,  7.555024f,  4.282188f,  0.890288f,  9.009603f,  6.672247f,
+                           10.287107f, 3.250285f,  17.159962f, 12.805244f, 7.266579f,  6.671443f,  4.756829f,
+                           14.331350f, 4.955475f,  15.988379f, 1.444935f,  8.917654f,  13.265950f, 14.192596f,
+                           6.813692f,  6.118729f,  9.446750f,  6.676908f,  2.862558f,  7.298118f,  14.044843f,
+                           4.047191f,  18.313578f, 14.433683f, 10.046828f, 6.272552f,  5.960752f,  7.687321f,
+                           17.799588f, 17.974497f, 3.092019f,  17.537077f, 5.673742f,  7.945506f,  16.820461f,
+                           3.382466f,  14.536867f, 10.431873f, 17.666089f},
+            std::vector<T>{19.883110f, 3.627721f,  12.381158f, 8.494785f,  0.744855f,  2.083576f,  3.628426f,
+                           13.435420f, 8.021385f,  16.324589f, 9.171570f,  5.194103f,  9.534415f,  3.747218f,
+                           14.976561f, 15.450245f, 0.690866f,  14.611735f, 12.058640f, 12.255162f, 11.922434f,
+                           5.324248f,  16.084200f, 11.910202f, 8.972001f,  8.331036f,  5.271550f,  3.376512f,
+                           17.947813f, 11.445078f, 19.813407f, 7.357054f,  18.609516f, 1.641881f,  15.659794f,
+                           12.757155f, 19.407852f, 15.042537f, 5.609916f,  5.240596f,  16.863105f, 2.939757f,
+                           7.419171f,  17.463287f, 15.461648f, 3.089222f,  0.349571f,  17.916363f, 17.127918f,
+                           9.218649f,  16.540375f, 19.735329f, 14.503906f, 2.743288f,  18.953856f, 7.761779f,
+                           15.795299f, 4.491015f,  16.724311f, 10.091499f, 8.233435f,  7.727666f,  17.705235f,
+                           10.873172f, 6.631204f,  4.461747f,  0.832513f,  7.237117f,  12.597311f, 13.430508f,
+                           11.884650f, 3.903417f,  8.122048f,  14.688200f, 3.733118f},
+            std::vector<T>{14.387985f,
+                           12.398350f,
+                           12.775042f,
+                           11.106416f,
+                           18.022651f,
+                           2.087257f,
+                           17.773750f,
+                           15.364595f,
+                           9.153267f,
+                           14.613577f,
+                           11.195361f,
+                           15.070744f,
+                           1.611076f,
+                           11.896046f,
+                           10.134009f},
+            std::vector<T>{9.273749f,
+                           12.871767f,
+                           16.940379f,
+                           9.644809f,
+                           8.121616f,
+                           12.174741f,
+                           11.509982f,
+                           10.122257f,
+                           4.616639f,
+                           13.560133f,
+                           3.175609f,
+                           5.129174f,
+                           2.827964f,
+                           9.646965f,
+                           9.387886f,
+                           1.972116f,
+                           17.192705f,
+                           6.235506f},
+            std::vector<T>{-130,    6.9375,   -28.25, -39.25,   -136, 1, 1,  1,  1,   1, 1, 1,    1,    1,     1,
+                           1,       1,        1,      1,        1,    1, 1,  1,  1,   1, 1, 1,    1,    1,     1,
+                           -196,    -172,     -1.125, -17.5,    -152, 1, 1,  1,  1,   1, 1, 1,    1,    1,     1,
+                           1,       1,        1,      1,        1,    1, 1,  1,  1,   1, 1, 1,    1,    1,     1,
+                           2.42188, -11.9375, -7.25,  -15.6875, 2.75, 1, 93, 72, 144, 1, 1, -768, -592, -1184, 1,
+                           1,       1,        1,      1,        1,    1, 1,  1,  1,   1, 1, 1,    1,    1,     1},
+            std::vector<T>{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1},
+            "augru_sequence_bfloat16"),
     };
     return params;
 }
 
 std::vector<AUGRUSequenceParams> generateCombinedParams() {
-    const std::vector<std::vector<AUGRUSequenceParams>> generatedParams {
+    const std::vector<std::vector<AUGRUSequenceParams>> generatedParams{
         generateParams<element::Type_t::f64>(),
         generateParams<element::Type_t::f32>(),
         generateParams<element::Type_t::f16>(),
@@ -722,7 +785,9 @@ std::vector<AUGRUSequenceParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_AUGRUSequence_With_Hardcoded_Refs, ReferenceAUGRUSequenceTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceAUGRUSequenceTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_AUGRUSequence_With_Hardcoded_Refs,
+                         ReferenceAUGRUSequenceTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceAUGRUSequenceTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/avg_pool.cpp b/src/plugins/template/tests/functional/op_reference/avg_pool.cpp
index ba97db25396a97..7bf582184f317f 100644
--- a/src/plugins/template/tests/functional/op_reference/avg_pool.cpp
+++ b/src/plugins/template/tests/functional/op_reference/avg_pool.cpp
@@ -2,10 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/avg_pool.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
-#include "openvino/op/avg_pool.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -15,18 +16,18 @@ namespace {
 struct AvgPoolParams {
     template <class IT>
     AvgPoolParams(const Shape& input_shape,
-              const Shape& output_shape,
-              const element::Type& input_type,
-              const element::Type& ouput_type,
-              const std::vector<IT>& input_values,
-              const std::vector<IT>& output_values,
-              const Strides& strides,
-              const Shape& pads_begin,
-              const Shape& pads_end,
-              const Shape& kernel,
-              const bool exclude_pad,
-              const op::RoundingType& rounding_type,
-              const op::PadType& pad_type)
+                  const Shape& output_shape,
+                  const element::Type& input_type,
+                  const element::Type& ouput_type,
+                  const std::vector<IT>& input_values,
+                  const std::vector<IT>& output_values,
+                  const Strides& strides,
+                  const Shape& pads_begin,
+                  const Shape& pads_end,
+                  const Shape& kernel,
+                  const bool exclude_pad,
+                  const op::RoundingType& rounding_type,
+                  const op::PadType& pad_type)
         : m_input_shape(input_shape),
           m_output_shape(output_shape),
           m_input_type(input_type),
@@ -88,14 +89,14 @@ class ReferenceAvgPoolLayerTest : public testing::TestWithParam<AvgPoolParams>,
 
 private:
     static std::shared_ptr<Model> CreateFunction(const Shape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const Strides& strides,
-                                                    const Shape& pads_begin,
-                                                    const Shape& pads_end,
-                                                    const Shape& kernel,
-                                                    const bool exclude_pad,
-                                                    const op::RoundingType rounding_type,
-                                                    const op::PadType pad_type) {
+                                                 const element::Type& input_type,
+                                                 const Strides& strides,
+                                                 const Shape& pads_begin,
+                                                 const Shape& pads_end,
+                                                 const Shape& kernel,
+                                                 const bool exclude_pad,
+                                                 const op::RoundingType rounding_type,
+                                                 const op::PadType pad_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto avgPool = std::make_shared<op::v1::AvgPool>(in,
                                                                strides,
@@ -113,8 +114,8 @@ TEST_P(ReferenceAvgPoolLayerTest, AvgPoolWithHardcodedRefs) {
     Exec();
 }
 
-template<typename T>
-std::vector<T> getContinuousIncreasingValue(size_t elementSize,  float step) {
+template <typename T>
+std::vector<T> getContinuousIncreasingValue(size_t elementSize, float step) {
     std::vector<T> a(elementSize);
     std::iota(std::begin(a), std::end(a), step);
     return a;
@@ -247,11 +248,9 @@ std::vector<AvgPoolParams> generateParamsForAvgPool() {
 }
 
 std::vector<AvgPoolParams> generateCombinedParamsForAvgPool() {
-    const std::vector<std::vector<AvgPoolParams>> allTypeParams{
-        generateParamsForAvgPool<element::Type_t::f32>(),
-        generateParamsForAvgPool<element::Type_t::f16>(),
-        generateParamsForAvgPool<element::Type_t::bf16>()
-    };
+    const std::vector<std::vector<AvgPoolParams>> allTypeParams{generateParamsForAvgPool<element::Type_t::f32>(),
+                                                                generateParamsForAvgPool<element::Type_t::f16>(),
+                                                                generateParamsForAvgPool<element::Type_t::bf16>()};
 
     std::vector<AvgPoolParams> combinedParams;
 
@@ -262,10 +261,9 @@ std::vector<AvgPoolParams> generateCombinedParamsForAvgPool() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_AvgPool_With_Hardcoded_Refs,
-    ReferenceAvgPoolLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForAvgPool()),
-    ReferenceAvgPoolLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_AvgPool_With_Hardcoded_Refs,
+                         ReferenceAvgPoolLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForAvgPool()),
+                         ReferenceAvgPoolLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/base_reference_test.cpp b/src/plugins/template/tests/functional/op_reference/base_reference_test.cpp
index d454e072f9ff94..d5f5a3a4f19b96 100644
--- a/src/plugins/template/tests/functional/op_reference/base_reference_test.cpp
+++ b/src/plugins/template/tests/functional/op_reference/base_reference_test.cpp
@@ -2,21 +2,21 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 #include "base_reference_test.hpp"
-#include "functional_test_utils/ov_plugin_cache.hpp"
-#include "shared_test_classes/base/layer_test_utils.hpp"
 
 #include <gtest/gtest.h>
 
+#include "functional_test_utils/ov_plugin_cache.hpp"
 #include "openvino/core/type/element_type.hpp"
 #include "openvino/runtime/allocator.hpp"
 #include "openvino/runtime/tensor.hpp"
+#include "shared_test_classes/base/layer_test_utils.hpp"
 #include "transformations/utils/utils.hpp"
 
 using namespace ov;
 
 namespace reference_tests {
 
-CommonReferenceTest::CommonReferenceTest(): targetDevice("TEMPLATE") {
+CommonReferenceTest::CommonReferenceTest() : targetDevice("TEMPLATE") {
     core = test::utils::PluginCache::get().core(targetDevice);
 }
 
@@ -75,8 +75,12 @@ void CommonReferenceTest::Validate() {
     }
 }
 
-void CommonReferenceTest::ValidateBlobs(const ov::Tensor& refBlob, const ov::Tensor& outBlob, const size_t blob_idx,
-                                        float threshold, float abs_threshold, size_t actual_comparision_size) {
+void CommonReferenceTest::ValidateBlobs(const ov::Tensor& refBlob,
+                                        const ov::Tensor& outBlob,
+                                        const size_t blob_idx,
+                                        float threshold,
+                                        float abs_threshold,
+                                        size_t actual_comparision_size) {
     ASSERT_EQ(refBlob.get_element_type(), outBlob.get_element_type())
         << "Incompatible element type for blob with index " << blob_idx;
     ASSERT_EQ(refBlob.get_byte_size(), outBlob.get_byte_size())
@@ -88,80 +92,110 @@ void CommonReferenceTest::ValidateBlobs(const ov::Tensor& refBlob, const ov::Ten
     const auto& element_type = refBlob.get_element_type();
     switch (element_type) {
     case ov::element::bf16:
-        LayerTestsUtils::LayerTestsCommon::Compare<ov::bfloat16, ov::bfloat16>(
-            refBlob.data<const ov::bfloat16>(), outBlob.data<const ov::bfloat16>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<ov::bfloat16, ov::bfloat16>(refBlob.data<const ov::bfloat16>(),
+                                                                               outBlob.data<const ov::bfloat16>(),
+                                                                               actual_comparision_size,
+                                                                               threshold,
+                                                                               abs_threshold);
         break;
     case ov::element::f16:
-        LayerTestsUtils::LayerTestsCommon::Compare<ov::float16, ov::float16>(
-            refBlob.data<const ov::float16>(), outBlob.data<const ov::float16>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<ov::float16, ov::float16>(refBlob.data<const ov::float16>(),
+                                                                             outBlob.data<const ov::float16>(),
+                                                                             actual_comparision_size,
+                                                                             threshold,
+                                                                             abs_threshold);
         break;
     case ov::element::f32:
-        LayerTestsUtils::LayerTestsCommon::Compare<float, float>(
-            refBlob.data<const float>(), outBlob.data<const float>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<float, float>(refBlob.data<const float>(),
+                                                                 outBlob.data<const float>(),
+                                                                 actual_comparision_size,
+                                                                 threshold,
+                                                                 abs_threshold);
         break;
     case ov::element::f64:
-        LayerTestsUtils::LayerTestsCommon::Compare<double, double>(
-            refBlob.data<const double>(), outBlob.data<const double>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<double, double>(refBlob.data<const double>(),
+                                                                   outBlob.data<const double>(),
+                                                                   actual_comparision_size,
+                                                                   threshold,
+                                                                   abs_threshold);
         break;
     case ov::element::i8:
-        LayerTestsUtils::LayerTestsCommon::Compare<int8_t, int8_t>(
-            refBlob.data<const int8_t>(), outBlob.data<const int8_t>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<int8_t, int8_t>(refBlob.data<const int8_t>(),
+                                                                   outBlob.data<const int8_t>(),
+                                                                   actual_comparision_size,
+                                                                   threshold,
+                                                                   abs_threshold);
         break;
     case ov::element::i16:
-        LayerTestsUtils::LayerTestsCommon::Compare<int16_t, int16_t>(
-            refBlob.data<const int16_t>(), outBlob.data<const int16_t>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<int16_t, int16_t>(refBlob.data<const int16_t>(),
+                                                                     outBlob.data<const int16_t>(),
+                                                                     actual_comparision_size,
+                                                                     threshold,
+                                                                     abs_threshold);
         break;
     case ov::element::i32:
-        LayerTestsUtils::LayerTestsCommon::Compare<int32_t, int32_t>(
-            refBlob.data<const int32_t>(), outBlob.data<const int32_t>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<int32_t, int32_t>(refBlob.data<const int32_t>(),
+                                                                     outBlob.data<const int32_t>(),
+                                                                     actual_comparision_size,
+                                                                     threshold,
+                                                                     abs_threshold);
         break;
     case ov::element::i64:
-        LayerTestsUtils::LayerTestsCommon::Compare<int64_t, int64_t>(
-            refBlob.data<const int64_t>(), outBlob.data<const int64_t>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<int64_t, int64_t>(refBlob.data<const int64_t>(),
+                                                                     outBlob.data<const int64_t>(),
+                                                                     actual_comparision_size,
+                                                                     threshold,
+                                                                     abs_threshold);
         break;
     case ov::element::boolean:
-        LayerTestsUtils::LayerTestsCommon::Compare<bool, bool>(
-            refBlob.data<const bool>(), outBlob.data<const bool>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<bool, bool>(refBlob.data<const bool>(),
+                                                               outBlob.data<const bool>(),
+                                                               actual_comparision_size,
+                                                               threshold,
+                                                               abs_threshold);
         break;
     case ov::element::u8:
-        LayerTestsUtils::LayerTestsCommon::Compare<uint8_t, uint8_t>(
-            refBlob.data<const uint8_t>(), outBlob.data<const uint8_t>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<uint8_t, uint8_t>(refBlob.data<const uint8_t>(),
+                                                                     outBlob.data<const uint8_t>(),
+                                                                     actual_comparision_size,
+                                                                     threshold,
+                                                                     abs_threshold);
         break;
     case ov::element::u16:
-        LayerTestsUtils::LayerTestsCommon::Compare<uint16_t, uint16_t>(
-            refBlob.data<const uint16_t>(), outBlob.data<const uint16_t>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<uint16_t, uint16_t>(refBlob.data<const uint16_t>(),
+                                                                       outBlob.data<const uint16_t>(),
+                                                                       actual_comparision_size,
+                                                                       threshold,
+                                                                       abs_threshold);
         break;
     case ov::element::u32:
-        LayerTestsUtils::LayerTestsCommon::Compare<uint32_t, uint32_t>(
-            refBlob.data<const uint32_t>(), outBlob.data<const uint32_t>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<uint32_t, uint32_t>(refBlob.data<const uint32_t>(),
+                                                                       outBlob.data<const uint32_t>(),
+                                                                       actual_comparision_size,
+                                                                       threshold,
+                                                                       abs_threshold);
         break;
     case ov::element::u64:
-        LayerTestsUtils::LayerTestsCommon::Compare<uint64_t, uint64_t>(
-            refBlob.data<const uint64_t>(), outBlob.data<const uint64_t>(),
-            actual_comparision_size, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<uint64_t, uint64_t>(refBlob.data<const uint64_t>(),
+                                                                       outBlob.data<const uint64_t>(),
+                                                                       actual_comparision_size,
+                                                                       threshold,
+                                                                       abs_threshold);
         break;
     case ov::element::i4:
     case ov::element::u4:
-        LayerTestsUtils::LayerTestsCommon::Compare<int8_t, int8_t>(
-            static_cast<const int8_t*>(refBlob.data()), static_cast<const int8_t*>(outBlob.data()),
-            actual_comparision_size / 2, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<int8_t, int8_t>(static_cast<const int8_t*>(refBlob.data()),
+                                                                   static_cast<const int8_t*>(outBlob.data()),
+                                                                   actual_comparision_size / 2,
+                                                                   threshold,
+                                                                   abs_threshold);
         break;
     case ov::element::u1:
-        LayerTestsUtils::LayerTestsCommon::Compare<int8_t, int8_t>(
-            static_cast<const int8_t*>(refBlob.data()), static_cast<const int8_t*>(outBlob.data()),
-            actual_comparision_size / 8, threshold, abs_threshold);
+        LayerTestsUtils::LayerTestsCommon::Compare<int8_t, int8_t>(static_cast<const int8_t*>(refBlob.data()),
+                                                                   static_cast<const int8_t*>(outBlob.data()),
+                                                                   actual_comparision_size / 8,
+                                                                   threshold,
+                                                                   abs_threshold);
         break;
     default:
         FAIL() << "Comparator for " << element_type << " element type isn't supported";
diff --git a/src/plugins/template/tests/functional/op_reference/base_reference_test.hpp b/src/plugins/template/tests/functional/op_reference/base_reference_test.hpp
index 75fea35cb4edc6..2add89bdbdaf78 100644
--- a/src/plugins/template/tests/functional/op_reference/base_reference_test.hpp
+++ b/src/plugins/template/tests/functional/op_reference/base_reference_test.hpp
@@ -55,9 +55,7 @@ ov::Tensor CreateTensor(const ov::element::Type& element_type, const std::vector
 
 // Create blob with correct input shape (not 1-dimensional). Will be used in tests with dynamic input shapes
 template <class T>
-ov::Tensor CreateTensor(const ov::Shape& shape,
-                                 const ov::element::Type& element_type,
-                                 const std::vector<T>& values) {
+ov::Tensor CreateTensor(const ov::Shape& shape, const ov::element::Type& element_type, const std::vector<T>& values) {
     ov::Tensor tensor{element_type, shape};
     size_t size = sizeof(T) * values.size();
     if (tensor.get_byte_size() < size)
diff --git a/src/plugins/template/tests/functional/op_reference/batch_norm.cpp b/src/plugins/template/tests/functional/op_reference/batch_norm.cpp
index 8e6d2873d5ed74..e5ac24c8df78b9 100644
--- a/src/plugins/template/tests/functional/op_reference/batch_norm.cpp
+++ b/src/plugins/template/tests/functional/op_reference/batch_norm.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/batch_norm.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/batch_norm.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -78,8 +79,8 @@ class ReferenceBatchNormV0LayerTest : public testing::TestWithParam<BatchNormPar
 
 private:
     static std::shared_ptr<Model> CreateFunction(const Shape& input_shape,
-                                                    const element::Type_t& input_type,
-                                                    const float epsilon) {
+                                                 const element::Type_t& input_type,
+                                                 const float epsilon) {
         Shape channel_shape{input_shape.at(1)};
         auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         auto gamma = std::make_shared<op::v0::Parameter>(input_type, channel_shape);
@@ -103,8 +104,8 @@ class ReferenceBatchNormV5LayerTest : public ReferenceBatchNormV0LayerTest {
 
 private:
     static std::shared_ptr<Model> CreateFunction(const Shape& input_shape,
-                                                    const element::Type_t& input_type,
-                                                    const float epsilon) {
+                                                 const element::Type_t& input_type,
+                                                 const float epsilon) {
         Shape channel_shape{input_shape.at(1)};
         auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         auto gamma = std::make_shared<op::v0::Parameter>(input_type, channel_shape);
@@ -130,7 +131,7 @@ std::vector<BatchNormParams> generateParamsForBatchNorm() {
     using T = typename element_type_traits<ET>::value_type;
 
     std::vector<BatchNormParams> params{
-     /*------------- 2d --------------*/
+        /*------------- 2d --------------*/
         BatchNormParams(Shape{2, 3},
                         Shape{2, 3},
                         ET,
@@ -175,7 +176,7 @@ std::vector<BatchNormParams> generateParamsForBatchNorm() {
                         std::vector<T>{0.0, 0.0, 0.0},
                         std::vector<T>{2.0, 6.0, 0.0},
                         0.25),
-     /*------------- 4d --------------*/
+        /*------------- 4d --------------*/
         BatchNormParams(Shape{2, 2, 2, 1},
                         Shape{2, 2, 2, 1},
                         ET,
@@ -201,41 +202,33 @@ std::vector<BatchNormParams> generateParamsForBatchNorm() {
                         std::vector<T>{1.0, 1.0},
                         std::vector<T>{1.0, 1.0},
                         0.001),
-        BatchNormParams(Shape{2, 2, 2, 1},
-                        Shape{2, 2, 2, 1},
-                        ET,
-                        ET,
-                        std::vector<T>{0.54881352f,
-                                       0.71518934f,
-                                       0.60276335f,
-                                       0.54488319f,
-                                       0.42365479f,
-                                       0.64589411f,
-                                       0.4375872f,
-                                       0.89177299f},
-                        std::vector<T>{-0.30327f,
-                                       1.1561f,
-                                       -0.096382f,
-                                       -0.434702f,
-                                       -1.4011f,
-                                       0.548275f,
-                                       -1.06187f,
-                                       1.59295f},
-                        std::vector<T>{1.0, 1.0},
-                        std::vector<T>{0.0f, 0.0f},
-                        std::vector<T>{0.583388f, 0.619252f},
-                        std::vector<T>{0.0119972f, 0.0282681f},
-                        0.001),
+        BatchNormParams(
+            Shape{2, 2, 2, 1},
+            Shape{2, 2, 2, 1},
+            ET,
+            ET,
+            std::vector<T>{0.54881352f,
+                           0.71518934f,
+                           0.60276335f,
+                           0.54488319f,
+                           0.42365479f,
+                           0.64589411f,
+                           0.4375872f,
+                           0.89177299f},
+            std::vector<T>{-0.30327f, 1.1561f, -0.096382f, -0.434702f, -1.4011f, 0.548275f, -1.06187f, 1.59295f},
+            std::vector<T>{1.0, 1.0},
+            std::vector<T>{0.0f, 0.0f},
+            std::vector<T>{0.583388f, 0.619252f},
+            std::vector<T>{0.0119972f, 0.0282681f},
+            0.001),
     };
 
     return params;
 }
 
 std::vector<BatchNormParams> generateCombinedParamsForBatchNorm() {
-    const std::vector<std::vector<BatchNormParams>> allTypeParams{
-        generateParamsForBatchNorm<element::Type_t::f32>(),
-        generateParamsForBatchNorm<element::Type_t::f16>()
-    };
+    const std::vector<std::vector<BatchNormParams>> allTypeParams{generateParamsForBatchNorm<element::Type_t::f32>(),
+                                                                  generateParamsForBatchNorm<element::Type_t::f16>()};
 
     std::vector<BatchNormParams> combinedParams;
 
@@ -246,16 +239,14 @@ std::vector<BatchNormParams> generateCombinedParamsForBatchNorm() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_BatchNorm_With_Hardcoded_Refs,
-    ReferenceBatchNormV0LayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForBatchNorm()),
-    ReferenceBatchNormV0LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BatchNorm_With_Hardcoded_Refs,
+                         ReferenceBatchNormV0LayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForBatchNorm()),
+                         ReferenceBatchNormV0LayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_BatchNorm_With_Hardcoded_Refs,
-    ReferenceBatchNormV5LayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForBatchNorm()),
-    ReferenceBatchNormV5LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BatchNorm_With_Hardcoded_Refs,
+                         ReferenceBatchNormV5LayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForBatchNorm()),
+                         ReferenceBatchNormV5LayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/batch_to_space.cpp b/src/plugins/template/tests/functional/op_reference/batch_to_space.cpp
index 7c8da263b078fd..10583280efd619 100644
--- a/src/plugins/template/tests/functional/op_reference/batch_to_space.cpp
+++ b/src/plugins/template/tests/functional/op_reference/batch_to_space.cpp
@@ -4,21 +4,27 @@
 
 #include <gtest/gtest.h>
 
+#include "base_reference_test.hpp"
 #include "openvino/opsets/opset1.hpp"
 #include "openvino/opsets/opset2.hpp"
-#include "base_reference_test.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct BatchToSpaceParams {
-    BatchToSpaceParams(const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& blockShapeTensor,
-                       const reference_tests::Tensor& cropsBeginTensor, const reference_tests::Tensor& cropsEndTensor,
-                       const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-                  dataTensor(dataTensor), blockShapeTensor(blockShapeTensor),
-                  cropsBeginTensor(cropsBeginTensor), cropsEndTensor(cropsEndTensor),
-                  expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    BatchToSpaceParams(const reference_tests::Tensor& dataTensor,
+                       const reference_tests::Tensor& blockShapeTensor,
+                       const reference_tests::Tensor& cropsBeginTensor,
+                       const reference_tests::Tensor& cropsEndTensor,
+                       const reference_tests::Tensor& expectedTensor,
+                       const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          blockShapeTensor(blockShapeTensor),
+          cropsBeginTensor(cropsBeginTensor),
+          cropsEndTensor(cropsEndTensor),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor blockShapeTensor;
@@ -80,7 +86,7 @@ TEST_P(ReferenceBatchToSpaceLayerTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<BatchToSpaceParams> generateBatchToSpaceParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<BatchToSpaceParams> batchToSpaceParams {
+    std::vector<BatchToSpaceParams> batchToSpaceParams{
         // input_with_shape_4x3
         BatchToSpaceParams(
             reference_tests::Tensor({4, 3}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
@@ -126,89 +132,78 @@ std::vector<BatchToSpaceParams> generateBatchToSpaceParams() {
 
         // input_with_shape_4x1x2x3
         BatchToSpaceParams(
-            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,
-                                                       7,  8,  9,  10, 11, 12,
-                                                       13, 14, 15, 16, 17, 18,
-                                                       19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 1, 2}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
-            reference_tests::Tensor({2, 1, 2, 6}, IN_ET, std::vector<T>{1, 13, 2, 14, 3, 15,
-                                                       4, 16, 5, 17, 6, 18,
-                                                       7, 19, 8, 20, 9, 21,
-                                                       10, 22, 11, 23, 12, 24}),
+            reference_tests::Tensor({2, 1, 2, 6}, IN_ET, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
+                                                                        7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
             "input_with_shape_4x1x2x3"),
         // input_with_shape_4x1x2x3_1
         BatchToSpaceParams(
-            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,
-                                                       7,  8,  9,  10, 11, 12,
-                                                       13, 14, 15, 16, 17, 18,
-                                                       19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 2, 1}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
-            reference_tests::Tensor({2, 1, 4, 3}, IN_ET, std::vector<T>{1,  2,  3,  13, 14, 15,
-                                                       4,  5,  6,  16, 17, 18,
-                                                       7,  8,  9,  19, 20, 21,
-                                                       10, 11, 12, 22, 23, 24}),
+            reference_tests::Tensor({2, 1, 4, 3}, IN_ET, std::vector<T>{1, 2, 3, 13, 14, 15, 4,  5,  6,  16, 17, 18,
+                                                                        7, 8, 9, 19, 20, 21, 10, 11, 12, 22, 23, 24}),
             "input_with_shape_4x1x2x3_1"),
         // input_with_shape_4x1x2x3_2
         BatchToSpaceParams(
-            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,
-                                                       7,  8,  9,  10, 11, 12,
-                                                       13, 14, 15, 16, 17, 18,
-                                                       19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 2, 2}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
-            reference_tests::Tensor({1, 1, 4, 6}, IN_ET, std::vector<T>{1,  7,  2,  8,  3,  9,
-                                                       13, 19, 14, 20, 15, 21,
-                                                       4,  10, 5,  11, 6,  12,
-                                                       16, 22, 17, 23, 18, 24}),
+            reference_tests::Tensor({1, 1, 4, 6}, IN_ET, std::vector<T>{1, 7,  2, 8,  3, 9,  13, 19, 14, 20, 15, 21,
+                                                                        4, 10, 5, 11, 6, 12, 16, 22, 17, 23, 18, 24}),
             "input_with_shape_4x1x2x3_2"),
 
         // input_with_shape_with_crop_4x1x2x3
         BatchToSpaceParams(
-            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,
-                                                       7,  8,  9,  10, 11, 12,
-                                                       13, 14, 15, 16, 17, 18,
-                                                       19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 2, 2}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 2}),
-            reference_tests::Tensor({1, 1, 4, 4}, IN_ET, std::vector<T>{1, 7,  2, 8,  13, 19, 14, 20,
-                                                       4, 10, 5, 11, 16, 22, 17, 23}),
+            reference_tests::Tensor({1, 1, 4, 4},
+                                    IN_ET,
+                                    std::vector<T>{1, 7, 2, 8, 13, 19, 14, 20, 4, 10, 5, 11, 16, 22, 17, 23}),
             "input_with_shape_with_crop_4x1x2x3"),
         // input_with_shape_with_crop_4x1x2x3_1
         BatchToSpaceParams(
-            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,
-                                                       7,  8,  9,  10, 11, 12,
-                                                       13, 14, 15, 16, 17, 18,
-                                                       19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 2, 2}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 2}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
-            reference_tests::Tensor({1, 1, 4, 4}, IN_ET, std::vector<T>{2, 8,  3, 9,  14, 20, 15, 21,
-                                                       5, 11, 6, 12, 17, 23, 18, 24}),
+            reference_tests::Tensor({1, 1, 4, 4},
+                                    IN_ET,
+                                    std::vector<T>{2, 8, 3, 9, 14, 20, 15, 21, 5, 11, 6, 12, 17, 23, 18, 24}),
             "input_with_shape_with_crop_4x1x2x3_1"),
         // input_with_shape_with_crop_4x1x2x3_2
         BatchToSpaceParams(
-            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,
-                                                       7,  8,  9,  10, 11, 12,
-                                                       13, 14, 15, 16, 17, 18,
-                                                       19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor({4, 1, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 2, 2}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 1, 0}),
             reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 1, 0}),
-            reference_tests::Tensor({1, 1, 2, 6}, IN_ET, std::vector<T>{13, 19, 14, 20, 15, 21,
-                                                       4,  10, 5,  11, 6,  12}),
+            reference_tests::Tensor({1, 1, 2, 6}, IN_ET, std::vector<T>{13, 19, 14, 20, 15, 21, 4, 10, 5, 11, 6, 12}),
             "input_with_shape_with_crop_4x1x2x3_2"),
     };
     return batchToSpaceParams;
 }
 
 std::vector<BatchToSpaceParams> generateBatchToSpaceCombinedParams() {
-    const std::vector<std::vector<BatchToSpaceParams>> batchToSpaceTypeParams {
+    const std::vector<std::vector<BatchToSpaceParams>> batchToSpaceTypeParams{
         generateBatchToSpaceParams<element::Type_t::i8>(),
         generateBatchToSpaceParams<element::Type_t::i16>(),
         generateBatchToSpaceParams<element::Type_t::i32>(),
@@ -230,6 +225,8 @@ std::vector<BatchToSpaceParams> generateBatchToSpaceCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_BatchToSpace_With_Hardcoded_Refs, ReferenceBatchToSpaceLayerTest,
-    testing::ValuesIn(generateBatchToSpaceCombinedParams()), ReferenceBatchToSpaceLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_BatchToSpace_With_Hardcoded_Refs,
+                         ReferenceBatchToSpaceLayerTest,
+                         testing::ValuesIn(generateBatchToSpaceCombinedParams()),
+                         ReferenceBatchToSpaceLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/binary_convolution.cpp b/src/plugins/template/tests/functional/op_reference/binary_convolution.cpp
index 0516be4126708c..1917163d832f4e 100644
--- a/src/plugins/template/tests/functional/op_reference/binary_convolution.cpp
+++ b/src/plugins/template/tests/functional/op_reference/binary_convolution.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/binary_convolution.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/binary_convolution.hpp"
 #include "base_reference_test.hpp"
 #include "openvino/opsets/opset8.hpp"
 
@@ -53,12 +54,14 @@ struct BinaryConvolutionParams {
     ov::CoordinateDiff padBegin;
     ov::CoordinateDiff padEnd;
     ov::Strides dialations;
-    ov::op::v1::BinaryConvolution::BinaryConvolutionMode mode = ov::op::v1::BinaryConvolution::BinaryConvolutionMode::XNOR_POPCOUNT;
+    ov::op::v1::BinaryConvolution::BinaryConvolutionMode mode =
+        ov::op::v1::BinaryConvolution::BinaryConvolutionMode::XNOR_POPCOUNT;
     float padValue;
     std::string testcaseName;
 };
 
-class ReferenceBinaryConvolutionLayerTest : public testing::TestWithParam<BinaryConvolutionParams>, public CommonReferenceTest {
+class ReferenceBinaryConvolutionLayerTest : public testing::TestWithParam<BinaryConvolutionParams>,
+                                            public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -88,20 +91,21 @@ class ReferenceBinaryConvolutionLayerTest : public testing::TestWithParam<Binary
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const BinaryConvolutionParams& params, const std::vector<uint8_t>& filterData) {
+    static std::shared_ptr<Model> CreateFunction(const BinaryConvolutionParams& params,
+                                                 const std::vector<uint8_t>& filterData) {
         const op::PadType auto_pad{op::PadType::EXPLICIT};
         const auto in = std::make_shared<op::v0::Parameter>(params.inType, params.inputShape);
         auto filter = std::make_shared<opset8::Constant>(ov::element::u1, params.filterShape, &filterData[0]);
         const auto BinaryConvolution = std::make_shared<op::v1::BinaryConvolution>(in,
-                                                                       filter,
-                                                                       params.strides,
-                                                                       params.padBegin,
-                                                                       params.padEnd,
-                                                                       params.dialations,
-                                                                       params.mode,
-                                                                       params.padValue,
-                                                                       auto_pad);
-        return std::make_shared<ov::Model>(NodeVector {BinaryConvolution}, ParameterVector {in});
+                                                                                   filter,
+                                                                                   params.strides,
+                                                                                   params.padBegin,
+                                                                                   params.padEnd,
+                                                                                   params.dialations,
+                                                                                   params.mode,
+                                                                                   params.padValue,
+                                                                                   auto_pad);
+        return std::make_shared<ov::Model>(NodeVector{BinaryConvolution}, ParameterVector{in});
     }
 };
 
@@ -113,194 +117,200 @@ template <element::Type_t IN_ET>
 std::vector<BinaryConvolutionParams> generateBinaryConvolutionParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<BinaryConvolutionParams> binaryConvolutionParams {
-// --------------------- 2D BinaryConvolution ------------------------------------------
-        BinaryConvolutionParams(PartialShape {1, 1, 4, 4},
-                                Shape {1, 1, 3, 3},
-                                PartialShape {1, 1, 2, 2},
+    std::vector<BinaryConvolutionParams> binaryConvolutionParams{
+        // --------------------- 2D BinaryConvolution ------------------------------------------
+        BinaryConvolutionParams(PartialShape{1, 1, 4, 4},
+                                Shape{1, 1, 3, 3},
+                                PartialShape{1, 1, 2, 2},
                                 IN_ET,
-                                std::vector<T>{1, 0, 0, 1,
-                                               1, 1, 0, 0,
-                                               0, 0, 0, 1,
-                                               1, 0, 1, 1},
-                                std::vector<uint8_t>{0xAA, 0x80}, // 10101010 10000000
-                                std::vector<T>{1, 1,
-                                               3, -1},
+                                std::vector<T>{1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1},
+                                std::vector<uint8_t>{0xAA, 0x80},  // 10101010 10000000
+                                std::vector<T>{1, 1, 3, -1},
                                 {1, 1},
                                 {0, 0},
                                 {0, 0},
                                 {1, 1}),
-        BinaryConvolutionParams(PartialShape {1, 1, 4, 4},
-                                Shape {1, 1, 3, 3},
-                                PartialShape {1, 1, 4, 4},
+        BinaryConvolutionParams(PartialShape{1, 1, 4, 4},
+                                Shape{1, 1, 3, 3},
+                                PartialShape{1, 1, 4, 4},
                                 IN_ET,
-                                std::vector<T>{1, 0, 0, 1,
-                                               1, 1, 0, 0,
-                                               0, 0, 0, 1,
-                                               1, 0, 1, 1},
-                                std::vector<uint8_t>{0xAA, 0x80}, // 10101010 10000000
-                                std::vector<T>{1, -3, -1, 1,
-                                               -3, 1, 1, -5,
-                                               -3, 3, -1, 1,
-                                               1, -5, 1, -3},
+                                std::vector<T>{1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1},
+                                std::vector<uint8_t>{0xAA, 0x80},  // 10101010 10000000
+                                std::vector<T>{1, -3, -1, 1, -3, 1, 1, -5, -3, 3, -1, 1, 1, -5, 1, -3},
                                 {1, 1},
                                 {1, 1},
                                 {1, 1},
                                 {1, 1}),
-        BinaryConvolutionParams(PartialShape {1, 1, 4, 4},
-                                Shape {1, 1, 3, 3},
-                                PartialShape {1, 1, 4, 4},
+        BinaryConvolutionParams(PartialShape{1, 1, 4, 4},
+                                Shape{1, 1, 3, 3},
+                                PartialShape{1, 1, 4, 4},
                                 IN_ET,
-                                std::vector<T>{1, 0, 0, 1,
-                                               1, 1, 0, 0,
-                                               0, 0, 0, 1,
-                                               1, 0, 1, 1},
-                                std::vector<uint8_t>{0xAA, 0x80}, // 10101010 10000000
-                                std::vector<T>{3, -1, 1, 3,
-                                               -1, 1, 1, -3,
-                                               -1, 3, -1, 3,
-                                               3, -3, 3, -1},
-                                {1, 1},
+                                std::vector<T>{1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1},
+                                std::vector<uint8_t>{0xAA, 0x80},  // 10101010 10000000
+                                std::vector<T>{3, -1, 1, 3, -1, 1, 1, -3, -1, 3, -1, 3, 3, -3, 3, -1},
                                 {1, 1},
                                 {1, 1},
                                 {1, 1},
-                                1.0f),
-        BinaryConvolutionParams(PartialShape {1, 1, 5, 5},
-                                Shape {1, 1, 3, 3},
-                                PartialShape {1, 1, 2, 2},
-                                IN_ET,
-                                std::vector<T>{0, 1, 1, 0, 1,
-                                               1, 1, 0, 1, 0,
-                                               0, 0, 1, 0, 1,
-                                               1, 1, 0, 1, 0,
-                                               0, 0, 1, 1, 1},
-                                std::vector<uint8_t>{0x2E, 0x00}, // 10101010 10000000
-                                std::vector<T>{-1, 3,
-                                               1, 1},
-                                {2, 2},
-                                {0, 0},
-                                {0, 0},
-                                {1, 1}),
-        BinaryConvolutionParams(PartialShape {1, 1, 7, 7},
-                                Shape {1, 1, 3, 3},
-                                PartialShape {1, 1, 3, 3},
-                                IN_ET,
-                                std::vector<T>{1, 1, 0, 0, 0, 1, 0,
-                                               0, 0, 1, 0, 1, 0, 0,
-                                               1, 1, 1, 1, 0, 1, 1,
-                                               0, 0, 0, 1, 1, 1, 0,
-                                               0, 1, 0, 0, 1, 1, 1,
-                                               1, 0, 1, 1, 0, 0, 0,
-                                               1, 1, 1, 0, 1, 0, 0},
-                                std::vector<uint8_t>{0x6B, 0x00}, // 10101010 10000000
-                                std::vector<T>{-5, -3, -5,
-                                               5, 1, 3,
-                                               -1, -1, 3},
                                 {1, 1},
-                                {0, 0},
-                                {0, 0},
-                                {2, 2}),
-        BinaryConvolutionParams(PartialShape {1, 1, 7, 7},
-                                Shape {1, 1, 3, 3},
-                                PartialShape {1, 1, 4, 4},
-                                IN_ET,
-                                std::vector<T>{1, 1, 0, 0, 0, 1, 0,
-                                              0, 0, 1, 0, 1, 0, 0,
-                                              1, 1, 1, 1, 0, 1, 1,
-                                              0, 0, 0, 1, 1, 1, 0,
-                                              0, 1, 0, 0, 1, 1, 1,
-                                              1, 0, 1, 1, 0, 0, 0,
-                                              1, 1, 1, 0, 1, 0, 0},
-                                std::vector<uint8_t>{0x6B, 0x00}, // 10101010 10000000
-                                std::vector<T>{1, 1, -1, 1,
-                                               1, -5, -5, 5,
-                                               3, -1, 3, 3,
-                                               -1, -1, 3, -3},
-                                {2, 2},
-                                {2, 2},
-                                {2, 2},
-                                {2, 2}),
-        BinaryConvolutionParams(PartialShape {1, 1, 7, 7},
-                                Shape {1, 1, 3, 3},
-                                PartialShape {1, 1, 4, 4},
-                                IN_ET,
-                                std::vector<T>{1, 1, 0, 0, 0, 1, 0,
-                                               0, 0, 1, 0, 1, 0, 0,
-                                               1, 1, 1, 1, 0, 1, 1,
-                                               0, 0, 0, 1, 1, 1, 0,
-                                               0, 1, 0, 0, 1, 1, 1,
-                                               1, 0, 1, 1, 0, 0, 0,
-                                               1, 1, 1, 0, 1, 0, 0},
-                                std::vector<uint8_t>{0x6B, 0x00}, // 10101010 10000000
-                                std::vector<T>{3, 3, 1, -1,
-                                               -1, -5, -5, 3,
-                                               1, -1, 3, 1,
-                                               -3, 1, 5, -1},
-                                {2, 2},
-                                {2, 2},
-                                {2, 2},
-                                {2, 2},
                                 1.0f),
-        BinaryConvolutionParams(PartialShape {1, 2, 4, 4},
-                                Shape {1, 2, 3, 3},
-                                PartialShape {1, 1, 2, 2},
+        BinaryConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            Shape{1, 1, 3, 3},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1},
+            std::vector<uint8_t>{0x2E, 0x00},  // 10101010 10000000
+            std::vector<T>{-1, 3, 1, 1},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        BinaryConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            Shape{1, 1, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1,
+                           1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0},
+            std::vector<uint8_t>{0x6B, 0x00},  // 10101010 10000000
+            std::vector<T>{-5, -3, -5, 5, 1, 3, -1, -1, 3},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {2, 2}),
+        BinaryConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            Shape{1, 1, 3, 3},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1,
+                           1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0},
+            std::vector<uint8_t>{0x6B, 0x00},  // 10101010 10000000
+            std::vector<T>{1, 1, -1, 1, 1, -5, -5, 5, 3, -1, 3, 3, -1, -1, 3, -3},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2}),
+        BinaryConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            Shape{1, 1, 3, 3},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1,
+                           1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0},
+            std::vector<uint8_t>{0x6B, 0x00},  // 10101010 10000000
+            std::vector<T>{3, 3, 1, -1, -1, -5, -5, 3, 1, -1, 3, 1, -3, 1, 5, -1},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            1.0f),
+        BinaryConvolutionParams(PartialShape{1, 2, 4, 4},
+                                Shape{1, 2, 3, 3},
+                                PartialShape{1, 1, 2, 2},
                                 IN_ET,
-                                std::vector<T>{
-                                        // channel 1
-                                        1, 0, 0, 1,
-                                        1, 1, 0, 0,
-                                        0, 0, 0, 1,
-                                        1, 0, 1, 1,
-                                        // channel 2
-                                        0, 1, 1, 0,
-                                        0, 0, 1, 1,
-                                        1, 1, 1, 0,
-                                        0, 1, 0, 0},
-                                std::vector<uint8_t>{0xAA, 0xAA, 0x80}, // 10101010 10000000
-                                std::vector<T>{2, 2,
-                                               6, -2},
+                                std::vector<T>{// channel 1
+                                               1,
+                                               0,
+                                               0,
+                                               1,
+                                               1,
+                                               1,
+                                               0,
+                                               0,
+                                               0,
+                                               0,
+                                               0,
+                                               1,
+                                               1,
+                                               0,
+                                               1,
+                                               1,
+                                               // channel 2
+                                               0,
+                                               1,
+                                               1,
+                                               0,
+                                               0,
+                                               0,
+                                               1,
+                                               1,
+                                               1,
+                                               1,
+                                               1,
+                                               0,
+                                               0,
+                                               1,
+                                               0,
+                                               0},
+                                std::vector<uint8_t>{0xAA, 0xAA, 0x80},  // 10101010 10000000
+                                std::vector<T>{2, 2, 6, -2},
                                 {1, 1},
                                 {0, 0},
                                 {0, 0},
                                 {1, 1}),
-        BinaryConvolutionParams(PartialShape {2, 1, 4, 4},
-                                Shape {1, 1, 3, 3},
-                                PartialShape {2, 1, 2, 2},
+        BinaryConvolutionParams(PartialShape{2, 1, 4, 4},
+                                Shape{1, 1, 3, 3},
+                                PartialShape{2, 1, 2, 2},
                                 IN_ET,
-                                std::vector<T>{
-                                        // batch 1
-                                        1, 0, 0, 1,
-                                        1, 1, 0, 0,
-                                        0, 0, 0, 1,
-                                        1, 0, 1, 1,
-                                        // batch 2
-                                        0, 0, 0, 0,
-                                        1, 1, 1, 0,
-                                        1, 1, 0, 1,
-                                        1, 0, 1, 0},
-                                std::vector<uint8_t>{0xAA, 0x80}, // 10101010 10000000
-                                std::vector<T>{
-                                        // batch 1
-                                        1, 1,
-                                        3, -1,
-                                        // batch 2
-                                        -3, 3,
-                                        5, -7},
+                                std::vector<T>{// batch 1
+                                               1,
+                                               0,
+                                               0,
+                                               1,
+                                               1,
+                                               1,
+                                               0,
+                                               0,
+                                               0,
+                                               0,
+                                               0,
+                                               1,
+                                               1,
+                                               0,
+                                               1,
+                                               1,
+                                               // batch 2
+                                               0,
+                                               0,
+                                               0,
+                                               0,
+                                               1,
+                                               1,
+                                               1,
+                                               0,
+                                               1,
+                                               1,
+                                               0,
+                                               1,
+                                               1,
+                                               0,
+                                               1,
+                                               0},
+                                std::vector<uint8_t>{0xAA, 0x80},  // 10101010 10000000
+                                std::vector<T>{                    // batch 1
+                                               1,
+                                               1,
+                                               3,
+                                               -1,
+                                               // batch 2
+                                               -3,
+                                               3,
+                                               5,
+                                               -7},
                                 {1, 1},
                                 {0, 0},
                                 {0, 0},
-                                {1, 1})
-    };
+                                {1, 1})};
     return binaryConvolutionParams;
 }
 
 std::vector<BinaryConvolutionParams> generateBinaryConvolutionCombinedParams() {
-    const std::vector<std::vector<BinaryConvolutionParams>> binaryConvolutionTypeParams {
+    const std::vector<std::vector<BinaryConvolutionParams>> binaryConvolutionTypeParams{
         generateBinaryConvolutionParams<element::Type_t::f32>(),
         generateBinaryConvolutionParams<element::Type_t::f16>(),
         generateBinaryConvolutionParams<element::Type_t::i64>(),
-        generateBinaryConvolutionParams<element::Type_t::i32>()
-        };
+        generateBinaryConvolutionParams<element::Type_t::i32>()};
     std::vector<BinaryConvolutionParams> combinedParams;
 
     for (const auto& params : binaryConvolutionTypeParams) {
@@ -309,7 +319,9 @@ std::vector<BinaryConvolutionParams> generateBinaryConvolutionCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_BinaryConvolution_With_Hardcoded_Refs, ReferenceBinaryConvolutionLayerTest,
-    testing::ValuesIn(generateBinaryConvolutionCombinedParams()), ReferenceBinaryConvolutionLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BinaryConvolution_With_Hardcoded_Refs,
+                         ReferenceBinaryConvolutionLayerTest,
+                         testing::ValuesIn(generateBinaryConvolutionCombinedParams()),
+                         ReferenceBinaryConvolutionLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/broadcast.cpp b/src/plugins/template/tests/functional/op_reference/broadcast.cpp
index e1038d23ec4c67..5cb9712c8b2b2d 100644
--- a/src/plugins/template/tests/functional/op_reference/broadcast.cpp
+++ b/src/plugins/template/tests/functional/op_reference/broadcast.cpp
@@ -4,20 +4,23 @@
 
 #include <gtest/gtest.h>
 
+#include "base_reference_test.hpp"
 #include "openvino/opsets/opset1.hpp"
 #include "openvino/opsets/opset3.hpp"
-#include "base_reference_test.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct BroadcastParams {
-    BroadcastParams(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& targetShapeTensor,
-        const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), targetShapeTensor(targetShapeTensor),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    BroadcastParams(const reference_tests::Tensor& dataTensor,
+                    const reference_tests::Tensor& targetShapeTensor,
+                    const reference_tests::Tensor& expectedTensor,
+                    const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          targetShapeTensor(targetShapeTensor),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor targetShapeTensor;
@@ -55,9 +58,10 @@ class ReferenceBroadcastTest : public testing::TestWithParam<BroadcastParams>, p
     static std::shared_ptr<Model> CreateFunction(const BroadcastParams& params) {
         const auto A = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto f = std::make_shared<Model>(
-            std::make_shared<opset1::Broadcast>(A, opset1::Constant::create(params.targetShapeTensor.type,
-                                                                            params.targetShapeTensor.shape,
-                                                                            params.targetShapeTensor.data.data())),
+            std::make_shared<opset1::Broadcast>(A,
+                                                opset1::Constant::create(params.targetShapeTensor.type,
+                                                                         params.targetShapeTensor.shape,
+                                                                         params.targetShapeTensor.data.data())),
             ParameterVector{A});
         return f;
     }
@@ -72,9 +76,10 @@ class ReferenceBroadcastTestV3 : public ReferenceBroadcastTest {
     static std::shared_ptr<Model> CreateFunction(const BroadcastParams& params) {
         const auto A = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto f = std::make_shared<Model>(
-            std::make_shared<opset3::Broadcast>(A, opset1::Constant::create(params.targetShapeTensor.type,
-                                                                            params.targetShapeTensor.shape,
-                                                                            params.targetShapeTensor.data.data())),
+            std::make_shared<opset3::Broadcast>(A,
+                                                opset1::Constant::create(params.targetShapeTensor.type,
+                                                                         params.targetShapeTensor.shape,
+                                                                         params.targetShapeTensor.data.data())),
             ParameterVector{A});
         return f;
     }
@@ -85,17 +90,19 @@ TEST_P(ReferenceBroadcastTestV3, CompareWithRefs) {
 }
 
 struct BroadcastParamsExplicitAxis : BroadcastParams {
-    BroadcastParamsExplicitAxis(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& targetShapeTensor,
-        const reference_tests::Tensor& axesMappingTensor, const reference_tests::Tensor& expectedTensor,
-        const std::string& testcaseName = "") :
-        BroadcastParams(dataTensor, targetShapeTensor, expectedTensor, testcaseName),
-        axesMappingTensor(axesMappingTensor) {}
+    BroadcastParamsExplicitAxis(const reference_tests::Tensor& dataTensor,
+                                const reference_tests::Tensor& targetShapeTensor,
+                                const reference_tests::Tensor& axesMappingTensor,
+                                const reference_tests::Tensor& expectedTensor,
+                                const std::string& testcaseName = "")
+        : BroadcastParams(dataTensor, targetShapeTensor, expectedTensor, testcaseName),
+          axesMappingTensor(axesMappingTensor) {}
 
     reference_tests::Tensor axesMappingTensor;
 };
 
-class ReferenceBroadcastTestExplicitAxis : public testing::TestWithParam<BroadcastParamsExplicitAxis>, public CommonReferenceTest {
+class ReferenceBroadcastTestExplicitAxis : public testing::TestWithParam<BroadcastParamsExplicitAxis>,
+                                           public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -144,12 +151,14 @@ TEST_P(ReferenceBroadcastTestExplicitAxis, CompareWithRefs) {
 }
 
 struct BroadcastParamsTestHelper {
-    BroadcastParamsTestHelper(
-        const Shape& shapeA,
-        const Shape& shapeR,
-        const AxisSet& axes, const std::string& testcaseName = "") :
-        shapeA(shapeA), shapeR(shapeR),
-        axes(axes), testcaseName(testcaseName) {}
+    BroadcastParamsTestHelper(const Shape& shapeA,
+                              const Shape& shapeR,
+                              const AxisSet& axes,
+                              const std::string& testcaseName = "")
+        : shapeA(shapeA),
+          shapeR(shapeR),
+          axes(axes),
+          testcaseName(testcaseName) {}
 
     Shape shapeA;
     Shape shapeR;
@@ -157,7 +166,8 @@ struct BroadcastParamsTestHelper {
     std::string testcaseName;
 };
 
-class ReferenceBroadcastTestTestHelper : public testing::TestWithParam<BroadcastParamsTestHelper>, public CommonReferenceTest {
+class ReferenceBroadcastTestTestHelper : public testing::TestWithParam<BroadcastParamsTestHelper>,
+                                         public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -197,7 +207,8 @@ class ReferenceBroadcastTestTestHelper : public testing::TestWithParam<Broadcast
         const auto shape_const = opset1::Constant::create(element::u64, Shape{params.shapeR.size()}, params.shapeR);
         std::shared_ptr<Node> broadcast;
         if (params.axes.size() > 0) {
-            auto axes_const = opset1::Constant::create(element::i64, Shape{params.axes.size()}, params.axes.to_vector());
+            auto axes_const =
+                opset1::Constant::create(element::i64, Shape{params.axes.size()}, params.axes.to_vector());
             broadcast = std::make_shared<opset1::Broadcast>(A, shape_const, axes_const);
         } else {
             broadcast = std::make_shared<opset1::Broadcast>(A, shape_const);
@@ -209,7 +220,7 @@ class ReferenceBroadcastTestTestHelper : public testing::TestWithParam<Broadcast
 protected:
     void GenerateRefOutData() {
         actualOutData.clear();
-        for (const auto &output : executableNetwork.outputs()) {
+        for (const auto& output : executableNetwork.outputs()) {
             actualOutData.emplace_back(inferRequest.get_tensor(output));
         }
         refOutData = actualOutData;
@@ -229,14 +240,14 @@ class ReferenceBroadcastTestExplicitAxisReversed : public ReferenceBroadcastTest
 private:
     static std::shared_ptr<Model> CreateFunction(const BroadcastParamsExplicitAxis& params) {
         const auto A = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
-        auto broadcast = std::make_shared<opset1::Broadcast>(
-            A,
-            opset1::Constant::create(params.targetShapeTensor.type,
-                                     params.targetShapeTensor.shape,
-                                     params.targetShapeTensor.data.data()),
-            opset1::Constant::create(params.axesMappingTensor.type,
-                                     params.axesMappingTensor.shape,
-                                     params.axesMappingTensor.data.data()));
+        auto broadcast =
+            std::make_shared<opset1::Broadcast>(A,
+                                                opset1::Constant::create(params.targetShapeTensor.type,
+                                                                         params.targetShapeTensor.shape,
+                                                                         params.targetShapeTensor.data.data()),
+                                                opset1::Constant::create(params.axesMappingTensor.type,
+                                                                         params.axesMappingTensor.shape,
+                                                                         params.axesMappingTensor.data.data()));
         auto reverse = std::make_shared<opset1::Reverse>(broadcast,
                                                          opset1::Constant::create(element::i64, {1}, {1}),
                                                          opset1::Reverse::Mode::INDEX);
@@ -252,38 +263,33 @@ TEST_P(ReferenceBroadcastTestExplicitAxisReversed, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<BroadcastParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<BroadcastParams> params {
-        BroadcastParams(
-            reference_tests::Tensor(ET, {}, std::vector<T>{6}),
-            reference_tests::Tensor(element::u64, {1}, std::vector<uint64_t>{4}),
-            reference_tests::Tensor(ET, {4}, std::vector<T>{6, 6, 6, 6}),
-            "broadcast_scalar_vector"),
-        BroadcastParams(
-            reference_tests::Tensor(ET, {}, std::vector<T>{6}),
-            reference_tests::Tensor(element::u64, {2}, std::vector<uint64_t>{2, 2}),
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{6, 6, 6, 6}),
-            "broadcast_scalar_matrix"),
-        BroadcastParams(
-            reference_tests::Tensor(ET, {}, std::vector<T>{6}),
-            reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{6, 6, 6, 6, 6, 6, 6, 6}),
-            "broadcast_scalar_tensor"),
-        BroadcastParams(
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{2, 4, 6, 8, 16, 32, 64, 127}),
-            reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{2, 4, 6, 8, 16, 32, 64, 127}),
-            "broadcast_trivial"),
-        BroadcastParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
-            reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{1, 2, 3, 4, 1, 2, 3, 4}),
-            "broadcast_matrix_0"),
+    std::vector<BroadcastParams> params{
+        BroadcastParams(reference_tests::Tensor(ET, {}, std::vector<T>{6}),
+                        reference_tests::Tensor(element::u64, {1}, std::vector<uint64_t>{4}),
+                        reference_tests::Tensor(ET, {4}, std::vector<T>{6, 6, 6, 6}),
+                        "broadcast_scalar_vector"),
+        BroadcastParams(reference_tests::Tensor(ET, {}, std::vector<T>{6}),
+                        reference_tests::Tensor(element::u64, {2}, std::vector<uint64_t>{2, 2}),
+                        reference_tests::Tensor(ET, {2, 2}, std::vector<T>{6, 6, 6, 6}),
+                        "broadcast_scalar_matrix"),
+        BroadcastParams(reference_tests::Tensor(ET, {}, std::vector<T>{6}),
+                        reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
+                        reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{6, 6, 6, 6, 6, 6, 6, 6}),
+                        "broadcast_scalar_tensor"),
+        BroadcastParams(reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{2, 4, 6, 8, 16, 32, 64, 127}),
+                        reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
+                        reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{2, 4, 6, 8, 16, 32, 64, 127}),
+                        "broadcast_trivial"),
+        BroadcastParams(reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
+                        reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
+                        reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{1, 2, 3, 4, 1, 2, 3, 4}),
+                        "broadcast_matrix_0"),
     };
     return params;
 }
 
 std::vector<BroadcastParams> generateCombinedParams() {
-    const std::vector<std::vector<BroadcastParams>> generatedParams {
+    const std::vector<std::vector<BroadcastParams>> generatedParams{
         generateParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
         generateParams<element::Type_t::i32>(),
@@ -305,22 +311,25 @@ std::vector<BroadcastParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs, ReferenceBroadcastTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceBroadcastTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs,
+                         ReferenceBroadcastTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceBroadcastTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs, ReferenceBroadcastTestV3,
-    testing::ValuesIn(generateCombinedParams()), ReferenceBroadcastTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs,
+                         ReferenceBroadcastTestV3,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceBroadcastTest::getTestCaseName);
 
 template <element::Type_t ET>
 std::vector<BroadcastParamsExplicitAxis> generateParamsExplicitAxis() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<BroadcastParamsExplicitAxis> params {
-        BroadcastParamsExplicitAxis(
-            reference_tests::Tensor(ET, {}, std::vector<T>{6}),
-            reference_tests::Tensor(element::u64, {2}, std::vector<uint64_t>{1, 2}),
-            reference_tests::Tensor(element::i64, {1}, std::vector<int64_t>{0}),
-            reference_tests::Tensor(ET, {1, 2}, std::vector<T>{6, 6}),
-            "broadcast_scalar_vector_explicit_axis_0"),
+    std::vector<BroadcastParamsExplicitAxis> params{
+        BroadcastParamsExplicitAxis(reference_tests::Tensor(ET, {}, std::vector<T>{6}),
+                                    reference_tests::Tensor(element::u64, {2}, std::vector<uint64_t>{1, 2}),
+                                    reference_tests::Tensor(element::i64, {1}, std::vector<int64_t>{0}),
+                                    reference_tests::Tensor(ET, {1, 2}, std::vector<T>{6, 6}),
+                                    "broadcast_scalar_vector_explicit_axis_0"),
         BroadcastParamsExplicitAxis(
             reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
             reference_tests::Tensor(element::u64, {2}, std::vector<uint64_t>{3, 4}),
@@ -333,30 +342,27 @@ std::vector<BroadcastParamsExplicitAxis> generateParamsExplicitAxis() {
             reference_tests::Tensor(element::i64, {1}, std::vector<int64_t>{1}),
             reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4}),
             "broadcast_vector_rowwise"),
-        BroadcastParamsExplicitAxis(
-            reference_tests::Tensor(ET, {1}, std::vector<T>{4}),
-            reference_tests::Tensor(element::u64, {2}, std::vector<uint64_t>{3, 1}),
-            reference_tests::Tensor(element::i64, {1}, std::vector<int64_t>{1}),
-            reference_tests::Tensor(ET, {3, 1}, std::vector<T>{4, 4, 4}),
-            "broadcast_scalar_to_matrix"),
-        BroadcastParamsExplicitAxis(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
-            reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
-            reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 2}),
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{1, 2, 1, 2, 3, 4, 3, 4}),
-            "broadcast_matrix_1"),
-        BroadcastParamsExplicitAxis(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
-            reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
-            reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 1}),
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{1, 1, 2, 2, 3, 3, 4, 4}),
-            "broadcast_matrix_2"),
+        BroadcastParamsExplicitAxis(reference_tests::Tensor(ET, {1}, std::vector<T>{4}),
+                                    reference_tests::Tensor(element::u64, {2}, std::vector<uint64_t>{3, 1}),
+                                    reference_tests::Tensor(element::i64, {1}, std::vector<int64_t>{1}),
+                                    reference_tests::Tensor(ET, {3, 1}, std::vector<T>{4, 4, 4}),
+                                    "broadcast_scalar_to_matrix"),
+        BroadcastParamsExplicitAxis(reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
+                                    reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
+                                    reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 2}),
+                                    reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{1, 2, 1, 2, 3, 4, 3, 4}),
+                                    "broadcast_matrix_1"),
+        BroadcastParamsExplicitAxis(reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
+                                    reference_tests::Tensor(element::u64, {3}, std::vector<uint64_t>{2, 2, 2}),
+                                    reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 1}),
+                                    reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{1, 1, 2, 2, 3, 3, 4, 4}),
+                                    "broadcast_matrix_2"),
     };
     return params;
 }
 
 std::vector<BroadcastParamsExplicitAxis> generateCombinedParamsExplicitAxis() {
-    const std::vector<std::vector<BroadcastParamsExplicitAxis>> generatedParams {
+    const std::vector<std::vector<BroadcastParamsExplicitAxis>> generatedParams{
         generateParamsExplicitAxis<element::Type_t::i8>(),
         generateParamsExplicitAxis<element::Type_t::i16>(),
         generateParamsExplicitAxis<element::Type_t::i32>(),
@@ -378,102 +384,36 @@ std::vector<BroadcastParamsExplicitAxis> generateCombinedParamsExplicitAxis() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs, ReferenceBroadcastTestExplicitAxis,
-    testing::ValuesIn(generateCombinedParamsExplicitAxis()), ReferenceBroadcastTestExplicitAxis::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs,
+                         ReferenceBroadcastTestExplicitAxis,
+                         testing::ValuesIn(generateCombinedParamsExplicitAxis()),
+                         ReferenceBroadcastTestExplicitAxis::getTestCaseName);
 
 std::vector<BroadcastParamsTestHelper> generateParamsTestHelper() {
-    std::vector<BroadcastParamsTestHelper> params {
-        BroadcastParamsTestHelper(
-            {2},
-            {3, 2, 4},
-            {1},
-            "broadcast_algo_vector_middle"),
-        BroadcastParamsTestHelper(
-            {2},
-            {3, 2},
-            {1},
-            "broadcast_algo_vector_forward_2"),
-        BroadcastParamsTestHelper(
-            {2},
-            {4, 3, 2},
-            {2},
-            "broadcast_algo_vector_forward_3"),
-        BroadcastParamsTestHelper(
-            {2},
-            {5, 4, 3, 2},
-            {3},
-            "broadcast_algo_vector_forward_4"),
-        BroadcastParamsTestHelper(
-            {},
-            {5, 4, 3, 2},
-            {},
-            "broadcast_algo_scalar"),
-        BroadcastParamsTestHelper(
-            {2},
-            {2, 3},
-            {0},
-            "broadcast_algo_vector_backward_2"),
-        BroadcastParamsTestHelper(
-            {2},
-            {2, 3, 4},
-            {0},
-            "broadcast_algo_vector_backward_3"),
-        BroadcastParamsTestHelper(
-            {2},
-            {2, 3, 4, 5},
-            {0},
-            "broadcast_algo_vector_backward_4"),
-        BroadcastParamsTestHelper(
-            {4, 5},
-            {2, 3, 4, 5},
-            {2, 3},
-            "broadcast_algo_matrix_backward_4"),
-        BroadcastParamsTestHelper(
-            {3, 5},
-            {2, 3, 4, 5},
-            {1, 3},
-            "broadcast_algo_matrix_stride_1"),
-        BroadcastParamsTestHelper(
-            {3, 4},
-            {2, 3, 4, 5},
-            {1, 2},
-            "broadcast_algo_matrix_stride_2"),
-        BroadcastParamsTestHelper(
-            {2, 4},
-            {2, 3, 4, 5},
-            {0, 2},
-            "broadcast_algo_matrix_stride_3"),
-        BroadcastParamsTestHelper(
-            {2, 3, 4},
-            {5, 2, 3, 4},
-            {1, 2, 3},
-            "broadcast_algo_3d_backward"),
-        BroadcastParamsTestHelper(
-            {2, 3, 4},
-            {2, 5, 3, 4},
-            {0, 2, 3},
-            "broadcast_algo_3d_stride_1"),
-        BroadcastParamsTestHelper(
-            {2, 3, 4},
-            {2, 3, 5, 4},
-            {0, 1, 3},
-            "broadcast_algo_3d_stride_2"),
-        BroadcastParamsTestHelper(
-            {3, 1},
-            {2, 3, 3},
-            {1, 2},
-            "broadcast_algo_3d_diffrent_rank"),
-        BroadcastParamsTestHelper(
-            {2, 3, 1, 1},
-            {2, 3, 4, 5},
-            {0, 1, 2, 3},
-            "broadcast_algo_4d_same_rank"),
+    std::vector<BroadcastParamsTestHelper> params{
+        BroadcastParamsTestHelper({2}, {3, 2, 4}, {1}, "broadcast_algo_vector_middle"),
+        BroadcastParamsTestHelper({2}, {3, 2}, {1}, "broadcast_algo_vector_forward_2"),
+        BroadcastParamsTestHelper({2}, {4, 3, 2}, {2}, "broadcast_algo_vector_forward_3"),
+        BroadcastParamsTestHelper({2}, {5, 4, 3, 2}, {3}, "broadcast_algo_vector_forward_4"),
+        BroadcastParamsTestHelper({}, {5, 4, 3, 2}, {}, "broadcast_algo_scalar"),
+        BroadcastParamsTestHelper({2}, {2, 3}, {0}, "broadcast_algo_vector_backward_2"),
+        BroadcastParamsTestHelper({2}, {2, 3, 4}, {0}, "broadcast_algo_vector_backward_3"),
+        BroadcastParamsTestHelper({2}, {2, 3, 4, 5}, {0}, "broadcast_algo_vector_backward_4"),
+        BroadcastParamsTestHelper({4, 5}, {2, 3, 4, 5}, {2, 3}, "broadcast_algo_matrix_backward_4"),
+        BroadcastParamsTestHelper({3, 5}, {2, 3, 4, 5}, {1, 3}, "broadcast_algo_matrix_stride_1"),
+        BroadcastParamsTestHelper({3, 4}, {2, 3, 4, 5}, {1, 2}, "broadcast_algo_matrix_stride_2"),
+        BroadcastParamsTestHelper({2, 4}, {2, 3, 4, 5}, {0, 2}, "broadcast_algo_matrix_stride_3"),
+        BroadcastParamsTestHelper({2, 3, 4}, {5, 2, 3, 4}, {1, 2, 3}, "broadcast_algo_3d_backward"),
+        BroadcastParamsTestHelper({2, 3, 4}, {2, 5, 3, 4}, {0, 2, 3}, "broadcast_algo_3d_stride_1"),
+        BroadcastParamsTestHelper({2, 3, 4}, {2, 3, 5, 4}, {0, 1, 3}, "broadcast_algo_3d_stride_2"),
+        BroadcastParamsTestHelper({3, 1}, {2, 3, 3}, {1, 2}, "broadcast_algo_3d_diffrent_rank"),
+        BroadcastParamsTestHelper({2, 3, 1, 1}, {2, 3, 4, 5}, {0, 1, 2, 3}, "broadcast_algo_4d_same_rank"),
     };
     return params;
 }
 
 std::vector<BroadcastParamsTestHelper> generateCombinedParamsTestHelper() {
-    const std::vector<std::vector<BroadcastParamsTestHelper>> generatedParams {
+    const std::vector<std::vector<BroadcastParamsTestHelper>> generatedParams{
         generateParamsTestHelper(),
     };
     std::vector<BroadcastParamsTestHelper> combinedParams;
@@ -484,13 +424,15 @@ std::vector<BroadcastParamsTestHelper> generateCombinedParamsTestHelper() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs, ReferenceBroadcastTestTestHelper,
-    testing::ValuesIn(generateCombinedParamsTestHelper()), ReferenceBroadcastTestTestHelper::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs,
+                         ReferenceBroadcastTestTestHelper,
+                         testing::ValuesIn(generateCombinedParamsTestHelper()),
+                         ReferenceBroadcastTestTestHelper::getTestCaseName);
 
 template <element::Type_t ET>
 std::vector<BroadcastParamsExplicitAxis> generateParamsExplicitAxisReversed() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<BroadcastParamsExplicitAxis> params {
+    std::vector<BroadcastParamsExplicitAxis> params{
         BroadcastParamsExplicitAxis(
             reference_tests::Tensor(ET, {4}, std::vector<T>{1, 2, 3, 4}),
             reference_tests::Tensor(element::u64, {2}, std::vector<uint64_t>{3, 4}),
@@ -502,7 +444,7 @@ std::vector<BroadcastParamsExplicitAxis> generateParamsExplicitAxisReversed() {
 }
 
 std::vector<BroadcastParamsExplicitAxis> generateCombinedParamsExplicitAxisReversed() {
-    const std::vector<std::vector<BroadcastParamsExplicitAxis>> generatedParams {
+    const std::vector<std::vector<BroadcastParamsExplicitAxis>> generatedParams{
         generateParamsExplicitAxisReversed<element::Type_t::i8>(),
         generateParamsExplicitAxisReversed<element::Type_t::i16>(),
         generateParamsExplicitAxisReversed<element::Type_t::i32>(),
@@ -524,6 +466,8 @@ std::vector<BroadcastParamsExplicitAxis> generateCombinedParamsExplicitAxisRever
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs, ReferenceBroadcastTestExplicitAxisReversed,
-    testing::ValuesIn(generateCombinedParamsExplicitAxisReversed()), ReferenceBroadcastTestExplicitAxis::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Broadcast_With_Hardcoded_Refs,
+                         ReferenceBroadcastTestExplicitAxisReversed,
+                         testing::ValuesIn(generateCombinedParamsExplicitAxisReversed()),
+                         ReferenceBroadcastTestExplicitAxis::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/bucketize.cpp b/src/plugins/template/tests/functional/op_reference/bucketize.cpp
index c26a21a8a7760a..a26caf7f31a9e5 100644
--- a/src/plugins/template/tests/functional/op_reference/bucketize.cpp
+++ b/src/plugins/template/tests/functional/op_reference/bucketize.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/bucketize.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/bucketize.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,9 +13,15 @@ using namespace ov;
 
 struct BucketizeParams {
     template <class IT, class BT, class OT>
-    BucketizeParams(const element::Type& input_type, const PartialShape& input_pshape, const std::vector<IT>& input,
-                    const element::Type& bucket_type, const PartialShape& bucket_pshape, const std::vector<BT>& buckets, bool with_right_bound,
-                    const element::Type& output_type, const std::vector<OT>& expected_output)
+    BucketizeParams(const element::Type& input_type,
+                    const PartialShape& input_pshape,
+                    const std::vector<IT>& input,
+                    const element::Type& bucket_type,
+                    const PartialShape& bucket_pshape,
+                    const std::vector<BT>& buckets,
+                    bool with_right_bound,
+                    const element::Type& output_type,
+                    const std::vector<OT>& expected_output)
         : input_type(input_type),
           input_pshape(input_pshape),
           input(CreateTensor(input_type, input)),
@@ -40,8 +47,12 @@ class ReferenceBucketizeLayerTest : public testing::TestWithParam<BucketizeParam
 public:
     void SetUp() override {
         auto params = GetParam();
-        function = CreateFunction(params.input_type, params.input_pshape, params.bucket_type, params.bucket_pshape,
-                                  params.with_right_bound, params.output_type);
+        function = CreateFunction(params.input_type,
+                                  params.input_pshape,
+                                  params.bucket_type,
+                                  params.bucket_pshape,
+                                  params.with_right_bound,
+                                  params.output_type);
         inputData = {params.input, params.buckets};
         refOutData = {params.expected_output};
     }
@@ -59,13 +70,17 @@ class ReferenceBucketizeLayerTest : public testing::TestWithParam<BucketizeParam
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const element::Type& input_type, const PartialShape& input_pshape,
-                                                    const element::Type& bucket_type, const PartialShape& bucket_pshape,
-                                                    const bool with_right_bound, const element::Type& output_type) {
+    static std::shared_ptr<Model> CreateFunction(const element::Type& input_type,
+                                                 const PartialShape& input_pshape,
+                                                 const element::Type& bucket_type,
+                                                 const PartialShape& bucket_pshape,
+                                                 const bool with_right_bound,
+                                                 const element::Type& output_type) {
         auto data = std::make_shared<op::v0::Parameter>(input_type, input_pshape);
         auto buckets = std::make_shared<op::v0::Parameter>(bucket_type, bucket_pshape);
-        return std::make_shared<Model>(std::make_shared<op::v3::Bucketize>(data, buckets, output_type, with_right_bound),
-                                              ParameterVector {data, buckets});
+        return std::make_shared<Model>(
+            std::make_shared<op::v3::Bucketize>(data, buckets, output_type, with_right_bound),
+            ParameterVector{data, buckets});
     }
 };
 
@@ -73,26 +88,27 @@ TEST_P(ReferenceBucketizeLayerTest, CompareWithHardcodedRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Bucketize_With_Hardcoded_Refs, ReferenceBucketizeLayerTest,
+INSTANTIATE_TEST_SUITE_P(smoke_Bucketize_With_Hardcoded_Refs,
+                         ReferenceBucketizeLayerTest,
                          ::testing::Values(
                              // fp32, int32, with_right_bound
                              BucketizeParams(element::f32,
-                                             PartialShape {10, 1},
-                                             std::vector<float> {8.f, 1.f, 2.f, 1.1f, 8.f, 10.f, 1.f, 10.2f, 0.f, 20.f},
+                                             PartialShape{10, 1},
+                                             std::vector<float>{8.f, 1.f, 2.f, 1.1f, 8.f, 10.f, 1.f, 10.2f, 0.f, 20.f},
                                              element::i32,
-                                             PartialShape {4},
-                                             std::vector<int32_t> {1, 4, 10, 20},
+                                             PartialShape{4},
+                                             std::vector<int32_t>{1, 4, 10, 20},
                                              true,
                                              element::i32,
-                                             std::vector<int32_t> {2, 0, 1, 1, 2, 2, 0, 3, 0, 3}),
+                                             std::vector<int32_t>{2, 0, 1, 1, 2, 2, 0, 3, 0, 3}),
                              // fp32, int32, with_right_bound
                              BucketizeParams(element::i32,
-                                             PartialShape {1, 1, 10},
-                                             std::vector<int32_t> {8, 1, 2, 1, 8, 5, 1, 5, 0, 20},
+                                             PartialShape{1, 1, 10},
+                                             std::vector<int32_t>{8, 1, 2, 1, 8, 5, 1, 5, 0, 20},
                                              element::i32,
-                                             PartialShape {4},
-                                             std::vector<int32_t> {1, 4, 10, 20},
+                                             PartialShape{4},
+                                             std::vector<int32_t>{1, 4, 10, 20},
                                              false,
                                              element::i32,
-                                             std::vector<int32_t> {2, 1, 1, 1, 2, 2, 1, 2, 0, 4})),
+                                             std::vector<int32_t>{2, 1, 1, 1, 2, 2, 1, 2, 0, 4})),
                          ReferenceBucketizeLayerTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/op_reference/ceiling.cpp b/src/plugins/template/tests/functional/op_reference/ceiling.cpp
index 0d351de47b60c4..6362b9de86d793 100644
--- a/src/plugins/template/tests/functional/op_reference/ceiling.cpp
+++ b/src/plugins/template/tests/functional/op_reference/ceiling.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/ceiling.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/ceiling.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,9 +16,9 @@ namespace {
 struct CeilingParams {
     template <class IT>
     CeilingParams(const PartialShape& shape,
-               const element::Type& iType,
-               const std::vector<IT>& iValues,
-               const std::vector<IT>& oValues)
+                  const element::Type& iType,
+                  const std::vector<IT>& iValues,
+                  const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -50,11 +52,11 @@ class ReferenceCeilingLayerTest : public testing::TestWithParam<CeilingParams>,
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto ceiling = std::make_shared<op::v0::Ceiling>(in);
-        return std::make_shared<Model>(NodeVector {ceiling}, ParameterVector {in});
+        return std::make_shared<Model>(NodeVector{ceiling}, ParameterVector{in});
     }
 };
 
@@ -66,12 +68,10 @@ template <element::Type_t IN_ET>
 std::vector<CeilingParams> generateParamsForCeilingFloat() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<CeilingParams> params{
-        CeilingParams(ov::PartialShape{4},
-                      IN_ET,
-                      std::vector<T>{-2.5f, -2.0f, 0.3f, 4.8f},
-                      std::vector<T>{-2.0f, -2.0f, 1.0f, 5.0f})
-    };
+    std::vector<CeilingParams> params{CeilingParams(ov::PartialShape{4},
+                                                    IN_ET,
+                                                    std::vector<T>{-2.5f, -2.0f, 0.3f, 4.8f},
+                                                    std::vector<T>{-2.0f, -2.0f, 1.0f, 5.0f})};
     return params;
 }
 
@@ -79,12 +79,10 @@ template <element::Type_t IN_ET>
 std::vector<CeilingParams> generateParamsForCeilingInt64() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<CeilingParams> params{
-        CeilingParams(ov::PartialShape{3},
-                     IN_ET,
-                     std::vector<T>{0, 1, 0x4000000000000001},
-                     std::vector<T>{0, 1, 0x4000000000000001})
-    };
+    std::vector<CeilingParams> params{CeilingParams(ov::PartialShape{3},
+                                                    IN_ET,
+                                                    std::vector<T>{0, 1, 0x4000000000000001},
+                                                    std::vector<T>{0, 1, 0x4000000000000001})};
     return params;
 }
 
@@ -92,12 +90,10 @@ template <element::Type_t IN_ET>
 std::vector<CeilingParams> generateParamsForCeilingInt32() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<CeilingParams> params{
-        CeilingParams(ov::PartialShape{4},
-                     IN_ET,
-                     std::vector<T>{2, 136314888, 0x40000010, 0x40000001},
-                     std::vector<T>{2, 136314888, 0x40000010, 0x40000001})
-    };
+    std::vector<CeilingParams> params{CeilingParams(ov::PartialShape{4},
+                                                    IN_ET,
+                                                    std::vector<T>{2, 136314888, 0x40000010, 0x40000001},
+                                                    std::vector<T>{2, 136314888, 0x40000010, 0x40000001})};
     return params;
 }
 
@@ -105,28 +101,24 @@ template <element::Type_t IN_ET>
 std::vector<CeilingParams> generateParamsForCeilingInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<CeilingParams> params{
-        CeilingParams(ov::PartialShape{4},
-                     IN_ET,
-                     std::vector<T>{2, 64, 0x40, 0x01},
-                     std::vector<T>{2, 64, 0x40, 0x01})
-    };
+    std::vector<CeilingParams> params{CeilingParams(ov::PartialShape{4},
+                                                    IN_ET,
+                                                    std::vector<T>{2, 64, 0x40, 0x01},
+                                                    std::vector<T>{2, 64, 0x40, 0x01})};
     return params;
 }
 
 std::vector<CeilingParams> generateCombinedParamsForCeiling() {
-    const std::vector<std::vector<CeilingParams>> allTypeParams{
-        generateParamsForCeilingFloat<element::Type_t::f32>(),
-        generateParamsForCeilingFloat<element::Type_t::f16>(),
-        generateParamsForCeilingInt64<element::Type_t::i64>(),
-        generateParamsForCeilingInt32<element::Type_t::i32>(),
-        generateParamsForCeilingInt<element::Type_t::i16>(),
-        generateParamsForCeilingInt<element::Type_t::i8>(),
-        generateParamsForCeilingInt64<element::Type_t::u64>(),
-        generateParamsForCeilingInt32<element::Type_t::u32>(),
-        generateParamsForCeilingInt<element::Type_t::u16>(),
-        generateParamsForCeilingInt<element::Type_t::u8>()
-    };
+    const std::vector<std::vector<CeilingParams>> allTypeParams{generateParamsForCeilingFloat<element::Type_t::f32>(),
+                                                                generateParamsForCeilingFloat<element::Type_t::f16>(),
+                                                                generateParamsForCeilingInt64<element::Type_t::i64>(),
+                                                                generateParamsForCeilingInt32<element::Type_t::i32>(),
+                                                                generateParamsForCeilingInt<element::Type_t::i16>(),
+                                                                generateParamsForCeilingInt<element::Type_t::i8>(),
+                                                                generateParamsForCeilingInt64<element::Type_t::u64>(),
+                                                                generateParamsForCeilingInt32<element::Type_t::u32>(),
+                                                                generateParamsForCeilingInt<element::Type_t::u16>(),
+                                                                generateParamsForCeilingInt<element::Type_t::u8>()};
 
     std::vector<CeilingParams> combinedParams;
 
@@ -137,10 +129,9 @@ std::vector<CeilingParams> generateCombinedParamsForCeiling() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Ceiling_With_Hardcoded_Refs,
-    ReferenceCeilingLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForCeiling()),
-    ReferenceCeilingLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Ceiling_With_Hardcoded_Refs,
+                         ReferenceCeilingLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForCeiling()),
+                         ReferenceCeilingLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/clamp.cpp b/src/plugins/template/tests/functional/op_reference/clamp.cpp
index f31068f59455b5..be977d60d16e62 100644
--- a/src/plugins/template/tests/functional/op_reference/clamp.cpp
+++ b/src/plugins/template/tests/functional/op_reference/clamp.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/clamp.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/clamp.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,8 +14,12 @@ using namespace ov;
 namespace {
 struct ClampParams {
     template <class IT>
-    ClampParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
-                const double min, const double max)
+    ClampParams(const ov::PartialShape& shape,
+                const ov::element::Type& iType,
+                const std::vector<IT>& iValues,
+                const std::vector<IT>& oValues,
+                const double min,
+                const double max)
         : min(min),
           max(max),
           pshape(shape),
@@ -53,11 +58,14 @@ class ReferenceClampLayerTest : public testing::TestWithParam<ClampParams>, publ
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const ov::PartialShape& input_shape, const ov::element::Type& input_type,
-                                                    const ov::element::Type& expected_output_type, const double min, const double max) {
+    static std::shared_ptr<Model> CreateFunction(const ov::PartialShape& input_shape,
+                                                 const ov::element::Type& input_type,
+                                                 const ov::element::Type& expected_output_type,
+                                                 const double min,
+                                                 const double max) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Clamp = std::make_shared<op::v0::Clamp>(in, min, max);
-        return std::make_shared<ov::Model>(NodeVector {Clamp}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Clamp}, ParameterVector{in});
     }
 };
 
@@ -72,32 +80,31 @@ std::vector<ClampParams> generateClampFloatParams() {
     auto max = std::numeric_limits<T>::max();
     auto pinf = std::numeric_limits<float>::infinity();
     auto ninf = -std::numeric_limits<float>::infinity();
-    std::vector<ClampParams> clampParams {
-        ClampParams(ov::PartialShape {5, 2},
+    std::vector<ClampParams> clampParams{
+        ClampParams(ov::PartialShape{5, 2},
                     IN_ET,
                     std::vector<T>{-0.1, 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8},
                     std::vector<T>{0.2, 0.2, 0.2, 0.2, 0.3, 0.4, 0.5, 0.6, 0.6, 0.6},
                     0.2,
                     0.6),
-        ClampParams(ov::PartialShape {5, 2},
+        ClampParams(ov::PartialShape{5, 2},
                     IN_ET,
                     std::vector<T>{min, max, ninf, pinf, 9.99999, 10.0, 10.000001, 19.999999, 20.0, 20.000001},
                     std::vector<T>{10.0, 20.0, 10.0, 20.0, 10.0, 10.0, 10.000001, 19.999999, 20.0, 20.0},
                     10.0,
                     20.0),
-        ClampParams(ov::PartialShape {5, 2},
+        ClampParams(ov::PartialShape{5, 2},
                     IN_ET,
                     std::vector<T>{min, max, ninf, pinf, 9.99999, 10.0, 10.000001, 19.999999, 20.0, 20.000001},
                     std::vector<T>{10.0, max, 10.0, pinf, 10.0, 10.0, 10.000001, 19.999999, 20.0, 20.000001},
                     10.0,
                     pinf),
-        ClampParams(ov::PartialShape {5, 2},
+        ClampParams(ov::PartialShape{5, 2},
                     IN_ET,
                     std::vector<T>{min, max, ninf, pinf, 9.99999, 10.0, 10.000001, 19.999999, 20.0, 20.000001},
                     std::vector<T>{min, 20.0, ninf, 20.0, 9.99999, 10.0, 10.000001, 19.999999, 20.0, 20.0},
                     ninf,
-                    20.0)
-    };
+                    20.0)};
     return clampParams;
 }
 
@@ -108,38 +115,36 @@ std::vector<ClampParams> generateClampIntParams() {
     auto max = std::numeric_limits<T>::max();
     auto pinf = std::numeric_limits<float>::infinity();
     auto ninf = -std::numeric_limits<float>::infinity();
-    std::vector<ClampParams> clampParams {
-        ClampParams(ov::PartialShape {6},
-                    IN_ET,
-                    std::vector<T>{-1, 3, -10, 20, 6, 2},
-                    std::vector<T>{1, 3, 1, 5, 5, 2},
-                    0.4,
-                    5.6),
-        ClampParams(ov::PartialShape {6},
-                    IN_ET,
-                    std::vector<T>{-6, 1, -2, 0, -1, 2},
-                    std::vector<T>{-5, -1, -2, -1, -1, -1},
-                    -5.6,
-                    -0.4),
-        ClampParams(ov::PartialShape {4, 2},
-                    IN_ET,
-                    std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
-                    std::vector<T>{10, 20, 10, 10, 11, 19, 20, 20},
-                    10.0,
-                    20.0),
-        ClampParams(ov::PartialShape {4, 2},
-                    IN_ET,
-                    std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
-                    std::vector<T>{10, max, 10, 10, 11, 19, 20, 21},
-                    10.0,
-                    pinf),
-        ClampParams(ov::PartialShape {4, 2},
-                    IN_ET,
-                    std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
-                    std::vector<T>{min, 20, 9, 10, 11, 19, 20, 20},
-                    ninf,
-                    20.0)
-    };
+    std::vector<ClampParams> clampParams{ClampParams(ov::PartialShape{6},
+                                                     IN_ET,
+                                                     std::vector<T>{-1, 3, -10, 20, 6, 2},
+                                                     std::vector<T>{1, 3, 1, 5, 5, 2},
+                                                     0.4,
+                                                     5.6),
+                                         ClampParams(ov::PartialShape{6},
+                                                     IN_ET,
+                                                     std::vector<T>{-6, 1, -2, 0, -1, 2},
+                                                     std::vector<T>{-5, -1, -2, -1, -1, -1},
+                                                     -5.6,
+                                                     -0.4),
+                                         ClampParams(ov::PartialShape{4, 2},
+                                                     IN_ET,
+                                                     std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
+                                                     std::vector<T>{10, 20, 10, 10, 11, 19, 20, 20},
+                                                     10.0,
+                                                     20.0),
+                                         ClampParams(ov::PartialShape{4, 2},
+                                                     IN_ET,
+                                                     std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
+                                                     std::vector<T>{10, max, 10, 10, 11, 19, 20, 21},
+                                                     10.0,
+                                                     pinf),
+                                         ClampParams(ov::PartialShape{4, 2},
+                                                     IN_ET,
+                                                     std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
+                                                     std::vector<T>{min, 20, 9, 10, 11, 19, 20, 20},
+                                                     ninf,
+                                                     20.0)};
     return clampParams;
 }
 
@@ -150,43 +155,39 @@ std::vector<ClampParams> generateClampUintParams() {
     T max = (static_cast<T>(1) << (std::numeric_limits<T>::digits - 1)) - 1;
     auto pinf = static_cast<double>(max);
     auto ninf = -std::numeric_limits<float>::infinity();
-    std::vector<ClampParams> clampParams {
-        ClampParams(ov::PartialShape {4, 2},
-                    IN_ET,
-                    std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
-                    std::vector<T>{10, 20, 10, 10, 11, 19, 20, 20},
-                    10.0,
-                    20.0),
-        ClampParams(ov::PartialShape {4, 2},
-                    IN_ET,
-                    std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
-                    std::vector<T>{10, max, 10, 10, 11, 19, 20, 21},
-                    10.0,
-                    pinf),
-        ClampParams(ov::PartialShape {4, 2},
-                    IN_ET,
-                    std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
-                    std::vector<T>{min, 20, 9, 10, 11, 19, 20, 20},
-                    ninf,
-                    20.0)
-    };
+    std::vector<ClampParams> clampParams{ClampParams(ov::PartialShape{4, 2},
+                                                     IN_ET,
+                                                     std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
+                                                     std::vector<T>{10, 20, 10, 10, 11, 19, 20, 20},
+                                                     10.0,
+                                                     20.0),
+                                         ClampParams(ov::PartialShape{4, 2},
+                                                     IN_ET,
+                                                     std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
+                                                     std::vector<T>{10, max, 10, 10, 11, 19, 20, 21},
+                                                     10.0,
+                                                     pinf),
+                                         ClampParams(ov::PartialShape{4, 2},
+                                                     IN_ET,
+                                                     std::vector<T>{min, max, 9, 10, 11, 19, 20, 21},
+                                                     std::vector<T>{min, 20, 9, 10, 11, 19, 20, 20},
+                                                     ninf,
+                                                     20.0)};
     return clampParams;
 }
 
 std::vector<ClampParams> generateClampCombinedParams() {
-    const std::vector<std::vector<ClampParams>> clampTypeParams {
-        generateClampFloatParams<element::Type_t::f32>(),
-        generateClampFloatParams<element::Type_t::f16>(),
-        generateClampFloatParams<element::Type_t::bf16>(),
-        generateClampIntParams<element::Type_t::i8>(),
-        generateClampIntParams<element::Type_t::i16>(),
-        generateClampIntParams<element::Type_t::i32>(),
-        generateClampIntParams<element::Type_t::i64>(),
-        generateClampUintParams<element::Type_t::u8>(),
-        generateClampUintParams<element::Type_t::u16>(),
-        generateClampUintParams<element::Type_t::u32>(),
-        generateClampUintParams<element::Type_t::u64>()
-        };
+    const std::vector<std::vector<ClampParams>> clampTypeParams{generateClampFloatParams<element::Type_t::f32>(),
+                                                                generateClampFloatParams<element::Type_t::f16>(),
+                                                                generateClampFloatParams<element::Type_t::bf16>(),
+                                                                generateClampIntParams<element::Type_t::i8>(),
+                                                                generateClampIntParams<element::Type_t::i16>(),
+                                                                generateClampIntParams<element::Type_t::i32>(),
+                                                                generateClampIntParams<element::Type_t::i64>(),
+                                                                generateClampUintParams<element::Type_t::u8>(),
+                                                                generateClampUintParams<element::Type_t::u16>(),
+                                                                generateClampUintParams<element::Type_t::u32>(),
+                                                                generateClampUintParams<element::Type_t::u64>()};
     std::vector<ClampParams> combinedParams;
 
     for (const auto& params : clampTypeParams) {
@@ -195,7 +196,9 @@ std::vector<ClampParams> generateClampCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Clamp_With_Hardcoded_Refs, ReferenceClampLayerTest,
-    testing::ValuesIn(generateClampCombinedParams()), ReferenceClampLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Clamp_With_Hardcoded_Refs,
+                         ReferenceClampLayerTest,
+                         testing::ValuesIn(generateClampCombinedParams()),
+                         ReferenceClampLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/comparison.cpp b/src/plugins/template/tests/functional/op_reference/comparison.cpp
index 71612aa3ddfe53..3fb8b1c50286e9 100644
--- a/src/plugins/template/tests/functional/op_reference/comparison.cpp
+++ b/src/plugins/template/tests/functional/op_reference/comparison.cpp
@@ -10,6 +10,6 @@ namespace {
 TEST_P(ReferenceComparisonLayerTest, CompareWithHardcodedRefs) {
     Exec();
 }
-} // namespace
-} //  namespace ComparisonOpsRefTestDefinitions
-} //  namespace reference_tests
+}  // namespace
+}  //  namespace ComparisonOpsRefTestDefinitions
+}  //  namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/comparison.hpp b/src/plugins/template/tests/functional/op_reference/comparison.hpp
index 16869dcbd2c087..6e363829715ec9 100644
--- a/src/plugins/template/tests/functional/op_reference/comparison.hpp
+++ b/src/plugins/template/tests/functional/op_reference/comparison.hpp
@@ -7,14 +7,14 @@
 #include "base_reference_test.hpp"
 #include "common_test_utils/test_enums.hpp"
 #include "openvino/op/equal.hpp"
-#include "openvino/op/not_equal.hpp"
 #include "openvino/op/greater.hpp"
 #include "openvino/op/greater_eq.hpp"
-#include "openvino/op/less.hpp"
-#include "openvino/op/less_eq.hpp"
-#include "openvino/op/is_inf.hpp"
 #include "openvino/op/is_finite.hpp"
+#include "openvino/op/is_inf.hpp"
 #include "openvino/op/is_nan.hpp"
+#include "openvino/op/less.hpp"
+#include "openvino/op/less_eq.hpp"
+#include "openvino/op/not_equal.hpp"
 
 using namespace ov;
 
@@ -41,7 +41,11 @@ class ReferenceComparisonLayerTest : public testing::TestWithParam<RefComparison
 public:
     void SetUp() override {
         const auto& params = GetParam();
-        function = CreateFunction(params.compType, params.input1.shape, params.input2.shape, params.input1.type, params.expected.type);
+        function = CreateFunction(params.compType,
+                                  params.input1.shape,
+                                  params.input2.shape,
+                                  params.input1.type,
+                                  params.expected.type);
         inputData = {params.input1.data, params.input2.data};
         refOutData = {params.expected.data};
     }
@@ -57,54 +61,56 @@ class ReferenceComparisonLayerTest : public testing::TestWithParam<RefComparison
     }
 
 private:
-    static std::shared_ptr<ov::Model> CreateFunction(ComparisonTypes comp_op_type, const ov::PartialShape& input_shape1,
-                                                            const ov::PartialShape& input_shape2, const ov::element::Type& input_type,
-                                                            const ov::element::Type& expected_output_type) {
+    static std::shared_ptr<ov::Model> CreateFunction(ComparisonTypes comp_op_type,
+                                                     const ov::PartialShape& input_shape1,
+                                                     const ov::PartialShape& input_shape2,
+                                                     const ov::element::Type& input_type,
+                                                     const ov::element::Type& expected_output_type) {
         const auto in0 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         std::shared_ptr<ov::Node> comp;
         switch (comp_op_type) {
         case ComparisonTypes::EQUAL: {
-            comp =  std::make_shared<ov::op::v1::Equal>(in0, in1);
+            comp = std::make_shared<ov::op::v1::Equal>(in0, in1);
             break;
         }
         case ComparisonTypes::NOT_EQUAL: {
-            comp =  std::make_shared<ov::op::v1::NotEqual>(in0, in1);
+            comp = std::make_shared<ov::op::v1::NotEqual>(in0, in1);
             break;
         }
         case ComparisonTypes::GREATER: {
-            comp =  std::make_shared<ov::op::v1::Greater>(in0, in1);
+            comp = std::make_shared<ov::op::v1::Greater>(in0, in1);
             break;
         }
         case ComparisonTypes::GREATER_EQUAL: {
-            comp =  std::make_shared<ov::op::v1::GreaterEqual>(in0, in1);
+            comp = std::make_shared<ov::op::v1::GreaterEqual>(in0, in1);
             break;
         }
         case ComparisonTypes::IS_FINITE: {
-            comp =  std::make_shared<ov::op::v10::IsFinite>(in0);
+            comp = std::make_shared<ov::op::v10::IsFinite>(in0);
             break;
         }
         case ComparisonTypes::IS_INF: {
-            comp =  std::make_shared<ov::op::v10::IsInf>(in0);
+            comp = std::make_shared<ov::op::v10::IsInf>(in0);
             break;
         }
         case ComparisonTypes::IS_NAN: {
-            comp =  std::make_shared<ov::op::v10::IsNaN>(in0);
+            comp = std::make_shared<ov::op::v10::IsNaN>(in0);
             break;
         }
         case ComparisonTypes::LESS: {
-            comp =  std::make_shared<ov::op::v1::Less>(in0, in1);
+            comp = std::make_shared<ov::op::v1::Less>(in0, in1);
             break;
         }
         case ComparisonTypes::LESS_EQUAL: {
-            comp =  std::make_shared<ov::op::v1::LessEqual>(in0, in1);
+            comp = std::make_shared<ov::op::v1::LessEqual>(in0, in1);
             break;
         }
         default: {
             throw std::runtime_error("Incorrect type of Comparison operation");
         }
         }
-        return std::make_shared<ov::Model>(ov::NodeVector {comp}, ov::ParameterVector {in0, in1});
+        return std::make_shared<ov::Model>(ov::NodeVector{comp}, ov::ParameterVector{in0, in1});
     }
 };
 }  // namespace ComparisonOpsRefTestDefinitions
diff --git a/src/plugins/template/tests/functional/op_reference/concat.cpp b/src/plugins/template/tests/functional/op_reference/concat.cpp
index 6f71ca01bc0a1c..b11a3d1e4a4658 100644
--- a/src/plugins/template/tests/functional/op_reference/concat.cpp
+++ b/src/plugins/template/tests/functional/op_reference/concat.cpp
@@ -4,20 +4,28 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct ConcatParams {
-    ConcatParams(
-        const PartialShape& dynamicShape,
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B,
-        const reference_tests::Tensor& C, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        dynamicShape(dynamicShape), A(A), B(B), C(C), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParams(const PartialShape& dynamicShape,
+                 const reference_tests::Tensor& A,
+                 const reference_tests::Tensor& B,
+                 const reference_tests::Tensor& C,
+                 const int32_t axis,
+                 const reference_tests::Tensor& expected,
+                 const std::string& testcaseName = "")
+        : dynamicShape(dynamicShape),
+          A(A),
+          B(B),
+          C(C),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     PartialShape dynamicShape;
     reference_tests::Tensor A;
@@ -70,7 +78,8 @@ class ReferenceConcatTest : public testing::TestWithParam<ConcatParams>, public
             B = std::make_shared<opset1::Parameter>(params.B.type, params.B.shape);
             C = std::make_shared<opset1::Parameter>(params.C.type, params.C.shape);
         }
-        auto f = std::make_shared<Model>(std::make_shared<opset1::Concat>(NodeVector{A, B, C}, params.axis), ParameterVector{A, B, C});
+        auto f = std::make_shared<Model>(std::make_shared<opset1::Concat>(NodeVector{A, B, C}, params.axis),
+                                         ParameterVector{A, B, C});
         return f;
     }
 };
@@ -82,7 +91,7 @@ TEST_P(ReferenceConcatTest, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParams> params {
+    std::vector<ConcatParams> params{
         ConcatParams(
             PartialShape::dynamic(),
             reference_tests::Tensor(ET, {2, 2}, std::vector<T>{2, 4, 8, 16}),
@@ -107,36 +116,33 @@ std::vector<ConcatParams> generateParams() {
             0,
             reference_tests::Tensor(ET, {8, 2}, std::vector<T>{2, 4, 8, 16, 1, 2, 4, 8, 16, 32, 2, 3, 5, 7, 11, 13}),
             "concat_matrix_rowwise"),
-        ConcatParams(
-            {},
-            reference_tests::Tensor(ET, {4}, std::vector<T>{2, 4, 8, 16}),
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 4, 8, 16, 32}),
-            reference_tests::Tensor(ET, {2}, std::vector<T>{18, 19}),
-            0,
-            reference_tests::Tensor(ET, {12}, std::vector<T>{2, 4, 8, 16, 1, 2, 4, 8, 16, 32, 18, 19}),
-            "concat_vector"),
-        ConcatParams(
-            {},
-            reference_tests::Tensor(ET, {1, 1, 1, 1}, std::vector<T>{1}),
-            reference_tests::Tensor(ET, {1, 1, 1, 1}, std::vector<T>{2}),
-            reference_tests::Tensor(ET, {1, 1, 1, 1}, std::vector<T>{3}),
-            0,
-            reference_tests::Tensor(ET, {3, 1, 1, 1}, std::vector<T>{1, 2, 3}),
-            "concat_4d_tensor"),
-        ConcatParams(
-            {},
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{1}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{2}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{3}),
-            0,
-            reference_tests::Tensor(ET, {3, 1}, std::vector<T>{1, 2, 3}),
-            "concat_2d_tensor"),
+        ConcatParams({},
+                     reference_tests::Tensor(ET, {4}, std::vector<T>{2, 4, 8, 16}),
+                     reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 4, 8, 16, 32}),
+                     reference_tests::Tensor(ET, {2}, std::vector<T>{18, 19}),
+                     0,
+                     reference_tests::Tensor(ET, {12}, std::vector<T>{2, 4, 8, 16, 1, 2, 4, 8, 16, 32, 18, 19}),
+                     "concat_vector"),
+        ConcatParams({},
+                     reference_tests::Tensor(ET, {1, 1, 1, 1}, std::vector<T>{1}),
+                     reference_tests::Tensor(ET, {1, 1, 1, 1}, std::vector<T>{2}),
+                     reference_tests::Tensor(ET, {1, 1, 1, 1}, std::vector<T>{3}),
+                     0,
+                     reference_tests::Tensor(ET, {3, 1, 1, 1}, std::vector<T>{1, 2, 3}),
+                     "concat_4d_tensor"),
+        ConcatParams({},
+                     reference_tests::Tensor(ET, {1, 1}, std::vector<T>{1}),
+                     reference_tests::Tensor(ET, {1, 1}, std::vector<T>{2}),
+                     reference_tests::Tensor(ET, {1, 1}, std::vector<T>{3}),
+                     0,
+                     reference_tests::Tensor(ET, {3, 1}, std::vector<T>{1, 2, 3}),
+                     "concat_2d_tensor"),
     };
     return params;
 }
 
 std::vector<ConcatParams> generateCombinedParams() {
-    const std::vector<std::vector<ConcatParams>> generatedParams {
+    const std::vector<std::vector<ConcatParams>> generatedParams{
         generateParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
         generateParams<element::Type_t::i32>(),
@@ -158,20 +164,24 @@ std::vector<ConcatParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceConcatTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceConcatTest::getTestCaseName);
 
 //// concat_vector_params, concat_vector_large
 
 struct ConcatParamsVectorLarge {
-    ConcatParamsVectorLarge(const uint32_t numInputs, const std::string& testcaseName = "") :
-        numInputs(numInputs), testcaseName(testcaseName) {}
+    ConcatParamsVectorLarge(const uint32_t numInputs, const std::string& testcaseName = "")
+        : numInputs(numInputs),
+          testcaseName(testcaseName) {}
 
     uint32_t numInputs;
     std::string testcaseName;
 };
 
-class ReferenceConcatTestVectorLarge : public testing::TestWithParam<ConcatParamsVectorLarge>, public CommonReferenceTest {
+class ReferenceConcatTestVectorLarge : public testing::TestWithParam<ConcatParamsVectorLarge>,
+                                       public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -213,7 +223,7 @@ TEST_P(ReferenceConcatTestVectorLarge, CompareWithRefs) {
 }
 
 std::vector<ConcatParamsVectorLarge> generateParamsVectorLarge() {
-    std::vector<ConcatParamsVectorLarge> params {
+    std::vector<ConcatParamsVectorLarge> params{
         ConcatParamsVectorLarge(100, "concat_vector_large_100"),
         ConcatParamsVectorLarge(128, "concat_vector_large_128"),
         ConcatParamsVectorLarge(999, "concat_vector_large_999"),
@@ -222,7 +232,7 @@ std::vector<ConcatParamsVectorLarge> generateParamsVectorLarge() {
 }
 
 std::vector<ConcatParamsVectorLarge> generateCombinedParamsVectorLarge() {
-    const std::vector<std::vector<ConcatParamsVectorLarge>> generatedParams {
+    const std::vector<std::vector<ConcatParamsVectorLarge>> generatedParams{
         generateParamsVectorLarge(),
     };
     std::vector<ConcatParamsVectorLarge> combinedParams;
@@ -233,16 +243,28 @@ std::vector<ConcatParamsVectorLarge> generateCombinedParamsVectorLarge() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestVectorLarge,
-    testing::ValuesIn(generateCombinedParamsVectorLarge()), ReferenceConcatTestVectorLarge::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestVectorLarge,
+                         testing::ValuesIn(generateCombinedParamsVectorLarge()),
+                         ReferenceConcatTestVectorLarge::getTestCaseName);
 
 //// concat_in_place_2d_tensor
 
 struct ConcatParamsInPlace2dTensor {
-    ConcatParamsInPlace2dTensor(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const reference_tests::Tensor& C, const reference_tests::Tensor& D, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), C(C), D(D), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsInPlace2dTensor(const reference_tests::Tensor& A,
+                                const reference_tests::Tensor& B,
+                                const reference_tests::Tensor& C,
+                                const reference_tests::Tensor& D,
+                                const int32_t axis,
+                                const reference_tests::Tensor& expected,
+                                const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          C(C),
+          D(D),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -253,7 +275,8 @@ struct ConcatParamsInPlace2dTensor {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestInPlace2dTensor : public testing::TestWithParam<ConcatParamsInPlace2dTensor>, public CommonReferenceTest {
+class ReferenceConcatTestInPlace2dTensor : public testing::TestWithParam<ConcatParamsInPlace2dTensor>,
+                                           public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -293,9 +316,9 @@ class ReferenceConcatTestInPlace2dTensor : public testing::TestWithParam<ConcatP
         const auto D = std::make_shared<opset1::Parameter>(params.D.type, params.D.shape);
         const auto add2 = std::make_shared<opset1::Add>(C, D);
         const auto subtract = std::make_shared<opset1::Subtract>(C, A);
-        const auto f = std::make_shared<Model>(
-            std::make_shared<opset1::Concat>(NodeVector{add1, add2, subtract}, params.axis),
-                                             ParameterVector{A, B, C, D});
+        const auto f =
+            std::make_shared<Model>(std::make_shared<opset1::Concat>(NodeVector{add1, add2, subtract}, params.axis),
+                                    ParameterVector{A, B, C, D});
         return f;
     }
 };
@@ -307,21 +330,20 @@ TEST_P(ReferenceConcatTestInPlace2dTensor, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsInPlace2dTensor> generateParamsInPlace2dTensor() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsInPlace2dTensor> params {
-        ConcatParamsInPlace2dTensor(
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{1}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{2}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{3}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{4}),
-            0,
-            reference_tests::Tensor(ET, {3, 1}, std::vector<T>{3, 7, 2}),
-            "concat_in_place_2d_tensor"),
+    std::vector<ConcatParamsInPlace2dTensor> params{
+        ConcatParamsInPlace2dTensor(reference_tests::Tensor(ET, {1, 1}, std::vector<T>{1}),
+                                    reference_tests::Tensor(ET, {1, 1}, std::vector<T>{2}),
+                                    reference_tests::Tensor(ET, {1, 1}, std::vector<T>{3}),
+                                    reference_tests::Tensor(ET, {1, 1}, std::vector<T>{4}),
+                                    0,
+                                    reference_tests::Tensor(ET, {3, 1}, std::vector<T>{3, 7, 2}),
+                                    "concat_in_place_2d_tensor"),
     };
     return params;
 }
 
 std::vector<ConcatParamsInPlace2dTensor> generateCombinedParamsInPlace2dTensor() {
-    const std::vector<std::vector<ConcatParamsInPlace2dTensor>> generatedParams {
+    const std::vector<std::vector<ConcatParamsInPlace2dTensor>> generatedParams{
         generateParamsInPlace2dTensor<element::Type_t::i32>(),
         generateParamsInPlace2dTensor<element::Type_t::i64>(),
         generateParamsInPlace2dTensor<element::Type_t::u32>(),
@@ -338,16 +360,28 @@ std::vector<ConcatParamsInPlace2dTensor> generateCombinedParamsInPlace2dTensor()
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestInPlace2dTensor,
-    testing::ValuesIn(generateCombinedParamsInPlace2dTensor()), ReferenceConcatTestInPlace2dTensor::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestInPlace2dTensor,
+                         testing::ValuesIn(generateCombinedParamsInPlace2dTensor()),
+                         ReferenceConcatTestInPlace2dTensor::getTestCaseName);
 
 //// concat_in_place_propagate_2d_tensor
 
 struct ConcatParamsInPlacePropagate2dTensor {
-    ConcatParamsInPlacePropagate2dTensor(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const reference_tests::Tensor& C, const reference_tests::Tensor& D, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), C(C), D(D), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsInPlacePropagate2dTensor(const reference_tests::Tensor& A,
+                                         const reference_tests::Tensor& B,
+                                         const reference_tests::Tensor& C,
+                                         const reference_tests::Tensor& D,
+                                         const int32_t axis,
+                                         const reference_tests::Tensor& expected,
+                                         const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          C(C),
+          D(D),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -358,7 +392,8 @@ struct ConcatParamsInPlacePropagate2dTensor {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestInPlacePropagate2dTensor : public testing::TestWithParam<ConcatParamsInPlacePropagate2dTensor>, public CommonReferenceTest {
+class ReferenceConcatTestInPlacePropagate2dTensor : public testing::TestWithParam<ConcatParamsInPlacePropagate2dTensor>,
+                                                    public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -399,9 +434,9 @@ class ReferenceConcatTestInPlacePropagate2dTensor : public testing::TestWithPara
         const auto add2 = std::make_shared<opset1::Add>(C, D);
         const auto concat1 = std::make_shared<opset1::Concat>(NodeVector{add1, add2}, params.axis);
         const auto subtract = std::make_shared<opset1::Subtract>(C, A);
-        const auto f = std::make_shared<Model>(
-            std::make_shared<opset1::Concat>(NodeVector{concat1, subtract}, params.axis),
-                                             ParameterVector{A, B, C, D});
+        const auto f =
+            std::make_shared<Model>(std::make_shared<opset1::Concat>(NodeVector{concat1, subtract}, params.axis),
+                                    ParameterVector{A, B, C, D});
         return f;
     }
 };
@@ -413,21 +448,20 @@ TEST_P(ReferenceConcatTestInPlacePropagate2dTensor, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsInPlacePropagate2dTensor> generateParamsInPlacePropagate2dTensor() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsInPlacePropagate2dTensor> params {
-        ConcatParamsInPlacePropagate2dTensor(
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{1}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{2}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{3}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{4}),
-            0,
-            reference_tests::Tensor(ET, {3, 1}, std::vector<T>{3, 7, 2}),
-            "concat_in_place_2d_tensor"),
+    std::vector<ConcatParamsInPlacePropagate2dTensor> params{
+        ConcatParamsInPlacePropagate2dTensor(reference_tests::Tensor(ET, {1, 1}, std::vector<T>{1}),
+                                             reference_tests::Tensor(ET, {1, 1}, std::vector<T>{2}),
+                                             reference_tests::Tensor(ET, {1, 1}, std::vector<T>{3}),
+                                             reference_tests::Tensor(ET, {1, 1}, std::vector<T>{4}),
+                                             0,
+                                             reference_tests::Tensor(ET, {3, 1}, std::vector<T>{3, 7, 2}),
+                                             "concat_in_place_2d_tensor"),
     };
     return params;
 }
 
 std::vector<ConcatParamsInPlacePropagate2dTensor> generateCombinedParamsInPlacePropagate2dTensor() {
-    const std::vector<std::vector<ConcatParamsInPlacePropagate2dTensor>> generatedParams {
+    const std::vector<std::vector<ConcatParamsInPlacePropagate2dTensor>> generatedParams{
         generateParamsInPlacePropagate2dTensor<element::Type_t::i32>(),
         generateParamsInPlacePropagate2dTensor<element::Type_t::i64>(),
         generateParamsInPlacePropagate2dTensor<element::Type_t::u32>(),
@@ -444,16 +478,24 @@ std::vector<ConcatParamsInPlacePropagate2dTensor> generateCombinedParamsInPlaceP
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestInPlacePropagate2dTensor,
-    testing::ValuesIn(generateCombinedParamsInPlacePropagate2dTensor()), ReferenceConcatTestInPlacePropagate2dTensor::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestInPlacePropagate2dTensor,
+                         testing::ValuesIn(generateCombinedParamsInPlacePropagate2dTensor()),
+                         ReferenceConcatTestInPlacePropagate2dTensor::getTestCaseName);
 
 //// concat_in_place_tree_1
 
 struct ConcatParamsInPlaceTree1 {
-    ConcatParamsInPlaceTree1(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsInPlaceTree1(const reference_tests::Tensor& A,
+                             const reference_tests::Tensor& B,
+                             const int32_t axis,
+                             const reference_tests::Tensor& expected,
+                             const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -462,7 +504,8 @@ struct ConcatParamsInPlaceTree1 {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestInPlaceTree1 : public testing::TestWithParam<ConcatParamsInPlaceTree1>, public CommonReferenceTest {
+class ReferenceConcatTestInPlaceTree1 : public testing::TestWithParam<ConcatParamsInPlaceTree1>,
+                                        public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -496,8 +539,7 @@ class ReferenceConcatTestInPlaceTree1 : public testing::TestWithParam<ConcatPara
         const auto add1 = std::make_shared<opset1::Add>(A, B);
         const auto add2 = std::make_shared<opset1::Add>(A, B);
         const auto concat = std::make_shared<opset1::Concat>(NodeVector{add1, add2}, params.axis);
-        const auto f = std::make_shared<Model>(std::make_shared<opset1::Add>(concat, concat),
-                                                  ParameterVector{A, B});
+        const auto f = std::make_shared<Model>(std::make_shared<opset1::Add>(concat, concat), ParameterVector{A, B});
         return f;
     }
 };
@@ -509,19 +551,18 @@ TEST_P(ReferenceConcatTestInPlaceTree1, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsInPlaceTree1> generateParamsInPlaceTree1() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsInPlaceTree1> params {
-        ConcatParamsInPlaceTree1(
-            reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
-            reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
-            1,
-            reference_tests::Tensor(ET, {1, 4, 2}, std::vector<T>{4, 4, 4, 4, 4, 4, 4, 4}),
-            "concat_in_place_tree_1"),
+    std::vector<ConcatParamsInPlaceTree1> params{
+        ConcatParamsInPlaceTree1(reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
+                                 reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
+                                 1,
+                                 reference_tests::Tensor(ET, {1, 4, 2}, std::vector<T>{4, 4, 4, 4, 4, 4, 4, 4}),
+                                 "concat_in_place_tree_1"),
     };
     return params;
 }
 
 std::vector<ConcatParamsInPlaceTree1> generateCombinedParamsInPlaceTree1() {
-    const std::vector<std::vector<ConcatParamsInPlaceTree1>> generatedParams {
+    const std::vector<std::vector<ConcatParamsInPlaceTree1>> generatedParams{
         generateParamsInPlaceTree1<element::Type_t::i32>(),
         generateParamsInPlaceTree1<element::Type_t::i64>(),
         generateParamsInPlaceTree1<element::Type_t::u32>(),
@@ -538,16 +579,24 @@ std::vector<ConcatParamsInPlaceTree1> generateCombinedParamsInPlaceTree1() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestInPlaceTree1,
-    testing::ValuesIn(generateCombinedParamsInPlaceTree1()), ReferenceConcatTestInPlaceTree1::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestInPlaceTree1,
+                         testing::ValuesIn(generateCombinedParamsInPlaceTree1()),
+                         ReferenceConcatTestInPlaceTree1::getTestCaseName);
 
 //// concat_in_place_tree_2
 
 struct ConcatParamsInPlaceTree2 {
-    ConcatParamsInPlaceTree2(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsInPlaceTree2(const reference_tests::Tensor& A,
+                             const reference_tests::Tensor& B,
+                             const int32_t axis,
+                             const reference_tests::Tensor& expected,
+                             const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -556,7 +605,8 @@ struct ConcatParamsInPlaceTree2 {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestInPlaceTree2 : public testing::TestWithParam<ConcatParamsInPlaceTree2>, public CommonReferenceTest {
+class ReferenceConcatTestInPlaceTree2 : public testing::TestWithParam<ConcatParamsInPlaceTree2>,
+                                        public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -592,8 +642,8 @@ class ReferenceConcatTestInPlaceTree2 : public testing::TestWithParam<ConcatPara
         const auto concat1 = std::make_shared<opset1::Concat>(NodeVector{add1, add2}, params.axis);
         const auto concat2 = std::make_shared<opset1::Concat>(NodeVector{add1, add2}, params.axis);
         const auto concat12 = std::make_shared<opset1::Concat>(NodeVector{concat1, concat2}, params.axis);
-        const auto f = std::make_shared<Model>(std::make_shared<opset1::Add>(concat12, concat12),
-                                                  ParameterVector{A, B});
+        const auto f =
+            std::make_shared<Model>(std::make_shared<opset1::Add>(concat12, concat12), ParameterVector{A, B});
         return f;
     }
 };
@@ -605,20 +655,19 @@ TEST_P(ReferenceConcatTestInPlaceTree2, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsInPlaceTree2> generateParamsInPlaceTree2() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsInPlaceTree2> params {
+    std::vector<ConcatParamsInPlaceTree2> params{
         ConcatParamsInPlaceTree2(
             reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
             reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
             1,
-            reference_tests::Tensor(ET, {1, 8, 2}, std::vector<T>{4, 4, 4, 4, 4, 4, 4, 4,
-                                                 4, 4, 4, 4, 4, 4, 4, 4}),
+            reference_tests::Tensor(ET, {1, 8, 2}, std::vector<T>{4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4}),
             "concat_in_place_tree_2"),
     };
     return params;
 }
 
 std::vector<ConcatParamsInPlaceTree2> generateCombinedParamsInPlaceTree2() {
-    const std::vector<std::vector<ConcatParamsInPlaceTree2>> generatedParams {
+    const std::vector<std::vector<ConcatParamsInPlaceTree2>> generatedParams{
         generateParamsInPlaceTree2<element::Type_t::i32>(),
         generateParamsInPlaceTree2<element::Type_t::i64>(),
         generateParamsInPlaceTree2<element::Type_t::u32>(),
@@ -635,16 +684,24 @@ std::vector<ConcatParamsInPlaceTree2> generateCombinedParamsInPlaceTree2() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestInPlaceTree2,
-    testing::ValuesIn(generateCombinedParamsInPlaceTree2()), ReferenceConcatTestInPlaceTree2::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestInPlaceTree2,
+                         testing::ValuesIn(generateCombinedParamsInPlaceTree2()),
+                         ReferenceConcatTestInPlaceTree2::getTestCaseName);
 
 //// concat_in_place_tree_3
 
 struct ConcatParamsInPlaceTree3 {
-    ConcatParamsInPlaceTree3(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsInPlaceTree3(const reference_tests::Tensor& A,
+                             const reference_tests::Tensor& B,
+                             const int32_t axis,
+                             const reference_tests::Tensor& expected,
+                             const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -653,7 +710,8 @@ struct ConcatParamsInPlaceTree3 {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestInPlaceTree3 : public testing::TestWithParam<ConcatParamsInPlaceTree3>, public CommonReferenceTest {
+class ReferenceConcatTestInPlaceTree3 : public testing::TestWithParam<ConcatParamsInPlaceTree3>,
+                                        public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -691,8 +749,8 @@ class ReferenceConcatTestInPlaceTree3 : public testing::TestWithParam<ConcatPara
         const auto concat12 = std::make_shared<opset1::Concat>(NodeVector{concat1, concat2}, params.axis);
         const auto concat34 = std::make_shared<opset1::Concat>(NodeVector{concat3, concat4}, params.axis);
         const auto concat14 = std::make_shared<opset1::Concat>(NodeVector{concat12, concat34}, params.axis);
-        const auto f = std::make_shared<Model>(std::make_shared<opset1::Add>(concat14, concat14),
-                                                  ParameterVector{A, B});
+        const auto f =
+            std::make_shared<Model>(std::make_shared<opset1::Add>(concat14, concat14), ParameterVector{A, B});
         return f;
     }
 };
@@ -704,22 +762,20 @@ TEST_P(ReferenceConcatTestInPlaceTree3, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsInPlaceTree3> generateParamsInPlaceTree3() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsInPlaceTree3> params {
+    std::vector<ConcatParamsInPlaceTree3> params{
         ConcatParamsInPlaceTree3(
             reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
             reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
             1,
-            reference_tests::Tensor(ET, {1, 16, 2}, std::vector<T>{2, 2, 2, 2, 2, 2, 2, 2,
-                                                  2, 2, 2, 2, 2, 2, 2, 2,
-                                                  2, 2, 2, 2, 2, 2, 2, 2,
-                                                  2, 2, 2, 2, 2, 2, 2, 2}),
+            reference_tests::Tensor(ET, {1, 16, 2}, std::vector<T>{2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,
+                                                                   2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2}),
             "concat_in_place_tree_3"),
     };
     return params;
 }
 
 std::vector<ConcatParamsInPlaceTree3> generateCombinedParamsInPlaceTree3() {
-    const std::vector<std::vector<ConcatParamsInPlaceTree3>> generatedParams {
+    const std::vector<std::vector<ConcatParamsInPlaceTree3>> generatedParams{
         generateParamsInPlaceTree3<element::Type_t::i32>(),
         generateParamsInPlaceTree3<element::Type_t::i64>(),
         generateParamsInPlaceTree3<element::Type_t::u32>(),
@@ -736,16 +792,24 @@ std::vector<ConcatParamsInPlaceTree3> generateCombinedParamsInPlaceTree3() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestInPlaceTree3,
-    testing::ValuesIn(generateCombinedParamsInPlaceTree3()), ReferenceConcatTestInPlaceTree3::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestInPlaceTree3,
+                         testing::ValuesIn(generateCombinedParamsInPlaceTree3()),
+                         ReferenceConcatTestInPlaceTree3::getTestCaseName);
 
 //// concat_in_place_add_concat
 
 struct ConcatParamsInPlaceAddConcat {
-    ConcatParamsInPlaceAddConcat(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsInPlaceAddConcat(const reference_tests::Tensor& A,
+                                 const reference_tests::Tensor& B,
+                                 const int32_t axis,
+                                 const reference_tests::Tensor& expected,
+                                 const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -754,7 +818,8 @@ struct ConcatParamsInPlaceAddConcat {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestInPlaceAddConcat : public testing::TestWithParam<ConcatParamsInPlaceAddConcat>, public CommonReferenceTest {
+class ReferenceConcatTestInPlaceAddConcat : public testing::TestWithParam<ConcatParamsInPlaceAddConcat>,
+                                            public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -801,19 +866,18 @@ TEST_P(ReferenceConcatTestInPlaceAddConcat, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsInPlaceAddConcat> generateParamsInPlaceAddConcat() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsInPlaceAddConcat> params {
-        ConcatParamsInPlaceAddConcat(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 1, 1, 1}),
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 1, 1, 1}),
-            0,
-            reference_tests::Tensor(ET, {4, 2}, std::vector<T>{4, 4, 4, 4, 8, 8, 8, 8}),
-            "concat_in_place_add_concat"),
+    std::vector<ConcatParamsInPlaceAddConcat> params{
+        ConcatParamsInPlaceAddConcat(reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 1, 1, 1}),
+                                     reference_tests::Tensor(ET, {2, 2}, std::vector<T>{1, 1, 1, 1}),
+                                     0,
+                                     reference_tests::Tensor(ET, {4, 2}, std::vector<T>{4, 4, 4, 4, 8, 8, 8, 8}),
+                                     "concat_in_place_add_concat"),
     };
     return params;
 }
 
 std::vector<ConcatParamsInPlaceAddConcat> generateCombinedParamsInPlaceAddConcat() {
-    const std::vector<std::vector<ConcatParamsInPlaceAddConcat>> generatedParams {
+    const std::vector<std::vector<ConcatParamsInPlaceAddConcat>> generatedParams{
         generateParamsInPlaceAddConcat<element::Type_t::i32>(),
         generateParamsInPlaceAddConcat<element::Type_t::i64>(),
         generateParamsInPlaceAddConcat<element::Type_t::u32>(),
@@ -830,16 +894,24 @@ std::vector<ConcatParamsInPlaceAddConcat> generateCombinedParamsInPlaceAddConcat
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestInPlaceAddConcat,
-    testing::ValuesIn(generateCombinedParamsInPlaceAddConcat()), ReferenceConcatTestInPlaceAddConcat::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestInPlaceAddConcat,
+                         testing::ValuesIn(generateCombinedParamsInPlaceAddConcat()),
+                         ReferenceConcatTestInPlaceAddConcat::getTestCaseName);
 
 //// concat_in_place_add_concat_2
 
 struct ConcatParamsInPlaceAddConcat2 {
-    ConcatParamsInPlaceAddConcat2(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsInPlaceAddConcat2(const reference_tests::Tensor& A,
+                                  const reference_tests::Tensor& B,
+                                  const int32_t axis,
+                                  const reference_tests::Tensor& expected,
+                                  const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -848,7 +920,8 @@ struct ConcatParamsInPlaceAddConcat2 {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestInPlaceAddConcat2 : public testing::TestWithParam<ConcatParamsInPlaceAddConcat2>, public CommonReferenceTest {
+class ReferenceConcatTestInPlaceAddConcat2 : public testing::TestWithParam<ConcatParamsInPlaceAddConcat2>,
+                                             public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -899,7 +972,7 @@ TEST_P(ReferenceConcatTestInPlaceAddConcat2, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsInPlaceAddConcat2> generateParamsInPlaceAddConcat2() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsInPlaceAddConcat2> params {
+    std::vector<ConcatParamsInPlaceAddConcat2> params{
         ConcatParamsInPlaceAddConcat2(
             reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
             reference_tests::Tensor(ET, {1, 2, 2}, std::vector<T>{1, 1, 1, 1}),
@@ -911,7 +984,7 @@ std::vector<ConcatParamsInPlaceAddConcat2> generateParamsInPlaceAddConcat2() {
 }
 
 std::vector<ConcatParamsInPlaceAddConcat2> generateCombinedParamsInPlaceAddConcat2() {
-    const std::vector<std::vector<ConcatParamsInPlaceAddConcat2>> generatedParams {
+    const std::vector<std::vector<ConcatParamsInPlaceAddConcat2>> generatedParams{
         generateParamsInPlaceAddConcat2<element::Type_t::i32>(),
         generateParamsInPlaceAddConcat2<element::Type_t::i64>(),
         generateParamsInPlaceAddConcat2<element::Type_t::u32>(),
@@ -928,16 +1001,26 @@ std::vector<ConcatParamsInPlaceAddConcat2> generateCombinedParamsInPlaceAddConca
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestInPlaceAddConcat2,
-    testing::ValuesIn(generateCombinedParamsInPlaceAddConcat2()), ReferenceConcatTestInPlaceAddConcat2::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestInPlaceAddConcat2,
+                         testing::ValuesIn(generateCombinedParamsInPlaceAddConcat2()),
+                         ReferenceConcatTestInPlaceAddConcat2::getTestCaseName);
 
 //// concat_5d
 
 struct ConcatParams5d {
-    ConcatParams5d(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const reference_tests::Tensor& C, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), C(C), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParams5d(const reference_tests::Tensor& A,
+                   const reference_tests::Tensor& B,
+                   const reference_tests::Tensor& C,
+                   const int32_t axis,
+                   const reference_tests::Tensor& expected,
+                   const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          C(C),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -994,58 +1077,71 @@ TEST_P(ReferenceConcatTest5d, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParams5d> generateParams5d() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParams5d> params {
+    std::vector<ConcatParams5d> params{
         ConcatParams5d(
-            reference_tests::Tensor(ET, {2, 3, 4, 3, 2}, []() -> std::vector<T> {
-                std::vector<T> data(2 * 3 * 4 * 3 * 2);
-                for (int i = 0; i < 2 * 3 * 4 * 3 * 2; i++) {
-                     data[i] = static_cast<T>(i + 1);
-                }
-                return data;
-            }()),
-            reference_tests::Tensor(ET, {2, 3, 3, 3, 2}, []() -> std::vector<T> {
-                std::vector<T> data(2 * 3 * 3 * 3 * 2);
-                for (int i = 0; i < 2 * 3 * 3 * 3 * 2; i++) {
-                    data[i] = 1000 + static_cast<T>(i + 1);
-                }
-            return data;}()),
-            reference_tests::Tensor(ET, {2, 3, 2, 3, 2}, []() -> std::vector<T> {
-                std::vector<T> data(2 * 3 * 2 * 3 * 2);
-                for (int i = 0; i < 2 * 3 * 2 * 3 * 2; i++) {
-                    data[i] = 2000 + static_cast<T>(i + 1);
-                }
-            return data;}()),
+            reference_tests::Tensor(ET,
+                                    {2, 3, 4, 3, 2},
+                                    []() -> std::vector<T> {
+                                        std::vector<T> data(2 * 3 * 4 * 3 * 2);
+                                        for (int i = 0; i < 2 * 3 * 4 * 3 * 2; i++) {
+                                            data[i] = static_cast<T>(i + 1);
+                                        }
+                                        return data;
+                                    }()),
+            reference_tests::Tensor(ET,
+                                    {2, 3, 3, 3, 2},
+                                    []() -> std::vector<T> {
+                                        std::vector<T> data(2 * 3 * 3 * 3 * 2);
+                                        for (int i = 0; i < 2 * 3 * 3 * 3 * 2; i++) {
+                                            data[i] = 1000 + static_cast<T>(i + 1);
+                                        }
+                                        return data;
+                                    }()),
+            reference_tests::Tensor(ET,
+                                    {2, 3, 2, 3, 2},
+                                    []() -> std::vector<T> {
+                                        std::vector<T> data(2 * 3 * 2 * 3 * 2);
+                                        for (int i = 0; i < 2 * 3 * 2 * 3 * 2; i++) {
+                                            data[i] = 2000 + static_cast<T>(i + 1);
+                                        }
+                                        return data;
+                                    }()),
             2,
-            reference_tests::Tensor(ET, {2, 3, 9, 3, 2}, std::vector<T>{
-                1.,    2.,    3.,    4.,    5.,    6.,    7.,    8.,    9.,    10.,   11.,   12.,   13.,   14.,   15.,
-                16.,   17.,   18.,   19.,   20.,   21.,   22.,   23.,   24.,   1001., 1002., 1003., 1004., 1005., 1006.,
-                1007., 1008., 1009., 1010., 1011., 1012., 1013., 1014., 1015., 1016., 1017., 1018., 2001., 2002., 2003.,
-                2004., 2005., 2006., 2007., 2008., 2009., 2010., 2011., 2012., 25.,   26.,   27.,   28.,   29.,   30.,
-                31.,   32.,   33.,   34.,   35.,   36.,   37.,   38.,   39.,   40.,   41.,   42.,   43.,   44.,   45.,
-                46.,   47.,   48.,   1019., 1020., 1021., 1022., 1023., 1024., 1025., 1026., 1027., 1028., 1029., 1030.,
-                1031., 1032., 1033., 1034., 1035., 1036., 2013., 2014., 2015., 2016., 2017., 2018., 2019., 2020., 2021.,
-                2022., 2023., 2024., 49.,   50.,   51.,   52.,   53.,   54.,   55.,   56.,   57.,   58.,   59.,   60.,
-                61.,   62.,   63.,   64.,   65.,   66.,   67.,   68.,   69.,   70.,   71.,   72.,   1037., 1038., 1039.,
-                1040., 1041., 1042., 1043., 1044., 1045., 1046., 1047., 1048., 1049., 1050., 1051., 1052., 1053., 1054.,
-                2025., 2026., 2027., 2028., 2029., 2030., 2031., 2032., 2033., 2034., 2035., 2036., 73.,   74.,   75.,
-                76.,   77.,   78.,   79.,   80.,   81.,   82.,   83.,   84.,   85.,   86.,   87.,   88.,   89.,   90.,
-                91.,   92.,   93.,   94.,   95.,   96.,   1055., 1056., 1057., 1058., 1059., 1060., 1061., 1062., 1063.,
-                1064., 1065., 1066., 1067., 1068., 1069., 1070., 1071., 1072., 2037., 2038., 2039., 2040., 2041., 2042.,
-                2043., 2044., 2045., 2046., 2047., 2048., 97.,   98.,   99.,   100.,  101.,  102.,  103.,  104.,  105.,
-                106.,  107.,  108.,  109.,  110.,  111.,  112.,  113.,  114.,  115.,  116.,  117.,  118.,  119.,  120.,
-                1073., 1074., 1075., 1076., 1077., 1078., 1079., 1080., 1081., 1082., 1083., 1084., 1085., 1086., 1087.,
-                1088., 1089., 1090., 2049., 2050., 2051., 2052., 2053., 2054., 2055., 2056., 2057., 2058., 2059., 2060.,
-                121.,  122.,  123.,  124.,  125.,  126.,  127.,  128.,  129.,  130.,  131.,  132.,  133.,  134.,  135.,
-                136.,  137.,  138.,  139.,  140.,  141.,  142.,  143.,  144.,  1091., 1092., 1093., 1094., 1095., 1096.,
-                1097., 1098., 1099., 1100., 1101., 1102., 1103., 1104., 1105., 1106., 1107., 1108., 2061., 2062., 2063.,
-                2064., 2065., 2066., 2067., 2068., 2069., 2070., 2071., 2072.}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3, 9, 3, 2},
+                std::vector<T>{
+                    1.,    2.,    3.,    4.,    5.,    6.,    7.,    8.,    9.,    10.,   11.,   12.,   13.,   14.,
+                    15.,   16.,   17.,   18.,   19.,   20.,   21.,   22.,   23.,   24.,   1001., 1002., 1003., 1004.,
+                    1005., 1006., 1007., 1008., 1009., 1010., 1011., 1012., 1013., 1014., 1015., 1016., 1017., 1018.,
+                    2001., 2002., 2003., 2004., 2005., 2006., 2007., 2008., 2009., 2010., 2011., 2012., 25.,   26.,
+                    27.,   28.,   29.,   30.,   31.,   32.,   33.,   34.,   35.,   36.,   37.,   38.,   39.,   40.,
+                    41.,   42.,   43.,   44.,   45.,   46.,   47.,   48.,   1019., 1020., 1021., 1022., 1023., 1024.,
+                    1025., 1026., 1027., 1028., 1029., 1030., 1031., 1032., 1033., 1034., 1035., 1036., 2013., 2014.,
+                    2015., 2016., 2017., 2018., 2019., 2020., 2021., 2022., 2023., 2024., 49.,   50.,   51.,   52.,
+                    53.,   54.,   55.,   56.,   57.,   58.,   59.,   60.,   61.,   62.,   63.,   64.,   65.,   66.,
+                    67.,   68.,   69.,   70.,   71.,   72.,   1037., 1038., 1039., 1040., 1041., 1042., 1043., 1044.,
+                    1045., 1046., 1047., 1048., 1049., 1050., 1051., 1052., 1053., 1054., 2025., 2026., 2027., 2028.,
+                    2029., 2030., 2031., 2032., 2033., 2034., 2035., 2036., 73.,   74.,   75.,   76.,   77.,   78.,
+                    79.,   80.,   81.,   82.,   83.,   84.,   85.,   86.,   87.,   88.,   89.,   90.,   91.,   92.,
+                    93.,   94.,   95.,   96.,   1055., 1056., 1057., 1058., 1059., 1060., 1061., 1062., 1063., 1064.,
+                    1065., 1066., 1067., 1068., 1069., 1070., 1071., 1072., 2037., 2038., 2039., 2040., 2041., 2042.,
+                    2043., 2044., 2045., 2046., 2047., 2048., 97.,   98.,   99.,   100.,  101.,  102.,  103.,  104.,
+                    105.,  106.,  107.,  108.,  109.,  110.,  111.,  112.,  113.,  114.,  115.,  116.,  117.,  118.,
+                    119.,  120.,  1073., 1074., 1075., 1076., 1077., 1078., 1079., 1080., 1081., 1082., 1083., 1084.,
+                    1085., 1086., 1087., 1088., 1089., 1090., 2049., 2050., 2051., 2052., 2053., 2054., 2055., 2056.,
+                    2057., 2058., 2059., 2060., 121.,  122.,  123.,  124.,  125.,  126.,  127.,  128.,  129.,  130.,
+                    131.,  132.,  133.,  134.,  135.,  136.,  137.,  138.,  139.,  140.,  141.,  142.,  143.,  144.,
+                    1091., 1092., 1093., 1094., 1095., 1096., 1097., 1098., 1099., 1100., 1101., 1102., 1103., 1104.,
+                    1105., 1106., 1107., 1108., 2061., 2062., 2063., 2064., 2065., 2066., 2067., 2068., 2069., 2070.,
+                    2071., 2072.}),
             "concat_5d"),
     };
     return params;
 }
 
 std::vector<ConcatParams5d> generateCombinedParams5d() {
-    const std::vector<std::vector<ConcatParams5d>> generatedParams {
+    const std::vector<std::vector<ConcatParams5d>> generatedParams{
         generateParams5d<element::Type_t::bf16>(),
         generateParams5d<element::Type_t::f16>(),
         generateParams5d<element::Type_t::f32>(),
@@ -1058,16 +1154,24 @@ std::vector<ConcatParams5d> generateCombinedParams5d() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTest5d,
-    testing::ValuesIn(generateCombinedParams5d()), ReferenceConcatTest5d::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTest5d,
+                         testing::ValuesIn(generateCombinedParams5d()),
+                         ReferenceConcatTest5d::getTestCaseName);
 
 //// concat_zero_length_1d_last
 
 struct ConcatParamsZeroLength1dLast {
-    ConcatParamsZeroLength1dLast(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsZeroLength1dLast(const reference_tests::Tensor& A,
+                                 const reference_tests::Tensor& B,
+                                 const int32_t axis,
+                                 const reference_tests::Tensor& expected,
+                                 const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -1076,7 +1180,8 @@ struct ConcatParamsZeroLength1dLast {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestZeroLength1dLast : public testing::TestWithParam<ConcatParamsZeroLength1dLast>, public CommonReferenceTest {
+class ReferenceConcatTestZeroLength1dLast : public testing::TestWithParam<ConcatParamsZeroLength1dLast>,
+                                            public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -1120,19 +1225,18 @@ TEST_P(ReferenceConcatTestZeroLength1dLast, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsZeroLength1dLast> generateParamsZeroLength1dLast() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsZeroLength1dLast> params {
-        ConcatParamsZeroLength1dLast(
-            reference_tests::Tensor(ET, {4}, std::vector<T>{1, 2, 3, 4}),
-            reference_tests::Tensor(ET, {0}, std::vector<T>{0}),
-            0,
-            reference_tests::Tensor(ET, {4}, std::vector<T>{1, 2, 3, 4}),
-            "concat_zero_length_1d_last"),
+    std::vector<ConcatParamsZeroLength1dLast> params{
+        ConcatParamsZeroLength1dLast(reference_tests::Tensor(ET, {4}, std::vector<T>{1, 2, 3, 4}),
+                                     reference_tests::Tensor(ET, {0}, std::vector<T>{0}),
+                                     0,
+                                     reference_tests::Tensor(ET, {4}, std::vector<T>{1, 2, 3, 4}),
+                                     "concat_zero_length_1d_last"),
     };
     return params;
 }
 
 std::vector<ConcatParamsZeroLength1dLast> generateCombinedParamsZeroLength1dLast() {
-    const std::vector<std::vector<ConcatParamsZeroLength1dLast>> generatedParams {
+    const std::vector<std::vector<ConcatParamsZeroLength1dLast>> generatedParams{
         generateParamsZeroLength1dLast<element::Type_t::i32>(),
         generateParamsZeroLength1dLast<element::Type_t::i64>(),
         generateParamsZeroLength1dLast<element::Type_t::u32>(),
@@ -1149,16 +1253,26 @@ std::vector<ConcatParamsZeroLength1dLast> generateCombinedParamsZeroLength1dLast
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestZeroLength1dLast,
-    testing::ValuesIn(generateCombinedParamsZeroLength1dLast()), ReferenceConcatTestZeroLength1dLast::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestZeroLength1dLast,
+                         testing::ValuesIn(generateCombinedParamsZeroLength1dLast()),
+                         ReferenceConcatTestZeroLength1dLast::getTestCaseName);
 
 //// concat_zero_length_1d_middle
 
 struct ConcatParamsZeroLength1dMiddle {
-    ConcatParamsZeroLength1dMiddle(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const reference_tests::Tensor& C, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), C(C), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsZeroLength1dMiddle(const reference_tests::Tensor& A,
+                                   const reference_tests::Tensor& B,
+                                   const reference_tests::Tensor& C,
+                                   const int32_t axis,
+                                   const reference_tests::Tensor& expected,
+                                   const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          C(C),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -1168,7 +1282,8 @@ struct ConcatParamsZeroLength1dMiddle {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestZeroLength1dMiddle : public testing::TestWithParam<ConcatParamsZeroLength1dMiddle>, public CommonReferenceTest {
+class ReferenceConcatTestZeroLength1dMiddle : public testing::TestWithParam<ConcatParamsZeroLength1dMiddle>,
+                                              public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -1215,20 +1330,19 @@ TEST_P(ReferenceConcatTestZeroLength1dMiddle, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsZeroLength1dMiddle> generateParamsZeroLength1dMiddle() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsZeroLength1dMiddle> params {
-        ConcatParamsZeroLength1dMiddle(
-            reference_tests::Tensor(ET, {4}, std::vector<T>{1, 2, 3, 4}),
-            reference_tests::Tensor(ET, {0}, std::vector<T>{0}),
-            reference_tests::Tensor(ET, {4}, std::vector<T>{5, 6, 7, 8}),
-            0,
-            reference_tests::Tensor(ET, {8}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8}),
-            "concat_zero_length_1d_middle"),
+    std::vector<ConcatParamsZeroLength1dMiddle> params{
+        ConcatParamsZeroLength1dMiddle(reference_tests::Tensor(ET, {4}, std::vector<T>{1, 2, 3, 4}),
+                                       reference_tests::Tensor(ET, {0}, std::vector<T>{0}),
+                                       reference_tests::Tensor(ET, {4}, std::vector<T>{5, 6, 7, 8}),
+                                       0,
+                                       reference_tests::Tensor(ET, {8}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8}),
+                                       "concat_zero_length_1d_middle"),
     };
     return params;
 }
 
 std::vector<ConcatParamsZeroLength1dMiddle> generateCombinedParamsZeroLength1dMiddle() {
-    const std::vector<std::vector<ConcatParamsZeroLength1dMiddle>> generatedParams {
+    const std::vector<std::vector<ConcatParamsZeroLength1dMiddle>> generatedParams{
         generateParamsZeroLength1dMiddle<element::Type_t::i32>(),
         generateParamsZeroLength1dMiddle<element::Type_t::i64>(),
         generateParamsZeroLength1dMiddle<element::Type_t::u32>(),
@@ -1245,16 +1359,22 @@ std::vector<ConcatParamsZeroLength1dMiddle> generateCombinedParamsZeroLength1dMi
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestZeroLength1dMiddle,
-    testing::ValuesIn(generateCombinedParamsZeroLength1dMiddle()), ReferenceConcatTestZeroLength1dMiddle::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestZeroLength1dMiddle,
+                         testing::ValuesIn(generateCombinedParamsZeroLength1dMiddle()),
+                         ReferenceConcatTestZeroLength1dMiddle::getTestCaseName);
 
 //// concat_zero_zero
 
 struct ConcatParamsZeroZero {
-    ConcatParamsZeroZero(
-        const reference_tests::Tensor& A, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsZeroZero(const reference_tests::Tensor& A,
+                         const int32_t axis,
+                         const reference_tests::Tensor& expected,
+                         const std::string& testcaseName = "")
+        : A(A),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     int32_t axis;
@@ -1303,18 +1423,17 @@ TEST_P(ReferenceConcatTestZeroZero, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsZeroZero> generateParamsZeroZero() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsZeroZero> params {
-        ConcatParamsZeroZero(
-            reference_tests::Tensor(ET, {0}, std::vector<T>{1}),
-            0,
-            reference_tests::Tensor(ET, {0}, std::vector<T>{}),
-            "concat_zero_zero"),
+    std::vector<ConcatParamsZeroZero> params{
+        ConcatParamsZeroZero(reference_tests::Tensor(ET, {0}, std::vector<T>{1}),
+                             0,
+                             reference_tests::Tensor(ET, {0}, std::vector<T>{}),
+                             "concat_zero_zero"),
     };
     return params;
 }
 
 std::vector<ConcatParamsZeroZero> generateCombinedParamsZeroZero() {
-    const std::vector<std::vector<ConcatParamsZeroZero>> generatedParams {
+    const std::vector<std::vector<ConcatParamsZeroZero>> generatedParams{
         generateParamsZeroZero<element::Type_t::i32>(),
         generateParamsZeroZero<element::Type_t::i64>(),
         generateParamsZeroZero<element::Type_t::u32>(),
@@ -1331,16 +1450,26 @@ std::vector<ConcatParamsZeroZero> generateCombinedParamsZeroZero() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestZeroZero,
-    testing::ValuesIn(generateCombinedParamsZeroZero()), ReferenceConcatTestZeroZero::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestZeroZero,
+                         testing::ValuesIn(generateCombinedParamsZeroZero()),
+                         ReferenceConcatTestZeroZero::getTestCaseName);
 
 //// concat_zero_length_4d_middle
 
 struct ConcatParamsZeroLength4dMiddle {
-    ConcatParamsZeroLength4dMiddle(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& B, const reference_tests::Tensor& C, const int32_t axis,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), B(B), C(C), axis(axis), expected(expected), testcaseName(testcaseName) {}
+    ConcatParamsZeroLength4dMiddle(const reference_tests::Tensor& A,
+                                   const reference_tests::Tensor& B,
+                                   const reference_tests::Tensor& C,
+                                   const int32_t axis,
+                                   const reference_tests::Tensor& expected,
+                                   const std::string& testcaseName = "")
+        : A(A),
+          B(B),
+          C(C),
+          axis(axis),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor B;
@@ -1350,7 +1479,8 @@ struct ConcatParamsZeroLength4dMiddle {
     std::string testcaseName;
 };
 
-class ReferenceConcatTestZeroLength4dMiddle : public testing::TestWithParam<ConcatParamsZeroLength4dMiddle>, public CommonReferenceTest {
+class ReferenceConcatTestZeroLength4dMiddle : public testing::TestWithParam<ConcatParamsZeroLength4dMiddle>,
+                                              public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -1397,7 +1527,7 @@ TEST_P(ReferenceConcatTestZeroLength4dMiddle, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ConcatParamsZeroLength4dMiddle> generateParamsZeroLength4dMiddle() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ConcatParamsZeroLength4dMiddle> params {
+    std::vector<ConcatParamsZeroLength4dMiddle> params{
         ConcatParamsZeroLength4dMiddle(
             reference_tests::Tensor(ET, {2, 2, 1, 1}, std::vector<T>{1, 2, 3, 4}),
             reference_tests::Tensor(ET, {2, 2, 0, 1}, std::vector<T>{0}),
@@ -1410,7 +1540,7 @@ std::vector<ConcatParamsZeroLength4dMiddle> generateParamsZeroLength4dMiddle() {
 }
 
 std::vector<ConcatParamsZeroLength4dMiddle> generateCombinedParamsZeroLength4dMiddle() {
-    const std::vector<std::vector<ConcatParamsZeroLength4dMiddle>> generatedParams {
+    const std::vector<std::vector<ConcatParamsZeroLength4dMiddle>> generatedParams{
         generateParamsZeroLength4dMiddle<element::Type_t::i32>(),
         generateParamsZeroLength4dMiddle<element::Type_t::i64>(),
         generateParamsZeroLength4dMiddle<element::Type_t::u32>(),
@@ -1427,8 +1557,9 @@ std::vector<ConcatParamsZeroLength4dMiddle> generateCombinedParamsZeroLength4dMi
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs, ReferenceConcatTestZeroLength4dMiddle,
-    testing::ValuesIn(generateCombinedParamsZeroLength4dMiddle()), ReferenceConcatTestZeroLength4dMiddle::getTestCaseName);
-
+INSTANTIATE_TEST_SUITE_P(smoke_Concat_With_Hardcoded_Refs,
+                         ReferenceConcatTestZeroLength4dMiddle,
+                         testing::ValuesIn(generateCombinedParamsZeroLength4dMiddle()),
+                         ReferenceConcatTestZeroLength4dMiddle::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/constant.cpp b/src/plugins/template/tests/functional/op_reference/constant.cpp
index 3f37e4a8e8f7db..ababb046e9c2b6 100644
--- a/src/plugins/template/tests/functional/op_reference/constant.cpp
+++ b/src/plugins/template/tests/functional/op_reference/constant.cpp
@@ -2,14 +2,16 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/constant.hpp"
+
 #include <gtest/gtest.h>
 
 #include <random>
-#include "openvino/op/constant.hpp"
-#include "openvino/op/abs.hpp"
-#include "openvino/op/equal.hpp"
+
 #include "base_reference_test.hpp"
 #include "functional_test_utils/skip_tests_config.hpp"
+#include "openvino/op/abs.hpp"
+#include "openvino/op/equal.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -18,8 +20,10 @@ namespace {
 struct ConstantParams {
     template <class IT, class OT>
     ConstantParams(const PartialShape& inputShape,
-                   const element::Type& inType, const element::Type& refType,
-                   const std::vector<IT>& inputData, const std::vector<OT>& refData,
+                   const element::Type& inType,
+                   const element::Type& refType,
+                   const std::vector<IT>& inputData,
+                   const std::vector<OT>& refData,
                    const std::string& test_name = "")
         : inputShape(inputShape),
           inType(inType),
@@ -155,9 +159,11 @@ TEST_P(ReferenceConstantLayerTest_EqualityBool, CompareWithHardcodedRefs) {
 template <element::Type_t IN_ET>
 std::vector<ConstantParams> generateConstantParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<ConstantParams> constantParams {
+    std::vector<ConstantParams> constantParams{
         // tensor_constant
-        ConstantParams({2, 2, 2}, IN_ET, IN_ET,
+        ConstantParams({2, 2, 2},
+                       IN_ET,
+                       IN_ET,
                        std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8},
                        std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8},
                        "tensor_constant"),
@@ -166,33 +172,41 @@ std::vector<ConstantParams> generateConstantParams() {
 }
 
 std::vector<ConstantParams> generateConstantDefinedTypeParams() {
-    std::vector<ConstantParams> constantParams {
+    std::vector<ConstantParams> constantParams{
         // scalar_constant_float32
-        ConstantParams({}, element::Type_t::f32, element::Type_t::f32,
-            std::vector<float>{4.75},
-            std::vector<float>{4.75f},
-            "scalar_constant_float32"),
+        ConstantParams({},
+                       element::Type_t::f32,
+                       element::Type_t::f32,
+                       std::vector<float>{4.75},
+                       std::vector<float>{4.75f},
+                       "scalar_constant_float32"),
         // scalar_constant_int64
-        ConstantParams({}, element::Type_t::i64, element::Type_t::i64,
-            std::vector<int64_t>{0x4000000000000001},
-            std::vector<int64_t>{0x4000000000000001},
-            "scalar_constant_int64"),
+        ConstantParams({},
+                       element::Type_t::i64,
+                       element::Type_t::i64,
+                       std::vector<int64_t>{0x4000000000000001},
+                       std::vector<int64_t>{0x4000000000000001},
+                       "scalar_constant_int64"),
         // tensor_constant_float32
-        ConstantParams({2, 2}, element::Type_t::f32, element::Type_t::f32,
-            std::vector<float>{4.75, 4.5, -5.25, 0.0},
-            std::vector<float>{4.75f, 4.5f, -5.25f, 0.0f},
-            "tensor_constant_float32"),
+        ConstantParams({2, 2},
+                       element::Type_t::f32,
+                       element::Type_t::f32,
+                       std::vector<float>{4.75, 4.5, -5.25, 0.0},
+                       std::vector<float>{4.75f, 4.5f, -5.25f, 0.0f},
+                       "tensor_constant_float32"),
         // tensor_constant_int64
-        ConstantParams({2}, element::Type_t::i64, element::Type_t::i64,
-            std::vector<int64_t>{0x4000000000000001, 0x4000000000000002},
-            std::vector<int64_t>{0x4000000000000001, 0x4000000000000002},
-            "tensor_constant_int64"),
+        ConstantParams({2},
+                       element::Type_t::i64,
+                       element::Type_t::i64,
+                       std::vector<int64_t>{0x4000000000000001, 0x4000000000000002},
+                       std::vector<int64_t>{0x4000000000000001, 0x4000000000000002},
+                       "tensor_constant_int64"),
     };
     return constantParams;
 }
 
 std::vector<ConstantParams> generateConstantCombinedParams() {
-    const std::vector<std::vector<ConstantParams>> constantTypeParams {
+    const std::vector<std::vector<ConstantParams>> constantTypeParams{
         generateConstantParams<element::Type_t::i8>(),
         generateConstantParams<element::Type_t::i16>(),
         generateConstantParams<element::Type_t::i32>(),
@@ -216,7 +230,7 @@ std::vector<ConstantParams> generateConstantCombinedParams() {
 }
 
 std::vector<ConstantParams> generateConstant2ConstantCombinedParams() {
-    const std::vector<std::vector<ConstantParams>> constantTypeParams {
+    const std::vector<std::vector<ConstantParams>> constantTypeParams{
         generateConstantParams<element::Type_t::i8>(),
         generateConstantParams<element::Type_t::i16>(),
         generateConstantParams<element::Type_t::i32>(),
@@ -241,9 +255,11 @@ std::vector<ConstantParams> generateConstant2ConstantCombinedParams() {
 template <element::Type_t IN_ET>
 std::vector<ConstantParams> generateConstantWithOpParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<ConstantParams> constantParams {
+    std::vector<ConstantParams> constantParams{
         // tensor_constant_with_op
-        ConstantParams({2, 2, 2}, IN_ET, IN_ET,
+        ConstantParams({2, 2, 2},
+                       IN_ET,
+                       IN_ET,
                        std::vector<T>{-1, 2, 3, -4, 5, -6, -7, 8},
                        std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8},
                        "tensor_constant_with_op"),
@@ -252,7 +268,7 @@ std::vector<ConstantParams> generateConstantWithOpParams() {
 }
 
 std::vector<ConstantParams> generateConstantWithOpCombinedParams() {
-    const std::vector<std::vector<ConstantParams>> constantTypeParams {
+    const std::vector<std::vector<ConstantParams>> constantTypeParams{
         generateConstantWithOpParams<element::Type_t::i8>(),
         generateConstantWithOpParams<element::Type_t::i16>(),
         generateConstantWithOpParams<element::Type_t::i32>(),
@@ -271,39 +287,53 @@ std::vector<ConstantParams> generateConstantWithOpCombinedParams() {
 }
 
 std::vector<ConstantParams> generateConstantDefinedTypeMultiUseCombinedParams() {
-    const std::vector<ConstantParams> combinedParams {
+    const std::vector<ConstantParams> combinedParams{
         // constant_multi_use
-        ConstantParams({}, element::Type_t::i32, element::Type_t::i32,
-            std::vector<int32_t>{388},
-            std::vector<int32_t>{388},
-            "constant_multi_use"),
+        ConstantParams({},
+                       element::Type_t::i32,
+                       element::Type_t::i32,
+                       std::vector<int32_t>{388},
+                       std::vector<int32_t>{388},
+                       "constant_multi_use"),
     };
     return combinedParams;
 }
 
 std::vector<ConstantParams> generateConstantDefinedTypeEqualityBoolCombinedParams() {
-    const std::vector<ConstantParams> combinedParams {
+    const std::vector<ConstantParams> combinedParams{
         // constant_equality_bool
-        ConstantParams({4}, element::Type_t::boolean, element::Type_t::boolean,
-            std::vector<char>{true, false, true, false},
-            std::vector<char>{true, false, true, false},
-            "constant_equality_bool"),
+        ConstantParams({4},
+                       element::Type_t::boolean,
+                       element::Type_t::boolean,
+                       std::vector<char>{true, false, true, false},
+                       std::vector<char>{true, false, true, false},
+                       "constant_equality_bool"),
     };
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs, ReferenceConstantLayerTest,
-    testing::ValuesIn(generateConstantCombinedParams()), ReferenceConstantLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs, ReferenceConstantLayerTest_2Constant,
-    testing::ValuesIn(generateConstant2ConstantCombinedParams()), ReferenceConstantLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs, ReferenceConstantLayerTest_WithOp,
-    testing::ValuesIn(generateConstantWithOpCombinedParams()), ReferenceConstantLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs, ReferenceConstantLayerTest_MultiUse,
-    testing::ValuesIn(generateConstantDefinedTypeMultiUseCombinedParams()), ReferenceConstantLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs, ReferenceConstantLayerTest_EqualityBool,
-    testing::ValuesIn(generateConstantDefinedTypeEqualityBoolCombinedParams()), ReferenceConstantLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs,
+                         ReferenceConstantLayerTest,
+                         testing::ValuesIn(generateConstantCombinedParams()),
+                         ReferenceConstantLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs,
+                         ReferenceConstantLayerTest_2Constant,
+                         testing::ValuesIn(generateConstant2ConstantCombinedParams()),
+                         ReferenceConstantLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs,
+                         ReferenceConstantLayerTest_WithOp,
+                         testing::ValuesIn(generateConstantWithOpCombinedParams()),
+                         ReferenceConstantLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs,
+                         ReferenceConstantLayerTest_MultiUse,
+                         testing::ValuesIn(generateConstantDefinedTypeMultiUseCombinedParams()),
+                         ReferenceConstantLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Constant_With_Hardcoded_Refs,
+                         ReferenceConstantLayerTest_EqualityBool,
+                         testing::ValuesIn(generateConstantDefinedTypeEqualityBoolCombinedParams()),
+                         ReferenceConstantLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/conversion.cpp b/src/plugins/template/tests/functional/op_reference/conversion.cpp
index ddb258cda0099e..9c32c7d052c256 100644
--- a/src/plugins/template/tests/functional/op_reference/conversion.cpp
+++ b/src/plugins/template/tests/functional/op_reference/conversion.cpp
@@ -10,6 +10,6 @@ namespace {
 TEST_P(ReferenceConversionLayerTest, CompareWithHardcodedRefs) {
     Exec();
 }
-} // namespace
-} // namespace ConversionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace
+}  // namespace ConversionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/conversion.hpp b/src/plugins/template/tests/functional/op_reference/conversion.hpp
index 0f6b324eb7573b..8c97f8dcc41c98 100644
--- a/src/plugins/template/tests/functional/op_reference/conversion.hpp
+++ b/src/plugins/template/tests/functional/op_reference/conversion.hpp
@@ -17,16 +17,24 @@ namespace ConversionOpsRefTestDefinitions {
 
 using ov::test::utils::ConversionTypes;
 
-static std::map<ConversionTypes, std::string> conversionNames = {
-    {ConversionTypes::CONVERT,      "Convert"},
-    {ConversionTypes::CONVERT_LIKE, "ConvertLike"}
-};
+static std::map<ConversionTypes, std::string> conversionNames = {{ConversionTypes::CONVERT, "Convert"},
+                                                                 {ConversionTypes::CONVERT_LIKE, "ConvertLike"}};
 
 struct ConvertParams {
     template <class IT, class OT>
-    ConvertParams(ConversionTypes convType, const ov::PartialShape& shape, const ov::element::Type& iType,
-                  const ov::element::Type& oType, const std::vector<IT>& iValues, const std::vector<OT>& oValues, size_t iSize = 0, size_t oSize = 0)
-        : conversionType(convType), pshape(shape), inType(iType), outType(oType), inputData(CreateTensor(iType, iValues, iSize)),
+    ConvertParams(ConversionTypes convType,
+                  const ov::PartialShape& shape,
+                  const ov::element::Type& iType,
+                  const ov::element::Type& oType,
+                  const std::vector<IT>& iValues,
+                  const std::vector<OT>& oValues,
+                  size_t iSize = 0,
+                  size_t oSize = 0)
+        : conversionType(convType),
+          pshape(shape),
+          inType(iType),
+          outType(oType),
+          inputData(CreateTensor(iType, iValues, iSize)),
           refData(CreateTensor(oType, oValues, oSize)) {}
     ConversionTypes conversionType;
     ov::PartialShape pshape;
@@ -56,9 +64,10 @@ class ReferenceConversionLayerTest : public testing::TestWithParam<ConvertParams
     }
 
 private:
-    static std::shared_ptr<ov::Model> CreateFunction(const ov::PartialShape& input_shape, const ov::element::Type& input_type,
-                                                        const ov::element::Type& expected_output_type,
-                                                        const ConversionTypes& conversion_type) {
+    static std::shared_ptr<ov::Model> CreateFunction(const ov::PartialShape& input_shape,
+                                                     const ov::element::Type& input_type,
+                                                     const ov::element::Type& expected_output_type,
+                                                     const ConversionTypes& conversion_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         std::shared_ptr<ov::Node> convert;
         if (conversion_type == ConversionTypes::CONVERT) {
@@ -69,8 +78,8 @@ class ReferenceConversionLayerTest : public testing::TestWithParam<ConvertParams
         } else {
             throw std::runtime_error("Incorrect type of Conversion operation");
         }
-        return std::make_shared<ov::Model>(ov::NodeVector {convert}, ov::ParameterVector {in});
+        return std::make_shared<ov::Model>(ov::NodeVector{convert}, ov::ParameterVector{in});
     }
 };
-} // namespace ConversionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ConversionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/convert.cpp b/src/plugins/template/tests/functional/op_reference/convert.cpp
index 61eb58ecb40cae..0f3e47148790be 100644
--- a/src/plugins/template/tests/functional/op_reference/convert.cpp
+++ b/src/plugins/template/tests/functional/op_reference/convert.cpp
@@ -2,10 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/convert.hpp"
+
 #include <gtest/gtest.h>
+
 #include <tuple>
 
-#include "openvino/op/convert.hpp"
 #include "conversion.hpp"
 
 using namespace ov;
@@ -15,392 +17,1277 @@ namespace ConversionOpsRefTestDefinitions {
 namespace {
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Conversion_With_Hardcoded_Refs, ReferenceConversionLayerTest,
+    smoke_Conversion_With_Hardcoded_Refs,
+    ReferenceConversionLayerTest,
     ::testing::Values(
         // destination boolean
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 3}, ov::element::u8, ov::element::boolean,
-                      std::vector<uint8_t> {0, 12, 23, 0, std::numeric_limits<uint8_t>::lowest(), std::numeric_limits<uint8_t>::max()},
-                      std::vector<char> {0, 1, 1, 0, 0, 1}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 3}, ov::element::i32, ov::element::boolean,
-                      std::vector<int32_t> {0, -12, 23, 0, std::numeric_limits<int32_t>::lowest(), std::numeric_limits<int32_t>::max()},
-                      std::vector<char> {0, 1, 1, 0, 1, 1}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {3, 3}, ov::element::f32, ov::element::boolean,
-                      std::vector<float> {0.f, 1.5745f, 0.12352f, 0.f, std::numeric_limits<float>::lowest(), std::numeric_limits<float>::max(),
-                                          std::numeric_limits<float>::min(), std::numeric_limits<float>::infinity(), -std::numeric_limits<float>::infinity()},
-                      std::vector<char> {0, 1, 1, 0, 1, 1, 1, 1, 1}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 3},
+                      ov::element::u8,
+                      ov::element::boolean,
+                      std::vector<uint8_t>{0,
+                                           12,
+                                           23,
+                                           0,
+                                           std::numeric_limits<uint8_t>::lowest(),
+                                           std::numeric_limits<uint8_t>::max()},
+                      std::vector<char>{0, 1, 1, 0, 0, 1}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 3},
+                      ov::element::i32,
+                      ov::element::boolean,
+                      std::vector<int32_t>{0,
+                                           -12,
+                                           23,
+                                           0,
+                                           std::numeric_limits<int32_t>::lowest(),
+                                           std::numeric_limits<int32_t>::max()},
+                      std::vector<char>{0, 1, 1, 0, 1, 1}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{3, 3},
+                      ov::element::f32,
+                      ov::element::boolean,
+                      std::vector<float>{0.f,
+                                         1.5745f,
+                                         0.12352f,
+                                         0.f,
+                                         std::numeric_limits<float>::lowest(),
+                                         std::numeric_limits<float>::max(),
+                                         std::numeric_limits<float>::min(),
+                                         std::numeric_limits<float>::infinity(),
+                                         -std::numeric_limits<float>::infinity()},
+                      std::vector<char>{0, 1, 1, 0, 1, 1, 1, 1, 1}),
         // destination bf16
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {1, 1, 3, 5}, ov::element::f32, ov::element::bf16,
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<bfloat16> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {11}, ov::element::u8, ov::element::bf16,
-                      std::vector<uint8_t> {0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142},
-                      std::vector<bfloat16> {0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}),
+        ConvertParams(
+            ConversionTypes::CONVERT,
+            ov::PartialShape{1, 1, 3, 5},
+            ov::element::f32,
+            ov::element::bf16,
+            std::
+                vector<float>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
+            std::vector<
+                bfloat16>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{11},
+                      ov::element::u8,
+                      ov::element::bf16,
+                      std::vector<uint8_t>{0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142},
+                      std::vector<bfloat16>{0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}),
 
         // destination f16
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {1, 1, 3, 5}, ov::element::f32, ov::element::f16,
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<float16> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {11}, ov::element::u8, ov::element::f16,
-                      std::vector<uint8_t> {0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}, std::vector<float16> {0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}),
+        ConvertParams(
+            ConversionTypes::CONVERT,
+            ov::PartialShape{1, 1, 3, 5},
+            ov::element::f32,
+            ov::element::f16,
+            std::
+                vector<float>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
+            std::vector<
+                float16>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{11},
+                      ov::element::u8,
+                      ov::element::f16,
+                      std::vector<uint8_t>{0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142},
+                      std::vector<float16>{0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}),
 
         // destination f32
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::u1, ov::element::f32, std::vector<uint8_t> {0xA0},
-                      std::vector<float> {1.0f, 0.0f, 1.0f, 0.0f}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::u4, ov::element::f32, std::vector<uint8_t> {0xFB, 0x0A},
-                      std::vector<float> {15.0f, 11.0f, 0.0f, 10.0f}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::u8, ov::element::f32, std::vector<uint8_t> {255, 128, 32, 0},
-                      std::vector<float> {255.0f, 128.0f, 32.0f, 0.0f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::u16, ov::element::f32,
-                      std::vector<uint16_t> {64000, 32000, 128, 0}, std::vector<float> {64000.0f, 32000.0f, 128.0f, 0.0f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::u32, ov::element::f32,
-                      std::vector<uint32_t> {4000000, 2000000, 128, 0}, std::vector<float> {4000000.0f, 2000000.0f, 128.0f, 0.0f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::u64, ov::element::f32,
-                      std::vector<uint64_t> {4000000, 2000000, 128, 0}, std::vector<float> {4000000.0f, 2000000.0f, 128.0f, 0.0f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::i4, ov::element::f32, std::vector<uint8_t> {0xFE, 0xF2},
-                      std::vector<float> {-1.0f, -2.0f, -1.0f, 2.0f}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::i8, ov::element::f32, std::vector<int8_t> {-127, -0, 0, 127},
-                      std::vector<float> {-127.0f, -0.0f, 0.0f, 127.0f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::i16, ov::element::f32,
-                      std::vector<int16_t> {-32000, -0, 0, 32000}, std::vector<float> {-32000.0f, -0.0f, 0.0f, 32000.0f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::i32, ov::element::f32,
-                      std::vector<int32_t> {-64000, -0, 0, 64000}, std::vector<float> {-64000.0f, -0.0f, 0.0f, 64000.0f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {2, 2}, ov::element::i64, ov::element::f32,
-                      std::vector<int64_t> {-64000, -0, 0, 64000}, std::vector<float> {-64000.0f, -0.0f, 0.0f, 64000.0f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {1, 1, 3, 5}, ov::element::bf16, ov::element::f32,
-                      std::vector<bfloat16> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {1, 1, 3, 5}, ov::element::f16, ov::element::f32,
-                      std::vector<float16> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {1, 1, 3, 5}, ov::element::f32, ov::element::f32,
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::u1,
+                      ov::element::f32,
+                      std::vector<uint8_t>{0xA0},
+                      std::vector<float>{1.0f, 0.0f, 1.0f, 0.0f},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::u4,
+                      ov::element::f32,
+                      std::vector<uint8_t>{0xFB, 0x0A},
+                      std::vector<float>{15.0f, 11.0f, 0.0f, 10.0f},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::u8,
+                      ov::element::f32,
+                      std::vector<uint8_t>{255, 128, 32, 0},
+                      std::vector<float>{255.0f, 128.0f, 32.0f, 0.0f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::u16,
+                      ov::element::f32,
+                      std::vector<uint16_t>{64000, 32000, 128, 0},
+                      std::vector<float>{64000.0f, 32000.0f, 128.0f, 0.0f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::u32,
+                      ov::element::f32,
+                      std::vector<uint32_t>{4000000, 2000000, 128, 0},
+                      std::vector<float>{4000000.0f, 2000000.0f, 128.0f, 0.0f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::u64,
+                      ov::element::f32,
+                      std::vector<uint64_t>{4000000, 2000000, 128, 0},
+                      std::vector<float>{4000000.0f, 2000000.0f, 128.0f, 0.0f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::i4,
+                      ov::element::f32,
+                      std::vector<uint8_t>{0xFE, 0xF2},
+                      std::vector<float>{-1.0f, -2.0f, -1.0f, 2.0f},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::i8,
+                      ov::element::f32,
+                      std::vector<int8_t>{-127, -0, 0, 127},
+                      std::vector<float>{-127.0f, -0.0f, 0.0f, 127.0f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::i16,
+                      ov::element::f32,
+                      std::vector<int16_t>{-32000, -0, 0, 32000},
+                      std::vector<float>{-32000.0f, -0.0f, 0.0f, 32000.0f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::i32,
+                      ov::element::f32,
+                      std::vector<int32_t>{-64000, -0, 0, 64000},
+                      std::vector<float>{-64000.0f, -0.0f, 0.0f, 64000.0f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{2, 2},
+                      ov::element::i64,
+                      ov::element::f32,
+                      std::vector<int64_t>{-64000, -0, 0, 64000},
+                      std::vector<float>{-64000.0f, -0.0f, 0.0f, 64000.0f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{1, 1, 3, 5},
+                      ov::element::bf16,
+                      ov::element::f32,
+                      std::vector<bfloat16>{0.5f,
+                                            1.5f,
+                                            0.5f,
+                                            2.5f,
+                                            1.5f,
+                                            0.5f,
+                                            3.5f,
+                                            2.5f,
+                                            0.5f,
+                                            0.5f,
+                                            2.5f,
+                                            0.5f,
+                                            0.5f,
+                                            0.5f,
+                                            1.5f},
+                      std::vector<float>{0.5f,
+                                         1.5f,
+                                         0.5f,
+                                         2.5f,
+                                         1.5f,
+                                         0.5f,
+                                         3.5f,
+                                         2.5f,
+                                         0.5f,
+                                         0.5f,
+                                         2.5f,
+                                         0.5f,
+                                         0.5f,
+                                         0.5f,
+                                         1.5f}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{1, 1, 3, 5},
+                      ov::element::f16,
+                      ov::element::f32,
+                      std::vector<float16>{0.5f,
+                                           1.5f,
+                                           0.5f,
+                                           2.5f,
+                                           1.5f,
+                                           0.5f,
+                                           3.5f,
+                                           2.5f,
+                                           0.5f,
+                                           0.5f,
+                                           2.5f,
+                                           0.5f,
+                                           0.5f,
+                                           0.5f,
+                                           1.5f},
+                      std::vector<float>{0.5f,
+                                         1.5f,
+                                         0.5f,
+                                         2.5f,
+                                         1.5f,
+                                         0.5f,
+                                         3.5f,
+                                         2.5f,
+                                         0.5f,
+                                         0.5f,
+                                         2.5f,
+                                         0.5f,
+                                         0.5f,
+                                         0.5f,
+                                         1.5f}),
+        ConvertParams(
+            ConversionTypes::CONVERT,
+            ov::PartialShape{1, 1, 3, 5},
+            ov::element::f32,
+            ov::element::f32,
+            std::
+                vector<float>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
+            std::vector<
+                float>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
 
         // destination i4
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u1, ov::element::i4, std::vector<uint8_t> {0xA0},
-                      std::vector<uint8_t> {0x10, 0x10}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::i4, std::vector<uint8_t> {0x12, 0x03},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::i4, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::i4, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::i4, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::i4, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::i4, std::vector<uint8_t> {0xFE, 0x03},
-                      std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::i4, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::i4, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::i4, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::i4, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::i4,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::i4,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::i4, std::vector<float> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u1,
+                      ov::element::i4,
+                      std::vector<uint8_t>{0xA0},
+                      std::vector<uint8_t>{0x10, 0x10},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i4,
+                      std::vector<uint8_t>{0x12, 0x03},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i4,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i4,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i4,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i4,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i4,
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i4,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i4,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i4,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i4,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i4,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i4,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i4,
+                      std::vector<float>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
         // destination i8
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::i8, std::vector<uint8_t> {0x81},
-                      std::vector<int8_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::i8, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int8_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::i8, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<int8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::i8, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<int8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::i8, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<int8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::i8, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<int8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::i8, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int8_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::i8, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::i8, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::i8, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::i8, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::i8,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<int8_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::i8,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<int8_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::i8, std::vector<float> {-1, -2, 2.2, 3.8},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::i8,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<int8_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i8,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int8_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i8,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<int8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i8,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<int8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i8,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<int8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i8,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<int8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i8,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int8_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i8,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i8,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i8,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i8,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i8,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<int8_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i8,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<int8_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i8,
+                      std::vector<float>{-1, -2, 2.2, 3.8},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
         // destination i16
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::i16, std::vector<uint8_t> {0x81},
-                      std::vector<int16_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::i16, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int16_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::i16, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<int16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::i16, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<int16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::i16, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<int16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::i16, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<int16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::i16, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int16_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::i16, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::i16, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::i16, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::i16, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::i16,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<int16_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::i16,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<int16_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::i16, std::vector<float> {-1, -2, 2.2, 3.8},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::i16,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<int16_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i16,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int16_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i16,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<int16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i16,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<int16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i16,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<int16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i16,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<int16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i16,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int16_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i16,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i16,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i16,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i16,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i16,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<int16_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i16,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<int16_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i16,
+                      std::vector<float>{-1, -2, 2.2, 3.8},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
         // destination i32
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::i32, std::vector<uint8_t> {0x81},
-                      std::vector<int32_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::i32, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int32_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::i32, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<int32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::i32, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<int32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::i32, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<int32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::i32, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<int32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::i32, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int32_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::i32, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::i32, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::i32, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::i32, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::i32,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<int32_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::i32,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<int32_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::i32, std::vector<float> {-1, -2, 2.2, 3.8},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::i32,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<int32_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i32,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int32_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i32,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<int32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i32,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<int32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i32,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<int32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i32,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<int32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i32,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int32_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i32,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i32,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i32,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i32,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i32,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<int32_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i32,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<int32_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i32,
+                      std::vector<float>{-1, -2, 2.2, 3.8},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
         // destination i64
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::i64, std::vector<uint8_t> {0x81},
-                      std::vector<int64_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::i64, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int64_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::i64, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<int64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::i64, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<int64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::i64, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<int64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::i64, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<int64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::i64, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int64_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::i64, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::i64, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::i64, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::i64, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::i64,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<int64_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::i64,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<int64_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::i64, std::vector<float> {-1, -2, 2.2, 3.8},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::i64,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<int64_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i64,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int64_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i64,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<int64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i64,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<int64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i64,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<int64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i64,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<int64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i64,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int64_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i64,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i64,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i64,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i64,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i64,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<int64_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i64,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<int64_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i64,
+                      std::vector<float>{-1, -2, 2.2, 3.8},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
 
         // destination u1
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::u1, std::vector<uint8_t> {0xA0},
-                      std::vector<uint8_t> {0xA0}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u4, ov::element::u1,
-                      std::vector<uint8_t> {0x10, 0x01, 0x00, 0x00}, std::vector<uint8_t> {0x90}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u8, ov::element::u1,
-                      std::vector<uint8_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u16, ov::element::u1,
-                      std::vector<uint16_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u32, ov::element::u1,
-                      std::vector<uint32_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u64, ov::element::u1,
-                      std::vector<uint64_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::i4, ov::element::u1,
-                      std::vector<uint8_t> {0x10, 0x01, 0x00, 0x00}, std::vector<uint8_t> {0x90}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::i8, ov::element::u1,
-                      std::vector<int8_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::i16, ov::element::u1,
-                      std::vector<int16_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::i32, ov::element::u1,
-                      std::vector<int32_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::i64, ov::element::u1,
-                      std::vector<int64_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::f16, ov::element::u1,
-                      std::vector<ov::float16> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::bf16, ov::element::u1,
-                      std::vector<ov::bfloat16> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::f32, ov::element::u1,
-                      std::vector<float> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u1,
+                      std::vector<uint8_t>{0xA0},
+                      std::vector<uint8_t>{0xA0},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u4,
+                      ov::element::u1,
+                      std::vector<uint8_t>{0x10, 0x01, 0x00, 0x00},
+                      std::vector<uint8_t>{0x90},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u8,
+                      ov::element::u1,
+                      std::vector<uint8_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u16,
+                      ov::element::u1,
+                      std::vector<uint16_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u32,
+                      ov::element::u1,
+                      std::vector<uint32_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u64,
+                      ov::element::u1,
+                      std::vector<uint64_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::i4,
+                      ov::element::u1,
+                      std::vector<uint8_t>{0x10, 0x01, 0x00, 0x00},
+                      std::vector<uint8_t>{0x90},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::i8,
+                      ov::element::u1,
+                      std::vector<int8_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::i16,
+                      ov::element::u1,
+                      std::vector<int16_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::i32,
+                      ov::element::u1,
+                      std::vector<int32_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::i64,
+                      ov::element::u1,
+                      std::vector<int64_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::f16,
+                      ov::element::u1,
+                      std::vector<ov::float16>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::bf16,
+                      ov::element::u1,
+                      std::vector<ov::bfloat16>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::f32,
+                      ov::element::u1,
+                      std::vector<float>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
 
         // destination u4
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u1, ov::element::u4, std::vector<uint8_t> {0xA0},
-                      std::vector<uint8_t> {0x10, 0x10}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::u4, std::vector<uint8_t> {0x12, 0x03},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::u4, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::u4, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::u4, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::u4, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::u4, std::vector<uint8_t> {0xFE, 0x03},
-                      std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::u4, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::u4, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::u4, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::u4, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::u4,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::u4,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::u4, std::vector<float> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u1,
+                      ov::element::u4,
+                      std::vector<uint8_t>{0xA0},
+                      std::vector<uint8_t>{0x10, 0x10},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u4,
+                      std::vector<uint8_t>{0x12, 0x03},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u4,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u4,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u4,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u4,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u4,
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u4,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u4,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u4,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u4,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u4,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u4,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u4,
+                      std::vector<float>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
 
         // destination u8
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::u8, std::vector<uint8_t> {0x81},
-                      std::vector<uint8_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::u8, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint8_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::u8, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::u8, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::u8, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::u8, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::u8, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint8_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::u8, std::vector<int8_t> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::u8, std::vector<int16_t> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::u8, std::vector<int32_t> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::u8, std::vector<int64_t> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::u8, std::vector<ov::float16> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::u8,
-                      std::vector<ov::bfloat16> {1, 2, 0, 3}, std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::u8, std::vector<float> {1, 2, 2.2, 3.8},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u8,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<uint8_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u8,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint8_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u8,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u8,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u8,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u8,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u8,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint8_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u8,
+                      std::vector<int8_t>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u8,
+                      std::vector<int16_t>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u8,
+                      std::vector<int32_t>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u8,
+                      std::vector<int64_t>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u8,
+                      std::vector<ov::float16>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u8,
+                      std::vector<ov::bfloat16>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u8,
+                      std::vector<float>{1, 2, 2.2, 3.8},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
 
         // destination u16
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::u16, std::vector<uint8_t> {0x81},
-                      std::vector<uint16_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::u16, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint16_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::u16, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::u16, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::u16, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::u16, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::u16, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint16_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::u16, std::vector<int8_t> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::u16, std::vector<int16_t> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::u16, std::vector<int32_t> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::u16, std::vector<int64_t> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::u16, std::vector<ov::float16> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::u16,
-                      std::vector<ov::bfloat16> {1, 2, 0, 3}, std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::u16, std::vector<float> {1, 2, 2.2, 3.8},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u16,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<uint16_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u16,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint16_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u16,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u16,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u16,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u16,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u16,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint16_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u16,
+                      std::vector<int8_t>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u16,
+                      std::vector<int16_t>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u16,
+                      std::vector<int32_t>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u16,
+                      std::vector<int64_t>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u16,
+                      std::vector<ov::float16>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u16,
+                      std::vector<ov::bfloat16>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u16,
+                      std::vector<float>{1, 2, 2.2, 3.8},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
 
         // destination u32
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::u32, std::vector<uint8_t> {0x81},
-                      std::vector<uint32_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::u32, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint32_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::u32, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::u32, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::u32, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::u32, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::u32, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint32_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::u32, std::vector<int8_t> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::u32, std::vector<int16_t> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::u32, std::vector<int32_t> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::u32, std::vector<int64_t> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::u32, std::vector<ov::float16> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::u32,
-                      std::vector<ov::bfloat16> {1, 2, 0, 3}, std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::u32, std::vector<float> {1, 2, 2.2, 3.8},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u32,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<uint32_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u32,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint32_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u32,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u32,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u32,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u32,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u32,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint32_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u32,
+                      std::vector<int8_t>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u32,
+                      std::vector<int16_t>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u32,
+                      std::vector<int32_t>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u32,
+                      std::vector<int64_t>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u32,
+                      std::vector<ov::float16>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u32,
+                      std::vector<ov::bfloat16>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u32,
+                      std::vector<float>{1, 2, 2.2, 3.8},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
         // destination u64
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {8}, ov::element::u1, ov::element::u64, std::vector<uint8_t> {0x81},
-                      std::vector<uint64_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u4, ov::element::u64, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint64_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u8, ov::element::u64, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u16, ov::element::u64, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u32, ov::element::u64, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::u64, ov::element::u64, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i4, ov::element::u64, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint64_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i8, ov::element::u64, std::vector<int8_t> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i16, ov::element::u64, std::vector<int16_t> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i32, ov::element::u64, std::vector<int32_t> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::i64, ov::element::u64, std::vector<int64_t> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f16, ov::element::u64, std::vector<ov::float16> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::bf16, ov::element::u64,
-                      std::vector<ov::bfloat16> {1, 2, 0, 3}, std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT, ov::PartialShape {4}, ov::element::f32, ov::element::u64, std::vector<float> {1, 2, 2.2, 3.8},
-                      std::vector<uint64_t> {1, 2, 2, 3})),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u64,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<uint64_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u64,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint64_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u64,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u64,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u64,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u64,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u64,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint64_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u64,
+                      std::vector<int8_t>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u64,
+                      std::vector<int16_t>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u64,
+                      std::vector<int32_t>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u64,
+                      std::vector<int64_t>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u64,
+                      std::vector<ov::float16>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u64,
+                      std::vector<ov::bfloat16>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u64,
+                      std::vector<float>{1, 2, 2.2, 3.8},
+                      std::vector<uint64_t>{1, 2, 2, 3})),
     ReferenceConversionLayerTest::getTestCaseName);
-} // namespace
-} // namespace ConversionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace
+}  // namespace ConversionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/convert_color_i420.cpp b/src/plugins/template/tests/functional/op_reference/convert_color_i420.cpp
index 4c21e52eed2316..844fdeb116344c 100644
--- a/src/plugins/template/tests/functional/op_reference/convert_color_i420.cpp
+++ b/src/plugins/template/tests/functional/op_reference/convert_color_i420.cpp
@@ -5,9 +5,9 @@
 #include <gtest/gtest.h>
 
 #include <openvino/core/model.hpp>
-#include <tuple>
-#include <openvino/op/i420_to_rgb.hpp>
 #include <openvino/op/i420_to_bgr.hpp>
+#include <openvino/op/i420_to_rgb.hpp>
+#include <tuple>
 
 #include "base_reference_test.hpp"
 #include "functional_test_utils/skip_tests_config.hpp"
@@ -20,8 +20,8 @@ class ReferenceConvertColorI420LayerTest : public testing::Test, public CommonRe
 public:
     void SetUp() override {
         SKIP_IF_CURRENT_TEST_IS_DISABLED()
-        abs_threshold = 1.f; // allow R, G, B absolute deviation to 1 (of max 255)
-        threshold = 1.f; // Ignore relative comparison (100%)
+        abs_threshold = 1.f;  // allow R, G, B absolute deviation to 1 (of max 255)
+        threshold = 1.f;      // Ignore relative comparison (100%)
     }
 
 public:
@@ -31,28 +31,28 @@ class ReferenceConvertColorI420LayerTest : public testing::Test, public CommonRe
         std::shared_ptr<Node> conv;
         conv = std::make_shared<T>(in);
         auto res = std::make_shared<op::v0::Result>(conv);
-        return std::make_shared<Model>(ResultVector{res}, ParameterVector {in});
+        return std::make_shared<Model>(ResultVector{res}, ParameterVector{in});
     }
 
     template <typename T>
-    static std::shared_ptr<Model> CreateFunction3(const reference_tests::Tensor& input1, const reference_tests::Tensor& input2, const reference_tests::Tensor& input3) {
+    static std::shared_ptr<Model> CreateFunction3(const reference_tests::Tensor& input1,
+                                                  const reference_tests::Tensor& input2,
+                                                  const reference_tests::Tensor& input3) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input1.type, input1.shape);
         const auto in2 = std::make_shared<op::v0::Parameter>(input2.type, input2.shape);
         const auto in3 = std::make_shared<op::v0::Parameter>(input3.type, input3.shape);
         std::shared_ptr<Node> conv;
         conv = std::make_shared<T>(in1, in2, in3);
         auto res = std::make_shared<op::v0::Result>(conv);
-        return std::make_shared<Model>(ResultVector{res}, ParameterVector {in1, in2, in3});
+        return std::make_shared<Model>(ResultVector{res}, ParameterVector{in1, in2, in3});
     }
 };
 
 TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_r_u8_single_rgb) {
-    auto input = std::vector<uint8_t> {0x51, 0x51, 0x51, 0x51,
-                                       0x51, 0x51, 0x51, 0x51,
-                                       0x5a, 0x5a, 0xf0, 0xf0};
+    auto input = std::vector<uint8_t>{0x51, 0x51, 0x51, 0x51, 0x51, 0x51, 0x51, 0x51, 0x5a, 0x5a, 0xf0, 0xf0};
     auto input_shape = Shape{1, 3, 4, 1};
-    auto exp_out = std::vector<uint8_t> {0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0,
-                                         0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0};
+    auto exp_out = std::vector<uint8_t>{0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0,
+                                        0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0};
     auto out_shape = Shape{1, 2, 4, 3};
     reference_tests::Tensor inp_tensor(input_shape, element::u8, input);
     inputData = {inp_tensor.data};
@@ -63,12 +63,10 @@ TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_r_u8_single_
 }
 
 TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_color_u8_single_bgr) {
-    auto input = std::vector<uint8_t> {0x51, 0xeb, 0x51, 0xeb,
-                                       0x51, 0xeb, 0x51, 0xeb,
-                                       0x6d, 0x6d, 0xb8, 0xb8};
+    auto input = std::vector<uint8_t>{0x51, 0xeb, 0x51, 0xeb, 0x51, 0xeb, 0x51, 0xeb, 0x6d, 0x6d, 0xb8, 0xb8};
     auto input_shape = Shape{1, 6, 2, 1};
-    auto exp_out = std::vector<uint8_t> {37, 37, 164, 217, 216, 255, 37, 37, 164, 217, 216, 255,
-                                         37, 37, 164, 217, 216, 255, 37, 37, 164, 217, 216, 255};
+    auto exp_out = std::vector<uint8_t>{37, 37, 164, 217, 216, 255, 37, 37, 164, 217, 216, 255,
+                                        37, 37, 164, 217, 216, 255, 37, 37, 164, 217, 216, 255};
     auto out_shape = Shape{1, 4, 2, 3};
 
     reference_tests::Tensor inp_tensor(input_shape, element::u8, input);
@@ -83,12 +81,10 @@ TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_color_u8_sin
 }
 
 TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_g_fp32_single_rgb) {
-    auto input = std::vector<float> {145.f, 145.f, 145.f, 145.f,
-                                     145.f, 145.f, 145.f, 145.f,
-                                     54.f, 54.f, 34.f, 34.f};
+    auto input = std::vector<float>{145.f, 145.f, 145.f, 145.f, 145.f, 145.f, 145.f, 145.f, 54.f, 54.f, 34.f, 34.f};
     auto input_shape = Shape{1, 3, 4, 1};
-    auto exp_out = std::vector<float> {0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0,
-                                       0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0};
+    auto exp_out = std::vector<float>{0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0,
+                                      0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0};
     auto out_shape = Shape{1, 2, 4, 3};
 
     reference_tests::Tensor inp_tensor(input_shape, element::f32, input);
@@ -103,23 +99,17 @@ TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_g_fp32_singl
 }
 
 TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_batch_fp32_three_bgr) {
-    auto input_y = std::vector<float> {81.f, 81.f, 81.f, 81.f,
-                                       145.f, 145.f, 145.f, 145.f,
-                                       41.f, 41.f, 41.f, 41.f};
+    auto input_y = std::vector<float>{81.f, 81.f, 81.f, 81.f, 145.f, 145.f, 145.f, 145.f, 41.f, 41.f, 41.f, 41.f};
     auto input_shape_y = Shape{3, 2, 2, 1};
 
-    auto input_u = std::vector<float> {90.,
-                                        54.,
-                                        240.};
+    auto input_u = std::vector<float>{90., 54., 240.};
     auto input_shape_u = Shape{3, 1, 1, 1};
 
-    auto input_v = std::vector<float> {240.,
-                                       34.,
-                                       110.};
+    auto input_v = std::vector<float>{240., 34., 110.};
     auto input_shape_v = Shape{3, 1, 1, 1};
-    auto exp_out = std::vector<float> {0, 0, 255., 0, 0, 255., 0, 0, 255., 0, 0, 255.,
-                                       0, 255., 0, 0, 255., 0, 0, 255., 0, 0, 255., 0,
-                                       255., 0, 0, 255., 0, 0, 255., 0, 0, 255., 0, 0};
+    auto exp_out =
+        std::vector<float>{0, 0,    255., 0, 0,    255., 0,    0, 255., 0,    0, 255., 0,    255., 0, 0,    255., 0,
+                           0, 255., 0,    0, 255., 0,    255., 0, 0,    255., 0, 0,    255., 0,    0, 255., 0,    0};
     auto out_shape = Shape{3, 2, 2, 3};
 
     reference_tests::Tensor inp_tensor_y(input_shape_y, element::f32, input_y);
@@ -136,25 +126,17 @@ TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_batch_fp32_t
 }
 
 TEST_F(ReferenceConvertColorI420LayerTest, CompareWithHardcodedRefs_color4x4_f32_three_rgb) {
-    auto input_y = std::vector<float> {81, 235,
-                                       81, 235,
-                                       81, 81,
-                                       81, 81,
-                                       145, 145,
-                                       145, 145,
-                                       41, 41,
-                                       41, 41};
+    auto input_y = std::vector<float>{81, 235, 81, 235, 81, 81, 81, 81, 145, 145, 145, 145, 41, 41, 41, 41};
     auto input_shape_y = Shape{1, 8, 2, 1};
 
-    auto input_u = std::vector<float> {109, 90, 54, 240};
+    auto input_u = std::vector<float>{109, 90, 54, 240};
     auto input_shape_u = Shape{1, 4, 1, 1};
-    auto input_v = std::vector<float> {184, 240, 34, 110};
+    auto input_v = std::vector<float>{184, 240, 34, 110};
     auto input_shape_v = Shape{1, 4, 1, 1};
 
-    auto exp_out = std::vector<float> {165, 37, 37, 255, 216, 217, 165, 37, 37, 255, 216, 217,
-                                       255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0,
-                                       0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255, 0,
-                                       0, 0, 255, 0, 0, 255, 0, 0, 255, 0, 0, 255};
+    auto exp_out = std::vector<float>{165, 37, 37,  255, 216, 217, 165, 37, 37, 255, 216, 217, 255, 0, 0, 255,
+                                      0,   0,  255, 0,   0,   255, 0,   0,  0,  255, 0,   0,   255, 0, 0, 255,
+                                      0,   0,  255, 0,   0,   0,   255, 0,  0,  255, 0,   0,   255, 0, 0, 255};
     auto out_shape = Shape{1, 2, 2, 3};
 
     reference_tests::Tensor inp_tensor_y(input_shape_y, element::f32, input_y);
diff --git a/src/plugins/template/tests/functional/op_reference/convert_color_nv12.cpp b/src/plugins/template/tests/functional/op_reference/convert_color_nv12.cpp
index 2eb13749da0b51..26d9c31bae3f1e 100644
--- a/src/plugins/template/tests/functional/op_reference/convert_color_nv12.cpp
+++ b/src/plugins/template/tests/functional/op_reference/convert_color_nv12.cpp
@@ -5,9 +5,9 @@
 #include <gtest/gtest.h>
 
 #include <openvino/core/model.hpp>
-#include <tuple>
-#include <openvino/op/nv12_to_rgb.hpp>
 #include <openvino/op/nv12_to_bgr.hpp>
+#include <openvino/op/nv12_to_rgb.hpp>
+#include <tuple>
 
 #include "base_reference_test.hpp"
 #include "functional_test_utils/skip_tests_config.hpp"
@@ -20,8 +20,8 @@ class ReferenceConvertColorNV12LayerTest : public testing::Test, public CommonRe
 public:
     void SetUp() override {
         SKIP_IF_CURRENT_TEST_IS_DISABLED()
-        abs_threshold = 2.f; // allow R, G, B absolute deviation to 2 (of max 255)
-        threshold = 1.f; // Ignore relative comparison (100%)
+        abs_threshold = 2.f;  // allow R, G, B absolute deviation to 2 (of max 255)
+        threshold = 1.f;      // Ignore relative comparison (100%)
     }
 
 public:
@@ -31,24 +31,25 @@ class ReferenceConvertColorNV12LayerTest : public testing::Test, public CommonRe
         std::shared_ptr<Node> conv;
         conv = std::make_shared<T>(in);
         auto res = std::make_shared<op::v0::Result>(conv);
-        return std::make_shared<Model>(ResultVector{res}, ParameterVector {in});
+        return std::make_shared<Model>(ResultVector{res}, ParameterVector{in});
     }
 
     template <typename T>
-    static std::shared_ptr<Model> CreateFunction2(const reference_tests::Tensor& input1, const reference_tests::Tensor& input2) {
+    static std::shared_ptr<Model> CreateFunction2(const reference_tests::Tensor& input1,
+                                                  const reference_tests::Tensor& input2) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input1.type, input1.shape);
         const auto in2 = std::make_shared<op::v0::Parameter>(input2.type, input2.shape);
         std::shared_ptr<Node> conv;
         conv = std::make_shared<T>(in1, in2);
         auto res = std::make_shared<op::v0::Result>(conv);
-        return std::make_shared<Model>(ResultVector{res}, ParameterVector {in1, in2});
+        return std::make_shared<Model>(ResultVector{res}, ParameterVector{in1, in2});
     }
 };
 
 TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_r_u8_single_rgb) {
-    auto input = std::vector<uint8_t> {0x51, 0x51, 0x51, 0x51, 0x5a, 0xf0};
+    auto input = std::vector<uint8_t>{0x51, 0x51, 0x51, 0x51, 0x5a, 0xf0};
     auto input_shape = Shape{1, 3, 2, 1};
-    auto exp_out = std::vector<uint8_t> {0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0};
+    auto exp_out = std::vector<uint8_t>{0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0, 0xff, 0, 0};
     auto out_shape = Shape{1, 2, 2, 3};
     reference_tests::Tensor inp_tensor(input_shape, element::u8, input);
     inputData = {inp_tensor.data};
@@ -59,9 +60,9 @@ TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_r_u8_single_
 }
 
 TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_color_u8_single_bgr) {
-    auto input = std::vector<uint8_t> {0x51, 0xeb, 0x51, 0xeb, 0x6d, 0xb8};
+    auto input = std::vector<uint8_t>{0x51, 0xeb, 0x51, 0xeb, 0x6d, 0xb8};
     auto input_shape = Shape{1, 3, 2, 1};
-    auto exp_out = std::vector<uint8_t> {37, 37, 164, 215, 216, 255, 37, 37, 164, 215, 216, 255};
+    auto exp_out = std::vector<uint8_t>{37, 37, 164, 215, 216, 255, 37, 37, 164, 215, 216, 255};
     auto out_shape = Shape{1, 2, 2, 3};
 
     reference_tests::Tensor inp_tensor(input_shape, element::u8, input);
@@ -76,9 +77,9 @@ TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_color_u8_sin
 }
 
 TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_g_fp32_single_rgb) {
-    auto input = std::vector<float> {145.f, 145.f, 145.f, 145.f, 54.f, 34.f};
+    auto input = std::vector<float>{145.f, 145.f, 145.f, 145.f, 54.f, 34.f};
     auto input_shape = Shape{1, 3, 2, 1};
-    auto exp_out = std::vector<float> {0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0};
+    auto exp_out = std::vector<float>{0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0, 0, 255.f, 0};
     auto out_shape = Shape{1, 2, 2, 3};
 
     reference_tests::Tensor inp_tensor(input_shape, element::f32, input);
@@ -93,19 +94,15 @@ TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_g_fp32_singl
 }
 
 TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_batch_fp32_two_bgr) {
-    auto input_y = std::vector<float> {81.f, 81.f, 81.f, 81.f,
-                                       145.f, 145.f, 145.f, 145.f,
-                                       41.f, 41.f, 41.f, 41.f};
+    auto input_y = std::vector<float>{81.f, 81.f, 81.f, 81.f, 145.f, 145.f, 145.f, 145.f, 41.f, 41.f, 41.f, 41.f};
     auto input_shape_y = Shape{3, 2, 2, 1};
 
-    auto input_uv = std::vector<float> {90., 240.,
-                                        54., 34.,
-                                        240., 110.};
+    auto input_uv = std::vector<float>{90., 240., 54., 34., 240., 110.};
     auto input_shape_uv = Shape{3, 1, 1, 2};
 
-    auto exp_out = std::vector<float> {0, 0, 255., 0, 0, 255., 0, 0, 255., 0, 0, 255.,
-                                       0, 255., 0, 0, 255., 0, 0, 255., 0, 0, 255., 0,
-                                       255., 0, 0, 255., 0, 0, 255., 0, 0, 255., 0, 0};
+    auto exp_out =
+        std::vector<float>{0, 0,    255., 0, 0,    255., 0,    0, 255., 0,    0, 255., 0,    255., 0, 0,    255., 0,
+                           0, 255., 0,    0, 255., 0,    255., 0, 0,    255., 0, 0,    255., 0,    0, 255., 0,    0};
     auto out_shape = Shape{3, 2, 2, 3};
 
     reference_tests::Tensor inp_tensor_y(input_shape_y, element::f32, input_y);
@@ -121,13 +118,13 @@ TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_batch_fp32_t
 }
 
 TEST_F(ReferenceConvertColorNV12LayerTest, CompareWithHardcodedRefs_color2x2_f32_two_rgb) {
-    auto input_y = std::vector<float> {81, 235, 81, 235};
+    auto input_y = std::vector<float>{81, 235, 81, 235};
     auto input_shape_y = Shape{1, 2, 2, 1};
 
-    auto input_uv = std::vector<float> {109, 184};
+    auto input_uv = std::vector<float>{109, 184};
     auto input_shape_uv = Shape{1, 1, 1, 2};
 
-    auto exp_out = std::vector<float> {164, 37, 37, 255, 216, 215, 164, 37, 37, 255, 216, 215};
+    auto exp_out = std::vector<float>{164, 37, 37, 255, 216, 215, 164, 37, 37, 255, 216, 215};
     auto out_shape = Shape{1, 2, 2, 3};
 
     reference_tests::Tensor inp_tensor_y(input_shape_y, element::f32, input_y);
diff --git a/src/plugins/template/tests/functional/op_reference/convert_like.cpp b/src/plugins/template/tests/functional/op_reference/convert_like.cpp
index 3ff098e4e14306..b46fe98af030c2 100644
--- a/src/plugins/template/tests/functional/op_reference/convert_like.cpp
+++ b/src/plugins/template/tests/functional/op_reference/convert_like.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/convert_like.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/convert_like.hpp"
 #include "conversion.hpp"
 
 using namespace ov;
@@ -14,393 +15,1277 @@ namespace ConversionOpsRefTestDefinitions {
 namespace {
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Conversion_With_Hardcoded_Refs, ReferenceConversionLayerTest,
+    smoke_Conversion_With_Hardcoded_Refs,
+    ReferenceConversionLayerTest,
     ::testing::Values(
         // destination boolean
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 3}, ov::element::u8, ov::element::boolean,
-                      std::vector<uint8_t> {0, 12, 23, 0, std::numeric_limits<uint8_t>::lowest(), std::numeric_limits<uint8_t>::max()},
-                      std::vector<char> {0, 1, 1, 0, 0, 1}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 3}, ov::element::i32, ov::element::boolean,
-                      std::vector<int32_t> {0, -12, 23, 0, std::numeric_limits<int32_t>::lowest(), std::numeric_limits<int32_t>::max()},
-                      std::vector<char> {0, 1, 1, 0, 1, 1}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {3, 3}, ov::element::f32, ov::element::boolean,
-                      std::vector<float> {0.f, 1.5745f, 0.12352f, 0.f, std::numeric_limits<float>::lowest(), std::numeric_limits<float>::max(),
-                                          std::numeric_limits<float>::min(), std::numeric_limits<float>::infinity(), -std::numeric_limits<float>::infinity()},
-                      std::vector<char> {0, 1, 1, 0, 1, 1, 1, 1, 1}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 3},
+                      ov::element::u8,
+                      ov::element::boolean,
+                      std::vector<uint8_t>{0,
+                                           12,
+                                           23,
+                                           0,
+                                           std::numeric_limits<uint8_t>::lowest(),
+                                           std::numeric_limits<uint8_t>::max()},
+                      std::vector<char>{0, 1, 1, 0, 0, 1}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 3},
+                      ov::element::i32,
+                      ov::element::boolean,
+                      std::vector<int32_t>{0,
+                                           -12,
+                                           23,
+                                           0,
+                                           std::numeric_limits<int32_t>::lowest(),
+                                           std::numeric_limits<int32_t>::max()},
+                      std::vector<char>{0, 1, 1, 0, 1, 1}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{3, 3},
+                      ov::element::f32,
+                      ov::element::boolean,
+                      std::vector<float>{0.f,
+                                         1.5745f,
+                                         0.12352f,
+                                         0.f,
+                                         std::numeric_limits<float>::lowest(),
+                                         std::numeric_limits<float>::max(),
+                                         std::numeric_limits<float>::min(),
+                                         std::numeric_limits<float>::infinity(),
+                                         -std::numeric_limits<float>::infinity()},
+                      std::vector<char>{0, 1, 1, 0, 1, 1, 1, 1, 1}),
         // destination bf16
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {1, 1, 3, 5}, ov::element::f32, ov::element::bf16,
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<bfloat16> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {11}, ov::element::u8, ov::element::bf16,
-                      std::vector<uint8_t> {0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142},
-                      std::vector<bfloat16> {0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}),
+        ConvertParams(
+            ConversionTypes::CONVERT_LIKE,
+            ov::PartialShape{1, 1, 3, 5},
+            ov::element::f32,
+            ov::element::bf16,
+            std::
+                vector<float>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
+            std::vector<
+                bfloat16>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{11},
+                      ov::element::u8,
+                      ov::element::bf16,
+                      std::vector<uint8_t>{0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142},
+                      std::vector<bfloat16>{0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}),
 
         // destination f16
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {1, 1, 3, 5}, ov::element::f32, ov::element::f16,
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<float16> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {11}, ov::element::u8, ov::element::f16,
-                      std::vector<uint8_t> {0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142},
-                      std::vector<float16> {0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}),
+        ConvertParams(
+            ConversionTypes::CONVERT_LIKE,
+            ov::PartialShape{1, 1, 3, 5},
+            ov::element::f32,
+            ov::element::f16,
+            std::
+                vector<float>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
+            std::vector<
+                float16>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{11},
+                      ov::element::u8,
+                      ov::element::f16,
+                      std::vector<uint8_t>{0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142},
+                      std::vector<float16>{0, 10, 15, 20, 43, 56, 78, 99, 102, 130, 142}),
 
         // destination f32
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::u1, ov::element::f32,
-                      std::vector<uint8_t> {0xA0}, std::vector<float> {1.0f, 0.0f, 1.0f, 0.0f}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::u4, ov::element::f32,
-                      std::vector<uint8_t> {0xFB, 0x0A}, std::vector<float> {15.0f, 11.0f, 0.0f, 10.0f}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::u8, ov::element::f32,
-                      std::vector<uint8_t> {255, 128, 32, 0}, std::vector<float> {255.0f, 128.0f, 32.0f, 0.0f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::u16, ov::element::f32,
-                      std::vector<uint16_t> {64000, 32000, 128, 0}, std::vector<float> {64000.0f, 32000.0f, 128.0f, 0.0f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::u32, ov::element::f32,
-                      std::vector<uint32_t> {4000000, 2000000, 128, 0}, std::vector<float> {4000000.0f, 2000000.0f, 128.0f, 0.0f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::u64, ov::element::f32,
-                      std::vector<uint64_t> {4000000, 2000000, 128, 0}, std::vector<float> {4000000.0f, 2000000.0f, 128.0f, 0.0f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::i4, ov::element::f32,
-                      std::vector<uint8_t> {0xFE, 0xF2}, std::vector<float> {-1.0f, -2.0f, -1.0f, 2.0f}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::i8, ov::element::f32,
-                      std::vector<int8_t> {-127, -0, 0, 127}, std::vector<float> {-127.0f, -0.0f, 0.0f, 127.0f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::i16, ov::element::f32,
-                      std::vector<int16_t> {-32000, -0, 0, 32000}, std::vector<float> {-32000.0f, -0.0f, 0.0f, 32000.0f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::i32, ov::element::f32,
-                      std::vector<int32_t> {-64000, -0, 0, 64000}, std::vector<float> {-64000.0f, -0.0f, 0.0f, 64000.0f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {2, 2}, ov::element::i64, ov::element::f32,
-                      std::vector<int64_t> {-64000, -0, 0, 64000}, std::vector<float> {-64000.0f, -0.0f, 0.0f, 64000.0f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {1, 1, 3, 5}, ov::element::bf16, ov::element::f32,
-                      std::vector<bfloat16> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {1, 1, 3, 5}, ov::element::f16, ov::element::f32,
-                      std::vector<float16> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {1, 1, 3, 5}, ov::element::f32, ov::element::f32,
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
-                      std::vector<float> {0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::u1,
+                      ov::element::f32,
+                      std::vector<uint8_t>{0xA0},
+                      std::vector<float>{1.0f, 0.0f, 1.0f, 0.0f},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::u4,
+                      ov::element::f32,
+                      std::vector<uint8_t>{0xFB, 0x0A},
+                      std::vector<float>{15.0f, 11.0f, 0.0f, 10.0f},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::u8,
+                      ov::element::f32,
+                      std::vector<uint8_t>{255, 128, 32, 0},
+                      std::vector<float>{255.0f, 128.0f, 32.0f, 0.0f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::u16,
+                      ov::element::f32,
+                      std::vector<uint16_t>{64000, 32000, 128, 0},
+                      std::vector<float>{64000.0f, 32000.0f, 128.0f, 0.0f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::u32,
+                      ov::element::f32,
+                      std::vector<uint32_t>{4000000, 2000000, 128, 0},
+                      std::vector<float>{4000000.0f, 2000000.0f, 128.0f, 0.0f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::u64,
+                      ov::element::f32,
+                      std::vector<uint64_t>{4000000, 2000000, 128, 0},
+                      std::vector<float>{4000000.0f, 2000000.0f, 128.0f, 0.0f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::i4,
+                      ov::element::f32,
+                      std::vector<uint8_t>{0xFE, 0xF2},
+                      std::vector<float>{-1.0f, -2.0f, -1.0f, 2.0f},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::i8,
+                      ov::element::f32,
+                      std::vector<int8_t>{-127, -0, 0, 127},
+                      std::vector<float>{-127.0f, -0.0f, 0.0f, 127.0f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::i16,
+                      ov::element::f32,
+                      std::vector<int16_t>{-32000, -0, 0, 32000},
+                      std::vector<float>{-32000.0f, -0.0f, 0.0f, 32000.0f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::i32,
+                      ov::element::f32,
+                      std::vector<int32_t>{-64000, -0, 0, 64000},
+                      std::vector<float>{-64000.0f, -0.0f, 0.0f, 64000.0f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{2, 2},
+                      ov::element::i64,
+                      ov::element::f32,
+                      std::vector<int64_t>{-64000, -0, 0, 64000},
+                      std::vector<float>{-64000.0f, -0.0f, 0.0f, 64000.0f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{1, 1, 3, 5},
+                      ov::element::bf16,
+                      ov::element::f32,
+                      std::vector<bfloat16>{0.5f,
+                                            1.5f,
+                                            0.5f,
+                                            2.5f,
+                                            1.5f,
+                                            0.5f,
+                                            3.5f,
+                                            2.5f,
+                                            0.5f,
+                                            0.5f,
+                                            2.5f,
+                                            0.5f,
+                                            0.5f,
+                                            0.5f,
+                                            1.5f},
+                      std::vector<float>{0.5f,
+                                         1.5f,
+                                         0.5f,
+                                         2.5f,
+                                         1.5f,
+                                         0.5f,
+                                         3.5f,
+                                         2.5f,
+                                         0.5f,
+                                         0.5f,
+                                         2.5f,
+                                         0.5f,
+                                         0.5f,
+                                         0.5f,
+                                         1.5f}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{1, 1, 3, 5},
+                      ov::element::f16,
+                      ov::element::f32,
+                      std::vector<float16>{0.5f,
+                                           1.5f,
+                                           0.5f,
+                                           2.5f,
+                                           1.5f,
+                                           0.5f,
+                                           3.5f,
+                                           2.5f,
+                                           0.5f,
+                                           0.5f,
+                                           2.5f,
+                                           0.5f,
+                                           0.5f,
+                                           0.5f,
+                                           1.5f},
+                      std::vector<float>{0.5f,
+                                         1.5f,
+                                         0.5f,
+                                         2.5f,
+                                         1.5f,
+                                         0.5f,
+                                         3.5f,
+                                         2.5f,
+                                         0.5f,
+                                         0.5f,
+                                         2.5f,
+                                         0.5f,
+                                         0.5f,
+                                         0.5f,
+                                         1.5f}),
+        ConvertParams(
+            ConversionTypes::CONVERT_LIKE,
+            ov::PartialShape{1, 1, 3, 5},
+            ov::element::f32,
+            ov::element::f32,
+            std::
+                vector<float>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f},
+            std::vector<
+                float>{0.5f, 1.5f, 0.5f, 2.5f, 1.5f, 0.5f, 3.5f, 2.5f, 0.5f, 0.5f, 2.5f, 0.5f, 0.5f, 0.5f, 1.5f}),
 
         // destination i4
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u1, ov::element::i4, std::vector<uint8_t> {0xA0},
-                      std::vector<uint8_t> {0x10, 0x10}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::i4, std::vector<uint8_t> {0x12, 0x03},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::i4, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::i4, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::i4, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::i4, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::i4, std::vector<uint8_t> {0xFE, 0x03},
-                      std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::i4, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::i4, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::i4, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::i4, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::i4,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::i4,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::i4, std::vector<float> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u1,
+                      ov::element::i4,
+                      std::vector<uint8_t>{0xA0},
+                      std::vector<uint8_t>{0x10, 0x10},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i4,
+                      std::vector<uint8_t>{0x12, 0x03},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i4,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i4,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i4,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i4,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i4,
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i4,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i4,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i4,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i4,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i4,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i4,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i4,
+                      std::vector<float>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
         // destination i8
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::i8, std::vector<uint8_t> {0x81},
-                      std::vector<int8_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::i8, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int8_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::i8, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<int8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::i8, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<int8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::i8, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<int8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::i8, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<int8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::i8, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int8_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::i8, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::i8, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::i8, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::i8, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::i8,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<int8_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::i8,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<int8_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::i8, std::vector<float> {-1, -2, 2, 3},
-                      std::vector<int8_t> {-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::i8,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<int8_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i8,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int8_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i8,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<int8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i8,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<int8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i8,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<int8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i8,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<int8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i8,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int8_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i8,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i8,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i8,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i8,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i8,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<int8_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i8,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<int8_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i8,
+                      std::vector<float>{-1, -2, 2, 3},
+                      std::vector<int8_t>{-1, -2, 2, 3}),
         // destination i16
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::i16, std::vector<uint8_t> {0x81},
-                      std::vector<int16_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::i16, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int16_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::i16, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<int16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::i16, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<int16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::i16, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<int16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::i16, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<int16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::i16, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int16_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::i16, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::i16, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::i16, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::i16, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::i16,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<int16_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::i16,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<int16_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::i16, std::vector<float> {-1, -2, 2, 3},
-                      std::vector<int16_t> {-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::i16,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<int16_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i16,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int16_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i16,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<int16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i16,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<int16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i16,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<int16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i16,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<int16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i16,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int16_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i16,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i16,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i16,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i16,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i16,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<int16_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i16,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<int16_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i16,
+                      std::vector<float>{-1, -2, 2, 3},
+                      std::vector<int16_t>{-1, -2, 2, 3}),
         // destination i32
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::i32, std::vector<uint8_t> {0x81},
-                      std::vector<int32_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::i32, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int32_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::i32, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<int32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::i32, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<int32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::i32, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<int32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::i32, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<int32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::i32, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int32_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::i32, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::i32, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::i32, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::i32, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::i32,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<int32_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::i32,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<int32_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::i32, std::vector<float> {-1, -2, 2, 3},
-                      std::vector<int32_t> {-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::i32,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<int32_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i32,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int32_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i32,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<int32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i32,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<int32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i32,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<int32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i32,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<int32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i32,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int32_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i32,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i32,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i32,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i32,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i32,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<int32_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i32,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<int32_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i32,
+                      std::vector<float>{-1, -2, 2, 3},
+                      std::vector<int32_t>{-1, -2, 2, 3}),
         // destination i64
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::i64, std::vector<uint8_t> {0x81},
-                      std::vector<int64_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::i64, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int64_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::i64, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<int64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::i64, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<int64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::i64, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<int64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::i64, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<int64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::i64, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<int64_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::i64, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::i64, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::i64, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::i64, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::i64,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<int64_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::i64,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<int64_t> {-1, -2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::i64, std::vector<float> {-1, -2, 2, 3},
-                      std::vector<int64_t> {-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::i64,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<int64_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::i64,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int64_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::i64,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<int64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::i64,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<int64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::i64,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<int64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::i64,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<int64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::i64,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<int64_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::i64,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::i64,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::i64,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::i64,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::i64,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<int64_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::i64,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<int64_t>{-1, -2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::i64,
+                      std::vector<float>{-1, -2, 2, 3},
+                      std::vector<int64_t>{-1, -2, 2, 3}),
 
         // destination u1
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::u1, std::vector<uint8_t> {0xA0},
-                      std::vector<uint8_t> {0xA0}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u4, ov::element::u1,
-                      std::vector<uint8_t> {0x10, 0x01, 0x00, 0x00}, std::vector<uint8_t> {0x90}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u8, ov::element::u1,
-                      std::vector<uint8_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u16, ov::element::u1,
-                      std::vector<uint16_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u32, ov::element::u1,
-                      std::vector<uint32_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u64, ov::element::u1,
-                      std::vector<uint64_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::i4, ov::element::u1,
-                      std::vector<uint8_t> {0x10, 0x01, 0x00, 0x00}, std::vector<uint8_t> {0x90}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::i8, ov::element::u1,
-                      std::vector<int8_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::i16, ov::element::u1,
-                      std::vector<int16_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::i32, ov::element::u1,
-                      std::vector<int32_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::i64, ov::element::u1,
-                      std::vector<int64_t> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::f16, ov::element::u1,
-                      std::vector<ov::float16> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::bf16, ov::element::u1,
-                      std::vector<ov::bfloat16> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::f32, ov::element::u1,
-                      std::vector<float> {1, 0, 1, 0, 0, 0, 0, 1}, std::vector<uint8_t> {0xA1}, 8, 8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u1,
+                      std::vector<uint8_t>{0xA0},
+                      std::vector<uint8_t>{0xA0},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u4,
+                      ov::element::u1,
+                      std::vector<uint8_t>{0x10, 0x01, 0x00, 0x00},
+                      std::vector<uint8_t>{0x90},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u8,
+                      ov::element::u1,
+                      std::vector<uint8_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u16,
+                      ov::element::u1,
+                      std::vector<uint16_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u32,
+                      ov::element::u1,
+                      std::vector<uint32_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u64,
+                      ov::element::u1,
+                      std::vector<uint64_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::i4,
+                      ov::element::u1,
+                      std::vector<uint8_t>{0x10, 0x01, 0x00, 0x00},
+                      std::vector<uint8_t>{0x90},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::i8,
+                      ov::element::u1,
+                      std::vector<int8_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::i16,
+                      ov::element::u1,
+                      std::vector<int16_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::i32,
+                      ov::element::u1,
+                      std::vector<int32_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::i64,
+                      ov::element::u1,
+                      std::vector<int64_t>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::f16,
+                      ov::element::u1,
+                      std::vector<ov::float16>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::bf16,
+                      ov::element::u1,
+                      std::vector<ov::bfloat16>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::f32,
+                      ov::element::u1,
+                      std::vector<float>{1, 0, 1, 0, 0, 0, 0, 1},
+                      std::vector<uint8_t>{0xA1},
+                      8,
+                      8),
 
         // destination u4
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u1, ov::element::u4, std::vector<uint8_t> {0xA0},
-                      std::vector<uint8_t> {0x10, 0x10}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::u4, std::vector<uint8_t> {0x12, 0x03},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::u4, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::u4, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::u4, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::u4, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {0x12, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::u4, std::vector<uint8_t> {0xFE, 0x03},
-                      std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::u4, std::vector<int8_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::u4, std::vector<int16_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::u4, std::vector<int32_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::u4, std::vector<int64_t> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::u4,
-                      std::vector<ov::float16> {-1, -2, 0, 3}, std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::u4,
-                      std::vector<ov::bfloat16> {-1, -2, 0, 3}, std::vector<uint8_t> {0xFE, 0x03}, 4, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::u4, std::vector<float> {-1, -2, 2, 3},
-                      std::vector<uint8_t> {0xFE, 0x23}, 4, 4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u1,
+                      ov::element::u4,
+                      std::vector<uint8_t>{0xA0},
+                      std::vector<uint8_t>{0x10, 0x10},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u4,
+                      std::vector<uint8_t>{0x12, 0x03},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u4,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u4,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u4,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u4,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{0x12, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u4,
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u4,
+                      std::vector<int8_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u4,
+                      std::vector<int16_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u4,
+                      std::vector<int32_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u4,
+                      std::vector<int64_t>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u4,
+                      std::vector<ov::float16>{-1, -2, 0, 3},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u4,
+                      std::vector<ov::bfloat16>{-1, -2, 0, 3},
+                      std::vector<uint8_t>{0xFE, 0x03},
+                      4,
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u4,
+                      std::vector<float>{-1, -2, 2, 3},
+                      std::vector<uint8_t>{0xFE, 0x23},
+                      4,
+                      4),
 
         // destination u8
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::u8, std::vector<uint8_t> {0x81},
-                      std::vector<uint8_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::u8, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint8_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::u8, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::u8, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::u8, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::u8, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::u8, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint8_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::u8, std::vector<int8_t> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::u8, std::vector<int16_t> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::u8, std::vector<int32_t> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::u8, std::vector<int64_t> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::u8,
-                      std::vector<ov::float16> {1, 2, 0, 3}, std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::u8,
-                      std::vector<ov::bfloat16> {1, 2, 0, 3}, std::vector<uint8_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::u8, std::vector<float> {1, 2, 2, 3},
-                      std::vector<uint8_t> {1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u8,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<uint8_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u8,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint8_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u8,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u8,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u8,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u8,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u8,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint8_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u8,
+                      std::vector<int8_t>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u8,
+                      std::vector<int16_t>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u8,
+                      std::vector<int32_t>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u8,
+                      std::vector<int64_t>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u8,
+                      std::vector<ov::float16>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u8,
+                      std::vector<ov::bfloat16>{1, 2, 0, 3},
+                      std::vector<uint8_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u8,
+                      std::vector<float>{1, 2, 2, 3},
+                      std::vector<uint8_t>{1, 2, 2, 3}),
 
         // destination u16
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::u16, std::vector<uint8_t> {0x81},
-                      std::vector<uint16_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::u16, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint16_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::u16, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::u16, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::u16, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::u16, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::u16, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint16_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::u16, std::vector<int8_t> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::u16, std::vector<int16_t> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::u16, std::vector<int32_t> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::u16, std::vector<int64_t> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::u16,
-                      std::vector<ov::float16> {1, 2, 0, 3}, std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::u16,
-                      std::vector<ov::bfloat16> {1, 2, 0, 3}, std::vector<uint16_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::u16, std::vector<float> {1, 2, 2, 3},
-                      std::vector<uint16_t> {1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u16,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<uint16_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u16,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint16_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u16,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u16,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u16,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u16,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u16,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint16_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u16,
+                      std::vector<int8_t>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u16,
+                      std::vector<int16_t>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u16,
+                      std::vector<int32_t>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u16,
+                      std::vector<int64_t>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u16,
+                      std::vector<ov::float16>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u16,
+                      std::vector<ov::bfloat16>{1, 2, 0, 3},
+                      std::vector<uint16_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u16,
+                      std::vector<float>{1, 2, 2, 3},
+                      std::vector<uint16_t>{1, 2, 2, 3}),
 
         // destination u32
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::u32, std::vector<uint8_t> {0x81},
-                      std::vector<uint32_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::u32, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint32_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::u32, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::u32, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::u32, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::u32, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::u32, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint32_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::u32, std::vector<int8_t> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::u32, std::vector<int16_t> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::u32, std::vector<int32_t> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::u32, std::vector<int64_t> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::u32,
-                      std::vector<ov::float16> {1, 2, 0, 3}, std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::u32,
-                      std::vector<ov::bfloat16> {1, 2, 0, 3}, std::vector<uint32_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::u32, std::vector<float> {1, 2, 2, 3},
-                      std::vector<uint32_t> {1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u32,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<uint32_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u32,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint32_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u32,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u32,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u32,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u32,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u32,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint32_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u32,
+                      std::vector<int8_t>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u32,
+                      std::vector<int16_t>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u32,
+                      std::vector<int32_t>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u32,
+                      std::vector<int64_t>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u32,
+                      std::vector<ov::float16>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u32,
+                      std::vector<ov::bfloat16>{1, 2, 0, 3},
+                      std::vector<uint32_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u32,
+                      std::vector<float>{1, 2, 2, 3},
+                      std::vector<uint32_t>{1, 2, 2, 3}),
         // destination u64
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {8}, ov::element::u1, ov::element::u64, std::vector<uint8_t> {0x81},
-                      std::vector<uint64_t> {1, 0, 0, 0, 0, 0, 0, 1}, 8),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u4, ov::element::u64, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint64_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u8, ov::element::u64, std::vector<uint8_t> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u16, ov::element::u64, std::vector<uint16_t> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u32, ov::element::u64, std::vector<uint32_t> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::u64, ov::element::u64, std::vector<uint64_t> {1, 2, 0, 3},
-                      std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i4, ov::element::u64, std::vector<uint8_t> {0x21, 0x43},
-                      std::vector<uint64_t> {2, 1, 4, 3}, 4),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i8, ov::element::u64, std::vector<int8_t> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i16, ov::element::u64, std::vector<int16_t> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i32, ov::element::u64, std::vector<int32_t> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::i64, ov::element::u64, std::vector<int64_t> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f16, ov::element::u64,
-                      std::vector<ov::float16> {1, 2, 0, 3}, std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::bf16, ov::element::u64,
-                      std::vector<ov::bfloat16> {1, 2, 0, 3}, std::vector<uint64_t> {1, 2, 0, 3}),
-        ConvertParams(ConversionTypes::CONVERT_LIKE, ov::PartialShape {4}, ov::element::f32, ov::element::u64, std::vector<float> {1, 2, 2, 3},
-                      std::vector<uint64_t> {1, 2, 2, 3})),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{8},
+                      ov::element::u1,
+                      ov::element::u64,
+                      std::vector<uint8_t>{0x81},
+                      std::vector<uint64_t>{1, 0, 0, 0, 0, 0, 0, 1},
+                      8),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u4,
+                      ov::element::u64,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint64_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u8,
+                      ov::element::u64,
+                      std::vector<uint8_t>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u16,
+                      ov::element::u64,
+                      std::vector<uint16_t>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u32,
+                      ov::element::u64,
+                      std::vector<uint32_t>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::u64,
+                      ov::element::u64,
+                      std::vector<uint64_t>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i4,
+                      ov::element::u64,
+                      std::vector<uint8_t>{0x21, 0x43},
+                      std::vector<uint64_t>{2, 1, 4, 3},
+                      4),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i8,
+                      ov::element::u64,
+                      std::vector<int8_t>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i16,
+                      ov::element::u64,
+                      std::vector<int16_t>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i32,
+                      ov::element::u64,
+                      std::vector<int32_t>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::i64,
+                      ov::element::u64,
+                      std::vector<int64_t>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f16,
+                      ov::element::u64,
+                      std::vector<ov::float16>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::bf16,
+                      ov::element::u64,
+                      std::vector<ov::bfloat16>{1, 2, 0, 3},
+                      std::vector<uint64_t>{1, 2, 0, 3}),
+        ConvertParams(ConversionTypes::CONVERT_LIKE,
+                      ov::PartialShape{4},
+                      ov::element::f32,
+                      ov::element::u64,
+                      std::vector<float>{1, 2, 2, 3},
+                      std::vector<uint64_t>{1, 2, 2, 3})),
     ReferenceConversionLayerTest::getTestCaseName);
-} // namespace
-} // namespace ConversionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace
+}  // namespace ConversionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/convolution.cpp b/src/plugins/template/tests/functional/op_reference/convolution.cpp
index 055921abe53c5b..64f4a5f82752e1 100644
--- a/src/plugins/template/tests/functional/op_reference/convolution.cpp
+++ b/src/plugins/template/tests/functional/op_reference/convolution.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/convolution.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/convolution.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,10 +14,17 @@ using namespace ov;
 namespace {
 struct ConvolutionParams {
     template <class IT>
-    ConvolutionParams(const PartialShape& inputShape, const PartialShape& filterShape, const PartialShape& outputShape,
+    ConvolutionParams(const PartialShape& inputShape,
+                      const PartialShape& filterShape,
+                      const PartialShape& outputShape,
                       const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues, const std::vector<IT>& oValues,
-                      const Strides& strides, const CoordinateDiff& padBegin, const CoordinateDiff& padEnd, const Strides& dialations)
+                      const std::vector<IT>& iValues,
+                      const std::vector<IT>& filterValues,
+                      const std::vector<IT>& oValues,
+                      const Strides& strides,
+                      const CoordinateDiff& padBegin,
+                      const CoordinateDiff& padEnd,
+                      const Strides& dialations)
         : inputShape(inputShape),
           filterShape(filterShape),
           outputShape(outputShape),
@@ -32,10 +40,17 @@ struct ConvolutionParams {
           dialations(dialations) {}
 
     template <class IT>
-    ConvolutionParams(const PartialShape& inputShape, const PartialShape& filterShape, const PartialShape& outputShape,
+    ConvolutionParams(const PartialShape& inputShape,
+                      const PartialShape& filterShape,
+                      const PartialShape& outputShape,
                       const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues, const std::vector<IT>& oValues,
-                      const Strides& strides, const CoordinateDiff& padBegin, const CoordinateDiff& padEnd, const Strides& dialations,
+                      const std::vector<IT>& iValues,
+                      const std::vector<IT>& filterValues,
+                      const std::vector<IT>& oValues,
+                      const Strides& strides,
+                      const CoordinateDiff& padBegin,
+                      const CoordinateDiff& padEnd,
+                      const Strides& dialations,
                       const bool convolutionOutlining)
         : inputShape(inputShape),
           filterShape(filterShape),
@@ -109,15 +124,15 @@ class ReferenceConvolutionLayerTest : public testing::TestWithParam<ConvolutionP
 
         if (params.convolutionOutlining == true) {
             const auto Convolution2 = std::make_shared<op::v1::Convolution>(Convolution,
-                                                                           filter,
-                                                                           params.strides,
-                                                                           params.padBegin,
-                                                                           params.padEnd,
-                                                                           params.dialations,
-                                                                           auto_pad);
-            return std::make_shared<ov::Model>(NodeVector {Convolution2}, ParameterVector {in, filter});
+                                                                            filter,
+                                                                            params.strides,
+                                                                            params.padBegin,
+                                                                            params.padEnd,
+                                                                            params.dialations,
+                                                                            auto_pad);
+            return std::make_shared<ov::Model>(NodeVector{Convolution2}, ParameterVector{in, filter});
         } else {
-            return std::make_shared<ov::Model>(NodeVector {Convolution}, ParameterVector {in, filter});
+            return std::make_shared<ov::Model>(NodeVector{Convolution}, ParameterVector{in, filter});
         }
     }
 };
@@ -130,9 +145,9 @@ template <element::Type_t IN_ET>
 std::vector<ConvolutionParams> generateConvolutionI8Params() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ConvolutionParams> convolutionParams {
-// --------------------- 1D convolution ------------------------------------------
-// clang-format off
+    std::vector<ConvolutionParams> convolutionParams{
+        // --------------------- 1D convolution ------------------------------------------
+        // clang-format off
         ConvolutionParams(PartialShape {1, 1, 6},
                           PartialShape {1, 1, 3},
                           PartialShape {1, 1, 4},
@@ -1069,12 +1084,11 @@ std::vector<ConvolutionParams> generateConvolutionFloatParams() {
 // clang-format on
 
 std::vector<ConvolutionParams> generateConvolutionCombinedParams() {
-    const std::vector<std::vector<ConvolutionParams>> convolutionTypeParams {
+    const std::vector<std::vector<ConvolutionParams>> convolutionTypeParams{
         generateConvolutionFloatParams<element::Type_t::f32>(),
         generateConvolutionFloatParams<element::Type_t::f16>(),
         generateConvolutionFloatParams<element::Type_t::bf16>(),
-        generateConvolutionI8Params<element::Type_t::i8>()
-        };
+        generateConvolutionI8Params<element::Type_t::i8>()};
     std::vector<ConvolutionParams> combinedParams;
 
     for (const auto& params : convolutionTypeParams) {
@@ -1083,7 +1097,9 @@ std::vector<ConvolutionParams> generateConvolutionCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Convolution_With_Hardcoded_Refs, ReferenceConvolutionLayerTest,
-    testing::ValuesIn(generateConvolutionCombinedParams()), ReferenceConvolutionLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Convolution_With_Hardcoded_Refs,
+                         ReferenceConvolutionLayerTest,
+                         testing::ValuesIn(generateConvolutionCombinedParams()),
+                         ReferenceConvolutionLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/convolution_backprop.cpp b/src/plugins/template/tests/functional/op_reference/convolution_backprop.cpp
index 9a58949a903781..adddcb5824c0ce 100644
--- a/src/plugins/template/tests/functional/op_reference/convolution_backprop.cpp
+++ b/src/plugins/template/tests/functional/op_reference/convolution_backprop.cpp
@@ -4,8 +4,8 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/op/convolution.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/convolution.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -13,10 +13,17 @@ using namespace ov;
 namespace {
 struct ConvolutionBackpropParams {
     template <class IT>
-    ConvolutionBackpropParams(const PartialShape& inputShape, const PartialShape& filterShape, const PartialShape& outputShape,
-                      const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues, const std::vector<IT>& oValues,
-                      const Strides& strides, const CoordinateDiff& padBegin, const CoordinateDiff& padEnd, const Strides& dialations)
+    ConvolutionBackpropParams(const PartialShape& inputShape,
+                              const PartialShape& filterShape,
+                              const PartialShape& outputShape,
+                              const element::Type& iType,
+                              const std::vector<IT>& iValues,
+                              const std::vector<IT>& filterValues,
+                              const std::vector<IT>& oValues,
+                              const Strides& strides,
+                              const CoordinateDiff& padBegin,
+                              const CoordinateDiff& padEnd,
+                              const Strides& dialations)
         : inputShape(inputShape),
           filterShape(filterShape),
           outputShape(outputShape),
@@ -32,11 +39,18 @@ struct ConvolutionBackpropParams {
           dialations(dialations) {}
 
     template <class IT>
-    ConvolutionBackpropParams(const PartialShape& inputShape, const PartialShape& filterShape, const PartialShape& outputShape,
-                      const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues, const std::vector<IT>& oValues,
-                      const Strides& strides, const CoordinateDiff& padBegin, const CoordinateDiff& padEnd, const Strides& dialations,
-                      const CoordinateDiff& outPadding)
+    ConvolutionBackpropParams(const PartialShape& inputShape,
+                              const PartialShape& filterShape,
+                              const PartialShape& outputShape,
+                              const element::Type& iType,
+                              const std::vector<IT>& iValues,
+                              const std::vector<IT>& filterValues,
+                              const std::vector<IT>& oValues,
+                              const Strides& strides,
+                              const CoordinateDiff& padBegin,
+                              const CoordinateDiff& padEnd,
+                              const Strides& dialations,
+                              const CoordinateDiff& outPadding)
         : inputShape(inputShape),
           filterShape(filterShape),
           outputShape(outputShape),
@@ -68,7 +82,8 @@ struct ConvolutionBackpropParams {
     ov::CoordinateDiff outPadding;
 };
 
-class ReferenceConvolutionBackpropLayerTest : public testing::TestWithParam<ConvolutionBackpropParams>, public CommonReferenceTest {
+class ReferenceConvolutionBackpropLayerTest : public testing::TestWithParam<ConvolutionBackpropParams>,
+                                              public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -99,15 +114,15 @@ class ReferenceConvolutionBackpropLayerTest : public testing::TestWithParam<Conv
         const auto in = std::make_shared<op::v0::Parameter>(params.inType, params.inputShape);
         const auto filter = std::make_shared<op::v0::Parameter>(params.inType, params.filterShape);
         const auto ConvolutionBackprop = std::make_shared<op::v1::ConvolutionBackpropData>(in,
-                                                                       filter,
-                                                                       params.strides,
-                                                                       params.padBegin,
-                                                                       params.padEnd,
-                                                                       params.dialations,
-                                                                       auto_pad,
-                                                                       params.outPadding);
+                                                                                           filter,
+                                                                                           params.strides,
+                                                                                           params.padBegin,
+                                                                                           params.padEnd,
+                                                                                           params.dialations,
+                                                                                           auto_pad,
+                                                                                           params.outPadding);
 
-        return std::make_shared<ov::Model>(NodeVector {ConvolutionBackprop}, ParameterVector {in, filter});
+        return std::make_shared<ov::Model>(NodeVector{ConvolutionBackprop}, ParameterVector{in, filter});
     }
 };
 
@@ -119,953 +134,2015 @@ template <element::Type_t IN_ET>
 std::vector<ConvolutionBackpropParams> generateConvolutionBackpropFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ConvolutionBackpropParams> convolutionBackpropParams {
-// --------------------- 1D ConvolutionBackprop ------------------------------------------
-        ConvolutionBackpropParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 6},
-                          IN_ET,
-                          std::vector<T>{5, 6, 7, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{10, 12, 19, 10, 7, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 4},
-                          IN_ET,
-                          std::vector<T>{5, 6, 7, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{12, 19, 10, 7},
-                          {1},
-                          {1},
-                          {1},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 5},
-                          IN_ET,
-                          std::vector<T>{5, 7},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{10, 0, 19, 0, 7},
-                          {2},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 5},
-                          IN_ET,
-                          std::vector<T>{5, 6, 7, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{12, 19, 10, 7, 2},
-                          {1},
-                          {1},
-                          {1},
-                          {1},
-                          {1}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 7},
-                          IN_ET,
-                          std::vector<T>{8, 5, 1},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{16, 10, 2, 0, 8, 5, 1},
-                          {1},
-                          {0},
-                          {0},
-                          {2},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 7},
-                          IN_ET,
-                          std::vector<T>{3, 9, 1, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{18, 0, 5, 0, 13, 0, 1},
-                          {2},
-                          {2},
-                          {2},
-                          {2},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2},
-                          PartialShape {1, 2, 3},
-                          PartialShape {1, 2, 4},
-                          IN_ET,
-                          std::vector<T>{10, 3},
-                          std::vector<T>{
-                                    // channel 1
-                                    2, 0, 1,
-                                    // channel 2
-                                    1, 0, 2},
-                          std::vector<T>{
-                                    // channel 1
-                                    20, 6, 10, 3,
-                                    // channel 2
-                                    10, 3, 20, 6},
-                          {1},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 2, 2},
-                          PartialShape {2, 1, 3},
-                          PartialShape {1, 1, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    4, 7,
-                                    // channel 2
-                                    5, 5},
-                          std::vector<T>{
-                                    // filter 1
-                                    2, 0, 1,
-                                    // filter 2
-                                    1, 0, 2},
-                          std::vector<T>{13, 19, 14, 17},
-                          {1},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {2, 1, 2},
-                          PartialShape {1, 1, 3},
-                          PartialShape {2, 1, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // batch 1
-                                    1, 3,
-                                    // batch 2
-                                    2, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{
-                                    // batch 1
-                                    2, 6, 1, 3,
-                                    // batch 2
-                                    4, 4, 2, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-// --------------------- 2D ConvolutionBackprop ------------------------------------------
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3,
-                                    7, 5},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    1, 5, 9, 9,
-                                    7, 20, 34, 15,
-                                    3, 18, 12, 3,
-                                    21, 29, 17, 5},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3,
-                                    7, 5},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    23, 35, 18,
-                                    23, 19, 8,
-                                    29, 17, 5},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7,
-                                    7, 5, 3, 1,
-                                    2, 4, 6, 8,
-                                    8, 6, 4, 2},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    20, 37, 27, 18,
-                                    22, 40, 60, 52,
-                                    41, 69, 49, 31,
-                                    18, 26, 34, 22},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 5, 5},
-                          IN_ET,
-                          std::vector<T>{
-                                    2, 5,
-                                    4, 3},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    2, 4, 11, 10, 15,
-                                    2, 2, 7, 5, 5,
-                                    10, 12, 32, 16, 14,
-                                    4, 4, 7, 3, 3,
-                                    12, 8, 13, 6, 3},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 6, 6},
-                          IN_ET,
-                          std::vector<T>{
-                                    2, 3,
-                                    4, 3},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    2, 3, 4, 6, 6, 9,
-                                    4, 3, 8, 6, 12, 9,
-                                    2, 3, 2, 3, 2, 3,
-                                    4, 3, 4, 3, 4, 3,
-                                    6, 9, 4, 6, 2, 3,
-                                    12, 9, 8, 6, 4, 3},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {2, 2},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 5, 5},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5,
-                                    7, 5, 3,
-                                    2, 4, 6},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    23, 0, 43, 0, 29,
-                                    0, 0, 0, 0, 0,
-                                    31, 0, 57, 0, 45,
-                                    0, 0, 0, 0, 0,
-                                    35, 0, 38, 0, 21},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 2, 3, 3},
-                          PartialShape {1, 2, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3,
-                                    7, 5},
-                          std::vector<T>{
-                                    // channel 1
-                                    5, 3, 5,
-                                    1, 3, 1,
-                                    4, 2, 4,
-                                    // channel 2
-                                    -5, 3, 5,
-                                    1, -3, 1,
-                                    4, 2, -4},
-                          std::vector<T>{
-                                    // channel 1
-                                    5, 18, 14, 15,
-                                    36, 52, 60, 28,
-                                    11, 40, 32, 17,
-                                    28, 34, 38, 20,
-                                    // channel 2
-                                    -5, -12, 14, 15,
-                                    -34, -4, 42, 28,
-                                    11, -2, -6, -7,
-                                    28, 34, -18, -20},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 2, 2, 2},
-                          PartialShape {2, 1, 3, 3},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 3,
-                                    7, 5,
-                                    // channel 2
-                                    2, 4,
-                                    8, 6},
-                          std::vector<T>{
-                                    // channel 1
-                                    5, 3, 5,
-                                    1, 3, 1,
-                                    4, 2, 4,
-                                    // channel 2
-                                   -5, 3, 5,
-                                    1, -3, 1,
-                                    4, 2, -4},
-                          std::vector<T>{
-                                    -5, 4, 36, 35,
-                                     -2, 44, 108, 62,
-                                     27, 42, 22, 7,
-                                     60, 74, 18, -4},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 2, 1, 1},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    2,
-                                    // channel 2
-                                    3},
-                          std::vector<T>{
-                                    // batch 0
-                                    // channel 1
-                                    5, 3,
-                                    1, 3,
-                                    // channel 2
-                                   -5, 3,
-                                    1, -3,
-                                    // batch 1
-                                    // channel 1
-                                    5, 3,
-                                    1, 3,
-                                    // channel 2
-                                   -5, 3,
-                                    1, -3},
-                          std::vector<T>{
-                                    25, 15, 5, 15, -25, 15, 5, -15},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {2, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {2, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // batch 1
-                                    1, 3,
-                                    1, 3,
-                                    // batch 2
-                                    -1, 3,
-                                    1, 3},
-                          std::vector<T>{
-                                    -5, 3, 5,
-                                    1, -3, 1,
-                                    4, 2, -4},
-                          std::vector<T>{
-                                    // batch 1
-                                    -5, -12, 14, 15,
-                                    -4, -12, 6, 18,
-                                    5, 14, -6, -9,
-                                    4, 14, 2, -12,
-                                    // batch 2
-                                    5, -18, 4, 15,
-                                    -6, -6, 4, 18,
-                                    -3, 10, 2, -9,
-                                    4, 14, 2, -12},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          {0, 0}),
-// --------------------- 3D convolution ------------------------------------------
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2, 2},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {1, 1, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    15, 3,
-                                    21, 10,
-                                    // depth: 2
-                                    10, 13,
-                                    11, 17},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                    15, 33, 51, 9,
-                                    21, 67, 86, 30,
-                                    30, 42, 43, 6,
-                                    42, 41, 52, 20,
-                                    // depth: 2
-                                    25, 66, 107, 48,
-                                    32, 116, 166, 81,
-                                    50, 89, 93, 32,
-                                    64, 86, 91, 54,
-                                    // depth: 3
-                                    25, 66, 107, 48,
-                                    32, 116, 166, 81,
-                                    50, 89, 93, 32,
-                                    64, 86, 91, 54,
-                                    // depth: 4
-                                    10, 33, 56, 39,
-                                    11, 49, 80, 51,
-                                    20, 47, 50, 26,
-                                    22, 45, 39, 34},
-                          {1, 1, 1},
-                          {0, 0, 0},
-                          {0, 0, 0},
-                          {1, 1, 1},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2, 2},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {1, 1, 3, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    15, 3,
-                                    21, 10,
-                                    // depth: 2
-                                    10, 13,
-                                    11, 17},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                    116, 166, 81,
-                                    89, 93, 32,
-                                    86, 91, 54,
-                                    // depth: 2
-                                    116, 166, 81,
-                                    89, 93, 32,
-                                    86, 91, 54,
-                                    // depth: 3
-                                    49, 80, 51,
-                                    47, 50, 26,
-                                    45, 39, 34},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {1, 1, 1}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4, 4, 4},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {1, 1, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 2
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 3
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 4
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                     12, 30, 36, 24,
-                                     26, 42, 42, 30,
-                                     34, 56, 54, 50,
-                                     14, 18, 24, 16,
-                                     // depth: 2
-                                     18, 45, 54, 36,
-                                     39, 63, 63, 45,
-                                     51, 84, 81, 75,
-                                     21, 27, 36, 24,
-                                     // depth: 3
-                                     18, 45, 54, 36,
-                                     39, 63, 63, 45,
-                                     51, 84, 81, 75,
-                                     21, 27, 36, 24,
-                                     // depth: 4
-                                     12, 30, 36, 24,
-                                     26, 42, 42, 30,
-                                     34, 56, 54, 50,
-                                     14, 18, 24, 16},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2, 2},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {1, 1, 5, 5, 5},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    15, 3,
-                                    21, 10,
-                                    // depth: 2
-                                    10, 13,
-                                    11, 17},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                    15, 30, 48, 6, 9,
-                                    0, 15, 0, 3, 0,
-                                    51, 57, 109, 23, 36,
-                                    0, 21, 0, 10, 0,
-                                    42, 21, 62, 10, 20,
-                                    // depth: 2
-                                    15, 30, 48, 6, 9,
-                                    0, 15, 0, 3, 0,
-                                    51, 57, 109, 23, 36,
-                                    0, 21, 0, 10, 0,
-                                    42, 21, 62, 10, 20,
-                                    // depth: 3
-                                    25, 50, 91, 32, 48,
-                                    0, 25, 0, 16, 0,
-                                    82, 89, 205, 70, 113,
-                                    0, 32, 0, 27, 0,
-                                    64, 32, 118, 27, 54,
-                                    // depth: 4
-                                    10, 20, 43, 26, 39,
-                                    0, 10, 0, 13, 0,
-                                    31, 32, 96, 47, 77,
-                                    0, 11, 0, 17, 0,
-                                    22, 11, 56, 17, 34,
-                                    // depth: 5
-                                    10, 20, 43, 26, 39,
-                                    0, 10, 0, 13, 0,
-                                    31, 32, 96, 47, 77,
-                                    0, 11, 0, 17, 0,
-                                    22, 11, 56, 17, 34},
-                          {2, 2, 2},
-                          {0, 0, 0},
-                          {0, 0, 0},
-                          {1, 1, 1},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4, 4, 4},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {1, 1, 7, 7, 7},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 2
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 3
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 4
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                    12, 0, 30, 0, 36, 0, 24,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    26, 0, 42, 0, 42, 0, 30,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    34, 0, 56, 0, 54, 0, 50,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    14, 0, 18, 0, 24, 0, 16,
-                                    // depth: 2
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    // depth: 3
-                                    18, 0, 45, 0, 54, 0, 36,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    39, 0, 63, 0, 63, 0, 45,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    51, 0, 84, 0, 81, 0, 75,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    21, 0, 27, 0, 36, 0, 24,
-                                    // depth: 4
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    // depth: 5
-                                    18, 0, 45, 0, 54, 0, 36,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    39, 0, 63, 0, 63, 0, 45,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    51, 0, 84, 0, 81, 0, 75,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    21, 0, 27, 0, 36, 0, 24,
-                                    // depth: 6
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    // depth: 7
-                                    12, 0, 30, 0, 36, 0, 24,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    26, 0, 42, 0, 42, 0, 30,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    34, 0, 56, 0, 54, 0, 50,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    14, 0, 18, 0, 24, 0, 16},
-                          {2, 2, 2},
-                          {2, 2, 2},
-                          {2, 2, 2},
-                          {2, 2, 2},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2, 2},
-                          PartialShape {1, 2, 3, 3, 3},
-                          PartialShape {1, 2, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 8,
-                                    1, 3,
-                                    // depth: 2
-                                    1, 7,
-                                    3, 8},
-                          std::vector<T>{
-                                    // -- channel 1 --
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // -- channel 2 --
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // -- channel 1 --
-                                    // depth: 1
-                                    1, 10, 19, 24,
-                                    1, 6, 17, 9,
-                                    2, 18, 13, 16,
-                                    2, 7, 5, 6,
-                                    // depth: 2
-                                    2, 19, 36, 45,
-                                    4, 21, 49, 33,
-                                    4, 36, 30, 30,
-                                    8, 26, 19, 22,
-                                    // depth: 3
-                                    2, 19, 36, 45,
-                                    4, 21, 49, 33,
-                                    4, 36, 30, 30,
-                                    8, 26, 19, 22,
-                                    // depth: 4
-                                    1, 9, 17, 21,
-                                    3, 15, 32, 24,
-                                    2, 18, 17, 14,
-                                    6, 19, 14, 16,
-                                    // -- channel 2 --
-                                    // depth: 1
-                                    1, 10, 19, 24,
-                                    1, 6, 17, 9,
-                                    2, 18, 13, 16,
-                                    2, 7, 5, 6,
-                                    // depth: 2
-                                    2, 19, 36, 45,
-                                    4, 21, 49, 33,
-                                    4, 36, 30, 30,
-                                    8, 26, 19, 22,
-                                    // depth: 3
-                                    2, 19, 36, 45,
-                                    4, 21, 49, 33,
-                                    4, 36, 30, 30,
-                                    8, 26, 19, 22,
-                                    // depth: 4
-                                    1, 9, 17, 21,
-                                    3, 15, 32, 24,
-                                    2, 18, 17, 14,
-                                    6, 19, 14, 16},
-                          {1, 1, 1},
-                          {0, 0, 0},
-                          {0, 0, 0},
-                          {1, 1, 1},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 2, 2, 2, 2},
-                          PartialShape {2, 1, 3, 3, 3},
-                          PartialShape {1, 1, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // -- in 1 --
-                                    // depth: 1
-                                    1, 3,
-                                    2, 5,
-                                    // depth: 2
-                                    1, 0,
-                                    3, 6,
-                                    // -- in 2 --
-                                    // depth: 1
-                                    1, 3,
-                                    2, 5,
-                                    // depth: 2
-                                    3, 0,
-                                    1, 8},
-                          std::vector<T>{
-                                    // -- filter 1 --
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // -- filter 2 --
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                     2, 10, 18, 18,
-                                     4, 20, 38, 30,
-                                     4, 18, 20, 12,
-                                     8, 24, 18, 20,
-                                     // depth: 2
-                                     6, 18, 30, 18,
-                                     8, 46, 78, 72,
-                                     12, 26, 42, 12,
-                                     16, 56, 40, 48,
-                                     // depth: 3
-                                     6, 18, 30, 18,
-                                     8, 46, 78, 72,
-                                     12, 26, 42, 12,
-                                     16, 56, 40, 48,
-                                     // depth: 4
-                                     4, 8, 12, 0,
-                                     4, 26, 40, 42,
-                                     8, 8, 22, 0,
-                                     8, 32, 22, 28},
-                          {1, 1, 1},
-                          {0, 0, 0},
-                          {0, 0, 0},
-                          {1, 1, 1},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {2, 1, 2, 2, 2},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {2, 1, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // -- batch 1 --
-                                    // depth: 1
-                                    1, 3,
-                                    2, 5,
-                                    // depth: 2
-                                    1, 0,
-                                    6, 4,
-                                    // -- batch 2 --
-                                    // depth: 1
-                                    1, 5,
-                                    2, 8,
-                                    // depth: 2
-                                    2, 1,
-                                    0, 5},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // -- batch 1 --
-                                     // depth: 1
-                                     1, 5, 9, 9,
-                                     2, 10, 19, 15,
-                                     2, 9, 10, 6,
-                                     4, 12, 9, 10,
-                                     // depth: 2
-                                     2, 7, 12, 9,
-                                     8, 27, 45, 27,
-                                     4, 16, 16, 6,
-                                     16, 26, 25, 18,
-                                     // depth: 3
-                                     2, 7, 12, 9,
-                                     8, 27, 45, 27,
-                                     4, 16, 16, 6,
-                                     16, 26, 25, 18,
-                                     // depth: 4
-                                     1, 2, 3, 0,
-                                     6, 17, 26, 12,
-                                     2, 7, 6, 0,
-                                     12, 14, 16, 8,
-                                     // -- batch 2 --
-                                     // depth: 1
-                                     1, 7, 13, 15,
-                                     2, 13, 27, 24,
-                                     2, 13, 15, 10,
-                                     4, 18, 12, 16,
-                                     // depth: 2
-                                     3, 12, 21, 18,
-                                     2, 20, 38, 39,
-                                     6, 17, 25, 12,
-                                     4, 28, 17, 26,
-                                     // depth: 3
-                                     3, 12, 21, 18,
-                                     2, 20, 38, 39,
-                                     6, 17, 25, 12,
-                                     4, 28, 17, 26,
-                                     // depth: 4
-                                     2, 5, 8, 3,
-                                     0, 7, 11, 15,
-                                     4, 4, 10, 2,
-                                     0, 10, 5, 10},
-                          {1, 1, 1},
-                          {0, 0, 0},
-                          {0, 0, 0},
-                          {1, 1, 1},
-                          {0, 0, 0})
-    };
+    std::vector<ConvolutionBackpropParams> convolutionBackpropParams{
+        // --------------------- 1D ConvolutionBackprop ------------------------------------------
+        ConvolutionBackpropParams(PartialShape{1, 1, 4},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 6},
+                                  IN_ET,
+                                  std::vector<T>{5, 6, 7, 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{10, 12, 19, 10, 7, 2},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 4},
+                                  IN_ET,
+                                  std::vector<T>{5, 6, 7, 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{12, 19, 10, 7},
+                                  {1},
+                                  {1},
+                                  {1},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 5},
+                                  IN_ET,
+                                  std::vector<T>{5, 7},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{10, 0, 19, 0, 7},
+                                  {2},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 5},
+                                  IN_ET,
+                                  std::vector<T>{5, 6, 7, 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{12, 19, 10, 7, 2},
+                                  {1},
+                                  {1},
+                                  {1},
+                                  {1},
+                                  {1}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 7},
+                                  IN_ET,
+                                  std::vector<T>{8, 5, 1},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{16, 10, 2, 0, 8, 5, 1},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {2},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 7},
+                                  IN_ET,
+                                  std::vector<T>{3, 9, 1, 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{18, 0, 5, 0, 13, 0, 1},
+                                  {2},
+                                  {2},
+                                  {2},
+                                  {2},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2},
+                                  PartialShape{1, 2, 3},
+                                  PartialShape{1, 2, 4},
+                                  IN_ET,
+                                  std::vector<T>{10, 3},
+                                  std::vector<T>{// channel 1
+                                                 2,
+                                                 0,
+                                                 1,
+                                                 // channel 2
+                                                 1,
+                                                 0,
+                                                 2},
+                                  std::vector<T>{// channel 1
+                                                 20,
+                                                 6,
+                                                 10,
+                                                 3,
+                                                 // channel 2
+                                                 10,
+                                                 3,
+                                                 20,
+                                                 6},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 2, 2},
+                                  PartialShape{2, 1, 3},
+                                  PartialShape{1, 1, 4},
+                                  IN_ET,
+                                  std::vector<T>{// channel 1
+                                                 4,
+                                                 7,
+                                                 // channel 2
+                                                 5,
+                                                 5},
+                                  std::vector<T>{// filter 1
+                                                 2,
+                                                 0,
+                                                 1,
+                                                 // filter 2
+                                                 1,
+                                                 0,
+                                                 2},
+                                  std::vector<T>{13, 19, 14, 17},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{2, 1, 2},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{2, 1, 4},
+                                  IN_ET,
+                                  std::vector<T>{// batch 1
+                                                 1,
+                                                 3,
+                                                 // batch 2
+                                                 2,
+                                                 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{// batch 1
+                                                 2,
+                                                 6,
+                                                 1,
+                                                 3,
+                                                 // batch 2
+                                                 4,
+                                                 4,
+                                                 2,
+                                                 2},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        // --------------------- 2D ConvolutionBackprop ------------------------------------------
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{1, 1, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{1, 3, 7, 5},
+                                  std::vector<T>{1, 2, 3, 0, 1, 0, 3, 2, 1},
+                                  std::vector<T>{1, 5, 9, 9, 7, 20, 34, 15, 3, 18, 12, 3, 21, 29, 17, 5},
+                                  {1, 1},
+                                  {0, 0},
+                                  {0, 0},
+                                  {1, 1},
+                                  {0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{1, 1, 3, 3},
+                                  IN_ET,
+                                  std::vector<T>{1, 3, 7, 5},
+                                  std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+                                  std::vector<T>{23, 35, 18, 23, 19, 8, 29, 17, 5},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4, 4},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{1, 1, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{1, 3, 5, 7, 7, 5, 3, 1, 2, 4, 6, 8, 8, 6, 4, 2},
+                                  std::vector<T>{1, 2, 3, 0, 1, 0, 2, 1, 2},
+                                  std::vector<T>{20, 37, 27, 18, 22, 40, 60, 52, 41, 69, 49, 31, 18, 26, 34, 22},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1},
+                                  {0, 0}),
+        ConvolutionBackpropParams(
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 5, 5},
+            IN_ET,
+            std::vector<T>{2, 5, 4, 3},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{2, 4, 11, 10, 15, 2, 2, 7, 5, 5, 10, 12, 32, 16, 14, 4, 4, 7, 3, 3, 12, 8, 13, 6, 3},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            {0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{1, 1, 6, 6},
+                                  IN_ET,
+                                  std::vector<T>{2, 3, 4, 3},
+                                  std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+                                  std::vector<T>{2, 3, 4, 6, 6, 9, 4, 3, 8, 6, 12, 9, 2,  3, 2, 3, 2, 3,
+                                                 4, 3, 4, 3, 4, 3, 6, 9, 4, 6, 2,  3, 12, 9, 8, 6, 4, 3},
+                                  {1, 1},
+                                  {0, 0},
+                                  {0, 0},
+                                  {2, 2},
+                                  {0, 0}),
+        ConvolutionBackpropParams(
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 5, 5},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 5, 3, 2, 4, 6},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{23, 0, 43, 0, 29, 0, 0, 0, 0, 0, 31, 0, 57, 0, 45, 0, 0, 0, 0, 0, 35, 0, 38, 0, 21},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2},
+                                  PartialShape{1, 2, 3, 3},
+                                  PartialShape{1, 2, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{1, 3, 7, 5},
+                                  std::vector<T>{// channel 1
+                                                 5,
+                                                 3,
+                                                 5,
+                                                 1,
+                                                 3,
+                                                 1,
+                                                 4,
+                                                 2,
+                                                 4,
+                                                 // channel 2
+                                                 -5,
+                                                 3,
+                                                 5,
+                                                 1,
+                                                 -3,
+                                                 1,
+                                                 4,
+                                                 2,
+                                                 -4},
+                                  std::vector<T>{// channel 1
+                                                 5,
+                                                 18,
+                                                 14,
+                                                 15,
+                                                 36,
+                                                 52,
+                                                 60,
+                                                 28,
+                                                 11,
+                                                 40,
+                                                 32,
+                                                 17,
+                                                 28,
+                                                 34,
+                                                 38,
+                                                 20,
+                                                 // channel 2
+                                                 -5,
+                                                 -12,
+                                                 14,
+                                                 15,
+                                                 -34,
+                                                 -4,
+                                                 42,
+                                                 28,
+                                                 11,
+                                                 -2,
+                                                 -6,
+                                                 -7,
+                                                 28,
+                                                 34,
+                                                 -18,
+                                                 -20},
+                                  {1, 1},
+                                  {0, 0},
+                                  {0, 0},
+                                  {1, 1},
+                                  {0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 2, 2, 2},
+                                  PartialShape{2, 1, 3, 3},
+                                  PartialShape{1, 1, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// channel 1
+                                                 1,
+                                                 3,
+                                                 7,
+                                                 5,
+                                                 // channel 2
+                                                 2,
+                                                 4,
+                                                 8,
+                                                 6},
+                                  std::vector<T>{// channel 1
+                                                 5,
+                                                 3,
+                                                 5,
+                                                 1,
+                                                 3,
+                                                 1,
+                                                 4,
+                                                 2,
+                                                 4,
+                                                 // channel 2
+                                                 -5,
+                                                 3,
+                                                 5,
+                                                 1,
+                                                 -3,
+                                                 1,
+                                                 4,
+                                                 2,
+                                                 -4},
+                                  std::vector<T>{-5, 4, 36, 35, -2, 44, 108, 62, 27, 42, 22, 7, 60, 74, 18, -4},
+                                  {1, 1},
+                                  {0, 0},
+                                  {0, 0},
+                                  {1, 1},
+                                  {0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 2, 1, 1},
+                                  PartialShape{2, 2, 2, 2},
+                                  PartialShape{1, 2, 2, 2},
+                                  IN_ET,
+                                  std::vector<T>{// channel 1
+                                                 2,
+                                                 // channel 2
+                                                 3},
+                                  std::vector<T>{// batch 0
+                                                 // channel 1
+                                                 5,
+                                                 3,
+                                                 1,
+                                                 3,
+                                                 // channel 2
+                                                 -5,
+                                                 3,
+                                                 1,
+                                                 -3,
+                                                 // batch 1
+                                                 // channel 1
+                                                 5,
+                                                 3,
+                                                 1,
+                                                 3,
+                                                 // channel 2
+                                                 -5,
+                                                 3,
+                                                 1,
+                                                 -3},
+                                  std::vector<T>{25, 15, 5, 15, -25, 15, 5, -15},
+                                  {1, 1},
+                                  {0, 0},
+                                  {0, 0},
+                                  {1, 1},
+                                  {0, 0}),
+        ConvolutionBackpropParams(PartialShape{2, 1, 2, 2},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{2, 1, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// batch 1
+                                                 1,
+                                                 3,
+                                                 1,
+                                                 3,
+                                                 // batch 2
+                                                 -1,
+                                                 3,
+                                                 1,
+                                                 3},
+                                  std::vector<T>{-5, 3, 5, 1, -3, 1, 4, 2, -4},
+                                  std::vector<T>{// batch 1
+                                                 -5,
+                                                 -12,
+                                                 14,
+                                                 15,
+                                                 -4,
+                                                 -12,
+                                                 6,
+                                                 18,
+                                                 5,
+                                                 14,
+                                                 -6,
+                                                 -9,
+                                                 4,
+                                                 14,
+                                                 2,
+                                                 -12,
+                                                 // batch 2
+                                                 5,
+                                                 -18,
+                                                 4,
+                                                 15,
+                                                 -6,
+                                                 -6,
+                                                 4,
+                                                 18,
+                                                 -3,
+                                                 10,
+                                                 2,
+                                                 -9,
+                                                 4,
+                                                 14,
+                                                 2,
+                                                 -12},
+                                  {1, 1},
+                                  {0, 0},
+                                  {0, 0},
+                                  {1, 1},
+                                  {0, 0}),
+        // --------------------- 3D convolution ------------------------------------------
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2, 2},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 15,
+                                                 3,
+                                                 21,
+                                                 10,
+                                                 // depth: 2
+                                                 10,
+                                                 13,
+                                                 11,
+                                                 17},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 15,
+                                                 33,
+                                                 51,
+                                                 9,
+                                                 21,
+                                                 67,
+                                                 86,
+                                                 30,
+                                                 30,
+                                                 42,
+                                                 43,
+                                                 6,
+                                                 42,
+                                                 41,
+                                                 52,
+                                                 20,
+                                                 // depth: 2
+                                                 25,
+                                                 66,
+                                                 107,
+                                                 48,
+                                                 32,
+                                                 116,
+                                                 166,
+                                                 81,
+                                                 50,
+                                                 89,
+                                                 93,
+                                                 32,
+                                                 64,
+                                                 86,
+                                                 91,
+                                                 54,
+                                                 // depth: 3
+                                                 25,
+                                                 66,
+                                                 107,
+                                                 48,
+                                                 32,
+                                                 116,
+                                                 166,
+                                                 81,
+                                                 50,
+                                                 89,
+                                                 93,
+                                                 32,
+                                                 64,
+                                                 86,
+                                                 91,
+                                                 54,
+                                                 // depth: 4
+                                                 10,
+                                                 33,
+                                                 56,
+                                                 39,
+                                                 11,
+                                                 49,
+                                                 80,
+                                                 51,
+                                                 20,
+                                                 47,
+                                                 50,
+                                                 26,
+                                                 22,
+                                                 45,
+                                                 39,
+                                                 34},
+                                  {1, 1, 1},
+                                  {0, 0, 0},
+                                  {0, 0, 0},
+                                  {1, 1, 1},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2, 2},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 15,
+                                                 3,
+                                                 21,
+                                                 10,
+                                                 // depth: 2
+                                                 10,
+                                                 13,
+                                                 11,
+                                                 17},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 116,
+                                                 166,
+                                                 81,
+                                                 89,
+                                                 93,
+                                                 32,
+                                                 86,
+                                                 91,
+                                                 54,
+                                                 // depth: 2
+                                                 116,
+                                                 166,
+                                                 81,
+                                                 89,
+                                                 93,
+                                                 32,
+                                                 86,
+                                                 91,
+                                                 54,
+                                                 // depth: 3
+                                                 49,
+                                                 80,
+                                                 51,
+                                                 47,
+                                                 50,
+                                                 26,
+                                                 45,
+                                                 39,
+                                                 34},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {1, 1, 1}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4, 4, 4},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 2
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 3
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 4
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 12,
+                                                 30,
+                                                 36,
+                                                 24,
+                                                 26,
+                                                 42,
+                                                 42,
+                                                 30,
+                                                 34,
+                                                 56,
+                                                 54,
+                                                 50,
+                                                 14,
+                                                 18,
+                                                 24,
+                                                 16,
+                                                 // depth: 2
+                                                 18,
+                                                 45,
+                                                 54,
+                                                 36,
+                                                 39,
+                                                 63,
+                                                 63,
+                                                 45,
+                                                 51,
+                                                 84,
+                                                 81,
+                                                 75,
+                                                 21,
+                                                 27,
+                                                 36,
+                                                 24,
+                                                 // depth: 3
+                                                 18,
+                                                 45,
+                                                 54,
+                                                 36,
+                                                 39,
+                                                 63,
+                                                 63,
+                                                 45,
+                                                 51,
+                                                 84,
+                                                 81,
+                                                 75,
+                                                 21,
+                                                 27,
+                                                 36,
+                                                 24,
+                                                 // depth: 4
+                                                 12,
+                                                 30,
+                                                 36,
+                                                 24,
+                                                 26,
+                                                 42,
+                                                 42,
+                                                 30,
+                                                 34,
+                                                 56,
+                                                 54,
+                                                 50,
+                                                 14,
+                                                 18,
+                                                 24,
+                                                 16},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2, 2},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 5, 5, 5},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 15,
+                                                 3,
+                                                 21,
+                                                 10,
+                                                 // depth: 2
+                                                 10,
+                                                 13,
+                                                 11,
+                                                 17},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 15,
+                                                 30,
+                                                 48,
+                                                 6,
+                                                 9,
+                                                 0,
+                                                 15,
+                                                 0,
+                                                 3,
+                                                 0,
+                                                 51,
+                                                 57,
+                                                 109,
+                                                 23,
+                                                 36,
+                                                 0,
+                                                 21,
+                                                 0,
+                                                 10,
+                                                 0,
+                                                 42,
+                                                 21,
+                                                 62,
+                                                 10,
+                                                 20,
+                                                 // depth: 2
+                                                 15,
+                                                 30,
+                                                 48,
+                                                 6,
+                                                 9,
+                                                 0,
+                                                 15,
+                                                 0,
+                                                 3,
+                                                 0,
+                                                 51,
+                                                 57,
+                                                 109,
+                                                 23,
+                                                 36,
+                                                 0,
+                                                 21,
+                                                 0,
+                                                 10,
+                                                 0,
+                                                 42,
+                                                 21,
+                                                 62,
+                                                 10,
+                                                 20,
+                                                 // depth: 3
+                                                 25,
+                                                 50,
+                                                 91,
+                                                 32,
+                                                 48,
+                                                 0,
+                                                 25,
+                                                 0,
+                                                 16,
+                                                 0,
+                                                 82,
+                                                 89,
+                                                 205,
+                                                 70,
+                                                 113,
+                                                 0,
+                                                 32,
+                                                 0,
+                                                 27,
+                                                 0,
+                                                 64,
+                                                 32,
+                                                 118,
+                                                 27,
+                                                 54,
+                                                 // depth: 4
+                                                 10,
+                                                 20,
+                                                 43,
+                                                 26,
+                                                 39,
+                                                 0,
+                                                 10,
+                                                 0,
+                                                 13,
+                                                 0,
+                                                 31,
+                                                 32,
+                                                 96,
+                                                 47,
+                                                 77,
+                                                 0,
+                                                 11,
+                                                 0,
+                                                 17,
+                                                 0,
+                                                 22,
+                                                 11,
+                                                 56,
+                                                 17,
+                                                 34,
+                                                 // depth: 5
+                                                 10,
+                                                 20,
+                                                 43,
+                                                 26,
+                                                 39,
+                                                 0,
+                                                 10,
+                                                 0,
+                                                 13,
+                                                 0,
+                                                 31,
+                                                 32,
+                                                 96,
+                                                 47,
+                                                 77,
+                                                 0,
+                                                 11,
+                                                 0,
+                                                 17,
+                                                 0,
+                                                 22,
+                                                 11,
+                                                 56,
+                                                 17,
+                                                 34},
+                                  {2, 2, 2},
+                                  {0, 0, 0},
+                                  {0, 0, 0},
+                                  {1, 1, 1},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4, 4, 4},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 7, 7, 7},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 2
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 3
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 4
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 12,
+                                                 0,
+                                                 30,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 24,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 26,
+                                                 0,
+                                                 42,
+                                                 0,
+                                                 42,
+                                                 0,
+                                                 30,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 34,
+                                                 0,
+                                                 56,
+                                                 0,
+                                                 54,
+                                                 0,
+                                                 50,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 14,
+                                                 0,
+                                                 18,
+                                                 0,
+                                                 24,
+                                                 0,
+                                                 16,
+                                                 // depth: 2
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 // depth: 3
+                                                 18,
+                                                 0,
+                                                 45,
+                                                 0,
+                                                 54,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 39,
+                                                 0,
+                                                 63,
+                                                 0,
+                                                 63,
+                                                 0,
+                                                 45,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 51,
+                                                 0,
+                                                 84,
+                                                 0,
+                                                 81,
+                                                 0,
+                                                 75,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 21,
+                                                 0,
+                                                 27,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 24,
+                                                 // depth: 4
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 // depth: 5
+                                                 18,
+                                                 0,
+                                                 45,
+                                                 0,
+                                                 54,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 39,
+                                                 0,
+                                                 63,
+                                                 0,
+                                                 63,
+                                                 0,
+                                                 45,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 51,
+                                                 0,
+                                                 84,
+                                                 0,
+                                                 81,
+                                                 0,
+                                                 75,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 21,
+                                                 0,
+                                                 27,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 24,
+                                                 // depth: 6
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 // depth: 7
+                                                 12,
+                                                 0,
+                                                 30,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 24,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 26,
+                                                 0,
+                                                 42,
+                                                 0,
+                                                 42,
+                                                 0,
+                                                 30,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 34,
+                                                 0,
+                                                 56,
+                                                 0,
+                                                 54,
+                                                 0,
+                                                 50,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 14,
+                                                 0,
+                                                 18,
+                                                 0,
+                                                 24,
+                                                 0,
+                                                 16},
+                                  {2, 2, 2},
+                                  {2, 2, 2},
+                                  {2, 2, 2},
+                                  {2, 2, 2},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2, 2},
+                                  PartialShape{1, 2, 3, 3, 3},
+                                  PartialShape{1, 2, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 8,
+                                                 1,
+                                                 3,
+                                                 // depth: 2
+                                                 1,
+                                                 7,
+                                                 3,
+                                                 8},
+                                  std::vector<T>{// -- channel 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // -- channel 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// -- channel 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 10,
+                                                 19,
+                                                 24,
+                                                 1,
+                                                 6,
+                                                 17,
+                                                 9,
+                                                 2,
+                                                 18,
+                                                 13,
+                                                 16,
+                                                 2,
+                                                 7,
+                                                 5,
+                                                 6,
+                                                 // depth: 2
+                                                 2,
+                                                 19,
+                                                 36,
+                                                 45,
+                                                 4,
+                                                 21,
+                                                 49,
+                                                 33,
+                                                 4,
+                                                 36,
+                                                 30,
+                                                 30,
+                                                 8,
+                                                 26,
+                                                 19,
+                                                 22,
+                                                 // depth: 3
+                                                 2,
+                                                 19,
+                                                 36,
+                                                 45,
+                                                 4,
+                                                 21,
+                                                 49,
+                                                 33,
+                                                 4,
+                                                 36,
+                                                 30,
+                                                 30,
+                                                 8,
+                                                 26,
+                                                 19,
+                                                 22,
+                                                 // depth: 4
+                                                 1,
+                                                 9,
+                                                 17,
+                                                 21,
+                                                 3,
+                                                 15,
+                                                 32,
+                                                 24,
+                                                 2,
+                                                 18,
+                                                 17,
+                                                 14,
+                                                 6,
+                                                 19,
+                                                 14,
+                                                 16,
+                                                 // -- channel 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 10,
+                                                 19,
+                                                 24,
+                                                 1,
+                                                 6,
+                                                 17,
+                                                 9,
+                                                 2,
+                                                 18,
+                                                 13,
+                                                 16,
+                                                 2,
+                                                 7,
+                                                 5,
+                                                 6,
+                                                 // depth: 2
+                                                 2,
+                                                 19,
+                                                 36,
+                                                 45,
+                                                 4,
+                                                 21,
+                                                 49,
+                                                 33,
+                                                 4,
+                                                 36,
+                                                 30,
+                                                 30,
+                                                 8,
+                                                 26,
+                                                 19,
+                                                 22,
+                                                 // depth: 3
+                                                 2,
+                                                 19,
+                                                 36,
+                                                 45,
+                                                 4,
+                                                 21,
+                                                 49,
+                                                 33,
+                                                 4,
+                                                 36,
+                                                 30,
+                                                 30,
+                                                 8,
+                                                 26,
+                                                 19,
+                                                 22,
+                                                 // depth: 4
+                                                 1,
+                                                 9,
+                                                 17,
+                                                 21,
+                                                 3,
+                                                 15,
+                                                 32,
+                                                 24,
+                                                 2,
+                                                 18,
+                                                 17,
+                                                 14,
+                                                 6,
+                                                 19,
+                                                 14,
+                                                 16},
+                                  {1, 1, 1},
+                                  {0, 0, 0},
+                                  {0, 0, 0},
+                                  {1, 1, 1},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 2, 2, 2, 2},
+                                  PartialShape{2, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// -- in 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 5,
+                                                 // depth: 2
+                                                 1,
+                                                 0,
+                                                 3,
+                                                 6,
+                                                 // -- in 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 5,
+                                                 // depth: 2
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 8},
+                                  std::vector<T>{// -- filter 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // -- filter 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 2,
+                                                 10,
+                                                 18,
+                                                 18,
+                                                 4,
+                                                 20,
+                                                 38,
+                                                 30,
+                                                 4,
+                                                 18,
+                                                 20,
+                                                 12,
+                                                 8,
+                                                 24,
+                                                 18,
+                                                 20,
+                                                 // depth: 2
+                                                 6,
+                                                 18,
+                                                 30,
+                                                 18,
+                                                 8,
+                                                 46,
+                                                 78,
+                                                 72,
+                                                 12,
+                                                 26,
+                                                 42,
+                                                 12,
+                                                 16,
+                                                 56,
+                                                 40,
+                                                 48,
+                                                 // depth: 3
+                                                 6,
+                                                 18,
+                                                 30,
+                                                 18,
+                                                 8,
+                                                 46,
+                                                 78,
+                                                 72,
+                                                 12,
+                                                 26,
+                                                 42,
+                                                 12,
+                                                 16,
+                                                 56,
+                                                 40,
+                                                 48,
+                                                 // depth: 4
+                                                 4,
+                                                 8,
+                                                 12,
+                                                 0,
+                                                 4,
+                                                 26,
+                                                 40,
+                                                 42,
+                                                 8,
+                                                 8,
+                                                 22,
+                                                 0,
+                                                 8,
+                                                 32,
+                                                 22,
+                                                 28},
+                                  {1, 1, 1},
+                                  {0, 0, 0},
+                                  {0, 0, 0},
+                                  {1, 1, 1},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{2, 1, 2, 2, 2},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{2, 1, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// -- batch 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 5,
+                                                 // depth: 2
+                                                 1,
+                                                 0,
+                                                 6,
+                                                 4,
+                                                 // -- batch 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 5,
+                                                 2,
+                                                 8,
+                                                 // depth: 2
+                                                 2,
+                                                 1,
+                                                 0,
+                                                 5},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// -- batch 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 5,
+                                                 9,
+                                                 9,
+                                                 2,
+                                                 10,
+                                                 19,
+                                                 15,
+                                                 2,
+                                                 9,
+                                                 10,
+                                                 6,
+                                                 4,
+                                                 12,
+                                                 9,
+                                                 10,
+                                                 // depth: 2
+                                                 2,
+                                                 7,
+                                                 12,
+                                                 9,
+                                                 8,
+                                                 27,
+                                                 45,
+                                                 27,
+                                                 4,
+                                                 16,
+                                                 16,
+                                                 6,
+                                                 16,
+                                                 26,
+                                                 25,
+                                                 18,
+                                                 // depth: 3
+                                                 2,
+                                                 7,
+                                                 12,
+                                                 9,
+                                                 8,
+                                                 27,
+                                                 45,
+                                                 27,
+                                                 4,
+                                                 16,
+                                                 16,
+                                                 6,
+                                                 16,
+                                                 26,
+                                                 25,
+                                                 18,
+                                                 // depth: 4
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 6,
+                                                 17,
+                                                 26,
+                                                 12,
+                                                 2,
+                                                 7,
+                                                 6,
+                                                 0,
+                                                 12,
+                                                 14,
+                                                 16,
+                                                 8,
+                                                 // -- batch 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 7,
+                                                 13,
+                                                 15,
+                                                 2,
+                                                 13,
+                                                 27,
+                                                 24,
+                                                 2,
+                                                 13,
+                                                 15,
+                                                 10,
+                                                 4,
+                                                 18,
+                                                 12,
+                                                 16,
+                                                 // depth: 2
+                                                 3,
+                                                 12,
+                                                 21,
+                                                 18,
+                                                 2,
+                                                 20,
+                                                 38,
+                                                 39,
+                                                 6,
+                                                 17,
+                                                 25,
+                                                 12,
+                                                 4,
+                                                 28,
+                                                 17,
+                                                 26,
+                                                 // depth: 3
+                                                 3,
+                                                 12,
+                                                 21,
+                                                 18,
+                                                 2,
+                                                 20,
+                                                 38,
+                                                 39,
+                                                 6,
+                                                 17,
+                                                 25,
+                                                 12,
+                                                 4,
+                                                 28,
+                                                 17,
+                                                 26,
+                                                 // depth: 4
+                                                 2,
+                                                 5,
+                                                 8,
+                                                 3,
+                                                 0,
+                                                 7,
+                                                 11,
+                                                 15,
+                                                 4,
+                                                 4,
+                                                 10,
+                                                 2,
+                                                 0,
+                                                 10,
+                                                 5,
+                                                 10},
+                                  {1, 1, 1},
+                                  {0, 0, 0},
+                                  {0, 0, 0},
+                                  {1, 1, 1},
+                                  {0, 0, 0})};
     return convolutionBackpropParams;
 }
 
@@ -1073,682 +2150,1451 @@ template <element::Type_t IN_ET>
 std::vector<ConvolutionBackpropParams> generateConvolutionBackpropUintParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ConvolutionBackpropParams> convolutionBackpropParams {
-// --------------------- 1D ConvolutionBackprop ------------------------------------------
-        ConvolutionBackpropParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 6},
-                          IN_ET,
-                          std::vector<T>{5, 6, 7, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{10, 12, 19, 10, 7, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 4},
-                          IN_ET,
-                          std::vector<T>{5, 6, 7, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{12, 19, 10, 7},
-                          {1},
-                          {1},
-                          {1},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 5},
-                          IN_ET,
-                          std::vector<T>{5, 7},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{10, 0, 19, 0, 7},
-                          {2},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 5},
-                          IN_ET,
-                          std::vector<T>{5, 6, 7, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{12, 19, 10, 7, 2},
-                          {1},
-                          {1},
-                          {1},
-                          {1},
-                          {1}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 7},
-                          IN_ET,
-                          std::vector<T>{8, 5, 1},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{16, 10, 2, 0, 8, 5, 1},
-                          {1},
-                          {0},
-                          {0},
-                          {2},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 3},
-                          PartialShape {1, 1, 7},
-                          IN_ET,
-                          std::vector<T>{3, 9, 1, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{18, 0, 5, 0, 13, 0, 1},
-                          {2},
-                          {2},
-                          {2},
-                          {2},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2},
-                          PartialShape {1, 2, 3},
-                          PartialShape {1, 2, 4},
-                          IN_ET,
-                          std::vector<T>{10, 3},
-                          std::vector<T>{
-                                    // channel 1
-                                    2, 0, 1,
-                                    // channel 2
-                                    1, 0, 2},
-                          std::vector<T>{
-                                    // channel 1
-                                    20, 6, 10, 3,
-                                    // channel 2
-                                    10, 3, 20, 6},
-                          {1},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {1, 2, 2},
-                          PartialShape {2, 1, 3},
-                          PartialShape {1, 1, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    4, 7,
-                                    // channel 2
-                                    5, 5},
-                          std::vector<T>{
-                                    // filter 1
-                                    2, 0, 1,
-                                    // filter 2
-                                    1, 0, 2},
-                          std::vector<T>{13, 19, 14, 17},
-                          {1},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-        ConvolutionBackpropParams(PartialShape {2, 1, 2},
-                          PartialShape {1, 1, 3},
-                          PartialShape {2, 1, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // batch 1
-                                    1, 3,
-                                    // batch 2
-                                    2, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{
-                                    // batch 1
-                                    2, 6, 1, 3,
-                                    // batch 2
-                                    4, 4, 2, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1},
-                          {0}),
-// --------------------- 2D ConvolutionBackprop ------------------------------------------
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3,
-                                    7, 5},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    1, 5, 9, 9,
-                                    7, 20, 34, 15,
-                                    3, 18, 12, 3,
-                                    21, 29, 17, 5},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3,
-                                    7, 5},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    23, 35, 18,
-                                    23, 19, 8,
-                                    29, 17, 5},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7,
-                                    7, 5, 3, 1,
-                                    2, 4, 6, 8,
-                                    8, 6, 4, 2},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    20, 37, 27, 18,
-                                    22, 40, 60, 52,
-                                    41, 69, 49, 31,
-                                    18, 26, 34, 22},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 5, 5},
-                          IN_ET,
-                          std::vector<T>{
-                                    2, 5,
-                                    4, 3},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    2, 4, 11, 10, 15,
-                                    2, 2, 7, 5, 5,
-                                    10, 12, 32, 16, 14,
-                                    4, 4, 7, 3, 3,
-                                    12, 8, 13, 6, 3},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 6, 6},
-                          IN_ET,
-                          std::vector<T>{
-                                    2, 3,
-                                    4, 3},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    2, 3, 4, 6, 6, 9,
-                                    4, 3, 8, 6, 12, 9,
-                                    2, 3, 2, 3, 2, 3,
-                                    4, 3, 4, 3, 4, 3,
-                                    6, 9, 4, 6, 2, 3,
-                                    12, 9, 8, 6, 4, 3},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {2, 2},
-                          {0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 5, 5},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5,
-                                    7, 5, 3,
-                                    2, 4, 6},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    23, 0, 43, 0, 29,
-                                    0, 0, 0, 0, 0,
-                                    31, 0, 57, 0, 45,
-                                    0, 0, 0, 0, 0,
-                                    35, 0, 38, 0, 21},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {0, 0}),
-// --------------------- 3D convolution ------------------------------------------
-        ConvolutionBackpropParams(PartialShape {1, 1, 4, 4, 4},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {1, 1, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 2
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 3
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 4
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                     12, 30, 36, 24,
-                                     26, 42, 42, 30,
-                                     34, 56, 54, 50,
-                                     14, 18, 24, 16,
-                                     // depth: 2
-                                     18, 45, 54, 36,
-                                     39, 63, 63, 45,
-                                     51, 84, 81, 75,
-                                     21, 27, 36, 24,
-                                     // depth: 3
-                                     18, 45, 54, 36,
-                                     39, 63, 63, 45,
-                                     51, 84, 81, 75,
-                                     21, 27, 36, 24,
-                                     // depth: 4
-                                     12, 30, 36, 24,
-                                     26, 42, 42, 30,
-                                     34, 56, 54, 50,
-                                     14, 18, 24, 16},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {1, 1, 1},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 4, 4, 4},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {1, 1, 7, 7, 7},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 2
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 3
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // depth: 4
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                    12, 0, 30, 0, 36, 0, 24,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    26, 0, 42, 0, 42, 0, 30,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    34, 0, 56, 0, 54, 0, 50,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    14, 0, 18, 0, 24, 0, 16,
-                                    // depth: 2
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    // depth: 3
-                                    18, 0, 45, 0, 54, 0, 36,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    39, 0, 63, 0, 63, 0, 45,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    51, 0, 84, 0, 81, 0, 75,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    21, 0, 27, 0, 36, 0, 24,
-                                    // depth: 4
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    // depth: 5
-                                    18, 0, 45, 0, 54, 0, 36,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    39, 0, 63, 0, 63, 0, 45,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    51, 0, 84, 0, 81, 0, 75,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    21, 0, 27, 0, 36, 0, 24,
-                                    // depth: 6
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    // depth: 7
-                                    12, 0, 30, 0, 36, 0, 24,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    26, 0, 42, 0, 42, 0, 30,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    34, 0, 56, 0, 54, 0, 50,
-                                    0, 0, 0, 0, 0, 0, 0,
-                                    14, 0, 18, 0, 24, 0, 16},
-                          {2, 2, 2},
-                          {2, 2, 2},
-                          {2, 2, 2},
-                          {2, 2, 2},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 1, 2, 2, 2},
-                          PartialShape {1, 2, 3, 3, 3},
-                          PartialShape {1, 2, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 8,
-                                    1, 3,
-                                    // depth: 2
-                                    1, 7,
-                                    3, 8},
-                          std::vector<T>{
-                                    // -- channel 1 --
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // -- channel 2 --
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // -- channel 1 --
-                                    // depth: 1
-                                    1, 10, 19, 24,
-                                    1, 6, 17, 9,
-                                    2, 18, 13, 16,
-                                    2, 7, 5, 6,
-                                    // depth: 2
-                                    2, 19, 36, 45,
-                                    4, 21, 49, 33,
-                                    4, 36, 30, 30,
-                                    8, 26, 19, 22,
-                                    // depth: 3
-                                    2, 19, 36, 45,
-                                    4, 21, 49, 33,
-                                    4, 36, 30, 30,
-                                    8, 26, 19, 22,
-                                    // depth: 4
-                                    1, 9, 17, 21,
-                                    3, 15, 32, 24,
-                                    2, 18, 17, 14,
-                                    6, 19, 14, 16,
-                                    // -- channel 2 --
-                                    // depth: 1
-                                    1, 10, 19, 24,
-                                    1, 6, 17, 9,
-                                    2, 18, 13, 16,
-                                    2, 7, 5, 6,
-                                    // depth: 2
-                                    2, 19, 36, 45,
-                                    4, 21, 49, 33,
-                                    4, 36, 30, 30,
-                                    8, 26, 19, 22,
-                                    // depth: 3
-                                    2, 19, 36, 45,
-                                    4, 21, 49, 33,
-                                    4, 36, 30, 30,
-                                    8, 26, 19, 22,
-                                    // depth: 4
-                                    1, 9, 17, 21,
-                                    3, 15, 32, 24,
-                                    2, 18, 17, 14,
-                                    6, 19, 14, 16},
-                          {1, 1, 1},
-                          {0, 0, 0},
-                          {0, 0, 0},
-                          {1, 1, 1},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {1, 2, 2, 2, 2},
-                          PartialShape {2, 1, 3, 3, 3},
-                          PartialShape {1, 1, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // -- in 1 --
-                                    // depth: 1
-                                    1, 3,
-                                    2, 5,
-                                    // depth: 2
-                                    1, 0,
-                                    3, 6,
-                                    // -- in 2 --
-                                    // depth: 1
-                                    1, 3,
-                                    2, 5,
-                                    // depth: 2
-                                    3, 0,
-                                    1, 8},
-                          std::vector<T>{
-                                    // -- filter 1 --
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // -- filter 2 --
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // depth: 1
-                                     2, 10, 18, 18,
-                                     4, 20, 38, 30,
-                                     4, 18, 20, 12,
-                                     8, 24, 18, 20,
-                                     // depth: 2
-                                     6, 18, 30, 18,
-                                     8, 46, 78, 72,
-                                     12, 26, 42, 12,
-                                     16, 56, 40, 48,
-                                     // depth: 3
-                                     6, 18, 30, 18,
-                                     8, 46, 78, 72,
-                                     12, 26, 42, 12,
-                                     16, 56, 40, 48,
-                                     // depth: 4
-                                     4, 8, 12, 0,
-                                     4, 26, 40, 42,
-                                     8, 8, 22, 0,
-                                     8, 32, 22, 28},
-                          {1, 1, 1},
-                          {0, 0, 0},
-                          {0, 0, 0},
-                          {1, 1, 1},
-                          {0, 0, 0}),
-        ConvolutionBackpropParams(PartialShape {2, 1, 2, 2, 2},
-                          PartialShape {1, 1, 3, 3, 3},
-                          PartialShape {2, 1, 4, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // -- batch 1 --
-                                    // depth: 1
-                                    1, 3,
-                                    2, 5,
-                                    // depth: 2
-                                    1, 0,
-                                    6, 4,
-                                    // -- batch 2 --
-                                    // depth: 1
-                                    1, 5,
-                                    2, 8,
-                                    // depth: 2
-                                    2, 1,
-                                    0, 5},
-                          std::vector<T>{
-                                    // depth: 1
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 2
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2,
-                                    // depth: 3
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    2, 1, 2},
-                          std::vector<T>{
-                                    // -- batch 1 --
-                                     // depth: 1
-                                     1, 5, 9, 9,
-                                     2, 10, 19, 15,
-                                     2, 9, 10, 6,
-                                     4, 12, 9, 10,
-                                     // depth: 2
-                                     2, 7, 12, 9,
-                                     8, 27, 45, 27,
-                                     4, 16, 16, 6,
-                                     16, 26, 25, 18,
-                                     // depth: 3
-                                     2, 7, 12, 9,
-                                     8, 27, 45, 27,
-                                     4, 16, 16, 6,
-                                     16, 26, 25, 18,
-                                     // depth: 4
-                                     1, 2, 3, 0,
-                                     6, 17, 26, 12,
-                                     2, 7, 6, 0,
-                                     12, 14, 16, 8,
-                                     // -- batch 2 --
-                                     // depth: 1
-                                     1, 7, 13, 15,
-                                     2, 13, 27, 24,
-                                     2, 13, 15, 10,
-                                     4, 18, 12, 16,
-                                     // depth: 2
-                                     3, 12, 21, 18,
-                                     2, 20, 38, 39,
-                                     6, 17, 25, 12,
-                                     4, 28, 17, 26,
-                                     // depth: 3
-                                     3, 12, 21, 18,
-                                     2, 20, 38, 39,
-                                     6, 17, 25, 12,
-                                     4, 28, 17, 26,
-                                     // depth: 4
-                                     2, 5, 8, 3,
-                                     0, 7, 11, 15,
-                                     4, 4, 10, 2,
-                                     0, 10, 5, 10},
-                          {1, 1, 1},
-                          {0, 0, 0},
-                          {0, 0, 0},
-                          {1, 1, 1},
-                          {0, 0, 0})
-    };
+    std::vector<ConvolutionBackpropParams> convolutionBackpropParams{
+        // --------------------- 1D ConvolutionBackprop ------------------------------------------
+        ConvolutionBackpropParams(PartialShape{1, 1, 4},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 6},
+                                  IN_ET,
+                                  std::vector<T>{5, 6, 7, 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{10, 12, 19, 10, 7, 2},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 4},
+                                  IN_ET,
+                                  std::vector<T>{5, 6, 7, 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{12, 19, 10, 7},
+                                  {1},
+                                  {1},
+                                  {1},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 5},
+                                  IN_ET,
+                                  std::vector<T>{5, 7},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{10, 0, 19, 0, 7},
+                                  {2},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 5},
+                                  IN_ET,
+                                  std::vector<T>{5, 6, 7, 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{12, 19, 10, 7, 2},
+                                  {1},
+                                  {1},
+                                  {1},
+                                  {1},
+                                  {1}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 7},
+                                  IN_ET,
+                                  std::vector<T>{8, 5, 1},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{16, 10, 2, 0, 8, 5, 1},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {2},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{1, 1, 7},
+                                  IN_ET,
+                                  std::vector<T>{3, 9, 1, 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{18, 0, 5, 0, 13, 0, 1},
+                                  {2},
+                                  {2},
+                                  {2},
+                                  {2},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2},
+                                  PartialShape{1, 2, 3},
+                                  PartialShape{1, 2, 4},
+                                  IN_ET,
+                                  std::vector<T>{10, 3},
+                                  std::vector<T>{// channel 1
+                                                 2,
+                                                 0,
+                                                 1,
+                                                 // channel 2
+                                                 1,
+                                                 0,
+                                                 2},
+                                  std::vector<T>{// channel 1
+                                                 20,
+                                                 6,
+                                                 10,
+                                                 3,
+                                                 // channel 2
+                                                 10,
+                                                 3,
+                                                 20,
+                                                 6},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{1, 2, 2},
+                                  PartialShape{2, 1, 3},
+                                  PartialShape{1, 1, 4},
+                                  IN_ET,
+                                  std::vector<T>{// channel 1
+                                                 4,
+                                                 7,
+                                                 // channel 2
+                                                 5,
+                                                 5},
+                                  std::vector<T>{// filter 1
+                                                 2,
+                                                 0,
+                                                 1,
+                                                 // filter 2
+                                                 1,
+                                                 0,
+                                                 2},
+                                  std::vector<T>{13, 19, 14, 17},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        ConvolutionBackpropParams(PartialShape{2, 1, 2},
+                                  PartialShape{1, 1, 3},
+                                  PartialShape{2, 1, 4},
+                                  IN_ET,
+                                  std::vector<T>{// batch 1
+                                                 1,
+                                                 3,
+                                                 // batch 2
+                                                 2,
+                                                 2},
+                                  std::vector<T>{2, 0, 1},
+                                  std::vector<T>{// batch 1
+                                                 2,
+                                                 6,
+                                                 1,
+                                                 3,
+                                                 // batch 2
+                                                 4,
+                                                 4,
+                                                 2,
+                                                 2},
+                                  {1},
+                                  {0},
+                                  {0},
+                                  {1},
+                                  {0}),
+        // --------------------- 2D ConvolutionBackprop ------------------------------------------
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{1, 1, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{1, 3, 7, 5},
+                                  std::vector<T>{1, 2, 3, 0, 1, 0, 3, 2, 1},
+                                  std::vector<T>{1, 5, 9, 9, 7, 20, 34, 15, 3, 18, 12, 3, 21, 29, 17, 5},
+                                  {1, 1},
+                                  {0, 0},
+                                  {0, 0},
+                                  {1, 1},
+                                  {0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{1, 1, 3, 3},
+                                  IN_ET,
+                                  std::vector<T>{1, 3, 7, 5},
+                                  std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+                                  std::vector<T>{23, 35, 18, 23, 19, 8, 29, 17, 5},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4, 4},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{1, 1, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{1, 3, 5, 7, 7, 5, 3, 1, 2, 4, 6, 8, 8, 6, 4, 2},
+                                  std::vector<T>{1, 2, 3, 0, 1, 0, 2, 1, 2},
+                                  std::vector<T>{20, 37, 27, 18, 22, 40, 60, 52, 41, 69, 49, 31, 18, 26, 34, 22},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1},
+                                  {1, 1},
+                                  {0, 0}),
+        ConvolutionBackpropParams(
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 5, 5},
+            IN_ET,
+            std::vector<T>{2, 5, 4, 3},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{2, 4, 11, 10, 15, 2, 2, 7, 5, 5, 10, 12, 32, 16, 14, 4, 4, 7, 3, 3, 12, 8, 13, 6, 3},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            {0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2},
+                                  PartialShape{1, 1, 3, 3},
+                                  PartialShape{1, 1, 6, 6},
+                                  IN_ET,
+                                  std::vector<T>{2, 3, 4, 3},
+                                  std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+                                  std::vector<T>{2, 3, 4, 6, 6, 9, 4, 3, 8, 6, 12, 9, 2,  3, 2, 3, 2, 3,
+                                                 4, 3, 4, 3, 4, 3, 6, 9, 4, 6, 2,  3, 12, 9, 8, 6, 4, 3},
+                                  {1, 1},
+                                  {0, 0},
+                                  {0, 0},
+                                  {2, 2},
+                                  {0, 0}),
+        ConvolutionBackpropParams(
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 5, 5},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 5, 3, 2, 4, 6},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{23, 0, 43, 0, 29, 0, 0, 0, 0, 0, 31, 0, 57, 0, 45, 0, 0, 0, 0, 0, 35, 0, 38, 0, 21},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {0, 0}),
+        // --------------------- 3D convolution ------------------------------------------
+        ConvolutionBackpropParams(PartialShape{1, 1, 4, 4, 4},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 2
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 3
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 4
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 12,
+                                                 30,
+                                                 36,
+                                                 24,
+                                                 26,
+                                                 42,
+                                                 42,
+                                                 30,
+                                                 34,
+                                                 56,
+                                                 54,
+                                                 50,
+                                                 14,
+                                                 18,
+                                                 24,
+                                                 16,
+                                                 // depth: 2
+                                                 18,
+                                                 45,
+                                                 54,
+                                                 36,
+                                                 39,
+                                                 63,
+                                                 63,
+                                                 45,
+                                                 51,
+                                                 84,
+                                                 81,
+                                                 75,
+                                                 21,
+                                                 27,
+                                                 36,
+                                                 24,
+                                                 // depth: 3
+                                                 18,
+                                                 45,
+                                                 54,
+                                                 36,
+                                                 39,
+                                                 63,
+                                                 63,
+                                                 45,
+                                                 51,
+                                                 84,
+                                                 81,
+                                                 75,
+                                                 21,
+                                                 27,
+                                                 36,
+                                                 24,
+                                                 // depth: 4
+                                                 12,
+                                                 30,
+                                                 36,
+                                                 24,
+                                                 26,
+                                                 42,
+                                                 42,
+                                                 30,
+                                                 34,
+                                                 56,
+                                                 54,
+                                                 50,
+                                                 14,
+                                                 18,
+                                                 24,
+                                                 16},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {1, 1, 1},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 4, 4, 4},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 7, 7, 7},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 2
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 3
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3,
+                                                 // depth: 4
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 1,
+                                                 2,
+                                                 1,
+                                                 1,
+                                                 3,
+                                                 3,
+                                                 2,
+                                                 3,
+                                                 3},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 12,
+                                                 0,
+                                                 30,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 24,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 26,
+                                                 0,
+                                                 42,
+                                                 0,
+                                                 42,
+                                                 0,
+                                                 30,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 34,
+                                                 0,
+                                                 56,
+                                                 0,
+                                                 54,
+                                                 0,
+                                                 50,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 14,
+                                                 0,
+                                                 18,
+                                                 0,
+                                                 24,
+                                                 0,
+                                                 16,
+                                                 // depth: 2
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 // depth: 3
+                                                 18,
+                                                 0,
+                                                 45,
+                                                 0,
+                                                 54,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 39,
+                                                 0,
+                                                 63,
+                                                 0,
+                                                 63,
+                                                 0,
+                                                 45,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 51,
+                                                 0,
+                                                 84,
+                                                 0,
+                                                 81,
+                                                 0,
+                                                 75,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 21,
+                                                 0,
+                                                 27,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 24,
+                                                 // depth: 4
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 // depth: 5
+                                                 18,
+                                                 0,
+                                                 45,
+                                                 0,
+                                                 54,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 39,
+                                                 0,
+                                                 63,
+                                                 0,
+                                                 63,
+                                                 0,
+                                                 45,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 51,
+                                                 0,
+                                                 84,
+                                                 0,
+                                                 81,
+                                                 0,
+                                                 75,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 21,
+                                                 0,
+                                                 27,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 24,
+                                                 // depth: 6
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 // depth: 7
+                                                 12,
+                                                 0,
+                                                 30,
+                                                 0,
+                                                 36,
+                                                 0,
+                                                 24,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 26,
+                                                 0,
+                                                 42,
+                                                 0,
+                                                 42,
+                                                 0,
+                                                 30,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 34,
+                                                 0,
+                                                 56,
+                                                 0,
+                                                 54,
+                                                 0,
+                                                 50,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 0,
+                                                 14,
+                                                 0,
+                                                 18,
+                                                 0,
+                                                 24,
+                                                 0,
+                                                 16},
+                                  {2, 2, 2},
+                                  {2, 2, 2},
+                                  {2, 2, 2},
+                                  {2, 2, 2},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 1, 2, 2, 2},
+                                  PartialShape{1, 2, 3, 3, 3},
+                                  PartialShape{1, 2, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 8,
+                                                 1,
+                                                 3,
+                                                 // depth: 2
+                                                 1,
+                                                 7,
+                                                 3,
+                                                 8},
+                                  std::vector<T>{// -- channel 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // -- channel 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// -- channel 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 10,
+                                                 19,
+                                                 24,
+                                                 1,
+                                                 6,
+                                                 17,
+                                                 9,
+                                                 2,
+                                                 18,
+                                                 13,
+                                                 16,
+                                                 2,
+                                                 7,
+                                                 5,
+                                                 6,
+                                                 // depth: 2
+                                                 2,
+                                                 19,
+                                                 36,
+                                                 45,
+                                                 4,
+                                                 21,
+                                                 49,
+                                                 33,
+                                                 4,
+                                                 36,
+                                                 30,
+                                                 30,
+                                                 8,
+                                                 26,
+                                                 19,
+                                                 22,
+                                                 // depth: 3
+                                                 2,
+                                                 19,
+                                                 36,
+                                                 45,
+                                                 4,
+                                                 21,
+                                                 49,
+                                                 33,
+                                                 4,
+                                                 36,
+                                                 30,
+                                                 30,
+                                                 8,
+                                                 26,
+                                                 19,
+                                                 22,
+                                                 // depth: 4
+                                                 1,
+                                                 9,
+                                                 17,
+                                                 21,
+                                                 3,
+                                                 15,
+                                                 32,
+                                                 24,
+                                                 2,
+                                                 18,
+                                                 17,
+                                                 14,
+                                                 6,
+                                                 19,
+                                                 14,
+                                                 16,
+                                                 // -- channel 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 10,
+                                                 19,
+                                                 24,
+                                                 1,
+                                                 6,
+                                                 17,
+                                                 9,
+                                                 2,
+                                                 18,
+                                                 13,
+                                                 16,
+                                                 2,
+                                                 7,
+                                                 5,
+                                                 6,
+                                                 // depth: 2
+                                                 2,
+                                                 19,
+                                                 36,
+                                                 45,
+                                                 4,
+                                                 21,
+                                                 49,
+                                                 33,
+                                                 4,
+                                                 36,
+                                                 30,
+                                                 30,
+                                                 8,
+                                                 26,
+                                                 19,
+                                                 22,
+                                                 // depth: 3
+                                                 2,
+                                                 19,
+                                                 36,
+                                                 45,
+                                                 4,
+                                                 21,
+                                                 49,
+                                                 33,
+                                                 4,
+                                                 36,
+                                                 30,
+                                                 30,
+                                                 8,
+                                                 26,
+                                                 19,
+                                                 22,
+                                                 // depth: 4
+                                                 1,
+                                                 9,
+                                                 17,
+                                                 21,
+                                                 3,
+                                                 15,
+                                                 32,
+                                                 24,
+                                                 2,
+                                                 18,
+                                                 17,
+                                                 14,
+                                                 6,
+                                                 19,
+                                                 14,
+                                                 16},
+                                  {1, 1, 1},
+                                  {0, 0, 0},
+                                  {0, 0, 0},
+                                  {1, 1, 1},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{1, 2, 2, 2, 2},
+                                  PartialShape{2, 1, 3, 3, 3},
+                                  PartialShape{1, 1, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// -- in 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 5,
+                                                 // depth: 2
+                                                 1,
+                                                 0,
+                                                 3,
+                                                 6,
+                                                 // -- in 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 5,
+                                                 // depth: 2
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 8},
+                                  std::vector<T>{// -- filter 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // -- filter 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// depth: 1
+                                                 2,
+                                                 10,
+                                                 18,
+                                                 18,
+                                                 4,
+                                                 20,
+                                                 38,
+                                                 30,
+                                                 4,
+                                                 18,
+                                                 20,
+                                                 12,
+                                                 8,
+                                                 24,
+                                                 18,
+                                                 20,
+                                                 // depth: 2
+                                                 6,
+                                                 18,
+                                                 30,
+                                                 18,
+                                                 8,
+                                                 46,
+                                                 78,
+                                                 72,
+                                                 12,
+                                                 26,
+                                                 42,
+                                                 12,
+                                                 16,
+                                                 56,
+                                                 40,
+                                                 48,
+                                                 // depth: 3
+                                                 6,
+                                                 18,
+                                                 30,
+                                                 18,
+                                                 8,
+                                                 46,
+                                                 78,
+                                                 72,
+                                                 12,
+                                                 26,
+                                                 42,
+                                                 12,
+                                                 16,
+                                                 56,
+                                                 40,
+                                                 48,
+                                                 // depth: 4
+                                                 4,
+                                                 8,
+                                                 12,
+                                                 0,
+                                                 4,
+                                                 26,
+                                                 40,
+                                                 42,
+                                                 8,
+                                                 8,
+                                                 22,
+                                                 0,
+                                                 8,
+                                                 32,
+                                                 22,
+                                                 28},
+                                  {1, 1, 1},
+                                  {0, 0, 0},
+                                  {0, 0, 0},
+                                  {1, 1, 1},
+                                  {0, 0, 0}),
+        ConvolutionBackpropParams(PartialShape{2, 1, 2, 2, 2},
+                                  PartialShape{1, 1, 3, 3, 3},
+                                  PartialShape{2, 1, 4, 4, 4},
+                                  IN_ET,
+                                  std::vector<T>{// -- batch 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 3,
+                                                 2,
+                                                 5,
+                                                 // depth: 2
+                                                 1,
+                                                 0,
+                                                 6,
+                                                 4,
+                                                 // -- batch 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 5,
+                                                 2,
+                                                 8,
+                                                 // depth: 2
+                                                 2,
+                                                 1,
+                                                 0,
+                                                 5},
+                                  std::vector<T>{// depth: 1
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 2
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2,
+                                                 // depth: 3
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 1,
+                                                 0,
+                                                 2,
+                                                 1,
+                                                 2},
+                                  std::vector<T>{// -- batch 1 --
+                                                 // depth: 1
+                                                 1,
+                                                 5,
+                                                 9,
+                                                 9,
+                                                 2,
+                                                 10,
+                                                 19,
+                                                 15,
+                                                 2,
+                                                 9,
+                                                 10,
+                                                 6,
+                                                 4,
+                                                 12,
+                                                 9,
+                                                 10,
+                                                 // depth: 2
+                                                 2,
+                                                 7,
+                                                 12,
+                                                 9,
+                                                 8,
+                                                 27,
+                                                 45,
+                                                 27,
+                                                 4,
+                                                 16,
+                                                 16,
+                                                 6,
+                                                 16,
+                                                 26,
+                                                 25,
+                                                 18,
+                                                 // depth: 3
+                                                 2,
+                                                 7,
+                                                 12,
+                                                 9,
+                                                 8,
+                                                 27,
+                                                 45,
+                                                 27,
+                                                 4,
+                                                 16,
+                                                 16,
+                                                 6,
+                                                 16,
+                                                 26,
+                                                 25,
+                                                 18,
+                                                 // depth: 4
+                                                 1,
+                                                 2,
+                                                 3,
+                                                 0,
+                                                 6,
+                                                 17,
+                                                 26,
+                                                 12,
+                                                 2,
+                                                 7,
+                                                 6,
+                                                 0,
+                                                 12,
+                                                 14,
+                                                 16,
+                                                 8,
+                                                 // -- batch 2 --
+                                                 // depth: 1
+                                                 1,
+                                                 7,
+                                                 13,
+                                                 15,
+                                                 2,
+                                                 13,
+                                                 27,
+                                                 24,
+                                                 2,
+                                                 13,
+                                                 15,
+                                                 10,
+                                                 4,
+                                                 18,
+                                                 12,
+                                                 16,
+                                                 // depth: 2
+                                                 3,
+                                                 12,
+                                                 21,
+                                                 18,
+                                                 2,
+                                                 20,
+                                                 38,
+                                                 39,
+                                                 6,
+                                                 17,
+                                                 25,
+                                                 12,
+                                                 4,
+                                                 28,
+                                                 17,
+                                                 26,
+                                                 // depth: 3
+                                                 3,
+                                                 12,
+                                                 21,
+                                                 18,
+                                                 2,
+                                                 20,
+                                                 38,
+                                                 39,
+                                                 6,
+                                                 17,
+                                                 25,
+                                                 12,
+                                                 4,
+                                                 28,
+                                                 17,
+                                                 26,
+                                                 // depth: 4
+                                                 2,
+                                                 5,
+                                                 8,
+                                                 3,
+                                                 0,
+                                                 7,
+                                                 11,
+                                                 15,
+                                                 4,
+                                                 4,
+                                                 10,
+                                                 2,
+                                                 0,
+                                                 10,
+                                                 5,
+                                                 10},
+                                  {1, 1, 1},
+                                  {0, 0, 0},
+                                  {0, 0, 0},
+                                  {1, 1, 1},
+                                  {0, 0, 0})};
     return convolutionBackpropParams;
 }
 
 std::vector<ConvolutionBackpropParams> generateConvolutionBackpropCombinedParams() {
-    const std::vector<std::vector<ConvolutionBackpropParams>> convolutionBackpropTypeParams {
+    const std::vector<std::vector<ConvolutionBackpropParams>> convolutionBackpropTypeParams{
         generateConvolutionBackpropFloatParams<element::Type_t::f64>(),
         generateConvolutionBackpropFloatParams<element::Type_t::f32>(),
         generateConvolutionBackpropFloatParams<element::Type_t::f16>(),
@@ -1761,7 +3607,7 @@ std::vector<ConvolutionBackpropParams> generateConvolutionBackpropCombinedParams
         generateConvolutionBackpropUintParams<element::Type_t::u32>(),
         generateConvolutionBackpropUintParams<element::Type_t::u16>(),
         generateConvolutionBackpropUintParams<element::Type_t::u8>(),
-        };
+    };
     std::vector<ConvolutionBackpropParams> combinedParams;
 
     for (const auto& params : convolutionBackpropTypeParams) {
@@ -1770,7 +3616,9 @@ std::vector<ConvolutionBackpropParams> generateConvolutionBackpropCombinedParams
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ConvolutionBackprop_With_Hardcoded_Refs, ReferenceConvolutionBackpropLayerTest,
-    testing::ValuesIn(generateConvolutionBackpropCombinedParams()), ReferenceConvolutionBackpropLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_ConvolutionBackprop_With_Hardcoded_Refs,
+                         ReferenceConvolutionBackpropLayerTest,
+                         testing::ValuesIn(generateConvolutionBackpropCombinedParams()),
+                         ReferenceConvolutionBackpropLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/cos.cpp b/src/plugins/template/tests/functional/op_reference/cos.cpp
index ed8fab2e027106..b992d0c5f8a1ef 100644
--- a/src/plugins/template/tests/functional/op_reference/cos.cpp
+++ b/src/plugins/template/tests/functional/op_reference/cos.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/cos.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/cos.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -42,7 +43,7 @@ class ReferenceCosLayerTest : public testing::TestWithParam<CosParams>, public C
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto Cos = std::make_shared<op::v0::Cos>(in);
-        return std::make_shared<ov::Model>(NodeVector {Cos}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Cos}, ParameterVector{in});
     }
 };
 
@@ -53,24 +54,33 @@ TEST_P(ReferenceCosLayerTest, CosWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Cos_With_Hardcoded_Refs, ReferenceCosLayerTest,
+    smoke_Cos_With_Hardcoded_Refs,
+    ReferenceCosLayerTest,
     ::testing::Values(
-        Builder {}
-            .input({{11}, element::f16, std::vector<ov::float16> {0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f}})
-            .expected({{11}, element::f16, std::vector<ov::float16> {1.00000000f,
-                                          0.96891242f,
-                                          0.96891242f,
-                                          0.87758256f,
-                                          0.87758256f,
-                                          0.54030231f,
-                                          0.54030231f,
-                                          -0.41614684f,
-                                          -0.41614684f,
-                                          -0.65364362f,
-                                          -0.65364362f}}),
-        Builder {}
-            .input({{11}, element::f32, std::vector<float> {0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f}})
-            .expected({{11}, element::f32, std::vector<float> {1.00000000f,
+        Builder{}
+            .input({{11},
+                    element::f16,
+                    std::vector<ov::float16>{0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{1.00000000f,
+                                                0.96891242f,
+                                                0.96891242f,
+                                                0.87758256f,
+                                                0.87758256f,
+                                                0.54030231f,
+                                                0.54030231f,
+                                                -0.41614684f,
+                                                -0.41614684f,
+                                                -0.65364362f,
+                                                -0.65364362f}}),
+        Builder{}
+            .input({{11},
+                    element::f32,
+                    std::vector<float>{0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{1.00000000f,
                                           0.96891242f,
                                           0.96891242f,
                                           0.87758256f,
@@ -81,18 +91,18 @@ INSTANTIATE_TEST_SUITE_P(
                                           -0.41614684f,
                                           -0.65364362f,
                                           -0.65364362f}}),
-        Builder {}
-            .input({{5}, element::i32, std::vector<int32_t> {1, 2, 3, 4, 5}})
-            .expected({{5}, element::i32, std::vector<int32_t> {1, 0, -1, -1, 0}}),
-        Builder {}
-            .input({{5}, element::i64, std::vector<int64_t> {1, 2, 3, 4, 5}})
-            .expected({{5}, element::i64, std::vector<int64_t> {1, 0, -1, -1, 0}}),
-        Builder {}
-            .input({{3}, element::u32, std::vector<uint32_t> {1, 2, 5}})
-            .expected({{3}, element::u32, std::vector<uint32_t> {1, 0, 0}}),
-        Builder {}
-            .input({{3}, element::u64, std::vector<uint64_t> {1, 2, 5}})
-            .expected({{3}, element::u64, std::vector<uint64_t> {1, 0, 0}})),
+        Builder{}
+            .input({{5}, element::i32, std::vector<int32_t>{1, 2, 3, 4, 5}})
+            .expected({{5}, element::i32, std::vector<int32_t>{1, 0, -1, -1, 0}}),
+        Builder{}
+            .input({{5}, element::i64, std::vector<int64_t>{1, 2, 3, 4, 5}})
+            .expected({{5}, element::i64, std::vector<int64_t>{1, 0, -1, -1, 0}}),
+        Builder{}
+            .input({{3}, element::u32, std::vector<uint32_t>{1, 2, 5}})
+            .expected({{3}, element::u32, std::vector<uint32_t>{1, 0, 0}}),
+        Builder{}
+            .input({{3}, element::u64, std::vector<uint64_t>{1, 2, 5}})
+            .expected({{3}, element::u64, std::vector<uint64_t>{1, 0, 0}})),
 
     ReferenceCosLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/cosh.cpp b/src/plugins/template/tests/functional/op_reference/cosh.cpp
index 55280c7fc23487..111fb2fae700a8 100644
--- a/src/plugins/template/tests/functional/op_reference/cosh.cpp
+++ b/src/plugins/template/tests/functional/op_reference/cosh.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/cosh.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/cosh.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -42,7 +43,7 @@ class ReferenceCoshLayerTest : public testing::TestWithParam<CoshParams>, public
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto Cosh = std::make_shared<op::v0::Cosh>(in);
-        return std::make_shared<ov::Model>(NodeVector {Cosh}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Cosh}, ParameterVector{in});
     }
 };
 
@@ -53,46 +54,55 @@ TEST_P(ReferenceCoshLayerTest, CoshWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Cosh_With_Hardcoded_Refs, ReferenceCoshLayerTest,
+    smoke_Cosh_With_Hardcoded_Refs,
+    ReferenceCoshLayerTest,
     ::testing::Values(
-        Builder {}
-            .input({{11}, element::f16, std::vector<ov::float16> {-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
-            .expected({{11}, element::f16, std::vector<ov::float16> {27.30823284f,
-                            3.76219569f,
-                            1.54308063f,
-                            1.12762597f,
-                            1.03141310f,
-                            1.00000000f,
-                            1.03141310f,
-                            1.12762597f,
-                            1.54308063f,
-                            3.76219569f,
-                            27.30823284f}}),
-        Builder {}
-            .input({{11}, element::f32, std::vector<float> {-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
-            .expected({{11}, element::f32, std::vector<float> {27.30823284f,
-                            3.76219569f,
-                            1.54308063f,
-                            1.12762597f,
-                            1.03141310f,
-                            1.00000000f,
-                            1.03141310f,
-                            1.12762597f,
-                            1.54308063f,
-                            3.76219569f,
-                            27.30823284f}}),
-        Builder {}
-            .input({{7}, element::i32, std::vector<int32_t> {-4, -2, -1, 0, 1, 2, 4}})
-            .expected({{7}, element::i32, std::vector<int32_t> {27, 4, 2, 1, 2, 4, 27}}),
-        Builder {}
-            .input({{7}, element::i64, std::vector<int64_t> {-4, -2, -1, 0, 1, 2, 4}})
-            .expected({{7}, element::i64, std::vector<int64_t> {27, 4, 2, 1, 2, 4, 27}}),
-        Builder {}
-            .input({{4}, element::u32, std::vector<uint32_t> {0, 1, 2, 4}})
-            .expected({{4}, element::u32, std::vector<uint32_t> {1, 2, 4, 27}}),
-        Builder {}
-            .input({{4}, element::u64, std::vector<uint64_t> {0, 1, 2, 4}})
-            .expected({{4}, element::u64, std::vector<uint64_t> {1, 2, 4, 27}})),
+        Builder{}
+            .input({{11},
+                    element::f16,
+                    std::vector<ov::float16>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{27.30823284f,
+                                                3.76219569f,
+                                                1.54308063f,
+                                                1.12762597f,
+                                                1.03141310f,
+                                                1.00000000f,
+                                                1.03141310f,
+                                                1.12762597f,
+                                                1.54308063f,
+                                                3.76219569f,
+                                                27.30823284f}}),
+        Builder{}
+            .input({{11},
+                    element::f32,
+                    std::vector<float>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{27.30823284f,
+                                          3.76219569f,
+                                          1.54308063f,
+                                          1.12762597f,
+                                          1.03141310f,
+                                          1.00000000f,
+                                          1.03141310f,
+                                          1.12762597f,
+                                          1.54308063f,
+                                          3.76219569f,
+                                          27.30823284f}}),
+        Builder{}
+            .input({{7}, element::i32, std::vector<int32_t>{-4, -2, -1, 0, 1, 2, 4}})
+            .expected({{7}, element::i32, std::vector<int32_t>{27, 4, 2, 1, 2, 4, 27}}),
+        Builder{}
+            .input({{7}, element::i64, std::vector<int64_t>{-4, -2, -1, 0, 1, 2, 4}})
+            .expected({{7}, element::i64, std::vector<int64_t>{27, 4, 2, 1, 2, 4, 27}}),
+        Builder{}
+            .input({{4}, element::u32, std::vector<uint32_t>{0, 1, 2, 4}})
+            .expected({{4}, element::u32, std::vector<uint32_t>{1, 2, 4, 27}}),
+        Builder{}
+            .input({{4}, element::u64, std::vector<uint64_t>{0, 1, 2, 4}})
+            .expected({{4}, element::u64, std::vector<uint64_t>{1, 2, 4, 27}})),
 
     ReferenceCoshLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/ctc_greedy_decoder.cpp b/src/plugins/template/tests/functional/op_reference/ctc_greedy_decoder.cpp
index 1384fe67479a03..4c68e737e20c31 100644
--- a/src/plugins/template/tests/functional/op_reference/ctc_greedy_decoder.cpp
+++ b/src/plugins/template/tests/functional/op_reference/ctc_greedy_decoder.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/ctc_greedy_decoder.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/ctc_greedy_decoder.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,11 +13,16 @@ using namespace ov;
 
 namespace {
 struct CTCGreedyDecoderParams {
-    CTCGreedyDecoderParams(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& masksTensor, int64_t ctcMergedRepeat,
-        const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), masksTensor(masksTensor), ctcMergedRepeat(ctcMergedRepeat),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    CTCGreedyDecoderParams(const reference_tests::Tensor& dataTensor,
+                           const reference_tests::Tensor& masksTensor,
+                           int64_t ctcMergedRepeat,
+                           const reference_tests::Tensor& expectedTensor,
+                           const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          masksTensor(masksTensor),
+          ctcMergedRepeat(ctcMergedRepeat),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor masksTensor;
@@ -25,7 +31,8 @@ struct CTCGreedyDecoderParams {
     std::string testcaseName;
 };
 
-class ReferenceCTCGreedyDecoderTest : public testing::TestWithParam<CTCGreedyDecoderParams>, public CommonReferenceTest {
+class ReferenceCTCGreedyDecoderTest : public testing::TestWithParam<CTCGreedyDecoderParams>,
+                                      public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -70,40 +77,68 @@ TEST_P(ReferenceCTCGreedyDecoderTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<CTCGreedyDecoderParams> generateParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<CTCGreedyDecoderParams> params {
+    std::vector<CTCGreedyDecoderParams> params{
         CTCGreedyDecoderParams(
-            reference_tests::Tensor(IN_ET, {3, 1, 3}, std::vector<T>{0.1f, 0.2f, 0.f, 0.4f, 0.3f, 0.f, 0.5f, 0.6f, 0.f}),
+            reference_tests::Tensor(IN_ET,
+                                    {3, 1, 3},
+                                    std::vector<T>{0.1f, 0.2f, 0.f, 0.4f, 0.3f, 0.f, 0.5f, 0.6f, 0.f}),
             reference_tests::Tensor(IN_ET, {3, 1}, std::vector<T>{1.0f, 1.0f, 1.0f}),
             false,
             reference_tests::Tensor(IN_ET, {1, 3, 1, 1}, std::vector<T>{1.0f, 0.0f, 1.0f}),
             "ctc_greedy_decoder"),
         CTCGreedyDecoderParams(
-            reference_tests::Tensor(IN_ET, {3, 2, 3}, std::vector<T>{
-                0.1f, 0.2f, 0.f, 0.15f, 0.25f, 0.f, 0.4f, 0.3f, 0.f, 0.45f, 0.35f, 0.f, 0.5f, 0.6f, 0.f, 0.55f, 0.65f, 0.f}),
+            reference_tests::Tensor(IN_ET,
+                                    {3, 2, 3},
+                                    std::vector<T>{0.1f,
+                                                   0.2f,
+                                                   0.f,
+                                                   0.15f,
+                                                   0.25f,
+                                                   0.f,
+                                                   0.4f,
+                                                   0.3f,
+                                                   0.f,
+                                                   0.45f,
+                                                   0.35f,
+                                                   0.f,
+                                                   0.5f,
+                                                   0.6f,
+                                                   0.f,
+                                                   0.55f,
+                                                   0.65f,
+                                                   0.f}),
             reference_tests::Tensor(IN_ET, {3, 2}, std::vector<T>{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f}),
             false,
             reference_tests::Tensor(IN_ET, {2, 3, 1, 1}, std::vector<T>{1.0f, 0.0f, 1.0f, 1.0f, 0.0f, 1.0f}),
             "ctc_greedy_decoder_multiple_batches"),
         CTCGreedyDecoderParams(
-            reference_tests::Tensor(IN_ET, {3, 1, 3}, std::vector<T>{0.1f, 0.2f, 0.f, 0.4f, 0.3f, 0.f, 0.5f, 0.6f, 0.f}),
+            reference_tests::Tensor(IN_ET,
+                                    {3, 1, 3},
+                                    std::vector<T>{0.1f, 0.2f, 0.f, 0.4f, 0.3f, 0.f, 0.5f, 0.6f, 0.f}),
             reference_tests::Tensor(IN_ET, {3, 1}, std::vector<T>{1.0f, 1.0f, 0.0f}),
             false,
             reference_tests::Tensor(IN_ET, {1, 3, 1, 1}, std::vector<T>{1.0f, 0.0f, -1.0f}),
             "ctc_greedy_decoder_single_batch_short_sequence"),
         CTCGreedyDecoderParams(
-            reference_tests::Tensor(IN_ET, {3, 1, 3}, std::vector<T>{0.1f, 0.2f, 0.f, 0.3f, 0.4f, 0.f, 0.6f, 0.5f, 0.f}),
+            reference_tests::Tensor(IN_ET,
+                                    {3, 1, 3},
+                                    std::vector<T>{0.1f, 0.2f, 0.f, 0.3f, 0.4f, 0.f, 0.6f, 0.5f, 0.f}),
             reference_tests::Tensor(IN_ET, {3, 1}, std::vector<T>{1.0f, 1.0f, 1.0f}),
             true,
             reference_tests::Tensor(IN_ET, {1, 3, 1, 1}, std::vector<T>{1.0f, 0.0f, -1.0f}),
             "ctc_greedy_decoder_merge"),
         CTCGreedyDecoderParams(
-            reference_tests::Tensor(IN_ET, {3, 1, 3}, std::vector<T>{0.1f, 0.2f, 0.f, 0.3f, 0.4f, 0.f, 0.6f, 0.5f, 0.f}),
+            reference_tests::Tensor(IN_ET,
+                                    {3, 1, 3},
+                                    std::vector<T>{0.1f, 0.2f, 0.f, 0.3f, 0.4f, 0.f, 0.6f, 0.5f, 0.f}),
             reference_tests::Tensor(IN_ET, {3, 1}, std::vector<T>{1.0f, 1.0f, 1.0f}),
             false,
             reference_tests::Tensor(IN_ET, {1, 3, 1, 1}, std::vector<T>{1.0f, 1.0f, 0.0f}),
             "ctc_greedy_decoder_single_no_merge"),
         CTCGreedyDecoderParams(
-            reference_tests::Tensor(IN_ET, {2, 2, 3}, std::vector<T>{0.1f, 0.2f, 0.f, 0.4f, 0.3f, 0.f, 0.5f, 0.6f, 0.f, 0.7f, 0.8f, 0.f}),
+            reference_tests::Tensor(IN_ET,
+                                    {2, 2, 3},
+                                    std::vector<T>{0.1f, 0.2f, 0.f, 0.4f, 0.3f, 0.f, 0.5f, 0.6f, 0.f, 0.7f, 0.8f, 0.f}),
             reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1.0f, 1.0f, 1.0f, 0.0f}),
             false,
             reference_tests::Tensor(IN_ET, {2, 2, 1, 1}, std::vector<T>{1.0f, 1.0f, 0.0f, -1.0f}),
@@ -113,7 +148,7 @@ std::vector<CTCGreedyDecoderParams> generateParams() {
 }
 
 std::vector<CTCGreedyDecoderParams> generateCombinedParams() {
-    const std::vector<std::vector<CTCGreedyDecoderParams>> generatedParams {
+    const std::vector<std::vector<CTCGreedyDecoderParams>> generatedParams{
         generateParams<element::Type_t::bf16>(),
         generateParams<element::Type_t::f16>(),
         generateParams<element::Type_t::f32>(),
@@ -127,6 +162,8 @@ std::vector<CTCGreedyDecoderParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_CTCGreedyDecoder_With_Hardcoded_Refs, ReferenceCTCGreedyDecoderTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceCTCGreedyDecoderTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_CTCGreedyDecoder_With_Hardcoded_Refs,
+                         ReferenceCTCGreedyDecoderTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceCTCGreedyDecoderTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/ctc_greedy_decoder_seq_len.cpp b/src/plugins/template/tests/functional/op_reference/ctc_greedy_decoder_seq_len.cpp
index 7c287cf3843869..2dadfd81d2634e 100644
--- a/src/plugins/template/tests/functional/op_reference/ctc_greedy_decoder_seq_len.cpp
+++ b/src/plugins/template/tests/functional/op_reference/ctc_greedy_decoder_seq_len.cpp
@@ -2,22 +2,32 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/ctc_greedy_decoder_seq_len.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/ctc_greedy_decoder_seq_len.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct CTCGreedyDecoderSeqLenParams {
-    CTCGreedyDecoderSeqLenParams(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& seqLenTensor, const reference_tests::Tensor& blankIndexTensor, int64_t mergeRepeated,
-        const reference_tests::Tensor& expectedTensor, const reference_tests::Tensor& expectedTensor2, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), seqLenTensor(seqLenTensor), blankIndexTensor(blankIndexTensor), mergeRepeated(mergeRepeated),
-        expectedTensor(expectedTensor), expectedTensor2(expectedTensor2), testcaseName(testcaseName) {}
+    CTCGreedyDecoderSeqLenParams(const reference_tests::Tensor& dataTensor,
+                                 const reference_tests::Tensor& seqLenTensor,
+                                 const reference_tests::Tensor& blankIndexTensor,
+                                 int64_t mergeRepeated,
+                                 const reference_tests::Tensor& expectedTensor,
+                                 const reference_tests::Tensor& expectedTensor2,
+                                 const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          seqLenTensor(seqLenTensor),
+          blankIndexTensor(blankIndexTensor),
+          mergeRepeated(mergeRepeated),
+          expectedTensor(expectedTensor),
+          expectedTensor2(expectedTensor2),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor seqLenTensor;
@@ -29,11 +39,18 @@ struct CTCGreedyDecoderSeqLenParams {
 };
 
 struct CTCGreedyDecoderSeqLenParamsNoOptionalInput {
-    CTCGreedyDecoderSeqLenParamsNoOptionalInput(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& seqLenTensor, int64_t mergeRepeated,
-        const reference_tests::Tensor& expectedTensor, const reference_tests::Tensor& expectedTensor2, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), seqLenTensor(seqLenTensor), mergeRepeated(mergeRepeated),
-        expectedTensor(expectedTensor), expectedTensor2(expectedTensor2), testcaseName(testcaseName) {}
+    CTCGreedyDecoderSeqLenParamsNoOptionalInput(const reference_tests::Tensor& dataTensor,
+                                                const reference_tests::Tensor& seqLenTensor,
+                                                int64_t mergeRepeated,
+                                                const reference_tests::Tensor& expectedTensor,
+                                                const reference_tests::Tensor& expectedTensor2,
+                                                const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          seqLenTensor(seqLenTensor),
+          mergeRepeated(mergeRepeated),
+          expectedTensor(expectedTensor),
+          expectedTensor2(expectedTensor2),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor seqLenTensor;
@@ -43,7 +60,8 @@ struct CTCGreedyDecoderSeqLenParamsNoOptionalInput {
     std::string testcaseName;
 };
 
-class ReferenceCTCGreedyDecoderSeqLenTest : public testing::TestWithParam<CTCGreedyDecoderSeqLenParams>, public CommonReferenceTest {
+class ReferenceCTCGreedyDecoderSeqLenTest : public testing::TestWithParam<CTCGreedyDecoderSeqLenParams>,
+                                            public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -77,16 +95,19 @@ class ReferenceCTCGreedyDecoderSeqLenTest : public testing::TestWithParam<CTCGre
         std::shared_ptr<Model> function;
         const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto seq_len = std::make_shared<op::v0::Parameter>(params.seqLenTensor.type, params.seqLenTensor.shape);
-        auto blank_index = std::make_shared<op::v0::Constant>(params.blankIndexTensor.type, params.blankIndexTensor.shape,
+        auto blank_index = std::make_shared<op::v0::Constant>(params.blankIndexTensor.type,
+                                                              params.blankIndexTensor.shape,
                                                               params.blankIndexTensor.data.data());
-        const auto decoder = std::make_shared<op::v6::CTCGreedyDecoderSeqLen>(data, seq_len, blank_index, params.mergeRepeated);
+        const auto decoder =
+            std::make_shared<op::v6::CTCGreedyDecoderSeqLen>(data, seq_len, blank_index, params.mergeRepeated);
         function = std::make_shared<ov::Model>(decoder->outputs(), ParameterVector{data, seq_len});
         return function;
     }
 };
 
-class ReferenceCTCGreedyDecoderSeqLenTestNoOptionalInput :
-    public testing::TestWithParam<CTCGreedyDecoderSeqLenParamsNoOptionalInput>, public CommonReferenceTest {
+class ReferenceCTCGreedyDecoderSeqLenTestNoOptionalInput
+    : public testing::TestWithParam<CTCGreedyDecoderSeqLenParamsNoOptionalInput>,
+      public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -135,7 +156,7 @@ TEST_P(ReferenceCTCGreedyDecoderSeqLenTestNoOptionalInput, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<CTCGreedyDecoderSeqLenParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<CTCGreedyDecoderSeqLenParams> params {
+    std::vector<CTCGreedyDecoderSeqLenParams> params{
         CTCGreedyDecoderSeqLenParams(
             reference_tests::Tensor(ET, {1, 3, 3}, std::vector<T>{0.1f, 0.2f, 0.f, 0.4f, 0.3f, 0.f, 0.5f, 0.6f, 0.f}),
             reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{2}),
@@ -153,8 +174,26 @@ std::vector<CTCGreedyDecoderSeqLenParams> generateParams() {
             reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{2}),
             "evaluate_ctc_greedy_decoder_seq_len_merge"),
         CTCGreedyDecoderSeqLenParams(
-            reference_tests::Tensor(ET, {2, 3, 3}, std::vector<T>{0.1f,  0.2f,  0.f, 0.15f, 0.25f, 0.f, 0.4f,  0.3f,  0.f,
-                                                 0.45f, 0.35f, 0.f, 0.5f,  0.6f,  0.f, 0.55f, 0.65f, 0.f}),
+            reference_tests::Tensor(ET,
+                                    {2, 3, 3},
+                                    std::vector<T>{0.1f,
+                                                   0.2f,
+                                                   0.f,
+                                                   0.15f,
+                                                   0.25f,
+                                                   0.f,
+                                                   0.4f,
+                                                   0.3f,
+                                                   0.f,
+                                                   0.45f,
+                                                   0.35f,
+                                                   0.f,
+                                                   0.5f,
+                                                   0.6f,
+                                                   0.f,
+                                                   0.55f,
+                                                   0.65f,
+                                                   0.f}),
             reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 1}),
             reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{2}),
             false,
@@ -162,9 +201,10 @@ std::vector<CTCGreedyDecoderSeqLenParams> generateParams() {
             reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 1}),
             "evaluate_ctc_greedy_decoder_seq_len_multiple_batches"),
         CTCGreedyDecoderSeqLenParams(
-            reference_tests::Tensor(ET, {3, 3, 3}, std::vector<T>{0.1f,  0.2f,  0.f, 0.15f, 0.25f, 0.f, 0.4f,  0.3f,  0.f,
-                                                 0.45f, 0.35f, 0.f, 0.5f,  0.6f,  0.f, 0.55f, 0.65f, 0.f,
-                                                 0.1f,  0.2f,  0.f, 0.15f, 0.25f, 0.f, 0.4f,  0.3f,  0.f}),
+            reference_tests::Tensor(ET, {3, 3, 3}, std::vector<T>{0.1f,  0.2f,  0.f,   0.15f, 0.25f, 0.f,  0.4f,
+                                                                  0.3f,  0.f,   0.45f, 0.35f, 0.f,   0.5f, 0.6f,
+                                                                  0.f,   0.55f, 0.65f, 0.f,   0.1f,  0.2f, 0.f,
+                                                                  0.15f, 0.25f, 0.f,   0.4f,  0.3f,  0.f}),
             reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{2, 3, 1}),
             reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{2}),
             false,
@@ -176,7 +216,7 @@ std::vector<CTCGreedyDecoderSeqLenParams> generateParams() {
 }
 
 std::vector<CTCGreedyDecoderSeqLenParams> generateCombinedParams() {
-    const std::vector<std::vector<CTCGreedyDecoderSeqLenParams>> generatedParams {
+    const std::vector<std::vector<CTCGreedyDecoderSeqLenParams>> generatedParams{
         generateParams<element::Type_t::bf16>(),
         generateParams<element::Type_t::f16>(),
         generateParams<element::Type_t::f32>(),
@@ -193,7 +233,7 @@ std::vector<CTCGreedyDecoderSeqLenParams> generateCombinedParams() {
 template <element::Type_t ET>
 std::vector<CTCGreedyDecoderSeqLenParamsNoOptionalInput> generateParamsNoOptionalInput() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<CTCGreedyDecoderSeqLenParamsNoOptionalInput> params {
+    std::vector<CTCGreedyDecoderSeqLenParamsNoOptionalInput> params{
         CTCGreedyDecoderSeqLenParamsNoOptionalInput(
             reference_tests::Tensor(ET, {1, 3, 3}, std::vector<T>{0.1f, 0.2f, 0.f, 0.4f, 0.3f, 0.f, 0.5f, 0.6f, 0.f}),
             reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{2}),
@@ -206,7 +246,7 @@ std::vector<CTCGreedyDecoderSeqLenParamsNoOptionalInput> generateParamsNoOptiona
 }
 
 std::vector<CTCGreedyDecoderSeqLenParamsNoOptionalInput> generateCombinedParamsNoOptionalInput() {
-    const std::vector<std::vector<CTCGreedyDecoderSeqLenParamsNoOptionalInput>> generatedParams {
+    const std::vector<std::vector<CTCGreedyDecoderSeqLenParamsNoOptionalInput>> generatedParams{
         generateParamsNoOptionalInput<element::Type_t::bf16>(),
         generateParamsNoOptionalInput<element::Type_t::f16>(),
         generateParamsNoOptionalInput<element::Type_t::f32>(),
@@ -220,9 +260,13 @@ std::vector<CTCGreedyDecoderSeqLenParamsNoOptionalInput> generateCombinedParamsN
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_CTCGreedyDecoderSeqLen_With_Hardcoded_Refs, ReferenceCTCGreedyDecoderSeqLenTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceCTCGreedyDecoderSeqLenTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_CTCGreedyDecoderSeqLen_With_Hardcoded_Refs,
+                         ReferenceCTCGreedyDecoderSeqLenTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceCTCGreedyDecoderSeqLenTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_CTCGreedyDecoderSeqLen_With_Hardcoded_Refs, ReferenceCTCGreedyDecoderSeqLenTestNoOptionalInput,
-    testing::ValuesIn(generateCombinedParamsNoOptionalInput()), ReferenceCTCGreedyDecoderSeqLenTestNoOptionalInput::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_CTCGreedyDecoderSeqLen_With_Hardcoded_Refs,
+                         ReferenceCTCGreedyDecoderSeqLenTestNoOptionalInput,
+                         testing::ValuesIn(generateCombinedParamsNoOptionalInput()),
+                         ReferenceCTCGreedyDecoderSeqLenTestNoOptionalInput::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/ctc_loss.cpp b/src/plugins/template/tests/functional/op_reference/ctc_loss.cpp
index b432f1d408054a..4aec555d6dbe88 100644
--- a/src/plugins/template/tests/functional/op_reference/ctc_loss.cpp
+++ b/src/plugins/template/tests/functional/op_reference/ctc_loss.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/ctc_loss.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/ctc_loss.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,8 +14,15 @@ using namespace ov;
 namespace {
 
 struct CTCLossParams {
-    CTCLossParams(const bool collapseRepeated, const bool mergeRepeated, const bool findUnique, const reference_tests::Tensor& logitsTensor, const reference_tests::Tensor& logitsLenTensor,
-                  const reference_tests::Tensor& labelsTensor, const reference_tests::Tensor& labelsLenTensor, const reference_tests::Tensor& blankIdxTensor, const reference_tests::Tensor& expectedTensor)
+    CTCLossParams(const bool collapseRepeated,
+                  const bool mergeRepeated,
+                  const bool findUnique,
+                  const reference_tests::Tensor& logitsTensor,
+                  const reference_tests::Tensor& logitsLenTensor,
+                  const reference_tests::Tensor& labelsTensor,
+                  const reference_tests::Tensor& labelsLenTensor,
+                  const reference_tests::Tensor& blankIdxTensor,
+                  const reference_tests::Tensor& expectedTensor)
         : preprocessCollapseRepeated(collapseRepeated),
           ctcMergeRepeated(mergeRepeated),
           unique(findUnique),
@@ -41,7 +49,11 @@ class ReferenceCTCLossLayerTest : public testing::TestWithParam<CTCLossParams>,
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.logits.data, params.logitsLen.data, params.labels.data, params.labelsLen.data, params.blankIdx.data};
+        inputData = {params.logits.data,
+                     params.logitsLen.data,
+                     params.labels.data,
+                     params.labelsLen.data,
+                     params.blankIdx.data};
         refOutData = {params.expected.data};
     }
     static std::string getTestCaseName(const testing::TestParamInfo<CTCLossParams>& obj) {
@@ -68,8 +80,15 @@ class ReferenceCTCLossLayerTest : public testing::TestWithParam<CTCLossParams>,
         const auto D = std::make_shared<op::v0::Parameter>(params.labelsLen.type, params.labelsLen.shape);  // labelsLen
         const auto E = std::make_shared<op::v0::Parameter>(params.blankIdx.type, params.blankIdx.shape);    // blankIdx
 
-        const auto ctcLoss = std::make_shared<op::v4::CTCLoss>(A, B, C, D, E, params.preprocessCollapseRepeated, params.ctcMergeRepeated, params.unique);
-        return std::make_shared<ov::Model>(NodeVector {ctcLoss}, ParameterVector {A, B, C, D, E});
+        const auto ctcLoss = std::make_shared<op::v4::CTCLoss>(A,
+                                                               B,
+                                                               C,
+                                                               D,
+                                                               E,
+                                                               params.preprocessCollapseRepeated,
+                                                               params.ctcMergeRepeated,
+                                                               params.unique);
+        return std::make_shared<ov::Model>(NodeVector{ctcLoss}, ParameterVector{A, B, C, D, E});
     }
 };
 
@@ -78,91 +97,153 @@ TEST_P(ReferenceCTCLossLayerTest, CompareWithRefs) {
 }
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_CTCLoss_With_Hardcoded_Refs, ReferenceCTCLossLayerTest,
-    ::testing::Values(CTCLossParams(false, false, false,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f32, std::vector<float> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f32, std::vector<float> {1.41223f, 14.1359f})),                                          // refOut
-                      CTCLossParams(false, false, true,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f32, std::vector<float> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f32, std::vector<float> {1.41223f, 14.1359f})),                                          // refOut
-                      CTCLossParams(false, true, false,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f32, std::vector<float> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f32, std::vector<float> {1.41156f, 13.2745f})),                                          // refOut
-                      CTCLossParams(true, false, false,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f32, std::vector<float> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f32, std::vector<float> {1.41223f, 14.1359f})),                                          // refOut
-                      CTCLossParams(false, true, true,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f32, std::vector<float> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f32, std::vector<float> {1.41156f, 13.2745f})),                                          // refOut
-                      CTCLossParams(true, true, true,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f32, std::vector<float> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f32, std::vector<float> {1.41223f, 13.2745f})),                                          // refOut
-                    // floating point type - float16
-                    CTCLossParams(false, false, false,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f16, std::vector<float16> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f16, std::vector<float16> {1.41223f, 14.1359f})),                                          // refOut
-                      CTCLossParams(false, false, true,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f16, std::vector<float16> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f16, std::vector<float16> {1.41223f, 14.1359f})),                                          // refOut
-                      CTCLossParams(false, true, false,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f16, std::vector<float16> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f16, std::vector<float16> {1.41156f, 13.2745f})),                                          // refOut
-                      CTCLossParams(true, false, false,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f16, std::vector<float16> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f16, std::vector<float16> {1.41223f, 14.1359f})),                                          // refOut
-                      CTCLossParams(false, true, true,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f16, std::vector<float16> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f16, std::vector<float16> {1.41156f, 13.2745f})),                                          // refOut
-                      CTCLossParams(true, true, true,  // collapse repeated, merge repeated, unique
-                                    reference_tests::Tensor({2, 3, 3}, element::f16, std::vector<float16> {0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),  // logits
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {3, 3}),                                                           // logitsLen
-                                    reference_tests::Tensor({2, 3}, element::i32, std::vector<int> {0, 1, 2, 1, 1, 1}),                                            // labels
-                                    reference_tests::Tensor({2}, element::i32, std::vector<int> {2, 1}),                                                           // labelsLen
-                                    reference_tests::Tensor({}, element::i32, std::vector<int> {2}),                                                               // blankIdx
-                                    reference_tests::Tensor({2}, element::f16, std::vector<float16> {1.41223f, 13.2745f}))),                                         // refOut
+    smoke_CTCLoss_With_Hardcoded_Refs,
+    ReferenceCTCLossLayerTest,
+    ::testing::Values(
+        CTCLossParams(false,
+                      false,
+                      false,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f32,
+                          std::vector<float>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),       // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                   // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),    // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                   // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                       // blankIdx
+                      reference_tests::Tensor({2}, element::f32, std::vector<float>{1.41223f, 14.1359f})),  // refOut
+        CTCLossParams(false,
+                      false,
+                      true,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f32,
+                          std::vector<float>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),       // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                   // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),    // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                   // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                       // blankIdx
+                      reference_tests::Tensor({2}, element::f32, std::vector<float>{1.41223f, 14.1359f})),  // refOut
+        CTCLossParams(false,
+                      true,
+                      false,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f32,
+                          std::vector<float>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),       // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                   // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),    // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                   // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                       // blankIdx
+                      reference_tests::Tensor({2}, element::f32, std::vector<float>{1.41156f, 13.2745f})),  // refOut
+        CTCLossParams(true,
+                      false,
+                      false,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f32,
+                          std::vector<float>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),       // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                   // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),    // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                   // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                       // blankIdx
+                      reference_tests::Tensor({2}, element::f32, std::vector<float>{1.41223f, 14.1359f})),  // refOut
+        CTCLossParams(false,
+                      true,
+                      true,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f32,
+                          std::vector<float>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),       // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                   // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),    // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                   // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                       // blankIdx
+                      reference_tests::Tensor({2}, element::f32, std::vector<float>{1.41156f, 13.2745f})),  // refOut
+        CTCLossParams(true,
+                      true,
+                      true,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f32,
+                          std::vector<float>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),       // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                   // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),    // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                   // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                       // blankIdx
+                      reference_tests::Tensor({2}, element::f32, std::vector<float>{1.41223f, 13.2745f})),  // refOut
+        // floating point type - float16
+        CTCLossParams(false,
+                      false,
+                      false,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f16,
+                          std::vector<float16>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),   // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                 // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),  // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                 // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                     // blankIdx
+                      reference_tests::Tensor({2}, element::f16, std::vector<float16>{1.41223f, 14.1359f})),  // refOut
+        CTCLossParams(false,
+                      false,
+                      true,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f16,
+                          std::vector<float16>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),   // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                 // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),  // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                 // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                     // blankIdx
+                      reference_tests::Tensor({2}, element::f16, std::vector<float16>{1.41223f, 14.1359f})),  // refOut
+        CTCLossParams(false,
+                      true,
+                      false,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f16,
+                          std::vector<float16>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),   // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                 // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),  // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                 // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                     // blankIdx
+                      reference_tests::Tensor({2}, element::f16, std::vector<float16>{1.41156f, 13.2745f})),  // refOut
+        CTCLossParams(true,
+                      false,
+                      false,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f16,
+                          std::vector<float16>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),   // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                 // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),  // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                 // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                     // blankIdx
+                      reference_tests::Tensor({2}, element::f16, std::vector<float16>{1.41223f, 14.1359f})),  // refOut
+        CTCLossParams(false,
+                      true,
+                      true,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f16,
+                          std::vector<float16>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),   // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                 // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),  // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                 // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                     // blankIdx
+                      reference_tests::Tensor({2}, element::f16, std::vector<float16>{1.41156f, 13.2745f})),  // refOut
+        CTCLossParams(true,
+                      true,
+                      true,  // collapse repeated, merge repeated, unique
+                      reference_tests::Tensor(
+                          {2, 3, 3},
+                          element::f16,
+                          std::vector<float16>{0, 1, 8, 5, 5, 2, 0, 7, 7, 10, 4, 5, 9, 0, 0, 5, 7, 0}),   // logits
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{3, 3}),                 // logitsLen
+                      reference_tests::Tensor({2, 3}, element::i32, std::vector<int>{0, 1, 2, 1, 1, 1}),  // labels
+                      reference_tests::Tensor({2}, element::i32, std::vector<int>{2, 1}),                 // labelsLen
+                      reference_tests::Tensor({}, element::i32, std::vector<int>{2}),                     // blankIdx
+                      reference_tests::Tensor({2}, element::f16, std::vector<float16>{1.41223f, 13.2745f}))),  // refOut
     ReferenceCTCLossLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/cum_sum.cpp b/src/plugins/template/tests/functional/op_reference/cum_sum.cpp
index dee306417ee73d..51ee19e188c3fa 100644
--- a/src/plugins/template/tests/functional/op_reference/cum_sum.cpp
+++ b/src/plugins/template/tests/functional/op_reference/cum_sum.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/cum_sum.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/cum_sum.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -14,8 +15,15 @@ namespace {
 struct CumSumParams {
     // Custom axis input and attributes
     template <class IT, class AT>
-    CumSumParams(const PartialShape& shape, const element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues, const bool execlusive,
-                 const bool reverse, const element::Type& axisType, AT axisVal, const PartialShape& axisShape)
+    CumSumParams(const PartialShape& shape,
+                 const element::Type& iType,
+                 const std::vector<IT>& iValues,
+                 const std::vector<IT>& oValues,
+                 const bool execlusive,
+                 const bool reverse,
+                 const element::Type& axisType,
+                 AT axisVal,
+                 const PartialShape& axisShape)
         : execlusive(execlusive),
           reverse(reverse),
           axisValue(axisVal),
@@ -24,14 +32,17 @@ struct CumSumParams {
           axisType(axisType),
           inType(iType),
           outType(iType),
-          axisData(CreateTensor(axisType, std::vector<AT> {axisVal})),
+          axisData(CreateTensor(axisType, std::vector<AT>{axisVal})),
           inputData(CreateTensor(iType, iValues)),
           refData(CreateTensor(iType, oValues)),
           testDefaults(false) {}
 
     // Default axis input and attributes
     template <class IT>
-    CumSumParams(const PartialShape& shape, const element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    CumSumParams(const PartialShape& shape,
+                 const element::Type& iType,
+                 const std::vector<IT>& iValues,
+                 const std::vector<IT>& oValues)
         : inShape(shape),
           axisType(element::i32),
           inType(iType),
@@ -65,7 +76,12 @@ class ReferenceCumSumLayerTest : public testing::TestWithParam<CumSumParams>, pu
             inputData = {params.inputData};
             refOutData = {params.refData};
         } else {
-            function = CreateFunction(params.inShape, params.inType, params.axisShape, params.axisType, params.execlusive, params.reverse);
+            function = CreateFunction(params.inShape,
+                                      params.inType,
+                                      params.axisShape,
+                                      params.axisType,
+                                      params.execlusive,
+                                      params.reverse);
             inputData = {params.inputData, params.axisData};
             refOutData = {params.refData};
         }
@@ -85,18 +101,22 @@ class ReferenceCumSumLayerTest : public testing::TestWithParam<CumSumParams>, pu
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& data_shape, const element::Type& data_type, const PartialShape& axis_shape,
-                                                    const element::Type& axis_type, const bool execlusive, const bool reverse) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& data_shape,
+                                                 const element::Type& data_type,
+                                                 const PartialShape& axis_shape,
+                                                 const element::Type& axis_type,
+                                                 const bool execlusive,
+                                                 const bool reverse) {
         const auto data_param = std::make_shared<op::v0::Parameter>(data_type, data_shape);
         const auto axis_param = std::make_shared<op::v0::Parameter>(axis_type, axis_shape);
         const auto cum_sum = std::make_shared<op::v0::CumSum>(data_param, axis_param, execlusive, reverse);
-        return std::make_shared<ov::Model>(NodeVector {cum_sum}, ParameterVector {data_param, axis_param});
+        return std::make_shared<ov::Model>(NodeVector{cum_sum}, ParameterVector{data_param, axis_param});
     }
 
     static std::shared_ptr<Model> CreateFunction(const PartialShape& data_shape, const element::Type& data_type) {
         const auto data_param = std::make_shared<op::v0::Parameter>(data_type, data_shape);
         const auto cum_sum = std::make_shared<op::v0::CumSum>(data_param);
-        return std::make_shared<ov::Model>(NodeVector {cum_sum}, ParameterVector {data_param});
+        return std::make_shared<ov::Model>(NodeVector{cum_sum}, ParameterVector{data_param});
     }
 };
 
@@ -107,73 +127,176 @@ TEST_P(ReferenceCumSumLayerTest, CompareWithHardcodedRefs) {
 template <element::Type_t IN_ET>
 std::vector<CumSumParams> generateCumSumParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<CumSumParams> opParams {
+    std::vector<CumSumParams> opParams{
         // Default axis input and attributes
-        CumSumParams(PartialShape {1}, type, std::vector<T> {3}, std::vector<T> {3}),
-        CumSumParams(PartialShape {6}, type, std::vector<T> {1, 2, 3, 4, 5, 6}, std::vector<T> {1, 3, 6, 10, 15, 21}),
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {0, 1, 2, 3, 4, 6, 8, 10}),
+        CumSumParams(PartialShape{1}, type, std::vector<T>{3}, std::vector<T>{3}),
+        CumSumParams(PartialShape{6}, type, std::vector<T>{1, 2, 3, 4, 5, 6}, std::vector<T>{1, 3, 6, 10, 15, 21}),
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{0, 1, 2, 3, 4, 6, 8, 10}),
         // Custom axis input and attributes
-        CumSumParams(PartialShape {6}, type, std::vector<T> {1, 2, 3, 4, 5, 6}, std::vector<T> {1, 3, 6, 10, 15, 21}, false, false, element::i32, int32_t(0),
-                     PartialShape {}),  // axis i32
-        CumSumParams(PartialShape {6}, type, std::vector<T> {1, 2, 3, 4, 5, 6}, std::vector<T> {1, 3, 6, 10, 15, 21}, false, false, element::i64, int64_t(0),
-                     PartialShape {}),  // axis i64
-        CumSumParams(PartialShape {6}, type, std::vector<T> {1, 2, 3, 4, 5, 6}, std::vector<T> {21, 20, 18, 15, 11, 6}, false, true, element::i64, int64_t(0),
-                     PartialShape {}),
-        CumSumParams(PartialShape {6}, type, std::vector<T> {1, 2, 3, 4, 5, 6}, std::vector<T> {0, 1, 3, 6, 10, 15}, true, false, element::i64, int64_t(0),
-                     PartialShape {}),
-        CumSumParams(PartialShape {6}, type, std::vector<T> {1, 2, 3, 4, 5, 6}, std::vector<T> {20, 18, 15, 11, 6, 0}, true, true, element::i64, int64_t(0),
-                     PartialShape {}),
-
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {0, 1, 2, 3, 4, 6, 8, 10}, false, false, element::i32,
-                    int32_t(0), PartialShape {}),
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {4, 6, 8, 10, 4, 5, 6, 7}, false, true, element::i32,
-                    int32_t(0), PartialShape {}),
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {0, 0, 0, 0, 0, 1, 2, 3}, true, false, element::i32,
-                    int32_t(0), PartialShape {}),
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {4, 5, 6, 7, 0, 0, 0, 0}, true, true, element::i32,
-                    int32_t(0), PartialShape {}),
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {0, 1, 3, 6, 4, 9, 15, 22}, false, false, element::i32,
-                     int32_t(1), PartialShape {}),
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {0, 0, 1, 3, 0, 4, 9, 15}, true, false, element::i32,
-                     int32_t(1), PartialShape {}),
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {6, 6, 5, 3, 22, 18, 13, 7}, false, true, element::i32,
-                     int32_t(1), PartialShape {}),
-        CumSumParams(PartialShape {2, 4}, type, std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7}, std::vector<T> {6, 5, 3, 0, 18, 13, 7, 0}, true, true, element::i32,
-                     int32_t(1), PartialShape {}),
-
-        CumSumParams(PartialShape {3, 2, 4}, type,
-                    std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7,
-                                    8, 9, 10, 11, 12, 13, 14, 15,
-                                    16, 17, 18, 19, 20, 21, 22, 23},
-                    std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7,
-                                    8, 10, 12, 14, 16, 18, 20, 22,
-                                    24, 27, 30, 33, 36, 39, 42, 45},
-                    false, false, element::i32, int32_t(0), PartialShape {}),
-        CumSumParams(PartialShape {3, 2, 4}, type,
-                    std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7,
-                                    8, 9, 10, 11, 12, 13, 14, 15,
-                                    16, 17, 18, 19, 20, 21, 22, 23},
-                    std::vector<T> {0,  1,  2,  3,  4,  6,  8, 10,
-                                    8,  9,  10, 11, 20, 22, 24, 26,
-                                    16, 17, 18, 19, 36, 38, 40, 42},
-                    false, false, element::i32, int32_t(1), PartialShape {}),
-        CumSumParams(PartialShape {3, 2, 4}, type,
-                    std::vector<T> {0, 1, 2, 3, 4, 5, 6, 7,
-                                    8, 9, 10, 11, 12, 13, 14, 15,
-                                    16, 17, 18, 19, 20, 21, 22, 23},
-                    std::vector<T> {0,  1,  3,  6,  4,  9,  15, 22,
-                                    8,  17, 27, 38, 12, 25, 39, 54,
-                                    16, 33, 51, 70, 20, 41, 63, 86},
-                    false, false, element::i32, int32_t(2), PartialShape {}),
+        CumSumParams(PartialShape{6},
+                     type,
+                     std::vector<T>{1, 2, 3, 4, 5, 6},
+                     std::vector<T>{1, 3, 6, 10, 15, 21},
+                     false,
+                     false,
+                     element::i32,
+                     int32_t(0),
+                     PartialShape{}),  // axis i32
+        CumSumParams(PartialShape{6},
+                     type,
+                     std::vector<T>{1, 2, 3, 4, 5, 6},
+                     std::vector<T>{1, 3, 6, 10, 15, 21},
+                     false,
+                     false,
+                     element::i64,
+                     int64_t(0),
+                     PartialShape{}),  // axis i64
+        CumSumParams(PartialShape{6},
+                     type,
+                     std::vector<T>{1, 2, 3, 4, 5, 6},
+                     std::vector<T>{21, 20, 18, 15, 11, 6},
+                     false,
+                     true,
+                     element::i64,
+                     int64_t(0),
+                     PartialShape{}),
+        CumSumParams(PartialShape{6},
+                     type,
+                     std::vector<T>{1, 2, 3, 4, 5, 6},
+                     std::vector<T>{0, 1, 3, 6, 10, 15},
+                     true,
+                     false,
+                     element::i64,
+                     int64_t(0),
+                     PartialShape{}),
+        CumSumParams(PartialShape{6},
+                     type,
+                     std::vector<T>{1, 2, 3, 4, 5, 6},
+                     std::vector<T>{20, 18, 15, 11, 6, 0},
+                     true,
+                     true,
+                     element::i64,
+                     int64_t(0),
+                     PartialShape{}),
+
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{0, 1, 2, 3, 4, 6, 8, 10},
+                     false,
+                     false,
+                     element::i32,
+                     int32_t(0),
+                     PartialShape{}),
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{4, 6, 8, 10, 4, 5, 6, 7},
+                     false,
+                     true,
+                     element::i32,
+                     int32_t(0),
+                     PartialShape{}),
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{0, 0, 0, 0, 0, 1, 2, 3},
+                     true,
+                     false,
+                     element::i32,
+                     int32_t(0),
+                     PartialShape{}),
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{4, 5, 6, 7, 0, 0, 0, 0},
+                     true,
+                     true,
+                     element::i32,
+                     int32_t(0),
+                     PartialShape{}),
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{0, 1, 3, 6, 4, 9, 15, 22},
+                     false,
+                     false,
+                     element::i32,
+                     int32_t(1),
+                     PartialShape{}),
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{0, 0, 1, 3, 0, 4, 9, 15},
+                     true,
+                     false,
+                     element::i32,
+                     int32_t(1),
+                     PartialShape{}),
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{6, 6, 5, 3, 22, 18, 13, 7},
+                     false,
+                     true,
+                     element::i32,
+                     int32_t(1),
+                     PartialShape{}),
+        CumSumParams(PartialShape{2, 4},
+                     type,
+                     std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7},
+                     std::vector<T>{6, 5, 3, 0, 18, 13, 7, 0},
+                     true,
+                     true,
+                     element::i32,
+                     int32_t(1),
+                     PartialShape{}),
+
+        CumSumParams(
+            PartialShape{3, 2, 4},
+            type,
+            std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23},
+            std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 18, 20, 22, 24, 27, 30, 33, 36, 39, 42, 45},
+            false,
+            false,
+            element::i32,
+            int32_t(0),
+            PartialShape{}),
+        CumSumParams(
+            PartialShape{3, 2, 4},
+            type,
+            std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23},
+            std::vector<T>{0, 1, 2, 3, 4, 6, 8, 10, 8, 9, 10, 11, 20, 22, 24, 26, 16, 17, 18, 19, 36, 38, 40, 42},
+            false,
+            false,
+            element::i32,
+            int32_t(1),
+            PartialShape{}),
+        CumSumParams(
+            PartialShape{3, 2, 4},
+            type,
+            std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23},
+            std::vector<T>{0, 1, 3, 6, 4, 9, 15, 22, 8, 17, 27, 38, 12, 25, 39, 54, 16, 33, 51, 70, 20, 41, 63, 86},
+            false,
+            false,
+            element::i32,
+            int32_t(2),
+            PartialShape{}),
     };
     return opParams;
 }
 
 std::vector<CumSumParams> generateCumSumCombinedParams() {
-    const std::vector<std::vector<CumSumParams>> opTypeParams {
-        generateCumSumParams<element::Type_t::bf16>(element::bf16), generateCumSumParams<element::Type_t::f16>(element::f16),
-        generateCumSumParams<element::Type_t::f32>(element::f32),   generateCumSumParams<element::Type_t::i32>(element::i32),
-        generateCumSumParams<element::Type_t::i64>(element::i64),   generateCumSumParams<element::Type_t::u32>(element::u32),
+    const std::vector<std::vector<CumSumParams>> opTypeParams{
+        generateCumSumParams<element::Type_t::bf16>(element::bf16),
+        generateCumSumParams<element::Type_t::f16>(element::f16),
+        generateCumSumParams<element::Type_t::f32>(element::f32),
+        generateCumSumParams<element::Type_t::i32>(element::i32),
+        generateCumSumParams<element::Type_t::i64>(element::i64),
+        generateCumSumParams<element::Type_t::u32>(element::u32),
         generateCumSumParams<element::Type_t::i8>(element::i8)};
     std::vector<CumSumParams> combinedParams;
     std::for_each(opTypeParams.begin(), opTypeParams.end(), [&](std::vector<CumSumParams> params) {
@@ -182,6 +305,8 @@ std::vector<CumSumParams> generateCumSumCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_CumSum_With_Hardcoded_Refs, ReferenceCumSumLayerTest, ::testing::ValuesIn(generateCumSumCombinedParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_CumSum_With_Hardcoded_Refs,
+                         ReferenceCumSumLayerTest,
+                         ::testing::ValuesIn(generateCumSumCombinedParams()),
                          ReferenceCumSumLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/deformable_convolution.cpp b/src/plugins/template/tests/functional/op_reference/deformable_convolution.cpp
index 38de9a5c62f853..4c0a6e6578d678 100644
--- a/src/plugins/template/tests/functional/op_reference/deformable_convolution.cpp
+++ b/src/plugins/template/tests/functional/op_reference/deformable_convolution.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/deformable_convolution.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/deformable_convolution.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,15 +14,23 @@ using namespace ov;
 namespace {
 struct DeformableConvolutionParams {
     template <class IT>
-    DeformableConvolutionParams(const PartialShape& inputShape, const PartialShape& filterShape,
-                      const PartialShape& offsetShape, const PartialShape& outputShape,
-                      const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues,
-                      const std::vector<IT>& offsetValues, const std::vector<IT>& oValues,
-                      const Strides& strides, const CoordinateDiff& padBegin, const CoordinateDiff& padEnd, const Strides& dialations,
-                      const int64_t group = 1, const int64_t deformableGroup = 1,
-                      const std::string& test_name = "",
-                      const bool use_bilinear_interpolation_padding = false)
+    DeformableConvolutionParams(const PartialShape& inputShape,
+                                const PartialShape& filterShape,
+                                const PartialShape& offsetShape,
+                                const PartialShape& outputShape,
+                                const element::Type& iType,
+                                const std::vector<IT>& iValues,
+                                const std::vector<IT>& filterValues,
+                                const std::vector<IT>& offsetValues,
+                                const std::vector<IT>& oValues,
+                                const Strides& strides,
+                                const CoordinateDiff& padBegin,
+                                const CoordinateDiff& padEnd,
+                                const Strides& dialations,
+                                const int64_t group = 1,
+                                const int64_t deformableGroup = 1,
+                                const std::string& test_name = "",
+                                const bool use_bilinear_interpolation_padding = false)
         : inputShape(inputShape),
           filterShape(filterShape),
           offsetShape(offsetShape),
@@ -44,15 +53,25 @@ struct DeformableConvolutionParams {
           use_bilinear_interpolation_padding(use_bilinear_interpolation_padding) {}
 
     template <class IT>
-    DeformableConvolutionParams(const PartialShape& inputShape, const PartialShape& filterShape,
-                      const PartialShape& offsetShape, const PartialShape& outputShape, const PartialShape& maskShape,
-                      const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues,
-                      const std::vector<IT>& offsetValues, const std::vector<IT>& oValues, const std::vector<IT>& maskValues,
-                      const Strides& strides, const CoordinateDiff& padBegin, const CoordinateDiff& padEnd, const Strides& dialations,
-                      const int64_t group = 1, const int64_t deformableGroup = 1,
-                      const std::string& test_name = "",
-                      const bool use_bilinear_interpolation_padding = false)
+    DeformableConvolutionParams(const PartialShape& inputShape,
+                                const PartialShape& filterShape,
+                                const PartialShape& offsetShape,
+                                const PartialShape& outputShape,
+                                const PartialShape& maskShape,
+                                const element::Type& iType,
+                                const std::vector<IT>& iValues,
+                                const std::vector<IT>& filterValues,
+                                const std::vector<IT>& offsetValues,
+                                const std::vector<IT>& oValues,
+                                const std::vector<IT>& maskValues,
+                                const Strides& strides,
+                                const CoordinateDiff& padBegin,
+                                const CoordinateDiff& padEnd,
+                                const Strides& dialations,
+                                const int64_t group = 1,
+                                const int64_t deformableGroup = 1,
+                                const std::string& test_name = "",
+                                const bool use_bilinear_interpolation_padding = false)
         : inputShape(inputShape),
           filterShape(filterShape),
           offsetShape(offsetShape),
@@ -102,7 +121,8 @@ struct DeformableConvolutionParams {
     bool use_bilinear_interpolation_padding;
 };
 
-class ReferenceDeformableConvolutionLayerTest : public testing::TestWithParam<DeformableConvolutionParams>, public CommonReferenceTest {
+class ReferenceDeformableConvolutionLayerTest : public testing::TestWithParam<DeformableConvolutionParams>,
+                                                public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -140,20 +160,21 @@ class ReferenceDeformableConvolutionLayerTest : public testing::TestWithParam<De
         const auto offset = std::make_shared<op::v0::Parameter>(params.offsetType, params.offsetShape);
         const auto filter = std::make_shared<op::v0::Parameter>(params.filterType, params.filterShape);
         const auto DeformableConvolution = std::make_shared<op::v1::DeformableConvolution>(in,
-                                                                       offset,
-                                                                       filter,
-                                                                       params.strides,
-                                                                       params.padBegin,
-                                                                       params.padEnd,
-                                                                       params.dialations,
-                                                                       auto_pad,
-                                                                       params.group,
-                                                                       params.deformableGroup);
-        return std::make_shared<ov::Model>(NodeVector {DeformableConvolution}, ParameterVector {in, offset, filter});
+                                                                                           offset,
+                                                                                           filter,
+                                                                                           params.strides,
+                                                                                           params.padBegin,
+                                                                                           params.padEnd,
+                                                                                           params.dialations,
+                                                                                           auto_pad,
+                                                                                           params.group,
+                                                                                           params.deformableGroup);
+        return std::make_shared<ov::Model>(NodeVector{DeformableConvolution}, ParameterVector{in, offset, filter});
     }
 };
 
-class ReferenceDeformableConvolutionV8LayerTest : public testing::TestWithParam<DeformableConvolutionParams>, public CommonReferenceTest {
+class ReferenceDeformableConvolutionV8LayerTest : public testing::TestWithParam<DeformableConvolutionParams>,
+                                                  public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -199,32 +220,36 @@ class ReferenceDeformableConvolutionV8LayerTest : public testing::TestWithParam<
         const auto filter = std::make_shared<op::v0::Parameter>(params.filterType, params.filterShape);
         if (params.maskShape.size() != 0) {
             const auto mask = std::make_shared<op::v0::Parameter>(params.maskType, params.maskShape);
-            const auto DeformableConvolutionV8 = std::make_shared<op::v8::DeformableConvolution>(in,
-                                                                        offset,
-                                                                        filter,
-                                                                        mask,
-                                                                        params.strides,
-                                                                        params.padBegin,
-                                                                        params.padEnd,
-                                                                        params.dialations,
-                                                                        auto_pad,
-                                                                        params.group,
-                                                                        params.deformableGroup,
-                                                                        params.use_bilinear_interpolation_padding);
-            return std::make_shared<ov::Model>(NodeVector {DeformableConvolutionV8}, ParameterVector {in, offset, filter, mask});
+            const auto DeformableConvolutionV8 =
+                std::make_shared<op::v8::DeformableConvolution>(in,
+                                                                offset,
+                                                                filter,
+                                                                mask,
+                                                                params.strides,
+                                                                params.padBegin,
+                                                                params.padEnd,
+                                                                params.dialations,
+                                                                auto_pad,
+                                                                params.group,
+                                                                params.deformableGroup,
+                                                                params.use_bilinear_interpolation_padding);
+            return std::make_shared<ov::Model>(NodeVector{DeformableConvolutionV8},
+                                               ParameterVector{in, offset, filter, mask});
         } else {
-            const auto DeformableConvolutionV8 = std::make_shared<op::v8::DeformableConvolution>(in,
-                                                                        offset,
-                                                                        filter,
-                                                                        params.strides,
-                                                                        params.padBegin,
-                                                                        params.padEnd,
-                                                                        params.dialations,
-                                                                        auto_pad,
-                                                                        params.group,
-                                                                        params.deformableGroup,
-                                                                        params.use_bilinear_interpolation_padding);
-            return std::make_shared<ov::Model>(NodeVector {DeformableConvolutionV8}, ParameterVector {in, offset, filter});
+            const auto DeformableConvolutionV8 =
+                std::make_shared<op::v8::DeformableConvolution>(in,
+                                                                offset,
+                                                                filter,
+                                                                params.strides,
+                                                                params.padBegin,
+                                                                params.padEnd,
+                                                                params.dialations,
+                                                                auto_pad,
+                                                                params.group,
+                                                                params.deformableGroup,
+                                                                params.use_bilinear_interpolation_padding);
+            return std::make_shared<ov::Model>(NodeVector{DeformableConvolutionV8},
+                                               ParameterVector{in, offset, filter});
         }
     }
 };
@@ -241,2537 +266,3845 @@ template <element::Type_t IN_ET>
 std::vector<DeformableConvolutionParams> generateDeformableConvolutionFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DeformableConvolutionParams> deformableConvolutionParams {
-// --------------------- 2D DeformableConvolution ------------------------------------------
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    -1.0f, -2.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    -12.0f, -12.0f, -12.0f,
-                                    -12.0f, -12.0f, -12.0f,
-                                    -12.0f, -12.0f, -12.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f,
-                                    7.0f, 5.0f, 3.0f,
-                                    1.0f, 3.0f, 5.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    0.0f, 1.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 0.0f,
-                                    9.0f, 12.0f, 16.0f, 5.0f,
-                                    15.0f, 20.0f, 16.0f, 3.0f,
-                                    2.0f, 7.0f, 13.0f, 5.0f},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f, 9.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, 0.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    3.0f, 2.0f, 1.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    57.0f, 94.0f,
-                                    66.0f, 102.0f},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 13.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    3.0f, 1.0f, 2.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    78.0f, 106.0f, 134.0f,
-                                    44.0f, 16.0f, -12.0f,
-                                    80.0f, 84.0f, 88.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {2, 2}),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 13.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    3.0f, 1.0f, 2.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    15.0f, 38.0f, 70.0f, 66.0f,
-                                    33.0f, 78.0f, 134.0f, 103.0f,
-                                    40.0f, 80.0f, 88.0f, 58.0f,
-                                    30.0f, 56.0f, 72.0f, 34.0f},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2}),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {1, 2, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 3.0f, 5.0f, 7.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f,
-                                    // channel 2
-                                    -1.0f, 3.0f, -5.0f, 7.0f,
-                                    7.0f, -5.0f, 3.0f, -1.0f,
-                                    -2.0f, 4.0f, -6.0f, 8.0f,
-                                    8.0f, -6.0f, 4.0f, -2.0f},
-                          std::vector<T>{
-                                    // channel 1
-                                    5.0f, 3.0f, 5.0f,
-                                    1.0f, 3.0f, 1.0f,
-                                    4.0f, 2.0f, 4.0f,
-                                    // channel 2
-                                    -5.0f, 3.0f, 5.0f,
-                                    1.0f, -3.0f, 1.0f,
-                                    4.0f, 2.0f, -4.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    142.0f, 102.0f,
-                                    94.0f, 160.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {2, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f},
-                          std::vector<T>{
-                                    // channel 1
-                                    5.0f, 3.0f, 5.0f,
-                                    1.0f, 3.0f, 1.0f,
-                                    4.0f, 2.0f, 4.0f,
-                                    // channel 2
-                                   -5.0f, 3.0f, 5.0f,
-                                    1.0f, -3.0f, 1.0f,
-                                    4.0f, 2.0f, -4.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // channel 1
-                                    104.0f, 140.0f,
-                                    145.0f, 109.0f,
-                                    // channel 2
-                                    16.0f, 28.0f,
-                                    19.0f, 7.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {2, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {2, 18, 2, 2},
-                          PartialShape {2, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // batch 1
-                                    1.0f, 3.0f, 2.0f, 1.0f,
-                                    1.0f, 3.0f, 3.0f, 1.0f,
-                                    2.0f, 1.0f, 1.0f, 3.0f,
-                                    3.0f, 2.0f, 3.0f, 3.0f,
-                                    // batch 2
-                                    -1.0f, 3.0f, 2.0f, -1.0f,
-                                    1.0f, 3.0f, -3.0f, 1.0f,
-                                    -2.0f, -1.0f, 1.0f, 3.0f,
-                                    3.0f, 2.0f, 3.0f, -3.0f},
-                          std::vector<T>{
-                                   -5.0f, 3.0f, 5.0f,
-                                    1.0f, -3.0f, 1.0f,
-                                    4.0f, 2.0f, -4.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // batch 1
-                                    15.0f, -15.0f,
-                                    23.0f, 2.0f,
-                                    // batch 2
-                                    -1.0f, -15.0f,
-                                    -5.0f, 6.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                     // channel 2
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    // channel 3
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    // channel 4
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // filter 1 channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // filter 2 channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // filter 2 channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // channel 1
-                                    356.0f, 392.0f,
-                                    464.0f, 500.0f,
-                                    // channel 2
-                                    -1004.0f, -1040.0f,
-                                    -1112.0f, -1148.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2),
-        DeformableConvolutionParams(PartialShape {1, 8, 3, 3},
-                          PartialShape {4, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 4, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    // channel 2
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    // channel 3
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    // channel 4
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f,
-                                    // channel 5
-                                    37.0f, 38.0f, 39.0f,
-                                    40.0f, 41.0f, 42.0f,
-                                    43.0f, 44.0f, 45.0f,
-                                    // channel 6
-                                    46.0f, 47.0f, 48.0f,
-                                    49.0f, 50.0f, 51.0f,
-                                    52.0f, 53.0f, 54.0f,
-                                    // channel 7
-                                    55.0f, 56.0f, 57.0f,
-                                    58.0f, 59.0f, 60.0f,
-                                    61.0f, 62.0f, 63.0f,
-                                    // channel 8
-                                    64.0f, 65.0f, 66.0f,
-                                    67.0f, 68.0f, 69.0f,
-                                    70.0f, 71.0f, 72.0f},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // filter 1 channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // filter 2 channel 1
-                                    9.0f, 10.0f,
-                                    11.0f, 12.0f,
-                                    // filter 2 channel 2
-                                    13.0f, 14.0f,
-                                    15.0f, 16.0f,
-                                    // filter 3 channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // filter 3 channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f,
-                                    // filter 4 channel 1
-                                    -9.0f, -10.0f,
-                                    -11.0f, -12.0f,
-                                    // filter 4 channel 2
-                                    -13.0f, -14.0f,
-                                    -15.0f, -16.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // channel 1
-                                    356.0f, 392.0f,
-                                    464.0f, 500.0f,
-                                    // channel 2
-                                    2636.0f, 2736.0f,
-                                    2936.0f, 3036.0f,
-                                    // channel 3
-                                    -1652.0f, -1688.0f,
-                                    -1760.0f, -1796.0f,
-                                    // channel 4
-                                    -6236.0f, -6336.0f,
-                                    -6536.0f, -6636.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          4),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {1, 2, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f,
-                                    -1.0f, -2.0f,
-                                    // channel 2
-                                    3.0f, 4.0f,
-                                    -3.0f, -4.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    -40.0f, -40.0f, -40.0f,
-                                    -40.0f, -40.0f, -40.0f,
-                                    -40.0f, -40.0f, -40.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    356.0f, 392.0f,
-                                    464.0f, 500.0f,
-                                    -1004.0f, -1040.0f,
-                                    -1112.0f, -1148.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          2),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    -1.0f, -2.0f},
-                          std::vector<T>{
-                                    // window 1 (Y=0, X=0) -> Y coordinate
-                                    1.0f, 1.0f, 1.0f, // out1 .. out 3
-                                    1.0f, 1.0f, 1.0f, // out4 .. out 6
-                                    1.0f, 1.0f, 1.0f, // out7 .. out 9
-                                    // window 1 (Y=0, X=0) -> X coordinate
-                                    1.0f, 1.0f, 1.0f, // out1 .. out 3
-                                    1.0f, 1.0f, 1.0f, // out4 .. out 6
-                                    1.0f, 1.0f, 1.0f, // out7 .. out 9
-                                    // window 2
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    // window 2
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    // window 3
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    // window 3
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    // window 4
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    // window 4
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f},
-                          std::vector<T>{
-                                    -12.0f, -12.0f, -4.0f,
-                                    -12.0f, -12.0f, -4.0f,
-                                    44.0f, 47.0f, 16.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offsets_1"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 7.0f, 7.0f,
-                                    7.0f, 6.0f, 3.0f, 1.0f,
-                                    4.0f, 4.0f, 2.0f, 8.0f,
-                                    1.0f, 1.0f, 1.0f, 2.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    0.0f, 1.0f, 0.0f,
-                                    3.0f, 2.0f, 1.0f},
-                          std::vector<T>{
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f},
-                          std::vector<T>{
-                                    56.0f, 39.0f, 44.0f, 18.0f,
-                                    38.0f, 56.0f, 65.0f, 0.0f,
-                                    19.0f, 38.0f, 20.0f, 20.0f,
-                                    6.0f, 19.0f, 33.0f, 0.0f},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f, 9.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, 0.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    3.0f, 2.0f, 1.0f},
-                          std::vector<T>{
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 0.0f},
-                          std::vector<T>{
-                                    57.0f, 40.0f,
-                                    38.0f, 102.0f},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offsets_stride"),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 13.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    3.0f, 1.0f, 2.0f},
-                          std::vector<T>{
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f,
-                                    1.0f, 2.0f, 0.0f,
-                                    0.0f, 2.0f, 0.0f,
-                                    1.0f, 0.0f, 1.0f},
-                          std::vector<T>{
-                                    16.0f, -2.0f, 134.0f,
-                                    44.0f, -4.0f, -12.0f,
-                                    10.0f, 84.0f, -4.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {2, 2},
-                          1,
-                          1,
-                          "integral_offset_dialation"),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 13.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    3.0f, 1.0f, 2.0f},
-                          std::vector<T>{
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f,
-                                    1.0f, 0.0f, 1.0f, 0.0f,
-                                    1.0f, 0.0f, 0.0f, 2.0f},
-                          std::vector<T>{
-                                    15.0f, 38.0f, 2.0f, 66.0f,
-                                    26.0f, 78.0f, 134.0f, 16.0f,
-                                    23.0f, 80.0f, -4.0f, 58.0f,
-                                    13.0f, 56.0f, 72.0f, -4.0f},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          1,
-                          1,
-                          "integral_offset_padding_stride_dialation"),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {1, 2, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 3.0f, 5.0f, 7.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f,
-                                    // channel 2
-                                    -1.0f, 3.0f, -5.0f, 7.0f,
-                                    7.0f, -5.0f, 3.0f, -1.0f,
-                                    -2.0f, 4.0f, -6.0f, 8.0f,
-                                    8.0f, -6.0f, 4.0f, -2.0f},
-                          std::vector<T>{
-                                    // channel 1
-                                    5.0f, 3.0f, 5.0f,
-                                    1.0f, 3.0f, 1.0f,
-                                    4.0f, 2.0f, 4.0f,
-                                    // channel 2
-                                    -5.0f, 3.0f, 5.0f,
-                                    1.0f, -3.0f, 1.0f,
-                                    4.0f, 2.0f, -4.0f},
-                          std::vector<T>{
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f,
-                                    1.0f, 1.0f,
-                                    0.0f, 2.0f},
-                          std::vector<T>{
-                                    160.0f, 32.0f,
-                                    94.0f, 20.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offset_input_channels"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {2, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f},
-                          std::vector<T>{
-                                    // filter 1
-                                    1.0f, 2.0f,
-                                    -1.0f, -2.0f,
-                                    // filter 2
-                                    3.0f, 4.0f,
-                                    -3.0f, -4.0f},
-                          std::vector<T>{
-                                    //channel 1: Y offsets
-                                    1.0f, 1.0f, 1.0f, // out1 .. out 3
-                                    1.0f, 1.0f, 1.0f, // out4 .. out 6
-                                    1.0f, 1.0f, 1.0f, // out7 .. out 9
-                                    //channel 1: X offsets
-                                    1.0f, 1.0f, 1.0f, // out1 .. out 3
-                                    1.0f, 1.0f, 1.0f, // out4 .. out 6
-                                    1.0f, 1.0f, 1.0f, // out7 .. out 9
-                                    //channel 2: Y offsets
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //channel 2: X offsets
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //channel 3: Y offsets
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //channel 3: X offsets
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //channel 4: Y offsets
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //channel 4: X offsets
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f},
-                          std::vector<T>{
-                                    // output 1
-                                    -12.0f, -12.0f, -4.0f,
-                                    -12.0f, -12.0f, -4.0f,
-                                    44.0f, 47.0f, 16.0f,
-                                    // output 2
-                                    -28.0f, -28.0f, -12.0f,
-                                    -28.0f, -28.0f, -12.0f,
-                                    102.0f, 109.0f, 48.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offset_output_channels"),
-        DeformableConvolutionParams(PartialShape {2, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {2, 8, 3, 3},
-                          PartialShape {2, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    //batch 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    //batch 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    -1.0f, -2.0f},
-                          std::vector<T>{
-                                    // batch1
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    // batch2
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f},
-                          std::vector<T>{
-                                    // batch 1
-                                    -12.0f, -12.0f, -4.0f,
-                                    -12.0f, -12.0f, -4.0f,
-                                    44.0f, 47.0f, 16.0f,
-                                    // batch 2
-                                    -12.0f, -12.0f, -12.0f,
-                                    -12.0f, -12.0f, -12.0f,
-                                    -12.0f, -12.0f, -12.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offset_batch"),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                     // channel 2
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    // channel 3
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    // channel 4
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                     // filter 1 channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                     // filter 2 channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // filter 2 channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    // window 1 (F_Y=0, F_X=0) -> I_Y coordinate
-                                    1.0f, 0.0f, 2.0f, 1.0f, // out1 .. out 4
-                                    // window 1 (F_Y=0, F_X=0) -> I_X coordinate
-                                    0.0f, 1.0f, 1.0f, 2.0f, // out1 .. out 4
-                                    // window 2 (F_Y=0, F_X=1) -> I_Y coordinate
-                                    1.0f, 1.0f, 1.0f, 1.0f, // out1 .. out 4
-                                    // window 2 (F_Y=0, F_X=1) -> I_X coordinate
-                                    1.0f, 1.0f, 1.0f, 1.0f, // out1 .. out 4
-                                    // window 3 (F_Y=1, F_X=0) -> I_Y coordinate
-                                    2.0f, 2.0f, 2.0f, 2.0f, // out1 .. out 4
-                                    // window 3 (F_Y=1, F_X=0) -> I_X coordinate
-                                    2.0f, 2.0f, 2.0f, 2.0f, // out1 .. out 4
-                                    // window 4 (F_Y=1, F_X=1) -> I_Y coordinate
-                                    2.0f, 2.0f, 2.0f, 2.0f, // out1 .. out 4
-                                    // window 4 (F_Y=1, F_X=1) -> I_X coordinate
-                                    2.0f, 2.0f, 2.0f, 2.0f}, // out1 .. out 4
-                          std::vector<T>{
-                                    // channel 1
-                                    171.0f, 63.0f,
-                                    126.0f, 0.0f,
-                                    // channel 2
-                                    -423.0f, -171.0f,
-                                    -270.0f, 0.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          1,
-                          "integral_offset_groups_basic"),
-        DeformableConvolutionParams(PartialShape {1, 8, 3, 3},
-                          PartialShape {4, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 4, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                     // channel 2
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    // channel 3
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    // channel 4
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f,
-                                     // channel 5
-                                    37.0f, 38.0f, 39.0f,
-                                    40.0f, 41.0f, 42.0f,
-                                    43.0f, 44.0f, 45.0f,
-                                     // channel 6
-                                    46.0f, 47.0f, 48.0f,
-                                    49.0f, 50.0f, 51.0f,
-                                    52.0f, 53.0f, 54.0f,
-                                     // channel 7
-                                    55.0f, 56.0f, 57.0f,
-                                    58.0f, 59.0f, 60.0f,
-                                    61.0f, 62.0f, 63.0f,
-                                     // channel 8
-                                    64.0f, 65.0f, 66.0f,
-                                    67.0f, 68.0f, 69.0f,
-                                    70.0f, 71.0f, 72.0f},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // filter 1 channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // filter 2 channel 1
-                                    9.0f, 10.0f,
-                                    11.0f, 12.0f,
-                                    // filter 2 channel 2
-                                    13.0f, 14.0f,
-                                    15.0f, 16.0f,
-                                    // filter 3 channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // filter 3 channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f,
-                                    // filter 4 channel 1
-                                    -9.0f, -10.0f,
-                                    -11.0f, -12.0f,
-                                    // filter 4 channel 2
-                                    -13.0f, -14.0f,
-                                    -15.0f, -16.0f},
-                          std::vector<T>{
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f},
-                          std::vector<T>{
-                                    // channel 1
-                                    500.0f, 234.0f,
-                                    219.0f, 99.0f,
-                                    // channel 2
-                                    3036.0f, 1482.0f,
-                                    1463.0f, 711.0f,
-                                    // channel 3
-                                    -1796.0f, -810.0f,
-                                    -723.0f, -315.0f,
-                                    // channel 4
-                                    -6636.0f, -3210.0f,
-                                    -3119.0f, -1503.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          4,
-                          1,
-                          "integral_offset_groups_complex"),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f2: channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    // defgroup 1
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //  defgroup 2
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f},
-                          std::vector<T>{
-                                    // output 1
-                                    610.0f, 646.0f, 612.0f,
-                                    754.0f, 790.0f, 732.0f,
-                                    768.0f, 797.0f, 792.0f,
-                                    // output 2
-                                    -610.0f, -646.0f, -612.0f,
-                                    -754.0f, -790.0f, -732.0f,
-                                    -768.0f, -797.0f, -792.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          2,
-                          "integral_offset_deforgroup_basic"),
-        DeformableConvolutionParams(PartialShape {1, 4, 4, 4},
-                          PartialShape {2, 4, 2, 2},
-                          PartialShape {1, 32, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f,
-                                    // channel 3
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 4
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f1: channel 3
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 4
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f2: channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f,
-                                    // f2: channel 3
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 4
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    // defgroup 1
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //  defgroup 2
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    // defgroup 3
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //  defgroup 4
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f},
-                          std::vector<T>{
-                                    // output 1
-                                    1220.0f, 1292.0f, 1224.0f,
-                                    1508.0f, 1580.0f, 1464.0f,
-                                    1536.0f, 1594.0f, 1584.0f,
-                                    // output 2
-                                    -1220.0f, -1292.0f, -1224.0f,
-                                    -1508.0f, -1580.0f, -1464.0f,
-                                    -1536.0f, -1594.0f, -1584.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          4,
-                          "integral_offset_deforgroup_complex1"),
-        DeformableConvolutionParams(PartialShape {1, 4, 4, 4},
-                          PartialShape {2, 4, 2, 2},
-                          PartialShape {1, 16, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f,
-                                    // channel 3
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 4
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f1: channel 3
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 4
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f2: channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f,
-                                    // f2: channel 3
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 4
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    // defgroup 1
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    //  defgroup 2
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f},
-                          std::vector<T>{
-                                    // output 1
-                                    1300.0f, 1372.0f, 992.0f,
-                                    1588.0f, 1660.0f, 1200.0f,
-                                    1228.0f, 1278.0f, 1096.0f,
-                                    // output 2
-                                    -1300.0f, -1372.0f, -992.0f,
-                                    -1588.0f, -1660.0f, -1200.0f,
-                                    -1228.0f, -1278.0f, -1096.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          2,
-                          "integral_offset_deforgroup_complex2"),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    // defgroup 1
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    1.0f, 1.0f, 1.0f, 1.0f,
-                                    // defgroup 2
-                                    0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f},
-                          std::vector<T>{
-                                    500.0f, 234.0f,
-                                    219.0f, 99.0f,
-                                    -1004.0f, -1040.0f,
-                                    -1112.0f, -1148.0f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          2,
-                          "integral_offset_groups_and_deforgroups"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    -1.0f, -2.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    -11.999998f, -11.999999f, -4.000000f,
-                                    -10.799999f, -10.800001f, -3.600004f,
-                                    44.300000f, 47.100000f, 16.000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "real_offset_default"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 7.0f, 7.0f,
-                                    7.0f, 6.0f, 3.0f, 1.0f,
-                                    4.0f, 4.0f, 2.0f, 8.0f,
-                                    1.0f, 1.0f, 1.0f, 2.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    0.0f, 1.0f, 0.0f,
-                                    3.0f, 2.0f, 1.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    54.870006f, 61.630001f, 43.230003f, 28.600002f,
-                                    35.590000f, 25.819999f, 20.880001f, 7.700000f,
-                                    19.089998f, 31.719999f, 19.250000f, 7.399999f,
-                                    6.299999f, 9.199999f, 5.099999f, 2.000000f},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          1,
-                          1,
-                          "real_offset_padding"),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f, 9.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, 0.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    1.0f, 1.0f, 1.0f,
-                                    3.0f, 2.0f, 1.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    61.229999f, 29.509998f,
-                                    39.640003f, 22.640003f},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "real_offset_stride"),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 13.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f, 14.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f, -1.0f, -3.0f, -5.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f, 0.0f, -2.0f, -4.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    1.0f, 1.0f, 0.0f,
-                                    3.0f, 1.0f, 2.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    15.260000f, 24.119997f, 6.439994f, -3.940005f,
-                                    26.440002f, 20.319999f, -0.500001f, -11.720002f,
-                                    23.500003f, 14.040000f, -1.279998f, -3.860000f,
-                                    12.500000f, -2.599999f, -5.299999f, -3.099999f},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          1,
-                          1,
-                          "real_offset_padding_stride_dialation"),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {1, 2, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 3.0f, 5.0f, 7.0f,
-                                    7.0f, 5.0f, 3.0f, 1.0f,
-                                    2.0f, 4.0f, 6.0f, 8.0f,
-                                    8.0f, 6.0f, 4.0f, 2.0f,
-                                    // channel 2
-                                    -1.0f, 3.0f, -5.0f, 7.0f,
-                                    7.0f, -5.0f, 3.0f, -1.0f,
-                                    -2.0f, 4.0f, -6.0f, 8.0f,
-                                    8.0f, -6.0f, 4.0f, -2.0f},
-                          std::vector<T>{
-                                    // channel 1
-                                    5.0f, 3.0f, 5.0f,
-                                    1.0f, 3.0f, 1.0f,
-                                    4.0f, 2.0f, 4.0f,
-                                    // channel 2
-                                    -5.0f, 3.0f, 5.0f,
-                                    1.0f, -3.0f, 1.0f,
-                                    4.0f, 2.0f, -4.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    148.000000f, 43.259998f,
-                                    91.279998f, 111.199996f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "real_offset_input_channels"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {2, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f},
-                          std::vector<T>{
-                                    // filter 1
-                                     1.0f, 2.0f,
-                                    -1.0f, -2.0f,
-                                    // filter 2
-                                     3.0f, 4.0f,
-                                    -3.0f, -4.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    // output 1
-                                    -12.000000f, -12.000000f, -4.000000f,
-                                    -10.799999f, -10.799995f, -3.600000f,
-                                    44.299999f, 47.099998f, 16.000000f,
-                                    // output 2
-                                    -28.000000f, -28.000000f, -12.000000f,
-                                    -25.200000f, -25.199993f, -10.800003f,
-                                    102.699996f, 109.300003f, 48.000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "real_offset_output_channels"),
-        DeformableConvolutionParams(PartialShape {2, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {2, 8, 3, 3},
-                          PartialShape {2, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    //batch 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    //batch 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    -1.0f, -2.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    // batch 1
-                                    -12.000000f, -12.000000f, -4.000000f,
-                                    -10.799999f, -10.799995f, -3.600000f,
-                                    44.299999f, 47.099998f, 16.000000f,
-                                    // batch 2
-                                    -12.000000f, -12.000000f, -4.000000f,
-                                    -10.799999f, -10.799995f, -3.600000f,
-                                    92.300003f, 95.099998f, 32.000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "real_offset_batch"),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    // channel 2
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    // channel 3
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    // channel 4
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // filter 1 channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // filter 2 channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // filter 2 channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    // channel 1
-                                    505.800020f, 235.800000f,
-                                    219.600000f, 99.000000f,
-                                    // channel 2
-                                    -1153.800000f, -523.800000f,
-                                    -471.600000f, -207.0000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          1,
-                          "real_offset_group_basic"),
-        DeformableConvolutionParams(PartialShape {1, 8, 3, 3},
-                          PartialShape {4, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 4, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    // channel 2
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    // channel 3
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    // channel 4
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f,
-                                    // channel 5
-                                    37.0f, 38.0f, 39.0f,
-                                    40.0f, 41.0f, 42.0f,
-                                    43.0f, 44.0f, 45.0f,
-                                    // channel 6
-                                    46.0f, 47.0f, 48.0f,
-                                    49.0f, 50.0f, 51.0f,
-                                    52.0f, 53.0f, 54.0f,
-                                    // channel 7
-                                    55.0f, 56.0f, 57.0f,
-                                    58.0f, 59.0f, 60.0f,
-                                    61.0f, 62.0f, 63.0f,
-                                    // channel 8
-                                    64.0f, 65.0f, 66.0f,
-                                    67.0f, 68.0f, 69.0f,
-                                    70.0f, 71.0f, 72.0f},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // filter 1 channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // filter 2 channel 1
-                                    9.0f, 10.0f,
-                                    11.0f, 12.0f,
-                                    // filter 2 channel 2
-                                    13.0f, 14.0f,
-                                    15.0f, 16.0f,
-                                    // filter 3 channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // filter 3 channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f,
-                                    // filter 4 channel 1
-                                    -9.0f, -10.0f,
-                                    -11.0f, -12.0f,
-                                    // filter 4 channel 2
-                                    -13.0f, -14.0f,
-                                    -15.0f, -16.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    // channel 1
-                                    505.800020f, 235.800000f,
-                                    219.600000f, 99.000000f,
-                                    // channel 2
-                                    3054.600000f, 1488.600000f,
-                                    1465.200100f, 711.000000f,
-                                    // channel 3
-                                    -1801.799900f, -811.80000f,
-                                    -723.600000f, -315.000000f,
-                                    // channel 4
-                                    -6654.600000f, -3216.600000f,
-                                    -3121.200000f, -1503.000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          4,
-                          1,
-                          "real_offset_groups_complex"),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f2: channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    // output 1
-                                    758.000000f, 792.000000f, 366.399993f,
-                                    893.200012f, 927.200012f, 426.399993f,
-                                    381.399993f, 394.600006f, 176.000000f,
-                                    // output 2
-                                    -758.000000f, -792.000000f, -366.399993f,
-                                    -893.200012f, -927.200012f, -426.399993f,
-                                    -381.399993f, -394.600006f, -176.000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          2,
-                          "real_offset_deforgroup_basic"),
-        DeformableConvolutionParams(PartialShape {1, 4, 4, 4},
-                          PartialShape {2, 4, 2, 2},
-                          PartialShape {1, 32, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f,
-                                    // channel 3
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 4
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f1: channel 3
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 4
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f2: channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f,
-                                    // f2: channel 3
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 4
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    // output 1
-                                    1516.000000f, 1583.999877f, 732.799987f,
-                                    1786.400146f, 1854.400024f, 852.799987f,
-                                    762.799987f, 789.200012f, 352.000000f,
-                                    // output 2
-                                    -1516.000000f, -1583.999877f, -732.799987f,
-                                    -1786.400146f, -1854.400024f, -852.799987f,
-                                    -762.799987f, -789.200012f, -352.000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          4,
-                          "real_offset_deforgroup_complex1"),
-        DeformableConvolutionParams(PartialShape {1, 4, 4, 4},
-                          PartialShape {2, 4, 2, 2},
-                          PartialShape {1, 16, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 2
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f,
-                                    // channel 3
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f,
-                                    // channel 4
-                                    17.0f, 18.0f, 19.0f, 20.0f,
-                                    21.0f, 22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f, 28.0f,
-                                    29.0f, 30.0f, 31.0f, 32.0f},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 2
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f1: channel 3
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    // f1: channel 4
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    // f2: channel 1
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 2
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f,
-                                    // f2: channel 3
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    // f2: channel 4
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    // output 1
-                                    1516.000000f, 1583.999877f, 732.799987f,
-                                    1786.400146f, 1854.400024f, 852.799987f,
-                                    762.799987f, 789.200012f, 352.000000f,
-                                    // output 2
-                                    -1516.000000f, -1583.999877f, -732.799987f,
-                                    -1786.400146f, -1854.400024f, -852.799987f,
-                                    -762.799987f, -789.200012f, -352.000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          2,
-                          "real_offset_deforgroup_complex2"),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    505.800020f, 235.800000f,
-                                    219.600000f, 99.000000f,
-                                    -1153.800000f, -523.800000f,
-                                    -471.600000f, -207.000000f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          2,
-                          "real_offset_groups_and_deforgroups"),
+    std::vector<DeformableConvolutionParams> deformableConvolutionParams{
+        // --------------------- 2D DeformableConvolution ------------------------------------------
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f},
+            std::vector<T>{1.0f, 2.0f, -1.0f, -2.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{-12.0f, -12.0f, -12.0f, -12.0f, -12.0f, -12.0f, -12.0f, -12.0f, -12.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1.0f, 3.0f, 5.0f, 7.0f, 5.0f, 3.0f, 1.0f, 3.0f, 5.0f},
+            std::vector<T>{1.0f, 2.0f, 0.0f, 1.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{1.0f,
+                           3.0f,
+                           5.0f,
+                           0.0f,
+                           9.0f,
+                           12.0f,
+                           16.0f,
+                           5.0f,
+                           15.0f,
+                           20.0f,
+                           16.0f,
+                           3.0f,
+                           2.0f,
+                           7.0f,
+                           13.0f,
+                           5.0f},
+            {1, 1},
+            {1, 1},
+            {1, 1},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f, 3.0f,  5.0f, 7.0f, 9.0f, 7.0f, 5.0f, 3.0f, 1.0f, 0.0f, 2.0f, 4.0f, 6.0f,
+                           8.0f, 10.0f, 8.0f, 6.0f, 4.0f, 2.0f, 0.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 1.0f, 1.0f, 1.0f, 3.0f, 2.0f, 1.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{57.0f, 94.0f, 66.0f, 102.0f},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1.0f,  3.0f,  5.0f,  7.0f, 9.0f, 11.0f, 13.0f, 7.0f,  5.0f,  3.0f, 1.0f, -1.0f, -3.0f,
+                           -5.0f, 2.0f,  4.0f,  6.0f, 8.0f, 10.0f, 12.0f, 14.0f, 8.0f,  6.0f, 4.0f, 2.0f,  0.0f,
+                           -2.0f, -4.0f, 2.0f,  4.0f, 6.0f, 8.0f,  10.0f, 12.0f, 14.0f, 7.0f, 5.0f, 3.0f,  1.0f,
+                           -1.0f, -3.0f, -5.0f, 8.0f, 6.0f, 4.0f,  2.0f,  0.0f,  -2.0f, -4.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 1.0f, 1.0f, 0.0f, 3.0f, 1.0f, 2.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{78.0f, 106.0f, 134.0f, 44.0f, 16.0f, -12.0f, 80.0f, 84.0f, 88.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {2, 2}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1.0f,  3.0f,  5.0f,  7.0f, 9.0f, 11.0f, 13.0f, 7.0f,  5.0f,  3.0f, 1.0f, -1.0f, -3.0f,
+                           -5.0f, 2.0f,  4.0f,  6.0f, 8.0f, 10.0f, 12.0f, 14.0f, 8.0f,  6.0f, 4.0f, 2.0f,  0.0f,
+                           -2.0f, -4.0f, 2.0f,  4.0f, 6.0f, 8.0f,  10.0f, 12.0f, 14.0f, 7.0f, 5.0f, 3.0f,  1.0f,
+                           -1.0f, -3.0f, -5.0f, 8.0f, 6.0f, 4.0f,  2.0f,  0.0f,  -2.0f, -4.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 1.0f, 1.0f, 0.0f, 3.0f, 1.0f, 2.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{15.0f,
+                           38.0f,
+                           70.0f,
+                           66.0f,
+                           33.0f,
+                           78.0f,
+                           134.0f,
+                           103.0f,
+                           40.0f,
+                           80.0f,
+                           88.0f,
+                           58.0f,
+                           30.0f,
+                           56.0f,
+                           72.0f,
+                           34.0f},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2}),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{1, 2, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1.0f,
+                           3.0f,
+                           5.0f,
+                           7.0f,
+                           7.0f,
+                           5.0f,
+                           3.0f,
+                           1.0f,
+                           2.0f,
+                           4.0f,
+                           6.0f,
+                           8.0f,
+                           8.0f,
+                           6.0f,
+                           4.0f,
+                           2.0f,
+                           // channel 2
+                           -1.0f,
+                           3.0f,
+                           -5.0f,
+                           7.0f,
+                           7.0f,
+                           -5.0f,
+                           3.0f,
+                           -1.0f,
+                           -2.0f,
+                           4.0f,
+                           -6.0f,
+                           8.0f,
+                           8.0f,
+                           -6.0f,
+                           4.0f,
+                           -2.0f},
+            std::vector<T>{// channel 1
+                           5.0f,
+                           3.0f,
+                           5.0f,
+                           1.0f,
+                           3.0f,
+                           1.0f,
+                           4.0f,
+                           2.0f,
+                           4.0f,
+                           // channel 2
+                           -5.0f,
+                           3.0f,
+                           5.0f,
+                           1.0f,
+                           -3.0f,
+                           1.0f,
+                           4.0f,
+                           2.0f,
+                           -4.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{142.0f, 102.0f, 94.0f, 160.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{2, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            IN_ET,
+            std::vector<
+                T>{1.0f, 3.0f, 5.0f, 7.0f, 7.0f, 5.0f, 3.0f, 1.0f, 2.0f, 4.0f, 6.0f, 8.0f, 8.0f, 6.0f, 4.0f, 2.0f},
+            std::vector<T>{// channel 1
+                           5.0f,
+                           3.0f,
+                           5.0f,
+                           1.0f,
+                           3.0f,
+                           1.0f,
+                           4.0f,
+                           2.0f,
+                           4.0f,
+                           // channel 2
+                           -5.0f,
+                           3.0f,
+                           5.0f,
+                           1.0f,
+                           -3.0f,
+                           1.0f,
+                           4.0f,
+                           2.0f,
+                           -4.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{// channel 1
+                           104.0f,
+                           140.0f,
+                           145.0f,
+                           109.0f,
+                           // channel 2
+                           16.0f,
+                           28.0f,
+                           19.0f,
+                           7.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{2, 1, 4, 4},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{2, 18, 2, 2},
+            PartialShape{2, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{// batch 1
+                           1.0f,
+                           3.0f,
+                           2.0f,
+                           1.0f,
+                           1.0f,
+                           3.0f,
+                           3.0f,
+                           1.0f,
+                           2.0f,
+                           1.0f,
+                           1.0f,
+                           3.0f,
+                           3.0f,
+                           2.0f,
+                           3.0f,
+                           3.0f,
+                           // batch 2
+                           -1.0f,
+                           3.0f,
+                           2.0f,
+                           -1.0f,
+                           1.0f,
+                           3.0f,
+                           -3.0f,
+                           1.0f,
+                           -2.0f,
+                           -1.0f,
+                           1.0f,
+                           3.0f,
+                           3.0f,
+                           2.0f,
+                           3.0f,
+                           -3.0f},
+            std::vector<T>{-5.0f, 3.0f, 5.0f, 1.0f, -3.0f, 1.0f, 4.0f, 2.0f, -4.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{// batch 1
+                           15.0f,
+                           -15.0f,
+                           23.0f,
+                           2.0f,
+                           // batch 2
+                           -1.0f,
+                           -15.0f,
+                           -5.0f,
+                           6.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(PartialShape{1, 4, 3, 3},
+                                    PartialShape{2, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 2, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   // channel 2
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   17.0f,
+                                                   18.0f,
+                                                   // channel 3
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   // channel 4
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f,
+                                                   33.0f,
+                                                   34.0f,
+                                                   35.0f,
+                                                   36.0f},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // filter 1 channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // filter 2 channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // filter 2 channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f},
+                                    std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+                                    std::vector<T>{// channel 1
+                                                   356.0f,
+                                                   392.0f,
+                                                   464.0f,
+                                                   500.0f,
+                                                   // channel 2
+                                                   -1004.0f,
+                                                   -1040.0f,
+                                                   -1112.0f,
+                                                   -1148.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    2),
+        DeformableConvolutionParams(PartialShape{1, 8, 3, 3},
+                                    PartialShape{4, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 4, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   // channel 2
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   17.0f,
+                                                   18.0f,
+                                                   // channel 3
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   // channel 4
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f,
+                                                   33.0f,
+                                                   34.0f,
+                                                   35.0f,
+                                                   36.0f,
+                                                   // channel 5
+                                                   37.0f,
+                                                   38.0f,
+                                                   39.0f,
+                                                   40.0f,
+                                                   41.0f,
+                                                   42.0f,
+                                                   43.0f,
+                                                   44.0f,
+                                                   45.0f,
+                                                   // channel 6
+                                                   46.0f,
+                                                   47.0f,
+                                                   48.0f,
+                                                   49.0f,
+                                                   50.0f,
+                                                   51.0f,
+                                                   52.0f,
+                                                   53.0f,
+                                                   54.0f,
+                                                   // channel 7
+                                                   55.0f,
+                                                   56.0f,
+                                                   57.0f,
+                                                   58.0f,
+                                                   59.0f,
+                                                   60.0f,
+                                                   61.0f,
+                                                   62.0f,
+                                                   63.0f,
+                                                   // channel 8
+                                                   64.0f,
+                                                   65.0f,
+                                                   66.0f,
+                                                   67.0f,
+                                                   68.0f,
+                                                   69.0f,
+                                                   70.0f,
+                                                   71.0f,
+                                                   72.0f},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // filter 1 channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // filter 2 channel 1
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   // filter 2 channel 2
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // filter 3 channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // filter 3 channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f,
+                                                   // filter 4 channel 1
+                                                   -9.0f,
+                                                   -10.0f,
+                                                   -11.0f,
+                                                   -12.0f,
+                                                   // filter 4 channel 2
+                                                   -13.0f,
+                                                   -14.0f,
+                                                   -15.0f,
+                                                   -16.0f},
+                                    std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+                                    std::vector<T>{// channel 1
+                                                   356.0f,
+                                                   392.0f,
+                                                   464.0f,
+                                                   500.0f,
+                                                   // channel 2
+                                                   2636.0f,
+                                                   2736.0f,
+                                                   2936.0f,
+                                                   3036.0f,
+                                                   // channel 3
+                                                   -1652.0f,
+                                                   -1688.0f,
+                                                   -1760.0f,
+                                                   -1796.0f,
+                                                   // channel 4
+                                                   -6236.0f,
+                                                   -6336.0f,
+                                                   -6536.0f,
+                                                   -6636.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    4),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{1, 2, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           // channel 2
+                           17.0f,
+                           18.0f,
+                           19.0f,
+                           20.0f,
+                           21.0f,
+                           22.0f,
+                           23.0f,
+                           24.0f,
+                           25.0f,
+                           26.0f,
+                           27.0f,
+                           28.0f,
+                           29.0f,
+                           30.0f,
+                           31.0f,
+                           32.0f},
+            std::vector<T>{// channel 1
+                           1.0f,
+                           2.0f,
+                           -1.0f,
+                           -2.0f,
+                           // channel 2
+                           3.0f,
+                           4.0f,
+                           -3.0f,
+                           -4.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{-40.0f, -40.0f, -40.0f, -40.0f, -40.0f, -40.0f, -40.0f, -40.0f, -40.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 4, 3, 3},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f,  2.0f,  3.0f,  4.0f,  5.0f,  6.0f,  7.0f,  8.0f,  9.0f,  10.0f, 11.0f, 12.0f,
+                           13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f,
+                           25.0f, 26.0f, 27.0f, 28.0f, 29.0f, 30.0f, 31.0f, 32.0f, 33.0f, 34.0f, 35.0f, 36.0f},
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{356.0f, 392.0f, 464.0f, 500.0f, -1004.0f, -1040.0f, -1112.0f, -1148.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            2,
+            2),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{1, 1, 2, 2},
+                                    PartialShape{1, 8, 3, 3},
+                                    PartialShape{1, 1, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f},
+                                    std::vector<T>{1.0f, 2.0f, -1.0f, -2.0f},
+                                    std::vector<T>{// window 1 (Y=0, X=0) -> Y coordinate
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out1 .. out 3
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out4 .. out 6
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out7 .. out 9
+                                                   // window 1 (Y=0, X=0) -> X coordinate
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out1 .. out 3
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out4 .. out 6
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out7 .. out 9
+                                                   // window 2
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // window 2
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // window 3
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // window 3
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // window 4
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // window 4
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f},
+                                    std::vector<T>{-12.0f, -12.0f, -4.0f, -12.0f, -12.0f, -4.0f, 44.0f, 47.0f, 16.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offsets_1"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<
+                T>{1.0f, 3.0f, 7.0f, 7.0f, 7.0f, 6.0f, 3.0f, 1.0f, 4.0f, 4.0f, 2.0f, 8.0f, 1.0f, 1.0f, 1.0f, 2.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 0.0f, 1.0f, 0.0f, 3.0f, 2.0f, 1.0f},
+            std::vector<T>{
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f},
+            std::vector<T>{56.0f,
+                           39.0f,
+                           44.0f,
+                           18.0f,
+                           38.0f,
+                           56.0f,
+                           65.0f,
+                           0.0f,
+                           19.0f,
+                           38.0f,
+                           20.0f,
+                           20.0f,
+                           6.0f,
+                           19.0f,
+                           33.0f,
+                           0.0f},
+            {1, 1},
+            {1, 1},
+            {1, 1},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f, 3.0f,  5.0f, 7.0f, 9.0f, 7.0f, 5.0f, 3.0f, 1.0f, 0.0f, 2.0f, 4.0f, 6.0f,
+                           8.0f, 10.0f, 8.0f, 6.0f, 4.0f, 2.0f, 0.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 1.0f, 1.0f, 1.0f, 3.0f, 2.0f, 1.0f},
+            std::vector<T>{0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f,
+                           0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+                           1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f,
+                           2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f,
+                           0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f},
+            std::vector<T>{57.0f, 40.0f, 38.0f, 102.0f},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "integral_offsets_stride"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1.0f,  3.0f,  5.0f,  7.0f, 9.0f, 11.0f, 13.0f, 7.0f,  5.0f,  3.0f, 1.0f, -1.0f, -3.0f,
+                           -5.0f, 2.0f,  4.0f,  6.0f, 8.0f, 10.0f, 12.0f, 14.0f, 8.0f,  6.0f, 4.0f, 2.0f,  0.0f,
+                           -2.0f, -4.0f, 2.0f,  4.0f, 6.0f, 8.0f,  10.0f, 12.0f, 14.0f, 7.0f, 5.0f, 3.0f,  1.0f,
+                           -1.0f, -3.0f, -5.0f, 8.0f, 6.0f, 4.0f,  2.0f,  0.0f,  -2.0f, -4.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 1.0f, 1.0f, 0.0f, 3.0f, 1.0f, 2.0f},
+            std::vector<T>{1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f,
+                           1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
+                           0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f,
+                           1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f,
+                           1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
+                           0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f,
+                           1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f,
+                           1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f,
+                           0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f,
+                           1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, 0.0f, 2.0f, 0.0f,
+                           1.0f, 0.0f, 1.0f, 1.0f, 2.0f, 0.0f, 0.0f, 2.0f, 0.0f, 1.0f, 0.0f, 1.0f},
+            std::vector<T>{16.0f, -2.0f, 134.0f, 44.0f, -4.0f, -12.0f, 10.0f, 84.0f, -4.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {2, 2},
+            1,
+            1,
+            "integral_offset_dialation"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1.0f,  3.0f,  5.0f,  7.0f, 9.0f, 11.0f, 13.0f, 7.0f,  5.0f,  3.0f, 1.0f, -1.0f, -3.0f,
+                           -5.0f, 2.0f,  4.0f,  6.0f, 8.0f, 10.0f, 12.0f, 14.0f, 8.0f,  6.0f, 4.0f, 2.0f,  0.0f,
+                           -2.0f, -4.0f, 2.0f,  4.0f, 6.0f, 8.0f,  10.0f, 12.0f, 14.0f, 7.0f, 5.0f, 3.0f,  1.0f,
+                           -1.0f, -3.0f, -5.0f, 8.0f, 6.0f, 4.0f,  2.0f,  0.0f,  -2.0f, -4.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 1.0f, 1.0f, 0.0f, 3.0f, 1.0f, 2.0f},
+            std::vector<T>{
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f,
+
+                1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f, 1.0f, 0.0f, 1.0f, 0.0f, 1.0f, 0.0f, 0.0f, 2.0f},
+            std::vector<T>{15.0f,
+                           38.0f,
+                           2.0f,
+                           66.0f,
+                           26.0f,
+                           78.0f,
+                           134.0f,
+                           16.0f,
+                           23.0f,
+                           80.0f,
+                           -4.0f,
+                           58.0f,
+                           13.0f,
+                           56.0f,
+                           72.0f,
+                           -4.0f},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            1,
+            1,
+            "integral_offset_padding_stride_dialation"),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{1, 2, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1.0f,
+                           3.0f,
+                           5.0f,
+                           7.0f,
+                           7.0f,
+                           5.0f,
+                           3.0f,
+                           1.0f,
+                           2.0f,
+                           4.0f,
+                           6.0f,
+                           8.0f,
+                           8.0f,
+                           6.0f,
+                           4.0f,
+                           2.0f,
+                           // channel 2
+                           -1.0f,
+                           3.0f,
+                           -5.0f,
+                           7.0f,
+                           7.0f,
+                           -5.0f,
+                           3.0f,
+                           -1.0f,
+                           -2.0f,
+                           4.0f,
+                           -6.0f,
+                           8.0f,
+                           8.0f,
+                           -6.0f,
+                           4.0f,
+                           -2.0f},
+            std::vector<T>{// channel 1
+                           5.0f,
+                           3.0f,
+                           5.0f,
+                           1.0f,
+                           3.0f,
+                           1.0f,
+                           4.0f,
+                           2.0f,
+                           4.0f,
+                           // channel 2
+                           -5.0f,
+                           3.0f,
+                           5.0f,
+                           1.0f,
+                           -3.0f,
+                           1.0f,
+                           4.0f,
+                           2.0f,
+                           -4.0f},
+            std::vector<T>{1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f,
+                           2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f,
+                           0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f,
+                           1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f,
+                           1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f, 1.0f, 1.0f, 0.0f, 2.0f},
+            std::vector<T>{160.0f, 32.0f, 94.0f, 20.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "integral_offset_input_channels"),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{2, 1, 2, 2},
+                                    PartialShape{1, 8, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f},
+                                    std::vector<T>{// filter 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   // filter 2
+                                                   3.0f,
+                                                   4.0f,
+                                                   -3.0f,
+                                                   -4.0f},
+                                    std::vector<T>{// channel 1: Y offsets
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out1 .. out 3
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out4 .. out 6
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out7 .. out 9
+                                                   // channel 1: X offsets
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out1 .. out 3
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out4 .. out 6
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out7 .. out 9
+                                                   // channel 2: Y offsets
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // channel 2: X offsets
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // channel 3: Y offsets
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // channel 3: X offsets
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // channel 4: Y offsets
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // channel 4: X offsets
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f},
+                                    std::vector<T>{// output 1
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -4.0f,
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -4.0f,
+                                                   44.0f,
+                                                   47.0f,
+                                                   16.0f,
+                                                   // output 2
+                                                   -28.0f,
+                                                   -28.0f,
+                                                   -12.0f,
+                                                   -28.0f,
+                                                   -28.0f,
+                                                   -12.0f,
+                                                   102.0f,
+                                                   109.0f,
+                                                   48.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offset_output_channels"),
+        DeformableConvolutionParams(PartialShape{2, 1, 4, 4},
+                                    PartialShape{1, 1, 2, 2},
+                                    PartialShape{2, 8, 3, 3},
+                                    PartialShape{2, 1, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// batch 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // batch 2
+                                                   17.0f,
+                                                   18.0f,
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f},
+                                    std::vector<T>{1.0f, 2.0f, -1.0f, -2.0f},
+                                    std::vector<T>{// batch1
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   // batch2
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f},
+                                    std::vector<T>{// batch 1
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -4.0f,
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -4.0f,
+                                                   44.0f,
+                                                   47.0f,
+                                                   16.0f,
+                                                   // batch 2
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -12.0f,
+                                                   -12.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offset_batch"),
+        DeformableConvolutionParams(PartialShape{1, 4, 3, 3},
+                                    PartialShape{2, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 2, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   // channel 2
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   17.0f,
+                                                   18.0f,
+                                                   // channel 3
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   // channel 4
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f,
+                                                   33.0f,
+                                                   34.0f,
+                                                   35.0f,
+                                                   36.0f},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // filter 1 channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // filter 2 channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // filter 2 channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f},
+                                    std::vector<T>{// window 1 (F_Y=0, F_X=0) -> I_Y coordinate
+                                                   1.0f,
+                                                   0.0f,
+                                                   2.0f,
+                                                   1.0f,  // out1 .. out 4
+                                                   // window 1 (F_Y=0, F_X=0) -> I_X coordinate
+                                                   0.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   2.0f,  // out1 .. out 4
+                                                   // window 2 (F_Y=0, F_X=1) -> I_Y coordinate
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out1 .. out 4
+                                                   // window 2 (F_Y=0, F_X=1) -> I_X coordinate
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,  // out1 .. out 4
+                                                   // window 3 (F_Y=1, F_X=0) -> I_Y coordinate
+                                                   2.0f,
+                                                   2.0f,
+                                                   2.0f,
+                                                   2.0f,  // out1 .. out 4
+                                                   // window 3 (F_Y=1, F_X=0) -> I_X coordinate
+                                                   2.0f,
+                                                   2.0f,
+                                                   2.0f,
+                                                   2.0f,  // out1 .. out 4
+                                                   // window 4 (F_Y=1, F_X=1) -> I_Y coordinate
+                                                   2.0f,
+                                                   2.0f,
+                                                   2.0f,
+                                                   2.0f,  // out1 .. out 4
+                                                   // window 4 (F_Y=1, F_X=1) -> I_X coordinate
+                                                   2.0f,
+                                                   2.0f,
+                                                   2.0f,
+                                                   2.0f},  // out1 .. out 4
+                                    std::vector<T>{        // channel 1
+                                                   171.0f,
+                                                   63.0f,
+                                                   126.0f,
+                                                   0.0f,
+                                                   // channel 2
+                                                   -423.0f,
+                                                   -171.0f,
+                                                   -270.0f,
+                                                   0.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    2,
+                                    1,
+                                    "integral_offset_groups_basic"),
+        DeformableConvolutionParams(PartialShape{1, 8, 3, 3},
+                                    PartialShape{4, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 4, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   // channel 2
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   17.0f,
+                                                   18.0f,
+                                                   // channel 3
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   // channel 4
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f,
+                                                   33.0f,
+                                                   34.0f,
+                                                   35.0f,
+                                                   36.0f,
+                                                   // channel 5
+                                                   37.0f,
+                                                   38.0f,
+                                                   39.0f,
+                                                   40.0f,
+                                                   41.0f,
+                                                   42.0f,
+                                                   43.0f,
+                                                   44.0f,
+                                                   45.0f,
+                                                   // channel 6
+                                                   46.0f,
+                                                   47.0f,
+                                                   48.0f,
+                                                   49.0f,
+                                                   50.0f,
+                                                   51.0f,
+                                                   52.0f,
+                                                   53.0f,
+                                                   54.0f,
+                                                   // channel 7
+                                                   55.0f,
+                                                   56.0f,
+                                                   57.0f,
+                                                   58.0f,
+                                                   59.0f,
+                                                   60.0f,
+                                                   61.0f,
+                                                   62.0f,
+                                                   63.0f,
+                                                   // channel 8
+                                                   64.0f,
+                                                   65.0f,
+                                                   66.0f,
+                                                   67.0f,
+                                                   68.0f,
+                                                   69.0f,
+                                                   70.0f,
+                                                   71.0f,
+                                                   72.0f},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // filter 1 channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // filter 2 channel 1
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   // filter 2 channel 2
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // filter 3 channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // filter 3 channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f,
+                                                   // filter 4 channel 1
+                                                   -9.0f,
+                                                   -10.0f,
+                                                   -11.0f,
+                                                   -12.0f,
+                                                   // filter 4 channel 2
+                                                   -13.0f,
+                                                   -14.0f,
+                                                   -15.0f,
+                                                   -16.0f},
+                                    std::vector<T>{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                                                   1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                                                   1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
+                                    std::vector<T>{// channel 1
+                                                   500.0f,
+                                                   234.0f,
+                                                   219.0f,
+                                                   99.0f,
+                                                   // channel 2
+                                                   3036.0f,
+                                                   1482.0f,
+                                                   1463.0f,
+                                                   711.0f,
+                                                   // channel 3
+                                                   -1796.0f,
+                                                   -810.0f,
+                                                   -723.0f,
+                                                   -315.0f,
+                                                   // channel 4
+                                                   -6636.0f,
+                                                   -3210.0f,
+                                                   -3119.0f,
+                                                   -1503.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    4,
+                                    1,
+                                    "integral_offset_groups_complex"),
+        DeformableConvolutionParams(PartialShape{1, 2, 4, 4},
+                                    PartialShape{2, 2, 2, 2},
+                                    PartialShape{1, 16, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // channel 2
+                                                   17.0f,
+                                                   18.0f,
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f},
+                                    std::vector<T>{// f1: channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // f1: channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // f2: channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // f2: channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f},
+                                    std::vector<T>{// defgroup 1
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   //  defgroup 2
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f},
+                                    std::vector<T>{// output 1
+                                                   610.0f,
+                                                   646.0f,
+                                                   612.0f,
+                                                   754.0f,
+                                                   790.0f,
+                                                   732.0f,
+                                                   768.0f,
+                                                   797.0f,
+                                                   792.0f,
+                                                   // output 2
+                                                   -610.0f,
+                                                   -646.0f,
+                                                   -612.0f,
+                                                   -754.0f,
+                                                   -790.0f,
+                                                   -732.0f,
+                                                   -768.0f,
+                                                   -797.0f,
+                                                   -792.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    2,
+                                    "integral_offset_deforgroup_basic"),
+        DeformableConvolutionParams(PartialShape{1, 4, 4, 4},
+                                    PartialShape{2, 4, 2, 2},
+                                    PartialShape{1, 32, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // channel 2
+                                                   17.0f,
+                                                   18.0f,
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f,
+                                                   // channel 3
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // channel 4
+                                                   17.0f,
+                                                   18.0f,
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f},
+                                    std::vector<T>{// f1: channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // f1: channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // f1: channel 3
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // f1: channel 4
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // f2: channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // f2: channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f,
+                                                   // f2: channel 3
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // f2: channel 4
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f},
+                                    std::vector<T>{// defgroup 1
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   //  defgroup 2
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   // defgroup 3
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   //  defgroup 4
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f},
+                                    std::vector<T>{// output 1
+                                                   1220.0f,
+                                                   1292.0f,
+                                                   1224.0f,
+                                                   1508.0f,
+                                                   1580.0f,
+                                                   1464.0f,
+                                                   1536.0f,
+                                                   1594.0f,
+                                                   1584.0f,
+                                                   // output 2
+                                                   -1220.0f,
+                                                   -1292.0f,
+                                                   -1224.0f,
+                                                   -1508.0f,
+                                                   -1580.0f,
+                                                   -1464.0f,
+                                                   -1536.0f,
+                                                   -1594.0f,
+                                                   -1584.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    4,
+                                    "integral_offset_deforgroup_complex1"),
+        DeformableConvolutionParams(PartialShape{1, 4, 4, 4},
+                                    PartialShape{2, 4, 2, 2},
+                                    PartialShape{1, 16, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // channel 2
+                                                   17.0f,
+                                                   18.0f,
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f,
+                                                   // channel 3
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // channel 4
+                                                   17.0f,
+                                                   18.0f,
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f},
+                                    std::vector<T>{// f1: channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // f1: channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // f1: channel 3
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // f1: channel 4
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // f2: channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // f2: channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f,
+                                                   // f2: channel 3
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // f2: channel 4
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f},
+                                    std::vector<T>{// defgroup 1
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   1.0f,
+                                                   //  defgroup 2
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f,
+                                                   0.0f},
+                                    std::vector<T>{// output 1
+                                                   1300.0f,
+                                                   1372.0f,
+                                                   992.0f,
+                                                   1588.0f,
+                                                   1660.0f,
+                                                   1200.0f,
+                                                   1228.0f,
+                                                   1278.0f,
+                                                   1096.0f,
+                                                   // output 2
+                                                   -1300.0f,
+                                                   -1372.0f,
+                                                   -992.0f,
+                                                   -1588.0f,
+                                                   -1660.0f,
+                                                   -1200.0f,
+                                                   -1228.0f,
+                                                   -1278.0f,
+                                                   -1096.0f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    2,
+                                    "integral_offset_deforgroup_complex2"),
+        DeformableConvolutionParams(
+            PartialShape{1, 4, 3, 3},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f,  2.0f,  3.0f,  4.0f,  5.0f,  6.0f,  7.0f,  8.0f,  9.0f,  10.0f, 11.0f, 12.0f,
+                           13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f,
+                           25.0f, 26.0f, 27.0f, 28.0f, 29.0f, 30.0f, 31.0f, 32.0f, 33.0f, 34.0f, 35.0f, 36.0f},
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{// defgroup 1
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           1.0f,
+                           // defgroup 2
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f},
+            std::vector<T>{500.0f, 234.0f, 219.0f, 99.0f, -1004.0f, -1040.0f, -1112.0f, -1148.0f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            2,
+            2,
+            "integral_offset_groups_and_deforgroups"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f},
+            std::vector<T>{1.0f, 2.0f, -1.0f, -2.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{-11.999998f,
+                           -11.999999f,
+                           -4.000000f,
+                           -10.799999f,
+                           -10.800001f,
+                           -3.600004f,
+                           44.300000f,
+                           47.100000f,
+                           16.000000f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "real_offset_default"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<
+                T>{1.0f, 3.0f, 7.0f, 7.0f, 7.0f, 6.0f, 3.0f, 1.0f, 4.0f, 4.0f, 2.0f, 8.0f, 1.0f, 1.0f, 1.0f, 2.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 0.0f, 1.0f, 0.0f, 3.0f, 2.0f, 1.0f},
+            std::vector<T>{
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{54.870006f,
+                           61.630001f,
+                           43.230003f,
+                           28.600002f,
+                           35.590000f,
+                           25.819999f,
+                           20.880001f,
+                           7.700000f,
+                           19.089998f,
+                           31.719999f,
+                           19.250000f,
+                           7.399999f,
+                           6.299999f,
+                           9.199999f,
+                           5.099999f,
+                           2.000000f},
+            {1, 1},
+            {1, 1},
+            {1, 1},
+            {1, 1},
+            1,
+            1,
+            "real_offset_padding"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f, 3.0f,  5.0f, 7.0f, 9.0f, 7.0f, 5.0f, 3.0f, 1.0f, 0.0f, 2.0f, 4.0f, 6.0f,
+                           8.0f, 10.0f, 8.0f, 6.0f, 4.0f, 2.0f, 0.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 1.0f, 1.0f, 1.0f, 3.0f, 2.0f, 1.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{61.229999f, 29.509998f, 39.640003f, 22.640003f},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "real_offset_stride"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1.0f,  3.0f,  5.0f,  7.0f, 9.0f, 11.0f, 13.0f, 7.0f,  5.0f,  3.0f, 1.0f, -1.0f, -3.0f,
+                           -5.0f, 2.0f,  4.0f,  6.0f, 8.0f, 10.0f, 12.0f, 14.0f, 8.0f,  6.0f, 4.0f, 2.0f,  0.0f,
+                           -2.0f, -4.0f, 2.0f,  4.0f, 6.0f, 8.0f,  10.0f, 12.0f, 14.0f, 7.0f, 5.0f, 3.0f,  1.0f,
+                           -1.0f, -3.0f, -5.0f, 8.0f, 6.0f, 4.0f,  2.0f,  0.0f,  -2.0f, -4.0f},
+            std::vector<T>{1.0f, 2.0f, 3.0f, 1.0f, 1.0f, 0.0f, 3.0f, 1.0f, 2.0f},
+            std::vector<T>{
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{15.260000f,
+                           24.119997f,
+                           6.439994f,
+                           -3.940005f,
+                           26.440002f,
+                           20.319999f,
+                           -0.500001f,
+                           -11.720002f,
+                           23.500003f,
+                           14.040000f,
+                           -1.279998f,
+                           -3.860000f,
+                           12.500000f,
+                           -2.599999f,
+                           -5.299999f,
+                           -3.099999f},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            1,
+            1,
+            "real_offset_padding_stride_dialation"),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{1, 2, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1.0f,
+                           3.0f,
+                           5.0f,
+                           7.0f,
+                           7.0f,
+                           5.0f,
+                           3.0f,
+                           1.0f,
+                           2.0f,
+                           4.0f,
+                           6.0f,
+                           8.0f,
+                           8.0f,
+                           6.0f,
+                           4.0f,
+                           2.0f,
+                           // channel 2
+                           -1.0f,
+                           3.0f,
+                           -5.0f,
+                           7.0f,
+                           7.0f,
+                           -5.0f,
+                           3.0f,
+                           -1.0f,
+                           -2.0f,
+                           4.0f,
+                           -6.0f,
+                           8.0f,
+                           8.0f,
+                           -6.0f,
+                           4.0f,
+                           -2.0f},
+            std::vector<T>{// channel 1
+                           5.0f,
+                           3.0f,
+                           5.0f,
+                           1.0f,
+                           3.0f,
+                           1.0f,
+                           4.0f,
+                           2.0f,
+                           4.0f,
+                           // channel 2
+                           -5.0f,
+                           3.0f,
+                           5.0f,
+                           1.0f,
+                           -3.0f,
+                           1.0f,
+                           4.0f,
+                           2.0f,
+                           -4.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{148.000000f, 43.259998f, 91.279998f, 111.199996f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "real_offset_input_channels"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{2, 1, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 2, 3, 3},
+            IN_ET,
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f},
+            std::vector<T>{// filter 1
+                           1.0f,
+                           2.0f,
+                           -1.0f,
+                           -2.0f,
+                           // filter 2
+                           3.0f,
+                           4.0f,
+                           -3.0f,
+                           -4.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{// output 1
+                           -12.000000f,
+                           -12.000000f,
+                           -4.000000f,
+                           -10.799999f,
+                           -10.799995f,
+                           -3.600000f,
+                           44.299999f,
+                           47.099998f,
+                           16.000000f,
+                           // output 2
+                           -28.000000f,
+                           -28.000000f,
+                           -12.000000f,
+                           -25.200000f,
+                           -25.199993f,
+                           -10.800003f,
+                           102.699996f,
+                           109.300003f,
+                           48.000000f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "real_offset_output_channels"),
+        DeformableConvolutionParams(
+            PartialShape{2, 1, 4, 4},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{2, 8, 3, 3},
+            PartialShape{2, 2, 3, 3},
+            IN_ET,
+            std::vector<T>{// batch 1
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           // batch 2
+                           17.0f,
+                           18.0f,
+                           19.0f,
+                           20.0f,
+                           21.0f,
+                           22.0f,
+                           23.0f,
+                           24.0f,
+                           25.0f,
+                           26.0f,
+                           27.0f,
+                           28.0f,
+                           29.0f,
+                           30.0f,
+                           31.0f,
+                           32.0f},
+            std::vector<T>{1.0f, 2.0f, -1.0f, -2.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{// batch 1
+                           -12.000000f,
+                           -12.000000f,
+                           -4.000000f,
+                           -10.799999f,
+                           -10.799995f,
+                           -3.600000f,
+                           44.299999f,
+                           47.099998f,
+                           16.000000f,
+                           // batch 2
+                           -12.000000f,
+                           -12.000000f,
+                           -4.000000f,
+                           -10.799999f,
+                           -10.799995f,
+                           -3.600000f,
+                           92.300003f,
+                           95.099998f,
+                           32.000000f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "real_offset_batch"),
+        DeformableConvolutionParams(PartialShape{1, 4, 3, 3},
+                                    PartialShape{2, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 2, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   // channel 2
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   17.0f,
+                                                   18.0f,
+                                                   // channel 3
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   // channel 4
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f,
+                                                   33.0f,
+                                                   34.0f,
+                                                   35.0f,
+                                                   36.0f},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // filter 1 channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // filter 2 channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // filter 2 channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f},
+                                    std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                                                   1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                                                   1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+                                    std::vector<T>{// channel 1
+                                                   505.800020f,
+                                                   235.800000f,
+                                                   219.600000f,
+                                                   99.000000f,
+                                                   // channel 2
+                                                   -1153.800000f,
+                                                   -523.800000f,
+                                                   -471.600000f,
+                                                   -207.0000000f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    2,
+                                    1,
+                                    "real_offset_group_basic"),
+        DeformableConvolutionParams(PartialShape{1, 8, 3, 3},
+                                    PartialShape{4, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 4, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   9.0f,
+                                                   // channel 2
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   17.0f,
+                                                   18.0f,
+                                                   // channel 3
+                                                   19.0f,
+                                                   20.0f,
+                                                   21.0f,
+                                                   22.0f,
+                                                   23.0f,
+                                                   24.0f,
+                                                   25.0f,
+                                                   26.0f,
+                                                   27.0f,
+                                                   // channel 4
+                                                   28.0f,
+                                                   29.0f,
+                                                   30.0f,
+                                                   31.0f,
+                                                   32.0f,
+                                                   33.0f,
+                                                   34.0f,
+                                                   35.0f,
+                                                   36.0f,
+                                                   // channel 5
+                                                   37.0f,
+                                                   38.0f,
+                                                   39.0f,
+                                                   40.0f,
+                                                   41.0f,
+                                                   42.0f,
+                                                   43.0f,
+                                                   44.0f,
+                                                   45.0f,
+                                                   // channel 6
+                                                   46.0f,
+                                                   47.0f,
+                                                   48.0f,
+                                                   49.0f,
+                                                   50.0f,
+                                                   51.0f,
+                                                   52.0f,
+                                                   53.0f,
+                                                   54.0f,
+                                                   // channel 7
+                                                   55.0f,
+                                                   56.0f,
+                                                   57.0f,
+                                                   58.0f,
+                                                   59.0f,
+                                                   60.0f,
+                                                   61.0f,
+                                                   62.0f,
+                                                   63.0f,
+                                                   // channel 8
+                                                   64.0f,
+                                                   65.0f,
+                                                   66.0f,
+                                                   67.0f,
+                                                   68.0f,
+                                                   69.0f,
+                                                   70.0f,
+                                                   71.0f,
+                                                   72.0f},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1.0f,
+                                                   2.0f,
+                                                   3.0f,
+                                                   4.0f,
+                                                   // filter 1 channel 2
+                                                   5.0f,
+                                                   6.0f,
+                                                   7.0f,
+                                                   8.0f,
+                                                   // filter 2 channel 1
+                                                   9.0f,
+                                                   10.0f,
+                                                   11.0f,
+                                                   12.0f,
+                                                   // filter 2 channel 2
+                                                   13.0f,
+                                                   14.0f,
+                                                   15.0f,
+                                                   16.0f,
+                                                   // filter 3 channel 1
+                                                   -1.0f,
+                                                   -2.0f,
+                                                   -3.0f,
+                                                   -4.0f,
+                                                   // filter 3 channel 2
+                                                   -5.0f,
+                                                   -6.0f,
+                                                   -7.0f,
+                                                   -8.0f,
+                                                   // filter 4 channel 1
+                                                   -9.0f,
+                                                   -10.0f,
+                                                   -11.0f,
+                                                   -12.0f,
+                                                   // filter 4 channel 2
+                                                   -13.0f,
+                                                   -14.0f,
+                                                   -15.0f,
+                                                   -16.0f},
+                                    std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                                                   1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                                                   1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+                                    std::vector<T>{// channel 1
+                                                   505.800020f,
+                                                   235.800000f,
+                                                   219.600000f,
+                                                   99.000000f,
+                                                   // channel 2
+                                                   3054.600000f,
+                                                   1488.600000f,
+                                                   1465.200100f,
+                                                   711.000000f,
+                                                   // channel 3
+                                                   -1801.799900f,
+                                                   -811.80000f,
+                                                   -723.600000f,
+                                                   -315.000000f,
+                                                   // channel 4
+                                                   -6654.600000f,
+                                                   -3216.600000f,
+                                                   -3121.200000f,
+                                                   -1503.000000f},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    4,
+                                    1,
+                                    "real_offset_groups_complex"),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 3, 3},
+            PartialShape{1, 2, 3, 3},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           // channel 2
+                           17.0f,
+                           18.0f,
+                           19.0f,
+                           20.0f,
+                           21.0f,
+                           22.0f,
+                           23.0f,
+                           24.0f,
+                           25.0f,
+                           26.0f,
+                           27.0f,
+                           28.0f,
+                           29.0f,
+                           30.0f,
+                           31.0f,
+                           32.0f},
+            std::vector<T>{// f1: channel 1
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           // f1: channel 2
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           // f2: channel 1
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           // f2: channel 2
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{// output 1
+                           758.000000f,
+                           792.000000f,
+                           366.399993f,
+                           893.200012f,
+                           927.200012f,
+                           426.399993f,
+                           381.399993f,
+                           394.600006f,
+                           176.000000f,
+                           // output 2
+                           -758.000000f,
+                           -792.000000f,
+                           -366.399993f,
+                           -893.200012f,
+                           -927.200012f,
+                           -426.399993f,
+                           -381.399993f,
+                           -394.600006f,
+                           -176.000000f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            2,
+            "real_offset_deforgroup_basic"),
+        DeformableConvolutionParams(
+            PartialShape{1, 4, 4, 4},
+            PartialShape{2, 4, 2, 2},
+            PartialShape{1, 32, 3, 3},
+            PartialShape{1, 2, 3, 3},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           // channel 2
+                           17.0f,
+                           18.0f,
+                           19.0f,
+                           20.0f,
+                           21.0f,
+                           22.0f,
+                           23.0f,
+                           24.0f,
+                           25.0f,
+                           26.0f,
+                           27.0f,
+                           28.0f,
+                           29.0f,
+                           30.0f,
+                           31.0f,
+                           32.0f,
+                           // channel 3
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           // channel 4
+                           17.0f,
+                           18.0f,
+                           19.0f,
+                           20.0f,
+                           21.0f,
+                           22.0f,
+                           23.0f,
+                           24.0f,
+                           25.0f,
+                           26.0f,
+                           27.0f,
+                           28.0f,
+                           29.0f,
+                           30.0f,
+                           31.0f,
+                           32.0f},
+            std::vector<T>{// f1: channel 1
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           // f1: channel 2
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           // f1: channel 3
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           // f1: channel 4
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           // f2: channel 1
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           // f2: channel 2
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f,
+                           // f2: channel 3
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           // f2: channel 4
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{// output 1
+                           1516.000000f,
+                           1583.999877f,
+                           732.799987f,
+                           1786.400146f,
+                           1854.400024f,
+                           852.799987f,
+                           762.799987f,
+                           789.200012f,
+                           352.000000f,
+                           // output 2
+                           -1516.000000f,
+                           -1583.999877f,
+                           -732.799987f,
+                           -1786.400146f,
+                           -1854.400024f,
+                           -852.799987f,
+                           -762.799987f,
+                           -789.200012f,
+                           -352.000000f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            4,
+            "real_offset_deforgroup_complex1"),
+        DeformableConvolutionParams(
+            PartialShape{1, 4, 4, 4},
+            PartialShape{2, 4, 2, 2},
+            PartialShape{1, 16, 3, 3},
+            PartialShape{1, 2, 3, 3},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           // channel 2
+                           17.0f,
+                           18.0f,
+                           19.0f,
+                           20.0f,
+                           21.0f,
+                           22.0f,
+                           23.0f,
+                           24.0f,
+                           25.0f,
+                           26.0f,
+                           27.0f,
+                           28.0f,
+                           29.0f,
+                           30.0f,
+                           31.0f,
+                           32.0f,
+                           // channel 3
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           // channel 4
+                           17.0f,
+                           18.0f,
+                           19.0f,
+                           20.0f,
+                           21.0f,
+                           22.0f,
+                           23.0f,
+                           24.0f,
+                           25.0f,
+                           26.0f,
+                           27.0f,
+                           28.0f,
+                           29.0f,
+                           30.0f,
+                           31.0f,
+                           32.0f},
+            std::vector<T>{// f1: channel 1
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           // f1: channel 2
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           // f1: channel 3
+                           1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           // f1: channel 4
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           // f2: channel 1
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           // f2: channel 2
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f,
+                           // f2: channel 3
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           // f2: channel 4
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{// output 1
+                           1516.000000f,
+                           1583.999877f,
+                           732.799987f,
+                           1786.400146f,
+                           1854.400024f,
+                           852.799987f,
+                           762.799987f,
+                           789.200012f,
+                           352.000000f,
+                           // output 2
+                           -1516.000000f,
+                           -1583.999877f,
+                           -732.799987f,
+                           -1786.400146f,
+                           -1854.400024f,
+                           -852.799987f,
+                           -762.799987f,
+                           -789.200012f,
+                           -352.000000f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            2,
+            "real_offset_deforgroup_complex2"),
+        DeformableConvolutionParams(
+            PartialShape{1, 4, 3, 3},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f,  2.0f,  3.0f,  4.0f,  5.0f,  6.0f,  7.0f,  8.0f,  9.0f,  10.0f, 11.0f, 12.0f,
+                           13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f,
+                           25.0f, 26.0f, 27.0f, 28.0f, 29.0f, 30.0f, 31.0f, 32.0f, 33.0f, 34.0f, 35.0f, 36.0f},
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{505.800020f,
+                           235.800000f,
+                           219.600000f,
+                           99.000000f,
+                           -1153.800000f,
+                           -523.800000f,
+                           -471.600000f,
+                           -207.000000f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            2,
+            2,
+            "real_offset_groups_and_deforgroups"),
     };
     return deformableConvolutionParams;
 }
@@ -2780,1843 +4113,2608 @@ template <element::Type_t IN_ET>
 std::vector<DeformableConvolutionParams> generateDeformableConvolutionIntParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DeformableConvolutionParams> deformableConvolutionParams {
-// --------------------- 2D DeformableConvolution ------------------------------------------
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16},
-                          std::vector<T>{
-                                    1, 2,
-                                    -1, -2},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    -12, -12, -12,
-                                    -12, -12, -12,
-                                    -12, -12, -12},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5,
-                                    7, 5, 3,
-                                    1, 3, 5},
-                          std::vector<T>{
-                                    1, 2,
-                                    0, 1},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    1, 3, 5, 0,
-                                    9, 12, 16, 5,
-                                    15, 20, 16, 3,
-                                    2, 7, 13, 5},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9,
-                                    7, 5, 3, 1, 0,
-                                    2, 4, 6, 8, 10,
-                                    8, 6, 4, 2, 0,
-                                    2, 4, 6, 8, 10},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    57, 94,
-                                    66, 102},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9, 11, 13,
-                                    7, 5, 3, 1, -1, -3, -5,
-                                    2, 4, 6, 8, 10, 12, 14,
-                                    8, 6, 4, 2, 0, -2, -4,
-                                    2, 4, 6, 8, 10, 12, 14,
-                                    7, 5, 3, 1, -1, -3, -5,
-                                    8, 6, 4, 2, 0, -2, -4},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 0,
-                                    3, 1, 2},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    78, 106, 134,
-                                    44, 16, -12,
-                                    80, 84, 88},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {2, 2}),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9, 11, 13,
-                                    7, 5, 3, 1, -1, -3, -5,
-                                    2, 4, 6, 8, 10, 12, 14,
-                                    8, 6, 4, 2, 0, -2, -4,
-                                    2, 4, 6, 8, 10, 12, 14,
-                                    7, 5, 3, 1, -1, -3, -5,
-                                    8, 6, 4, 2, 0, -2, -4},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 0,
-                                    3, 1, 2},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    15, 38, 70, 66,
-                                    33, 78, 134, 103,
-                                    40, 80, 88, 58,
-                                    30, 56, 72, 34},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2}),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {1, 2, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 3, 5, 7,
-                                    7, 5, 3, 1,
-                                    2, 4, 6, 8,
-                                    8, 6, 4, 2,
-                                    // channel 2
-                                    -1, 3, -5, 7,
-                                    7, -5, 3, -1,
-                                    -2, 4, -6, 8,
-                                    8, -6, 4, -2},
-                          std::vector<T>{
-                                    // channel 1
-                                    5, 3, 5,
-                                    1, 3, 1,
-                                    4, 2, 4,
-                                    // channel 2
-                                    -5, 3, 5,
-                                    1, -3, 1,
-                                    4, 2, -4},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    142, 102,
-                                    94, 160},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {2, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7,
-                                    7, 5, 3, 1,
-                                    2, 4, 6, 8,
-                                    8, 6, 4, 2},
-                          std::vector<T>{
-                                    // channel 1
-                                    5, 3, 5,
-                                    1, 3, 1,
-                                    4, 2, 4,
-                                    // channel 2
-                                   -5, 3, 5,
-                                    1, -3, 1,
-                                    4, 2, -4},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // channel 1
-                                    104, 140,
-                                    145, 109,
-                                    // channel 2
-                                    16, 28,
-                                    19, 7},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {2, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {2, 18, 2, 2},
-                          PartialShape {2, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // batch 1
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // batch 2
-                                    -1, 3, 2, -1,
-                                    1, 3, -3, 1,
-                                    -2, -1, 1, 3,
-                                    3, 2, 3, -3},
-                          std::vector<T>{
-                                   -5, 3, 5,
-                                    1, -3, 1,
-                                    4, 2, -4},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // batch 1
-                                    15, -15,
-                                    23, 2,
-                                    // batch 2
-                                    -1, -15,
-                                    -5, 6},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3,
-                                    4, 5, 6,
-                                    7, 8, 9,
-                                     // channel 2
-                                    10, 11, 12,
-                                    13, 14, 15,
-                                    16, 17, 18,
-                                    // channel 3
-                                    19, 20, 21,
-                                    22, 23, 24,
-                                    25, 26, 27,
-                                    // channel 4
-                                    28, 29, 30,
-                                    31, 32, 33,
-                                    34, 35, 36},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1, 2,
-                                    3, 4,
-                                    // filter 1 channel 2
-                                    5, 6,
-                                    7, 8,
-                                    // filter 2 channel 1
-                                    -1, -2,
-                                    -3, -4,
-                                    // filter 2 channel 2
-                                    -5, -6,
-                                    -7, -8},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // channel 1
-                                    356, 392,
-                                    464, 500,
-                                    // channel 2
-                                    -1004, -1040,
-                                    -1112, -1148},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2),
-        DeformableConvolutionParams(PartialShape {1, 8, 3, 3},
-                          PartialShape {4, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 4, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3,
-                                    4, 5, 6,
-                                    7, 8, 9,
-                                    // channel 2
-                                    10, 11, 12,
-                                    13, 14, 15,
-                                    16, 17, 18,
-                                    // channel 3
-                                    19, 20, 21,
-                                    22, 23, 24,
-                                    25, 26, 27,
-                                    // channel 4
-                                    28, 29, 30,
-                                    31, 32, 33,
-                                    34, 35, 36,
-                                    // channel 5
-                                    37, 38, 39,
-                                    40, 41, 42,
-                                    43, 44, 45,
-                                    // channel 6
-                                    46, 47, 48,
-                                    49, 50, 51,
-                                    52, 53, 54,
-                                    // channel 7
-                                    55, 56, 57,
-                                    58, 59, 60,
-                                    61, 62, 63,
-                                    // channel 8
-                                    64, 65, 66,
-                                    67, 68, 69,
-                                    70, 71, 72},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1, 2,
-                                    3, 4,
-                                    // filter 1 channel 2
-                                    5, 6,
-                                    7, 8,
-                                    // filter 2 channel 1
-                                    9, 10,
-                                    11, 12,
-                                    // filter 2 channel 2
-                                    13, 14,
-                                    15, 16,
-                                    // filter 3 channel 1
-                                    -1, -2,
-                                    -3, -4,
-                                    // filter 3 channel 2
-                                    -5, -6,
-                                    -7, -8,
-                                    // filter 4 channel 1
-                                    -9, -10,
-                                    -11, -12,
-                                    // filter 4 channel 2
-                                    -13, -14,
-                                    -15, -16},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // channel 1
-                                    356, 392,
-                                    464, 500,
-                                    // channel 2
-                                    2636, 2736,
-                                    2936, 3036,
-                                    // channel 3
-                                    -1652, -1688,
-                                    -1760, -1796,
-                                    // channel 4
-                                    -6236, -6336,
-                                    -6536, -6636},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          4),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {1, 2, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    // channel 2
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32},
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2,
-                                    -1, -2,
-                                    // channel 2
-                                    3, 4,
-                                    -3, -4},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    -40, -40, -40,
-                                    -40, -40, -40,
-                                    -40, -40, -40},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    4, 5, 6,
-                                    7, 8, 9,
-                                    10, 11, 12,
-                                    13, 14, 15,
-                                    16, 17, 18,
-                                    19, 20, 21,
-                                    22, 23, 24,
-                                    25, 26, 27,
-                                    28, 29, 30,
-                                    31, 32, 33,
-                                    34, 35, 36},
-                          std::vector<T>{
-                                    1, 2,
-                                    3, 4,
-                                    5, 6,
-                                    7, 8,
-                                    -1, -2,
-                                    -3, -4,
-                                    -5, -6,
-                                    -7, -8},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    356, 392,
-                                    464, 500,
-                                    -1004, -1040,
-                                    -1112, -1148},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          2),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16},
-                          std::vector<T>{
-                                    1, 2,
-                                    -1, -2},
-                          std::vector<T>{
-                                    // window 1 (Y=0, X=0) -> Y coordinate
-                                    1, 1, 1, // out1 .. out 3
-                                    1, 1, 1, // out4 .. out 6
-                                    1, 1, 1, // out7 .. out 9
-                                    // window 1 (Y=0, X=0) -> X coordinate
-                                    1, 1, 1, // out1 .. out 3
-                                    1, 1, 1, // out4 .. out 6
-                                    1, 1, 1, // out7 .. out 9
-                                    // window 2
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 2
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 3
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 3
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 4
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 4
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1},
-                          std::vector<T>{
-                                    -12, -12, -4,
-                                    -12, -12, -4,
-                                    44, 47, 16},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offsets_1"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 7, 7,
-                                    7, 6, 3, 1,
-                                    4, 4, 2, 8,
-                                    1, 1, 1, 2},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2},
-                          std::vector<T>{
-                                    56, 39, 44, 18,
-                                    38, 56, 65, 0,
-                                    19, 38, 20, 20,
-                                    6, 19, 33, 0},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9,
-                                    7, 5, 3, 1, 0,
-                                    2, 4, 6, 8, 10,
-                                    8, 6, 4, 2, 0,
-                                    2, 4, 6, 8, 10},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0},
-                          std::vector<T>{
-                                    57, 40,
-                                    38, 102},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offsets_stride"),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9, 11, 13,
-                                    7, 5, 3, 1, -1, -3, -5,
-                                    2, 4, 6, 8, 10, 12, 14,
-                                    8, 6, 4, 2, 0, -2, -4,
-                                    2, 4, 6, 8, 10, 12, 14,
-                                    7, 5, 3, 1, -1, -3, -5,
-                                    8, 6, 4, 2, 0, -2, -4},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 0,
-                                    3, 1, 2},
-                          std::vector<T>{
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 1, 0,
-                                    0, 2, 0,
-                                    1, 0, 1,
-                                    1, 2, 0,
-                                    0, 2, 0,
-                                    1, 0, 1},
-                          std::vector<T>{
-                                    16, -2, 134,
-                                    44, -4, -12,
-                                    10, 84, -4},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {2, 2},
-                          1,
-                          1,
-                          "integral_offset_dialation"),
-        DeformableConvolutionParams(PartialShape {1, 1, 7, 7},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9, 11, 13,
-                                    7, 5, 3, 1, -1, -3, -5,
-                                    2, 4, 6, 8, 10, 12, 14,
-                                    8, 6, 4, 2, 0, -2, -4,
-                                    2, 4, 6, 8, 10, 12, 14,
-                                    7, 5, 3, 1, -1, -3, -5,
-                                    8, 6, 4, 2, 0, -2, -4},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 0,
-                                    3, 1, 2},
-                          std::vector<T>{
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2},
-                          std::vector<T>{
-                                    15, 38, 2, 66,
-                                    26, 78, 134, 16,
-                                    23, 80, -4, 58,
-                                    13, 56, 72, -4},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          {2, 2},
-                          1,
-                          1,
-                          "integral_offset_padding_stride_dialation"),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {1, 2, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 3, 5, 7,
-                                    7, 5, 3, 1,
-                                    2, 4, 6, 8,
-                                    8, 6, 4, 2,
-                                    // channel 2
-                                    -1, 3, -5, 7,
-                                    7, -5, 3, -1,
-                                    -2, 4, -6, 8,
-                                    8, -6, 4, -2},
-                          std::vector<T>{
-                                    // channel 1
-                                    5, 3, 5,
-                                    1, 3, 1,
-                                    4, 2, 4,
-                                    // channel 2
-                                    -5, 3, 5,
-                                    1, -3, 1,
-                                    4, 2, -4},
-                          std::vector<T>{
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2,
-                                    1, 1,
-                                    0, 2},
-                          std::vector<T>{
-                                    160, 32,
-                                    94, 20},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offset_input_channels"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {2, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16},
-                          std::vector<T>{
-                                    // filter 1
-                                    1, 2,
-                                    -1, -2,
-                                    // filter 2
-                                    3, 4,
-                                    -3, -4},
-                          std::vector<T>{
-                                    //channel 1: Y offsets
-                                    1, 1, 1, // out1 .. out 3
-                                    1, 1, 1, // out4 .. out 6
-                                    1, 1, 1, // out7 .. out 9
-                                    //channel 1: X offsets
-                                    1, 1, 1, // out1 .. out 3
-                                    1, 1, 1, // out4 .. out 6
-                                    1, 1, 1, // out7 .. out 9
-                                    //channel 2: Y offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 2: X offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 3: Y offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 3: X offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 4: Y offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 4: X offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1},
-                          std::vector<T>{
-                                    // output 1
-                                    -12, -12, -4,
-                                    -12, -12, -4,
-                                    44, 47, 16,
-                                    // output 2
-                                    -28, -28, -12,
-                                    -28, -28, -12,
-                                    102, 109, 48},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offset_output_channels"),
-        DeformableConvolutionParams(PartialShape {2, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {2, 8, 3, 3},
-                          PartialShape {2, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    //batch 1
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    //batch 2
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32},
-                          std::vector<T>{
-                                    1, 2,
-                                    -1, -2},
-                          std::vector<T>{
-                                    // batch1
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // batch2
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0},
-                          std::vector<T>{
-                                    // batch 1
-                                    -12, -12, -4,
-                                    -12, -12, -4,
-                                    44, 47, 16,
-                                    // batch 2
-                                    -12, -12, -12,
-                                    -12, -12, -12,
-                                    -12, -12, -12},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offset_batch"),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3,
-                                    4, 5, 6,
-                                    7, 8, 9,
-                                     // channel 2
-                                    10, 11, 12,
-                                    13, 14, 15,
-                                    16, 17, 18,
-                                    // channel 3
-                                    19, 20, 21,
-                                    22, 23, 24,
-                                    25, 26, 27,
-                                    // channel 4
-                                    28, 29, 30,
-                                    31, 32, 33,
-                                    34, 35, 36},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1, 2,
-                                    3, 4,
-                                     // filter 1 channel 2
-                                    5, 6,
-                                    7, 8,
-                                     // filter 2 channel 1
-                                    -1, -2,
-                                    -3, -4,
-                                    // filter 2 channel 2
-                                    -5, -6,
-                                    -7, -8},
-                          std::vector<T>{
-                                    // window 1 (F_Y=0, F_X=0) -> I_Y coordinate
-                                    1, 0, 2, 1, // out1 .. out 4
-                                    // window 1 (F_Y=0, F_X=0) -> I_X coordinate
-                                    0, 1, 1, 2, // out1 .. out 4
-                                    // window 2 (F_Y=0, F_X=1) -> I_Y coordinate
-                                    1, 1, 1, 1, // out1 .. out 4
-                                    // window 2 (F_Y=0, F_X=1) -> I_X coordinate
-                                    1, 1, 1, 1, // out1 .. out 4
-                                    // window 3 (F_Y=1, F_X=0) -> I_Y coordinate
-                                    2, 2, 2, 2, // out1 .. out 4
-                                    // window 3 (F_Y=1, F_X=0) -> I_X coordinate
-                                    2, 2, 2, 2, // out1 .. out 4
-                                    // window 4 (F_Y=1, F_X=1) -> I_Y coordinate
-                                    2, 2, 2, 2, // out1 .. out 4
-                                    // window 4 (F_Y=1, F_X=1) -> I_X coordinate
-                                    2, 2, 2, 2}, // out1 .. out 4
-                          std::vector<T>{
-                                    // channel 1
-                                    171, 63,
-                                    126, 0,
-                                    // channel 2
-                                    -423, -171,
-                                    -270, 0},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          1,
-                          "integral_offset_groups_basic"),
-        DeformableConvolutionParams(PartialShape {1, 8, 3, 3},
-                          PartialShape {4, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          PartialShape {1, 4, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3,
-                                    4, 5, 6,
-                                    7, 8, 9,
-                                     // channel 2
-                                    10, 11, 12,
-                                    13, 14, 15,
-                                    16, 17, 18,
-                                    // channel 3
-                                    19, 20, 21,
-                                    22, 23, 24,
-                                    25, 26, 27,
-                                    // channel 4
-                                    28, 29, 30,
-                                    31, 32, 33,
-                                    34, 35, 36,
-                                     // channel 5
-                                    37, 38, 39,
-                                    40, 41, 42,
-                                    43, 44, 45,
-                                     // channel 6
-                                    46, 47, 48,
-                                    49, 50, 51,
-                                    52, 53, 54,
-                                     // channel 7
-                                    55, 56, 57,
-                                    58, 59, 60,
-                                    61, 62, 63,
-                                     // channel 8
-                                    64, 65, 66,
-                                    67, 68, 69,
-                                    70, 71, 72},
-                          std::vector<T>{
-                                    // filter 1 channel 1
-                                    1, 2,
-                                    3, 4,
-                                    // filter 1 channel 2
-                                    5, 6,
-                                    7, 8,
-                                    // filter 2 channel 1
-                                    9, 10,
-                                    11, 12,
-                                    // filter 2 channel 2
-                                    13, 14,
-                                    15, 16,
-                                    // filter 3 channel 1
-                                    -1, -2,
-                                    -3, -4,
-                                    // filter 3 channel 2
-                                    -5, -6,
-                                    -7, -8,
-                                    // filter 4 channel 1
-                                    -9, -10,
-                                    -11, -12,
-                                    // filter 4 channel 2
-                                    -13, -14,
-                                    -15, -16},
-                          std::vector<T>{
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1},
-                          std::vector<T>{
-                                    // channel 1
-                                    500, 234,
-                                    219, 99,
-                                    // channel 2
-                                    3036, 1482,
-                                    1463, 711,
-                                    // channel 3
-                                    -1796, -810,
-                                    -723, -315,
-                                    // channel 4
-                                    -6636, -3210,
-                                    -3119, -1503},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          4,
-                          1,
-                          "integral_offset_groups_complex"),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    // channel 2
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1, 2,
-                                    3, 4,
-                                    // f1: channel 2
-                                    5, 6,
-                                    7, 8,
-                                    // f2: channel 1
-                                    -1, -2,
-                                    -3, -4,
-                                    // f2: channel 2
-                                    -5, -6,
-                                    -7, -8},
-                          std::vector<T>{
-                                    // defgroup 1
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //  defgroup 2
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0},
-                          std::vector<T>{
-                                    // output 1
-                                    610, 646, 612,
-                                    754, 790, 732,
-                                    768, 797, 792,
-                                    // output 2
-                                    -610, -646, -612,
-                                    -754, -790, -732,
-                                    -768, -797, -792},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          2,
-                          "integral_offset_deforgroup_basic"),
-        DeformableConvolutionParams(PartialShape {1, 4, 4, 4},
-                          PartialShape {2, 4, 2, 2},
-                          PartialShape {1, 32, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    // channel 2
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32,
-                                    // channel 3
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    // channel 4
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1, 2,
-                                    3, 4,
-                                    // f1: channel 2
-                                    5, 6,
-                                    7, 8,
-                                    // f1: channel 3
-                                    1, 2,
-                                    3, 4,
-                                    // f1: channel 4
-                                    5, 6,
-                                    7, 8,
-                                    // f2: channel 1
-                                    -1, -2,
-                                    -3, -4,
-                                    // f2: channel 2
-                                    -5, -6,
-                                    -7, -8,
-                                    // f2: channel 3
-                                    -1, -2,
-                                    -3, -4,
-                                    // f2: channel 4
-                                    -5, -6,
-                                    -7, -8},
-                          std::vector<T>{
-                                    // defgroup 1
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //  defgroup 2
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    // defgroup 3
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //  defgroup 4
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0},
-                          std::vector<T>{
-                                    // output 1
-                                    1220, 1292, 1224,
-                                    1508, 1580, 1464,
-                                    1536, 1594, 1584,
-                                    // output 2
-                                    -1220, -1292, -1224,
-                                    -1508, -1580, -1464,
-                                    -1536, -1594, -1584},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          4,
-                          "integral_offset_deforgroup_complex1"),
-        DeformableConvolutionParams(PartialShape {1, 4, 4, 4},
-                          PartialShape {2, 4, 2, 2},
-                          PartialShape {1, 16, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    // channel 2
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32,
-                                    // channel 3
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    // channel 4
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32},
-                          std::vector<T>{
-                                    // f1: channel 1
-                                    1, 2,
-                                    3, 4,
-                                    // f1: channel 2
-                                    5, 6,
-                                    7, 8,
-                                    // f1: channel 3
-                                    1, 2,
-                                    3, 4,
-                                    // f1: channel 4
-                                    5, 6,
-                                    7, 8,
-                                    // f2: channel 1
-                                    -1, -2,
-                                    -3, -4,
-                                    // f2: channel 2
-                                    -5, -6,
-                                    -7, -8,
-                                    // f2: channel 3
-                                    -1, -2,
-                                    -3, -4,
-                                    // f2: channel 4
-                                    -5, -6,
-                                    -7, -8},
-                          std::vector<T>{
-                                    // defgroup 1
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //  defgroup 2
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0},
-                          std::vector<T>{
-                                    // output 1
-                                    1300, 1372, 992,
-                                    1588, 1660, 1200,
-                                    1228, 1278, 1096,
-                                    // output 2
-                                    -1300, -1372, -992,
-                                    -1588, -1660, -1200,
-                                    -1228, -1278, -1096},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          2,
-                          "integral_offset_deforgroup_complex2"),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    4, 5, 6,
-                                    7, 8, 9,
-                                    10, 11, 12,
-                                    13, 14, 15,
-                                    16, 17, 18,
-                                    19, 20, 21,
-                                    22, 23, 24,
-                                    25, 26, 27,
-                                    28, 29, 30,
-                                    31, 32, 33,
-                                    34, 35, 36},
-                          std::vector<T>{
-                                    1, 2,
-                                    3, 4,
-                                    5, 6,
-                                    7, 8,
-                                    -1, -2,
-                                    -3, -4,
-                                    -5, -6,
-                                    -7, -8},
-                          std::vector<T>{
-                                    // defgroup 1
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    1, 1, 1, 1,
-                                    // defgroup 2
-                                    0, 0, 0, 0,
-                                    0, 0, 0, 0,
-                                    0, 0, 0, 0,
-                                    0, 0, 0, 0,
-                                    0, 0, 0, 0,
-                                    0, 0, 0, 0,
-                                    0, 0, 0, 0,
-                                    0, 0, 0, 0},
-                          std::vector<T>{
-                                    500, 234,
-                                    219, 99,
-                                    -1004, -1040,
-                                    -1112, -1148},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          2,
-                          "integral_offset_groups_and_deforgroups"),
+    std::vector<DeformableConvolutionParams> deformableConvolutionParams{
+        // --------------------- 2D DeformableConvolution ------------------------------------------
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16},
+            std::vector<T>{1, 2, -1, -2},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{-12, -12, -12, -12, -12, -12, -12, -12, -12},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 5, 3, 1, 3, 5},
+            std::vector<T>{1, 2, 0, 1},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{1, 3, 5, 0, 9, 12, 16, 5, 15, 20, 16, 3, 2, 7, 13, 5},
+            {1, 1},
+            {1, 1},
+            {1, 1},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 9, 7, 5, 3, 1, 0, 2, 4, 6, 8, 10, 8, 6, 4, 2, 0, 2, 4, 6, 8, 10},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{57, 94, 66, 102},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1, 3,  5,  7, 9, 11, 13, 7,  5,  3,  1, -1, -3, -5, 2,  4,  6,  8, 10, 12, 14, 8, 6,  4, 2,
+                           0, -2, -4, 2, 4, 6,  8,  10, 12, 14, 7, 5,  3,  1,  -1, -3, -5, 8, 6,  4,  2,  0, -2, -4},
+            std::vector<T>{1, 2, 3, 1, 1, 0, 3, 1, 2},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{78, 106, 134, 44, 16, -12, 80, 84, 88},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {2, 2}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1, 3,  5,  7, 9, 11, 13, 7,  5,  3,  1, -1, -3, -5, 2,  4,  6,  8, 10, 12, 14, 8, 6,  4, 2,
+                           0, -2, -4, 2, 4, 6,  8,  10, 12, 14, 7, 5,  3,  1,  -1, -3, -5, 8, 6,  4,  2,  0, -2, -4},
+            std::vector<T>{1, 2, 3, 1, 1, 0, 3, 1, 2},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{15, 38, 70, 66, 33, 78, 134, 103, 40, 80, 88, 58, 30, 56, 72, 34},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2}),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{1, 2, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1,
+                           3,
+                           5,
+                           7,
+                           7,
+                           5,
+                           3,
+                           1,
+                           2,
+                           4,
+                           6,
+                           8,
+                           8,
+                           6,
+                           4,
+                           2,
+                           // channel 2
+                           -1,
+                           3,
+                           -5,
+                           7,
+                           7,
+                           -5,
+                           3,
+                           -1,
+                           -2,
+                           4,
+                           -6,
+                           8,
+                           8,
+                           -6,
+                           4,
+                           -2},
+            std::vector<T>{// channel 1
+                           5,
+                           3,
+                           5,
+                           1,
+                           3,
+                           1,
+                           4,
+                           2,
+                           4,
+                           // channel 2
+                           -5,
+                           3,
+                           5,
+                           1,
+                           -3,
+                           1,
+                           4,
+                           2,
+                           -4},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{142, 102, 94, 160},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{2, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 7, 5, 3, 1, 2, 4, 6, 8, 8, 6, 4, 2},
+            std::vector<T>{// channel 1
+                           5,
+                           3,
+                           5,
+                           1,
+                           3,
+                           1,
+                           4,
+                           2,
+                           4,
+                           // channel 2
+                           -5,
+                           3,
+                           5,
+                           1,
+                           -3,
+                           1,
+                           4,
+                           2,
+                           -4},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{// channel 1
+                           104,
+                           140,
+                           145,
+                           109,
+                           // channel 2
+                           16,
+                           28,
+                           19,
+                           7},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{2, 1, 4, 4},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{2, 18, 2, 2},
+            PartialShape{2, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{// batch 1
+                           1,
+                           3,
+                           2,
+                           1,
+                           1,
+                           3,
+                           3,
+                           1,
+                           2,
+                           1,
+                           1,
+                           3,
+                           3,
+                           2,
+                           3,
+                           3,
+                           // batch 2
+                           -1,
+                           3,
+                           2,
+                           -1,
+                           1,
+                           3,
+                           -3,
+                           1,
+                           -2,
+                           -1,
+                           1,
+                           3,
+                           3,
+                           2,
+                           3,
+                           -3},
+            std::vector<T>{-5, 3, 5, 1, -3, 1, 4, 2, -4},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{// batch 1
+                           15,
+                           -15,
+                           23,
+                           2,
+                           // batch 2
+                           -1,
+                           -15,
+                           -5,
+                           6},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(PartialShape{1, 4, 3, 3},
+                                    PartialShape{2, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 2, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   // channel 2
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   17,
+                                                   18,
+                                                   // channel 3
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   // channel 4
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32,
+                                                   33,
+                                                   34,
+                                                   35,
+                                                   36},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // filter 1 channel 2
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // filter 2 channel 1
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // filter 2 channel 2
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8},
+                                    std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+                                    std::vector<T>{// channel 1
+                                                   356,
+                                                   392,
+                                                   464,
+                                                   500,
+                                                   // channel 2
+                                                   -1004,
+                                                   -1040,
+                                                   -1112,
+                                                   -1148},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    2),
+        DeformableConvolutionParams(PartialShape{1, 8, 3, 3},
+                                    PartialShape{4, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 4, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   // channel 2
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   17,
+                                                   18,
+                                                   // channel 3
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   // channel 4
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32,
+                                                   33,
+                                                   34,
+                                                   35,
+                                                   36,
+                                                   // channel 5
+                                                   37,
+                                                   38,
+                                                   39,
+                                                   40,
+                                                   41,
+                                                   42,
+                                                   43,
+                                                   44,
+                                                   45,
+                                                   // channel 6
+                                                   46,
+                                                   47,
+                                                   48,
+                                                   49,
+                                                   50,
+                                                   51,
+                                                   52,
+                                                   53,
+                                                   54,
+                                                   // channel 7
+                                                   55,
+                                                   56,
+                                                   57,
+                                                   58,
+                                                   59,
+                                                   60,
+                                                   61,
+                                                   62,
+                                                   63,
+                                                   // channel 8
+                                                   64,
+                                                   65,
+                                                   66,
+                                                   67,
+                                                   68,
+                                                   69,
+                                                   70,
+                                                   71,
+                                                   72},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // filter 1 channel 2
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // filter 2 channel 1
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   // filter 2 channel 2
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // filter 3 channel 1
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // filter 3 channel 2
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8,
+                                                   // filter 4 channel 1
+                                                   -9,
+                                                   -10,
+                                                   -11,
+                                                   -12,
+                                                   // filter 4 channel 2
+                                                   -13,
+                                                   -14,
+                                                   -15,
+                                                   -16},
+                                    std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                   0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+                                    std::vector<T>{// channel 1
+                                                   356,
+                                                   392,
+                                                   464,
+                                                   500,
+                                                   // channel 2
+                                                   2636,
+                                                   2736,
+                                                   2936,
+                                                   3036,
+                                                   // channel 3
+                                                   -1652,
+                                                   -1688,
+                                                   -1760,
+                                                   -1796,
+                                                   // channel 4
+                                                   -6236,
+                                                   -6336,
+                                                   -6536,
+                                                   -6636},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    4),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{1, 2, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1,
+                           2,
+                           3,
+                           4,
+                           5,
+                           6,
+                           7,
+                           8,
+                           9,
+                           10,
+                           11,
+                           12,
+                           13,
+                           14,
+                           15,
+                           16,
+                           // channel 2
+                           17,
+                           18,
+                           19,
+                           20,
+                           21,
+                           22,
+                           23,
+                           24,
+                           25,
+                           26,
+                           27,
+                           28,
+                           29,
+                           30,
+                           31,
+                           32},
+            std::vector<T>{// channel 1
+                           1,
+                           2,
+                           -1,
+                           -2,
+                           // channel 2
+                           3,
+                           4,
+                           -3,
+                           -4},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{-40, -40, -40, -40, -40, -40, -40, -40, -40},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 4, 3, 3},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            IN_ET,
+            std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18,
+                           19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36},
+            std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, -1, -2, -3, -4, -5, -6, -7, -8},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{356, 392, 464, 500, -1004, -1040, -1112, -1148},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            2,
+            2),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{1, 1, 2, 2},
+                                    PartialShape{1, 8, 3, 3},
+                                    PartialShape{1, 1, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16},
+                                    std::vector<T>{1, 2, -1, -2},
+                                    std::vector<T>{// window 1 (Y=0, X=0) -> Y coordinate
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 3
+                                                   1,
+                                                   1,
+                                                   1,  // out4 .. out 6
+                                                   1,
+                                                   1,
+                                                   1,  // out7 .. out 9
+                                                   // window 1 (Y=0, X=0) -> X coordinate
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 3
+                                                   1,
+                                                   1,
+                                                   1,  // out4 .. out 6
+                                                   1,
+                                                   1,
+                                                   1,  // out7 .. out 9
+                                                   // window 2
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 2
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 3
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 3
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 4
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 4
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1},
+                                    std::vector<T>{-12, -12, -4, -12, -12, -4, 44, 47, 16},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offsets_1"),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{1, 1, 3, 3},
+                                    PartialShape{1, 18, 4, 4},
+                                    PartialShape{1, 1, 4, 4},
+                                    IN_ET,
+                                    std::vector<T>{1, 3, 7, 7, 7, 6, 3, 1, 4, 4, 2, 8, 1, 1, 1, 2},
+                                    std::vector<T>{1, 2, 3, 0, 1, 0, 3, 2, 1},
+                                    std::vector<T>{1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2},
+                                    std::vector<T>{56, 39, 44, 18, 38, 56, 65, 0, 19, 38, 20, 20, 6, 19, 33, 0},
+                                    {1, 1},
+                                    {1, 1},
+                                    {1, 1},
+                                    {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 9, 7, 5, 3, 1, 0, 2, 4, 6, 8, 10, 8, 6, 4, 2, 0, 2, 4, 6, 8, 10},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0,
+                           0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0,
+                           0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0},
+            std::vector<T>{57, 40, 38, 102},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "integral_offsets_stride"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1, 3,  5,  7, 9, 11, 13, 7,  5,  3,  1, -1, -3, -5, 2,  4,  6,  8, 10, 12, 14, 8, 6,  4, 2,
+                           0, -2, -4, 2, 4, 6,  8,  10, 12, 14, 7, 5,  3,  1,  -1, -3, -5, 8, 6,  4,  2,  0, -2, -4},
+            std::vector<T>{1, 2, 3, 1, 1, 0, 3, 1, 2},
+            std::vector<T>{1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1,
+                           1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1,
+                           1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1,
+                           1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1,
+                           1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1,
+                           1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 1, 0, 0, 2, 0, 1, 0, 1, 1, 2, 0, 0, 2, 0, 1, 0, 1},
+            std::vector<T>{16, -2, 134, 44, -4, -12, 10, 84, -4},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {2, 2},
+            1,
+            1,
+            "integral_offset_dialation"),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 7, 7},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1, 3,  5,  7, 9, 11, 13, 7,  5,  3,  1, -1, -3, -5, 2,  4,  6,  8, 10, 12, 14, 8, 6,  4, 2,
+                           0, -2, -4, 2, 4, 6,  8,  10, 12, 14, 7, 5,  3,  1,  -1, -3, -5, 8, 6,  4,  2,  0, -2, -4},
+            std::vector<T>{1, 2, 3, 1, 1, 0, 3, 1, 2},
+            std::vector<T>{1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                           1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2},
+            std::vector<T>{15, 38, 2, 66, 26, 78, 134, 16, 23, 80, -4, 58, 13, 56, 72, -4},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            {2, 2},
+            1,
+            1,
+            "integral_offset_padding_stride_dialation"),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{1, 2, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1,
+                           3,
+                           5,
+                           7,
+                           7,
+                           5,
+                           3,
+                           1,
+                           2,
+                           4,
+                           6,
+                           8,
+                           8,
+                           6,
+                           4,
+                           2,
+                           // channel 2
+                           -1,
+                           3,
+                           -5,
+                           7,
+                           7,
+                           -5,
+                           3,
+                           -1,
+                           -2,
+                           4,
+                           -6,
+                           8,
+                           8,
+                           -6,
+                           4,
+                           -2},
+            std::vector<T>{// channel 1
+                           5,
+                           3,
+                           5,
+                           1,
+                           3,
+                           1,
+                           4,
+                           2,
+                           4,
+                           // channel 2
+                           -5,
+                           3,
+                           5,
+                           1,
+                           -3,
+                           1,
+                           4,
+                           2,
+                           -4},
+            std::vector<T>{1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2,
+                           1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2,
+                           1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2, 1, 1, 0, 2},
+            std::vector<T>{160, 32, 94, 20},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "integral_offset_input_channels"),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{2, 1, 2, 2},
+                                    PartialShape{1, 8, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16},
+                                    std::vector<T>{// filter 1
+                                                   1,
+                                                   2,
+                                                   -1,
+                                                   -2,
+                                                   // filter 2
+                                                   3,
+                                                   4,
+                                                   -3,
+                                                   -4},
+                                    std::vector<T>{// channel 1: Y offsets
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 3
+                                                   1,
+                                                   1,
+                                                   1,  // out4 .. out 6
+                                                   1,
+                                                   1,
+                                                   1,  // out7 .. out 9
+                                                   // channel 1: X offsets
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 3
+                                                   1,
+                                                   1,
+                                                   1,  // out4 .. out 6
+                                                   1,
+                                                   1,
+                                                   1,  // out7 .. out 9
+                                                   // channel 2: Y offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 2: X offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 3: Y offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 3: X offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 4: Y offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 4: X offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1},
+                                    std::vector<T>{// output 1
+                                                   -12,
+                                                   -12,
+                                                   -4,
+                                                   -12,
+                                                   -12,
+                                                   -4,
+                                                   44,
+                                                   47,
+                                                   16,
+                                                   // output 2
+                                                   -28,
+                                                   -28,
+                                                   -12,
+                                                   -28,
+                                                   -28,
+                                                   -12,
+                                                   102,
+                                                   109,
+                                                   48},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offset_output_channels"),
+        DeformableConvolutionParams(PartialShape{2, 1, 4, 4},
+                                    PartialShape{1, 1, 2, 2},
+                                    PartialShape{2, 8, 3, 3},
+                                    PartialShape{2, 1, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// batch 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // batch 2
+                                                   17,
+                                                   18,
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32},
+                                    std::vector<T>{1, 2, -1, -2},
+                                    std::vector<T>{// batch1
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // batch2
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0},
+                                    std::vector<T>{// batch 1
+                                                   -12,
+                                                   -12,
+                                                   -4,
+                                                   -12,
+                                                   -12,
+                                                   -4,
+                                                   44,
+                                                   47,
+                                                   16,
+                                                   // batch 2
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offset_batch"),
+        DeformableConvolutionParams(PartialShape{1, 4, 3, 3},
+                                    PartialShape{2, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 2, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   // channel 2
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   17,
+                                                   18,
+                                                   // channel 3
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   // channel 4
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32,
+                                                   33,
+                                                   34,
+                                                   35,
+                                                   36},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // filter 1 channel 2
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // filter 2 channel 1
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // filter 2 channel 2
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8},
+                                    std::vector<T>{// window 1 (F_Y=0, F_X=0) -> I_Y coordinate
+                                                   1,
+                                                   0,
+                                                   2,
+                                                   1,  // out1 .. out 4
+                                                   // window 1 (F_Y=0, F_X=0) -> I_X coordinate
+                                                   0,
+                                                   1,
+                                                   1,
+                                                   2,  // out1 .. out 4
+                                                   // window 2 (F_Y=0, F_X=1) -> I_Y coordinate
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 4
+                                                   // window 2 (F_Y=0, F_X=1) -> I_X coordinate
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 4
+                                                   // window 3 (F_Y=1, F_X=0) -> I_Y coordinate
+                                                   2,
+                                                   2,
+                                                   2,
+                                                   2,  // out1 .. out 4
+                                                   // window 3 (F_Y=1, F_X=0) -> I_X coordinate
+                                                   2,
+                                                   2,
+                                                   2,
+                                                   2,  // out1 .. out 4
+                                                   // window 4 (F_Y=1, F_X=1) -> I_Y coordinate
+                                                   2,
+                                                   2,
+                                                   2,
+                                                   2,  // out1 .. out 4
+                                                   // window 4 (F_Y=1, F_X=1) -> I_X coordinate
+                                                   2,
+                                                   2,
+                                                   2,
+                                                   2},  // out1 .. out 4
+                                    std::vector<T>{     // channel 1
+                                                   171,
+                                                   63,
+                                                   126,
+                                                   0,
+                                                   // channel 2
+                                                   -423,
+                                                   -171,
+                                                   -270,
+                                                   0},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    2,
+                                    1,
+                                    "integral_offset_groups_basic"),
+        DeformableConvolutionParams(PartialShape{1, 8, 3, 3},
+                                    PartialShape{4, 2, 2, 2},
+                                    PartialShape{1, 8, 2, 2},
+                                    PartialShape{1, 4, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   // channel 2
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   17,
+                                                   18,
+                                                   // channel 3
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   // channel 4
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32,
+                                                   33,
+                                                   34,
+                                                   35,
+                                                   36,
+                                                   // channel 5
+                                                   37,
+                                                   38,
+                                                   39,
+                                                   40,
+                                                   41,
+                                                   42,
+                                                   43,
+                                                   44,
+                                                   45,
+                                                   // channel 6
+                                                   46,
+                                                   47,
+                                                   48,
+                                                   49,
+                                                   50,
+                                                   51,
+                                                   52,
+                                                   53,
+                                                   54,
+                                                   // channel 7
+                                                   55,
+                                                   56,
+                                                   57,
+                                                   58,
+                                                   59,
+                                                   60,
+                                                   61,
+                                                   62,
+                                                   63,
+                                                   // channel 8
+                                                   64,
+                                                   65,
+                                                   66,
+                                                   67,
+                                                   68,
+                                                   69,
+                                                   70,
+                                                   71,
+                                                   72},
+                                    std::vector<T>{// filter 1 channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // filter 1 channel 2
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // filter 2 channel 1
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   // filter 2 channel 2
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // filter 3 channel 1
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // filter 3 channel 2
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8,
+                                                   // filter 4 channel 1
+                                                   -9,
+                                                   -10,
+                                                   -11,
+                                                   -12,
+                                                   // filter 4 channel 2
+                                                   -13,
+                                                   -14,
+                                                   -15,
+                                                   -16},
+                                    std::vector<T>{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
+                                                   1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1},
+                                    std::vector<T>{// channel 1
+                                                   500,
+                                                   234,
+                                                   219,
+                                                   99,
+                                                   // channel 2
+                                                   3036,
+                                                   1482,
+                                                   1463,
+                                                   711,
+                                                   // channel 3
+                                                   -1796,
+                                                   -810,
+                                                   -723,
+                                                   -315,
+                                                   // channel 4
+                                                   -6636,
+                                                   -3210,
+                                                   -3119,
+                                                   -1503},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    4,
+                                    1,
+                                    "integral_offset_groups_complex"),
+        DeformableConvolutionParams(PartialShape{1, 2, 4, 4},
+                                    PartialShape{2, 2, 2, 2},
+                                    PartialShape{1, 16, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // channel 2
+                                                   17,
+                                                   18,
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32},
+                                    std::vector<T>{// f1: channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // f1: channel 2
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // f2: channel 1
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // f2: channel 2
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8},
+                                    std::vector<T>{// defgroup 1
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   //  defgroup 2
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0},
+                                    std::vector<T>{// output 1
+                                                   610,
+                                                   646,
+                                                   612,
+                                                   754,
+                                                   790,
+                                                   732,
+                                                   768,
+                                                   797,
+                                                   792,
+                                                   // output 2
+                                                   -610,
+                                                   -646,
+                                                   -612,
+                                                   -754,
+                                                   -790,
+                                                   -732,
+                                                   -768,
+                                                   -797,
+                                                   -792},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    2,
+                                    "integral_offset_deforgroup_basic"),
+        DeformableConvolutionParams(PartialShape{1, 4, 4, 4},
+                                    PartialShape{2, 4, 2, 2},
+                                    PartialShape{1, 32, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // channel 2
+                                                   17,
+                                                   18,
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32,
+                                                   // channel 3
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // channel 4
+                                                   17,
+                                                   18,
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32},
+                                    std::vector<T>{// f1: channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // f1: channel 2
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // f1: channel 3
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // f1: channel 4
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // f2: channel 1
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // f2: channel 2
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8,
+                                                   // f2: channel 3
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // f2: channel 4
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8},
+                                    std::vector<T>{// defgroup 1
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   //  defgroup 2
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   // defgroup 3
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   //  defgroup 4
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0},
+                                    std::vector<T>{// output 1
+                                                   1220,
+                                                   1292,
+                                                   1224,
+                                                   1508,
+                                                   1580,
+                                                   1464,
+                                                   1536,
+                                                   1594,
+                                                   1584,
+                                                   // output 2
+                                                   -1220,
+                                                   -1292,
+                                                   -1224,
+                                                   -1508,
+                                                   -1580,
+                                                   -1464,
+                                                   -1536,
+                                                   -1594,
+                                                   -1584},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    4,
+                                    "integral_offset_deforgroup_complex1"),
+        DeformableConvolutionParams(PartialShape{1, 4, 4, 4},
+                                    PartialShape{2, 4, 2, 2},
+                                    PartialShape{1, 16, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // channel 2
+                                                   17,
+                                                   18,
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32,
+                                                   // channel 3
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // channel 4
+                                                   17,
+                                                   18,
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32},
+                                    std::vector<T>{// f1: channel 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // f1: channel 2
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // f1: channel 3
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   // f1: channel 4
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   // f2: channel 1
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // f2: channel 2
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8,
+                                                   // f2: channel 3
+                                                   -1,
+                                                   -2,
+                                                   -3,
+                                                   -4,
+                                                   // f2: channel 4
+                                                   -5,
+                                                   -6,
+                                                   -7,
+                                                   -8},
+                                    std::vector<T>{// defgroup 1
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   //  defgroup 2
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0},
+                                    std::vector<T>{// output 1
+                                                   1300,
+                                                   1372,
+                                                   992,
+                                                   1588,
+                                                   1660,
+                                                   1200,
+                                                   1228,
+                                                   1278,
+                                                   1096,
+                                                   // output 2
+                                                   -1300,
+                                                   -1372,
+                                                   -992,
+                                                   -1588,
+                                                   -1660,
+                                                   -1200,
+                                                   -1228,
+                                                   -1278,
+                                                   -1096},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    2,
+                                    "integral_offset_deforgroup_complex2"),
+        DeformableConvolutionParams(
+            PartialShape{1, 4, 3, 3},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            IN_ET,
+            std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18,
+                           19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36},
+            std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, -1, -2, -3, -4, -5, -6, -7, -8},
+            std::vector<T>{// defgroup 1
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           1,
+                           // defgroup 2
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0,
+                           0},
+            std::vector<T>{500, 234, 219, 99, -1004, -1040, -1112, -1148},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            2,
+            2,
+            "integral_offset_groups_and_deforgroups"),
     };
     return deformableConvolutionParams;
 }
@@ -4625,583 +6723,687 @@ template <element::Type_t IN_ET>
 std::vector<DeformableConvolutionParams> generateDeformableConvolutionInt8Params() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DeformableConvolutionParams> deformableConvolutionParams {
-// --------------------- 2D DeformableConvolution ------------------------------------------
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16},
-                          std::vector<T>{
-                                    1, 2,
-                                    -1, -2},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    -12, -12, -12,
-                                    -12, -12, -12,
-                                    -12, -12, -12},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5,
-                                    7, 5, 3,
-                                    1, 3, 5},
-                          std::vector<T>{
-                                    1, 2,
-                                    0, 1},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    1, 3, 5, 0,
-                                    9, 12, 16, 5,
-                                    15, 20, 16, 3,
-                                    2, 7, 13, 5},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9,
-                                    7, 5, 3, 1, 0,
-                                    2, 4, 6, 8, 10,
-                                    8, 6, 4, 2, 0,
-                                    2, 4, 6, 8, 10},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    57, 94,
-                                    66, 102},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {2, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {2, 18, 2, 2},
-                          PartialShape {2, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    // batch 1
-                                    1, 3, 2, 1,
-                                    1, 3, 3, 1,
-                                    2, 1, 1, 3,
-                                    3, 2, 3, 3,
-                                    // batch 2
-                                    -1, 3, 2, -1,
-                                    1, 3, -3, 1,
-                                    -2, -1, 1, 3,
-                                    3, 2, 3, -3},
-                          std::vector<T>{
-                                   -5, 3, 5,
-                                    1, -3, 1,
-                                    4, 2, -4},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    // batch 1
-                                    15, -15,
-                                    23, 2,
-                                    // batch 2
-                                    -1, -15,
-                                    -5, 6},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 2, 4, 4},
-                          PartialShape {1, 2, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    // channel 2
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32},
-                          std::vector<T>{
-                                    // channel 1
-                                    1, 2,
-                                    -1, -2,
-                                    // channel 2
-                                    3, 4,
-                                    -3, -4},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    -40, -40, -40,
-                                    -40, -40, -40,
-                                    -40, -40, -40},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16},
-                          std::vector<T>{
-                                    1, 2,
-                                    -1, -2},
-                          std::vector<T>{
-                                    // window 1 (Y=0, X=0) -> Y coordinate
-                                    1, 1, 1, // out1 .. out 3
-                                    1, 1, 1, // out4 .. out 6
-                                    1, 1, 1, // out7 .. out 9
-                                    // window 1 (Y=0, X=0) -> X coordinate
-                                    1, 1, 1, // out1 .. out 3
-                                    1, 1, 1, // out4 .. out 6
-                                    1, 1, 1, // out7 .. out 9
-                                    // window 2
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 2
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 3
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 3
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 4
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // window 4
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1},
-                          std::vector<T>{
-                                    -12, -12, -4,
-                                    -12, -12, -4,
-                                    44, 47, 16},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offsets_1"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 7, 7,
-                                    7, 6, 3, 1,
-                                    4, 4, 2, 8,
-                                    1, 1, 1, 2},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2},
-                          std::vector<T>{
-                                    56, 39, 44, 18,
-                                    38, 56, 65, 0,
-                                    19, 38, 20, 20,
-                                    6, 19, 33, 0},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9,
-                                    7, 5, 3, 1, 0,
-                                    2, 4, 6, 8, 10,
-                                    8, 6, 4, 2, 0,
-                                    2, 4, 6, 8, 10},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0},
-                          std::vector<T>{
-                                    57, 40,
-                                    38, 102},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offsets_stride"),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {2, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 2, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16},
-                          std::vector<T>{
-                                    // filter 1
-                                    1, 2,
-                                    -1, -2,
-                                    // filter 2
-                                    3, 4,
-                                    -3, -4},
-                          std::vector<T>{
-                                    //channel 1: Y offsets
-                                    1, 1, 1, // out1 .. out 3
-                                    1, 1, 1, // out4 .. out 6
-                                    1, 1, 1, // out7 .. out 9
-                                    //channel 1: X offsets
-                                    1, 1, 1, // out1 .. out 3
-                                    1, 1, 1, // out4 .. out 6
-                                    1, 1, 1, // out7 .. out 9
-                                    //channel 2: Y offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 2: X offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 3: Y offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 3: X offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 4: Y offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    //channel 4: X offsets
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1},
-                          std::vector<T>{
-                                    // output 1
-                                    -12, -12, -4,
-                                    -12, -12, -4,
-                                    44, 47, 16,
-                                    // output 2
-                                    -28, -28, -12,
-                                    -28, -28, -12,
-                                    102, 109, 48},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offset_output_channels"),
-        DeformableConvolutionParams(PartialShape {2, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {2, 8, 3, 3},
-                          PartialShape {2, 1, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    //batch 1
-                                    1, 2, 3, 4,
-                                    5, 6, 7, 8,
-                                    9, 10, 11, 12,
-                                    13, 14, 15, 16,
-                                    //batch 2
-                                    17, 18, 19, 20,
-                                    21, 22, 23, 24,
-                                    25, 26, 27, 28,
-                                    29, 30, 31, 32},
-                          std::vector<T>{
-                                    1, 2,
-                                    -1, -2},
-                          std::vector<T>{
-                                    // batch1
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    1, 1, 1,
-                                    // batch2
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0,
-
-                                    0, 0, 0,
-                                    0, 0, 0,
-                                    0, 0, 0},
-                          std::vector<T>{
-                                    // batch 1
-                                    -12, -12, -4,
-                                    -12, -12, -4,
-                                    44, 47, 16,
-                                    // batch 2
-                                    -12, -12, -12,
-                                    -12, -12, -12,
-                                    -12, -12, -12},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offset_batch"),
+    std::vector<DeformableConvolutionParams> deformableConvolutionParams{
+        // --------------------- 2D DeformableConvolution ------------------------------------------
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16},
+            std::vector<T>{1, 2, -1, -2},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{-12, -12, -12, -12, -12, -12, -12, -12, -12},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 5, 3, 1, 3, 5},
+            std::vector<T>{1, 2, 0, 1},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{1, 3, 5, 0, 9, 12, 16, 5, 15, 20, 16, 3, 2, 7, 13, 5},
+            {1, 1},
+            {1, 1},
+            {1, 1},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 9, 7, 5, 3, 1, 0, 2, 4, 6, 8, 10, 8, 6, 4, 2, 0, 2, 4, 6, 8, 10},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{57, 94, 66, 102},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{2, 1, 4, 4},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{2, 18, 2, 2},
+            PartialShape{2, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{// batch 1
+                           1,
+                           3,
+                           2,
+                           1,
+                           1,
+                           3,
+                           3,
+                           1,
+                           2,
+                           1,
+                           1,
+                           3,
+                           3,
+                           2,
+                           3,
+                           3,
+                           // batch 2
+                           -1,
+                           3,
+                           2,
+                           -1,
+                           1,
+                           3,
+                           -3,
+                           1,
+                           -2,
+                           -1,
+                           1,
+                           3,
+                           3,
+                           2,
+                           3,
+                           -3},
+            std::vector<T>{-5, 3, 5, 1, -3, 1, 4, 2, -4},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{// batch 1
+                           15,
+                           -15,
+                           23,
+                           2,
+                           // batch 2
+                           -1,
+                           -15,
+                           -5,
+                           6},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 4, 4},
+            PartialShape{1, 2, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            IN_ET,
+            std::vector<T>{// channel 1
+                           1,
+                           2,
+                           3,
+                           4,
+                           5,
+                           6,
+                           7,
+                           8,
+                           9,
+                           10,
+                           11,
+                           12,
+                           13,
+                           14,
+                           15,
+                           16,
+                           // channel 2
+                           17,
+                           18,
+                           19,
+                           20,
+                           21,
+                           22,
+                           23,
+                           24,
+                           25,
+                           26,
+                           27,
+                           28,
+                           29,
+                           30,
+                           31,
+                           32},
+            std::vector<T>{// channel 1
+                           1,
+                           2,
+                           -1,
+                           -2,
+                           // channel 2
+                           3,
+                           4,
+                           -3,
+                           -4},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{-40, -40, -40, -40, -40, -40, -40, -40, -40},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{1, 1, 2, 2},
+                                    PartialShape{1, 8, 3, 3},
+                                    PartialShape{1, 1, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16},
+                                    std::vector<T>{1, 2, -1, -2},
+                                    std::vector<T>{// window 1 (Y=0, X=0) -> Y coordinate
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 3
+                                                   1,
+                                                   1,
+                                                   1,  // out4 .. out 6
+                                                   1,
+                                                   1,
+                                                   1,  // out7 .. out 9
+                                                   // window 1 (Y=0, X=0) -> X coordinate
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 3
+                                                   1,
+                                                   1,
+                                                   1,  // out4 .. out 6
+                                                   1,
+                                                   1,
+                                                   1,  // out7 .. out 9
+                                                   // window 2
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 2
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 3
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 3
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 4
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // window 4
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1},
+                                    std::vector<T>{-12, -12, -4, -12, -12, -4, 44, 47, 16},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offsets_1"),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{1, 1, 3, 3},
+                                    PartialShape{1, 18, 4, 4},
+                                    PartialShape{1, 1, 4, 4},
+                                    IN_ET,
+                                    std::vector<T>{1, 3, 7, 7, 7, 6, 3, 1, 4, 4, 2, 8, 1, 1, 1, 2},
+                                    std::vector<T>{1, 2, 3, 0, 1, 0, 3, 2, 1},
+                                    std::vector<T>{1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2},
+                                    std::vector<T>{56, 39, 44, 18, 38, 56, 65, 0, 19, 38, 20, 20, 6, 19, 33, 0},
+                                    {1, 1},
+                                    {1, 1},
+                                    {1, 1},
+                                    {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 9, 7, 5, 3, 1, 0, 2, 4, 6, 8, 10, 8, 6, 4, 2, 0, 2, 4, 6, 8, 10},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0,
+                           0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0,
+                           0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0},
+            std::vector<T>{57, 40, 38, 102},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "integral_offsets_stride"),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{2, 1, 2, 2},
+                                    PartialShape{1, 8, 3, 3},
+                                    PartialShape{1, 2, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16},
+                                    std::vector<T>{// filter 1
+                                                   1,
+                                                   2,
+                                                   -1,
+                                                   -2,
+                                                   // filter 2
+                                                   3,
+                                                   4,
+                                                   -3,
+                                                   -4},
+                                    std::vector<T>{// channel 1: Y offsets
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 3
+                                                   1,
+                                                   1,
+                                                   1,  // out4 .. out 6
+                                                   1,
+                                                   1,
+                                                   1,  // out7 .. out 9
+                                                   // channel 1: X offsets
+                                                   1,
+                                                   1,
+                                                   1,  // out1 .. out 3
+                                                   1,
+                                                   1,
+                                                   1,  // out4 .. out 6
+                                                   1,
+                                                   1,
+                                                   1,  // out7 .. out 9
+                                                   // channel 2: Y offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 2: X offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 3: Y offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 3: X offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 4: Y offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // channel 4: X offsets
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1},
+                                    std::vector<T>{// output 1
+                                                   -12,
+                                                   -12,
+                                                   -4,
+                                                   -12,
+                                                   -12,
+                                                   -4,
+                                                   44,
+                                                   47,
+                                                   16,
+                                                   // output 2
+                                                   -28,
+                                                   -28,
+                                                   -12,
+                                                   -28,
+                                                   -28,
+                                                   -12,
+                                                   102,
+                                                   109,
+                                                   48},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offset_output_channels"),
+        DeformableConvolutionParams(PartialShape{2, 1, 4, 4},
+                                    PartialShape{1, 1, 2, 2},
+                                    PartialShape{2, 8, 3, 3},
+                                    PartialShape{2, 1, 3, 3},
+                                    IN_ET,
+                                    std::vector<T>{// batch 1
+                                                   1,
+                                                   2,
+                                                   3,
+                                                   4,
+                                                   5,
+                                                   6,
+                                                   7,
+                                                   8,
+                                                   9,
+                                                   10,
+                                                   11,
+                                                   12,
+                                                   13,
+                                                   14,
+                                                   15,
+                                                   16,
+                                                   // batch 2
+                                                   17,
+                                                   18,
+                                                   19,
+                                                   20,
+                                                   21,
+                                                   22,
+                                                   23,
+                                                   24,
+                                                   25,
+                                                   26,
+                                                   27,
+                                                   28,
+                                                   29,
+                                                   30,
+                                                   31,
+                                                   32},
+                                    std::vector<T>{1, 2, -1, -2},
+                                    std::vector<T>{// batch1
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   1,
+                                                   // batch2
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0,
+                                                   0},
+                                    std::vector<T>{// batch 1
+                                                   -12,
+                                                   -12,
+                                                   -4,
+                                                   -12,
+                                                   -12,
+                                                   -4,
+                                                   44,
+                                                   47,
+                                                   16,
+                                                   // batch 2
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12,
+                                                   -12},
+                                    {1, 1},
+                                    {0, 0},
+                                    {0, 0},
+                                    {1, 1},
+                                    1,
+                                    1,
+                                    "integral_offset_batch"),
     };
     return deformableConvolutionParams;
 }
@@ -5210,248 +7412,108 @@ template <element::Type_t IN_ET>
 std::vector<DeformableConvolutionParams> generateDeformableConvolutionUintParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DeformableConvolutionParams> deformableConvolutionParams {
-// --------------------- 2D DeformableConvolution ------------------------------------------
-        DeformableConvolutionParams(PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5,
-                                    7, 5, 3,
-                                    1, 3, 5},
-                          std::vector<T>{
-                                    1, 2,
-                                    0, 1},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    1, 3, 5, 0,
-                                    9, 12, 16, 5,
-                                    15, 20, 16, 3,
-                                    2, 7, 13, 5},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9,
-                                    7, 5, 3, 1, 0,
-                                    2, 4, 6, 8, 10,
-                                    8, 6, 4, 2, 0,
-                                    2, 4, 6, 8, 10},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-                                    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
-                          std::vector<T>{
-                                    57, 94,
-                                    66, 102},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 4, 4},
-                          PartialShape {1, 1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 7, 7,
-                                    7, 6, 3, 1,
-                                    4, 4, 2, 8,
-                                    1, 1, 1, 2},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    0, 1, 0,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2,
-                                    1, 0, 1, 0,
-                                    1, 0, 0, 2},
-                          std::vector<T>{
-                                    56, 39, 44, 18,
-                                    38, 56, 65, 0,
-                                    19, 38, 20, 20,
-                                    6, 19, 33, 0},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
-        DeformableConvolutionParams(PartialShape {1, 1, 5, 5},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 18, 2, 2},
-                          PartialShape {1, 1, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1, 3, 5, 7, 9,
-                                    7, 5, 3, 1, 0,
-                                    2, 4, 6, 8, 10,
-                                    8, 6, 4, 2, 0,
-                                    2, 4, 6, 8, 10},
-                          std::vector<T>{
-                                    1, 2, 3,
-                                    1, 1, 1,
-                                    3, 2, 1},
-                          std::vector<T>{
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0,
-                                    0, 2,
-                                    1, 0},
-                          std::vector<T>{
-                                    57, 40,
-                                    38, 102},
-                          {2, 2},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "integral_offsets_stride"),
+    std::vector<DeformableConvolutionParams> deformableConvolutionParams{
+        // --------------------- 2D DeformableConvolution ------------------------------------------
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 4, 4},
+            PartialShape{1, 1, 4, 4},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 5, 3, 1, 3, 5},
+            std::vector<T>{1, 2, 0, 1},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{1, 3, 5, 0, 9, 12, 16, 5, 15, 20, 16, 3, 2, 7, 13, 5},
+            {1, 1},
+            {1, 1},
+            {1, 1},
+            {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 9, 7, 5, 3, 1, 0, 2, 4, 6, 8, 10, 8, 6, 4, 2, 0, 2, 4, 6, 8, 10},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                           0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+            std::vector<T>{57, 94, 66, 102},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1}),
+        DeformableConvolutionParams(PartialShape{1, 1, 4, 4},
+                                    PartialShape{1, 1, 3, 3},
+                                    PartialShape{1, 18, 4, 4},
+                                    PartialShape{1, 1, 4, 4},
+                                    IN_ET,
+                                    std::vector<T>{1, 3, 7, 7, 7, 6, 3, 1, 4, 4, 2, 8, 1, 1, 1, 2},
+                                    std::vector<T>{1, 2, 3, 0, 1, 0, 3, 2, 1},
+                                    std::vector<T>{1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2,
+
+                                                   1, 0, 1, 0, 1, 0, 0, 2, 1, 0, 1, 0, 1, 0, 0, 2},
+                                    std::vector<T>{56, 39, 44, 18, 38, 56, 65, 0, 19, 38, 20, 20, 6, 19, 33, 0},
+                                    {1, 1},
+                                    {1, 1},
+                                    {1, 1},
+                                    {1, 1}),
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 5, 5},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 18, 2, 2},
+            PartialShape{1, 1, 2, 2},
+            IN_ET,
+            std::vector<T>{1, 3, 5, 7, 9, 7, 5, 3, 1, 0, 2, 4, 6, 8, 10, 8, 6, 4, 2, 0, 2, 4, 6, 8, 10},
+            std::vector<T>{1, 2, 3, 1, 1, 1, 3, 2, 1},
+            std::vector<T>{0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0,
+                           0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0,
+                           0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0, 0, 2, 1, 0},
+            std::vector<T>{57, 40, 38, 102},
+            {2, 2},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "integral_offsets_stride"),
     };
     return deformableConvolutionParams;
 }
@@ -5460,287 +7522,214 @@ template <element::Type_t IN_ET>
 std::vector<DeformableConvolutionParams> generateDeformableConvolutionV8MaskParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DeformableConvolutionParams> deformableConvolutionParams {
-        DeformableConvolutionParams(PartialShape {1, 1, 4, 4},
-                          PartialShape {1, 1, 2, 2},
-                          PartialShape {1, 8, 3, 3},
-                          PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 4, 3, 3},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f, 4.0f,
-                                    5.0f, 6.0f, 7.0f, 8.0f,
-                                    9.0f, 10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f, 16.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    -1.0f, -2.0f},
-                          std::vector<T>{
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                    0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f},
-                          std::vector<T>{
-                                    -6.0f, -6.0f, -6.0f,
-                                    -6.0f, -6.0f, -6.0f,
-                                    -6.0f, -6.0f, -6.0f},
-                          std::vector<T>{
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f,
-                                    0.5f, 0.5f, 0.5f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          1,
-                          "v8_zeroed_offset_default_mask",
-                          true),
-        DeformableConvolutionParams(PartialShape {1, 4, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f,
-                                    19.0f, 20.0f, 21.0f,
-                                    22.0f, 23.0f, 24.0f,
-                                    25.0f, 26.0f, 27.0f,
-                                    28.0f, 29.0f, 30.0f,
-                                    31.0f, 32.0f, 33.0f,
-                                    34.0f, 35.0f, 36.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    220.15443f ,   38.199608f,
-                                    32.643005f,   59.340614f,
-                                    -419.0005f  , -252.08015f,
-                                    -182.44444f , -165.99335f},
-                          std::vector<T>{
-                                    0.64f,
-                                    0.18f,
-                                    0.23f,
-                                    0.74f,
-                                    0.89f,
-                                    0.70f,
-                                    0.13f,
-                                    0.99f,
-                                    0.48f,
-                                    0.20f,
-                                    0.67f,
-                                    0.88f,
-                                    0.17f,
-                                    0.19f,
-                                    0.53f,
-                                    0.22f,
-                                    0.50f,
-                                    0.07f,
-                                    0.21f,
-                                    0.99f,
-                                    0.09f,
-                                    0.28f,
-                                    0.66f,
-                                    0.91f,
-                                    0.28f,
-                                    0.89f,
-                                    0.91f,
-                                    0.39f,
-                                    0.70f,
-                                    0.67f,
-                                    0.26f,
-                                    0.09f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          2,
-                          2,
-                          "v8_real_offset_groups_deforgroups_mask",
-                          true),
-        DeformableConvolutionParams(PartialShape {1, 2, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
-                                    1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
-                          std::vector<T>{
-                                    184.25163,  101.04752,
-                                    77.46842,   77.56562,
-                                    -184.25163, -101.04752,
-                                    -77.46842,  -77.56562},
-                          std::vector<T>{
-                                    0.64f,
-                                    0.18f,
-                                    0.23f,
-                                    0.74f,
-                                    0.89f,
-                                    0.70f,
-                                    0.13f,
-                                    0.99f,
-                                    0.48f,
-                                    0.20f,
-                                    0.67f,
-                                    0.88f,
-                                    0.17f,
-                                    0.19f,
-                                    0.53f,
-                                    0.22f,
-                                    0.50f,
-                                    0.07f,
-                                    0.21f,
-                                    0.99f,
-                                    0.09f,
-                                    0.28f,
-                                    0.66f,
-                                    0.91f,
-                                    0.28f,
-                                    0.89f,
-                                    0.91f,
-                                    0.39f,
-                                    0.70f,
-                                    0.67f,
-                                    0.26f,
-                                    0.09f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          2,
-                          "v8_real_offset_groups_deforgroups_mask_2",
-                          true),
-        DeformableConvolutionParams(PartialShape {1, 2, 3, 3},
-                          PartialShape {2, 2, 2, 2},
-                          PartialShape {1, 16, 2, 2},
-                          PartialShape {1, 2, 2, 2},
-                          PartialShape {1, 8, 2, 2},
-                          IN_ET,
-                          std::vector<T>{
-                                    1.0f, 2.0f, 3.0f,
-                                    4.0f, 5.0f, 6.0f,
-                                    7.0f, 8.0f, 9.0f,
-                                    10.0f, 11.0f, 12.0f,
-                                    13.0f, 14.0f, 15.0f,
-                                    16.0f, 17.0f, 18.0f},
-                          std::vector<T>{
-                                    1.0f, 2.0f,
-                                    3.0f, 4.0f,
-                                    5.0f, 6.0f,
-                                    7.0f, 8.0f,
-                                    -1.0f, -2.0f,
-                                    -3.0f, -4.0f,
-                                    -5.0f, -6.0f,
-                                    -7.0f, -8.0f},
-                          std::vector<T>{
-                                    -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f,
-                                    -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f,
-                                    -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f,
-                                    -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f},
-                          std::vector<T>{
-                                    45.910797,  104.8302,
-                                    63.12059 ,  151.47789,
-                                    -45.910797, -104.8302,
-                                    -63.12059 , -151.47789},
-                          std::vector<T>{
-                                    0.64f,
-                                    0.18f,
-                                    0.23f,
-                                    0.74f,
-                                    0.89f,
-                                    0.70f,
-                                    0.13f,
-                                    0.99f,
-                                    0.48f,
-                                    0.20f,
-                                    0.67f,
-                                    0.88f,
-                                    0.17f,
-                                    0.19f,
-                                    0.53f,
-                                    0.22f,
-                                    0.50f,
-                                    0.07f,
-                                    0.21f,
-                                    0.99f,
-                                    0.09f,
-                                    0.28f,
-                                    0.66f,
-                                    0.91f,
-                                    0.28f,
-                                    0.89f,
-                                    0.91f,
-                                    0.39f,
-                                    0.70f,
-                                    0.67f,
-                                    0.26f,
-                                    0.09f},
-                          {1, 1},
-                          {0, 0},
-                          {0, 0},
-                          {1, 1},
-                          1,
-                          2,
-                          "v8_neg_offset_groups_deforgroups_mask",
-                          true),
+    std::vector<DeformableConvolutionParams> deformableConvolutionParams{
+        DeformableConvolutionParams(
+            PartialShape{1, 1, 4, 4},
+            PartialShape{1, 1, 2, 2},
+            PartialShape{1, 8, 3, 3},
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 4, 3, 3},
+            IN_ET,
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f},
+            std::vector<T>{1.0f, 2.0f, -1.0f, -2.0f},
+            std::vector<T>{0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+                           0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+                           0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+                           0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+                           0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f},
+            std::vector<T>{-6.0f, -6.0f, -6.0f, -6.0f, -6.0f, -6.0f, -6.0f, -6.0f, -6.0f},
+            std::vector<T>{0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,
+                           0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f,
+                           0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f, 0.5f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            1,
+            "v8_zeroed_offset_default_mask",
+            true),
+        DeformableConvolutionParams(
+            PartialShape{1, 4, 3, 3},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            PartialShape{1, 8, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f,  2.0f,  3.0f,  4.0f,  5.0f,  6.0f,  7.0f,  8.0f,  9.0f,  10.0f, 11.0f, 12.0f,
+                           13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f, 19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f,
+                           25.0f, 26.0f, 27.0f, 28.0f, 29.0f, 30.0f, 31.0f, 32.0f, 33.0f, 34.0f, 35.0f, 36.0f},
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<
+                T>{220.15443f, 38.199608f, 32.643005f, 59.340614f, -419.0005f, -252.08015f, -182.44444f, -165.99335f},
+            std::vector<T>{0.64f, 0.18f, 0.23f, 0.74f, 0.89f, 0.70f, 0.13f, 0.99f, 0.48f, 0.20f, 0.67f,
+                           0.88f, 0.17f, 0.19f, 0.53f, 0.22f, 0.50f, 0.07f, 0.21f, 0.99f, 0.09f, 0.28f,
+                           0.66f, 0.91f, 0.28f, 0.89f, 0.91f, 0.39f, 0.70f, 0.67f, 0.26f, 0.09f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            2,
+            2,
+            "v8_real_offset_groups_deforgroups_mask",
+            true),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 3, 3},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            PartialShape{1, 8, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           17.0f,
+                           18.0f},
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f,
+                           1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f, 1.1f},
+            std::vector<T>{184.25163, 101.04752, 77.46842, 77.56562, -184.25163, -101.04752, -77.46842, -77.56562},
+            std::vector<T>{0.64f, 0.18f, 0.23f, 0.74f, 0.89f, 0.70f, 0.13f, 0.99f, 0.48f, 0.20f, 0.67f,
+                           0.88f, 0.17f, 0.19f, 0.53f, 0.22f, 0.50f, 0.07f, 0.21f, 0.99f, 0.09f, 0.28f,
+                           0.66f, 0.91f, 0.28f, 0.89f, 0.91f, 0.39f, 0.70f, 0.67f, 0.26f, 0.09f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            2,
+            "v8_real_offset_groups_deforgroups_mask_2",
+            true),
+        DeformableConvolutionParams(
+            PartialShape{1, 2, 3, 3},
+            PartialShape{2, 2, 2, 2},
+            PartialShape{1, 16, 2, 2},
+            PartialShape{1, 2, 2, 2},
+            PartialShape{1, 8, 2, 2},
+            IN_ET,
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           9.0f,
+                           10.0f,
+                           11.0f,
+                           12.0f,
+                           13.0f,
+                           14.0f,
+                           15.0f,
+                           16.0f,
+                           17.0f,
+                           18.0f},
+            std::vector<T>{1.0f,
+                           2.0f,
+                           3.0f,
+                           4.0f,
+                           5.0f,
+                           6.0f,
+                           7.0f,
+                           8.0f,
+                           -1.0f,
+                           -2.0f,
+                           -3.0f,
+                           -4.0f,
+                           -5.0f,
+                           -6.0f,
+                           -7.0f,
+                           -8.0f},
+            std::vector<T>{-1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f,
+                           -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f,
+                           -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f,
+                           -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f,
+                           -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f, -1.1f},
+            std::vector<T>{45.910797, 104.8302, 63.12059, 151.47789, -45.910797, -104.8302, -63.12059, -151.47789},
+            std::vector<T>{0.64f, 0.18f, 0.23f, 0.74f, 0.89f, 0.70f, 0.13f, 0.99f, 0.48f, 0.20f, 0.67f,
+                           0.88f, 0.17f, 0.19f, 0.53f, 0.22f, 0.50f, 0.07f, 0.21f, 0.99f, 0.09f, 0.28f,
+                           0.66f, 0.91f, 0.28f, 0.89f, 0.91f, 0.39f, 0.70f, 0.67f, 0.26f, 0.09f},
+            {1, 1},
+            {0, 0},
+            {0, 0},
+            {1, 1},
+            1,
+            2,
+            "v8_neg_offset_groups_deforgroups_mask",
+            true),
     };
     return deformableConvolutionParams;
 }
 
 std::vector<DeformableConvolutionParams> generateDeformableConvolutionCombinedParams() {
-    const std::vector<std::vector<DeformableConvolutionParams>> deformableConvolutionTypeParams {
+    const std::vector<std::vector<DeformableConvolutionParams>> deformableConvolutionTypeParams{
         generateDeformableConvolutionFloatParams<element::Type_t::f64>(),
         generateDeformableConvolutionFloatParams<element::Type_t::f32>(),
         generateDeformableConvolutionFloatParams<element::Type_t::f16>(),
@@ -5752,8 +7741,7 @@ std::vector<DeformableConvolutionParams> generateDeformableConvolutionCombinedPa
         generateDeformableConvolutionUintParams<element::Type_t::u64>(),
         generateDeformableConvolutionUintParams<element::Type_t::u32>(),
         generateDeformableConvolutionUintParams<element::Type_t::u16>(),
-        generateDeformableConvolutionUintParams<element::Type_t::u8>()
-        };
+        generateDeformableConvolutionUintParams<element::Type_t::u8>()};
     std::vector<DeformableConvolutionParams> combinedParams;
 
     for (const auto& params : deformableConvolutionTypeParams) {
@@ -5763,7 +7751,7 @@ std::vector<DeformableConvolutionParams> generateDeformableConvolutionCombinedPa
 }
 
 std::vector<DeformableConvolutionParams> generateDeformableConvolutionV8CombinedParams() {
-    const std::vector<std::vector<DeformableConvolutionParams>> deformableConvolutionTypeParams {
+    const std::vector<std::vector<DeformableConvolutionParams>> deformableConvolutionTypeParams{
         generateDeformableConvolutionFloatParams<element::Type_t::f64>(),
         generateDeformableConvolutionFloatParams<element::Type_t::f32>(),
         generateDeformableConvolutionFloatParams<element::Type_t::f16>(),
@@ -5779,8 +7767,7 @@ std::vector<DeformableConvolutionParams> generateDeformableConvolutionV8Combined
         generateDeformableConvolutionUintParams<element::Type_t::u64>(),
         generateDeformableConvolutionUintParams<element::Type_t::u32>(),
         generateDeformableConvolutionUintParams<element::Type_t::u16>(),
-        generateDeformableConvolutionUintParams<element::Type_t::u8>()
-        };
+        generateDeformableConvolutionUintParams<element::Type_t::u8>()};
     std::vector<DeformableConvolutionParams> combinedParams;
 
     for (const auto& params : deformableConvolutionTypeParams) {
@@ -5789,10 +7776,14 @@ std::vector<DeformableConvolutionParams> generateDeformableConvolutionV8Combined
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_DeformableConvolution_With_Hardcoded_Refs, ReferenceDeformableConvolutionLayerTest,
-    testing::ValuesIn(generateDeformableConvolutionCombinedParams()), ReferenceDeformableConvolutionLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_DeformableConvolution_With_Hardcoded_Refs,
+                         ReferenceDeformableConvolutionLayerTest,
+                         testing::ValuesIn(generateDeformableConvolutionCombinedParams()),
+                         ReferenceDeformableConvolutionLayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_DeformableConvolutionV8_With_Hardcoded_Refs, ReferenceDeformableConvolutionV8LayerTest,
-    testing::ValuesIn(generateDeformableConvolutionV8CombinedParams()), ReferenceDeformableConvolutionV8LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_DeformableConvolutionV8_With_Hardcoded_Refs,
+                         ReferenceDeformableConvolutionV8LayerTest,
+                         testing::ValuesIn(generateDeformableConvolutionV8CombinedParams()),
+                         ReferenceDeformableConvolutionV8LayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/deformable_psroi_pooling.cpp b/src/plugins/template/tests/functional/op_reference/deformable_psroi_pooling.cpp
index 1ae803ac83aca1..858c5d287f4206 100644
--- a/src/plugins/template/tests/functional/op_reference/deformable_psroi_pooling.cpp
+++ b/src/plugins/template/tests/functional/op_reference/deformable_psroi_pooling.cpp
@@ -5,8 +5,9 @@
 #include <gtest/gtest.h>
 
 #include <random>
-#include "openvino/op/psroi_pooling.hpp"
+
 #include "base_reference_test.hpp"
+#include "openvino/op/psroi_pooling.hpp"
 #include "openvino/opsets/opset1.hpp"
 
 using namespace reference_tests;
@@ -15,12 +16,24 @@ using namespace ov;
 namespace {
 struct DeformablePSROIPoolingParams {
     template <class IT>
-    DeformablePSROIPoolingParams(const size_t batch_in, const size_t channel_in, const size_t height_in, const size_t width_in,
-                                 const float spatial_scale, const size_t group_size, const int64_t spatial_bins_x, const int64_t spatial_bins_y,
-                                 const float trans_std, const int64_t part_size, const size_t rois_dim,
-                                 const ov::element::Type& iType, const bool is_input_generation_iota, const float inputValue,
-                                 const std::vector<IT>& roisValues, const std::vector<IT>& oValues,
-                                 const std::string& test_name = "", const std::string& mode = "bilinear_deformable")
+    DeformablePSROIPoolingParams(const size_t batch_in,
+                                 const size_t channel_in,
+                                 const size_t height_in,
+                                 const size_t width_in,
+                                 const float spatial_scale,
+                                 const size_t group_size,
+                                 const int64_t spatial_bins_x,
+                                 const int64_t spatial_bins_y,
+                                 const float trans_std,
+                                 const int64_t part_size,
+                                 const size_t rois_dim,
+                                 const ov::element::Type& iType,
+                                 const bool is_input_generation_iota,
+                                 const float inputValue,
+                                 const std::vector<IT>& roisValues,
+                                 const std::vector<IT>& oValues,
+                                 const std::string& test_name = "",
+                                 const std::string& mode = "bilinear_deformable")
         : groupSize(group_size),
           spatialBinsX(spatial_bins_x),
           spatialBinsY(spatial_bins_y),
@@ -33,34 +46,48 @@ struct DeformablePSROIPoolingParams {
           outType(iType),
           roisData(CreateTensor(iType, roisValues)),
           testcaseName(test_name) {
-              outputDim = (channel_in / (group_size * group_size)) - (static_cast<size_t>(channel_in / (group_size * group_size)) % 2);
-              inputShape = Shape{batch_in, channel_in, height_in, width_in};
-              roisShape = Shape{rois_dim, 5};
+        outputDim = (channel_in / (group_size * group_size)) -
+                    (static_cast<size_t>(channel_in / (group_size * group_size)) % 2);
+        inputShape = Shape{batch_in, channel_in, height_in, width_in};
+        roisShape = Shape{rois_dim, 5};
 
-              std::vector<IT> inputValues(shape_size(inputShape.get_shape()));
-              if (is_input_generation_iota)
-                  std::iota(inputValues.begin(), inputValues.end(), inputValue);
-              else
-                  std::fill(inputValues.begin(), inputValues.end(), inputValue);
-              inputData = CreateTensor(iType, inputValues);
+        std::vector<IT> inputValues(shape_size(inputShape.get_shape()));
+        if (is_input_generation_iota)
+            std::iota(inputValues.begin(), inputValues.end(), inputValue);
+        else
+            std::fill(inputValues.begin(), inputValues.end(), inputValue);
+        inputData = CreateTensor(iType, inputValues);
 
-              if (oValues.size() > 1) {
-                  refData = CreateTensor(iType, oValues);
-              } else {
-                  Shape output_shape{rois_dim, outputDim, group_size, group_size};
-                  std::vector<IT> expected_output_values(shape_size(output_shape));
-                  std::fill(expected_output_values.begin(), expected_output_values.end(), oValues[0]);
-                  refData = CreateTensor(iType, expected_output_values);
-              }
-          }
+        if (oValues.size() > 1) {
+            refData = CreateTensor(iType, oValues);
+        } else {
+            Shape output_shape{rois_dim, outputDim, group_size, group_size};
+            std::vector<IT> expected_output_values(shape_size(output_shape));
+            std::fill(expected_output_values.begin(), expected_output_values.end(), oValues[0]);
+            refData = CreateTensor(iType, expected_output_values);
+        }
+    }
 
     template <class IT>
-    DeformablePSROIPoolingParams(const size_t batch_in, const size_t channel_in, const size_t height_in, const size_t width_in,
-                                 const float spatial_scale, const size_t group_size, const int64_t spatial_bins_x, const int64_t spatial_bins_y,
-                                 const float trans_std, const int64_t part_size, const size_t rois_dim,
-                                 const ov::element::Type& iType, const bool is_input_generation_iota, const float inputValue, const float offsetValue,
-                                 const std::vector<IT>& roisValues, const std::vector<IT>& oValues,
-                                 const std::string& test_name = "", const std::string& mode = "bilinear_deformable")
+    DeformablePSROIPoolingParams(const size_t batch_in,
+                                 const size_t channel_in,
+                                 const size_t height_in,
+                                 const size_t width_in,
+                                 const float spatial_scale,
+                                 const size_t group_size,
+                                 const int64_t spatial_bins_x,
+                                 const int64_t spatial_bins_y,
+                                 const float trans_std,
+                                 const int64_t part_size,
+                                 const size_t rois_dim,
+                                 const ov::element::Type& iType,
+                                 const bool is_input_generation_iota,
+                                 const float inputValue,
+                                 const float offsetValue,
+                                 const std::vector<IT>& roisValues,
+                                 const std::vector<IT>& oValues,
+                                 const std::string& test_name = "",
+                                 const std::string& mode = "bilinear_deformable")
         : groupSize(group_size),
           spatialBinsX(spatial_bins_x),
           spatialBinsY(spatial_bins_y),
@@ -74,31 +101,31 @@ struct DeformablePSROIPoolingParams {
           outType(iType),
           roisData(CreateTensor(iType, roisValues)),
           testcaseName(test_name) {
-              outputDim = (channel_in / (group_size * group_size)) - ((channel_in / (group_size * group_size)) % 2);
-              inputShape = Shape{batch_in, channel_in, height_in, width_in};
-              roisShape = Shape{rois_dim, 5};
-              offsetsShape = Shape{rois_dim, 2, group_size, group_size};
+        outputDim = (channel_in / (group_size * group_size)) - ((channel_in / (group_size * group_size)) % 2);
+        inputShape = Shape{batch_in, channel_in, height_in, width_in};
+        roisShape = Shape{rois_dim, 5};
+        offsetsShape = Shape{rois_dim, 2, group_size, group_size};
 
-              std::vector<IT> inputValues(shape_size(inputShape.get_shape()));
-              if (is_input_generation_iota)
-                  std::iota(inputValues.begin(), inputValues.end(), inputValue);
-              else
-                  std::fill(inputValues.begin(), inputValues.end(), inputValue);
-              inputData = CreateTensor(iType, inputValues);
+        std::vector<IT> inputValues(shape_size(inputShape.get_shape()));
+        if (is_input_generation_iota)
+            std::iota(inputValues.begin(), inputValues.end(), inputValue);
+        else
+            std::fill(inputValues.begin(), inputValues.end(), inputValue);
+        inputData = CreateTensor(iType, inputValues);
 
-              std::vector<IT> offsetsValues(shape_size(offsetsShape.get_shape()));
-              std::fill(offsetsValues.begin(), offsetsValues.end(), offsetValue);
-              offsetsData = CreateTensor(iType, offsetsValues);
+        std::vector<IT> offsetsValues(shape_size(offsetsShape.get_shape()));
+        std::fill(offsetsValues.begin(), offsetsValues.end(), offsetValue);
+        offsetsData = CreateTensor(iType, offsetsValues);
 
-              if (oValues.size() > 1) {
-                  refData = CreateTensor(iType, oValues);
-              } else {
-                  Shape output_shape{rois_dim, outputDim, group_size, group_size};
-                  std::vector<IT> expected_output_values(shape_size(output_shape));
-                  std::fill(expected_output_values.begin(), expected_output_values.end(), oValues[0]);
-                  refData = CreateTensor(iType, expected_output_values);
-              }
-          }
+        if (oValues.size() > 1) {
+            refData = CreateTensor(iType, oValues);
+        } else {
+            Shape output_shape{rois_dim, outputDim, group_size, group_size};
+            std::vector<IT> expected_output_values(shape_size(output_shape));
+            std::fill(expected_output_values.begin(), expected_output_values.end(), oValues[0]);
+            refData = CreateTensor(iType, expected_output_values);
+        }
+    }
 
     size_t groupSize;
     int64_t spatialBinsX;
@@ -123,7 +150,8 @@ struct DeformablePSROIPoolingParams {
     std::string testcaseName;
 };
 
-class ReferenceDeformablePSROIPoolingLayerTest : public testing::TestWithParam<DeformablePSROIPoolingParams>, public CommonReferenceTest {
+class ReferenceDeformablePSROIPoolingLayerTest : public testing::TestWithParam<DeformablePSROIPoolingParams>,
+                                                 public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -159,29 +187,30 @@ class ReferenceDeformablePSROIPoolingLayerTest : public testing::TestWithParam<D
         if (params.offsetsShape.size() != 0) {
             const auto offsets = std::make_shared<op::v0::Parameter>(params.offsetsType, params.offsetsShape);
             const auto DeformablePSROIPooling = std::make_shared<opset1::DeformablePSROIPooling>(input,
-                                                                            rois,
-                                                                            offsets,
-                                                                            params.outputDim,
-                                                                            params.spatialScale,
-                                                                            params.groupSize,
-                                                                            params.mode,
-                                                                            params.spatialBinsX,
-                                                                            params.spatialBinsY,
-                                                                            params.transStd,
-                                                                            params.partSize);
-            return std::make_shared<ov::Model>(NodeVector {DeformablePSROIPooling}, ParameterVector {input, rois, offsets});
+                                                                                                 rois,
+                                                                                                 offsets,
+                                                                                                 params.outputDim,
+                                                                                                 params.spatialScale,
+                                                                                                 params.groupSize,
+                                                                                                 params.mode,
+                                                                                                 params.spatialBinsX,
+                                                                                                 params.spatialBinsY,
+                                                                                                 params.transStd,
+                                                                                                 params.partSize);
+            return std::make_shared<ov::Model>(NodeVector{DeformablePSROIPooling},
+                                               ParameterVector{input, rois, offsets});
         } else {
             const auto DeformablePSROIPooling = std::make_shared<opset1::DeformablePSROIPooling>(input,
-                                                                            rois,
-                                                                            params.outputDim,
-                                                                            params.spatialScale,
-                                                                            params.groupSize,
-                                                                            params.mode,
-                                                                            params.spatialBinsX,
-                                                                            params.spatialBinsY,
-                                                                            params.transStd,
-                                                                            params.partSize);
-            return std::make_shared<ov::Model>(NodeVector {DeformablePSROIPooling}, ParameterVector {input, rois});
+                                                                                                 rois,
+                                                                                                 params.outputDim,
+                                                                                                 params.spatialScale,
+                                                                                                 params.groupSize,
+                                                                                                 params.mode,
+                                                                                                 params.spatialBinsX,
+                                                                                                 params.spatialBinsY,
+                                                                                                 params.transStd,
+                                                                                                 params.partSize);
+            return std::make_shared<ov::Model>(NodeVector{DeformablePSROIPooling}, ParameterVector{input, rois});
         }
     }
 };
@@ -194,152 +223,403 @@ template <element::Type_t IN_ET>
 std::vector<DeformablePSROIPoolingParams> generateDeformablePSROIPoolingFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DeformablePSROIPoolingParams> deformablePSROIPoolingParams {
-        DeformablePSROIPoolingParams(1, 16, 2, 2, // batch_in, channel_in, height_in, width_in
-                                     0.0625, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 1, 2, // trans_std, part_size, rois_dim
-                                     IN_ET, true, 0, 0.0, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 1, 2, 4, 6,
-                                                    0, 0, 3, 10, 4},
-                                     std::vector<T>{
-                                                    // First ROI
-                                                    0, 4, 8, 12,
-                                                    16, 20, 24, 28,
-                                                    32, 36, 40, 44,
-                                                    48, 52, 56, 60,
+    std::vector<DeformablePSROIPoolingParams> deformablePSROIPoolingParams{
+        DeformablePSROIPoolingParams(1,
+                                     16,
+                                     2,
+                                     2,  // batch_in, channel_in, height_in, width_in
+                                     0.0625,
+                                     2,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     1,
+                                     2,  // trans_std, part_size, rois_dim
+                                     IN_ET,
+                                     true,
+                                     0,
+                                     0.0,           // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    1,
+                                                    2,
+                                                    4,
+                                                    6,
+                                                    0,
+                                                    0,
+                                                    3,
+                                                    10,
+                                                    4},
+                                     std::vector<T>{// First ROI
+                                                    0,
+                                                    4,
+                                                    8,
+                                                    12,
+                                                    16,
+                                                    20,
+                                                    24,
+                                                    28,
+                                                    32,
+                                                    36,
+                                                    40,
+                                                    44,
+                                                    48,
+                                                    52,
+                                                    56,
+                                                    60,
                                                     // Second ROI
-                                                    0, 4, 8,  12,
-                                                    16, 20, 24, 28,
-                                                    32, 36, 40, 44,
-                                                    48, 52, 56, 60},
-                                                    "offset_00"),
-        DeformablePSROIPoolingParams(1, 16, 2, 2, // batch_in, channel_in, height_in, width_in
-                                     0.0625, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 1, 2, // trans_std, part_size, rois_dim
-                                     IN_ET, true, 0, 0.2, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 1, 2, 4, 6,
-                                                    0, 0, 3, 10, 4},
-                                     std::vector<T>{
-                                                    // First ROI
-                                                    0, 4, 8, 12,
-                                                    16, 20, 24, 28,
-                                                    32, 36, 40, 44,
-                                                    48, 52, 56, 60,
+                                                    0,
+                                                    4,
+                                                    8,
+                                                    12,
+                                                    16,
+                                                    20,
+                                                    24,
+                                                    28,
+                                                    32,
+                                                    36,
+                                                    40,
+                                                    44,
+                                                    48,
+                                                    52,
+                                                    56,
+                                                    60},
+                                     "offset_00"),
+        DeformablePSROIPoolingParams(1,
+                                     16,
+                                     2,
+                                     2,  // batch_in, channel_in, height_in, width_in
+                                     0.0625,
+                                     2,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     1,
+                                     2,  // trans_std, part_size, rois_dim
+                                     IN_ET,
+                                     true,
+                                     0,
+                                     0.2,           // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    1,
+                                                    2,
+                                                    4,
+                                                    6,
+                                                    0,
+                                                    0,
+                                                    3,
+                                                    10,
+                                                    4},
+                                     std::vector<T>{// First ROI
+                                                    0,
+                                                    4,
+                                                    8,
+                                                    12,
+                                                    16,
+                                                    20,
+                                                    24,
+                                                    28,
+                                                    32,
+                                                    36,
+                                                    40,
+                                                    44,
+                                                    48,
+                                                    52,
+                                                    56,
+                                                    60,
                                                     // Second ROI
-                                                    0, 4, 8,  12,
-                                                    16, 20, 24, 28,
-                                                    32, 36, 40, 44,
-                                                    48, 52, 56, 60},
-                                                    "offset_0p2"),
-        DeformablePSROIPoolingParams(1, 16, 2, 2, // batch_in, channel_in, height_in, width_in
-                                     0.0625, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 1, 2, // trans_std, part_size, rois_dim
-                                     IN_ET, true, 0, 0.5, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 1, 2, 4, 6,
-                                                    0, 5, 3, 10, 4},
-                                     std::vector<T>{
-                                                    // First ROI
-                                                    0, 4, 8, 12,
-                                                    16, 20, 24, 28,
-                                                    32, 36, 40, 44,
-                                                    48, 52, 56, 60,
+                                                    0,
+                                                    4,
+                                                    8,
+                                                    12,
+                                                    16,
+                                                    20,
+                                                    24,
+                                                    28,
+                                                    32,
+                                                    36,
+                                                    40,
+                                                    44,
+                                                    48,
+                                                    52,
+                                                    56,
+                                                    60},
+                                     "offset_0p2"),
+        DeformablePSROIPoolingParams(1,
+                                     16,
+                                     2,
+                                     2,  // batch_in, channel_in, height_in, width_in
+                                     0.0625,
+                                     2,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     1,
+                                     2,  // trans_std, part_size, rois_dim
+                                     IN_ET,
+                                     true,
+                                     0,
+                                     0.5,           // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    1,
+                                                    2,
+                                                    4,
+                                                    6,
+                                                    0,
+                                                    5,
+                                                    3,
+                                                    10,
+                                                    4},
+                                     std::vector<T>{// First ROI
+                                                    0,
+                                                    4,
+                                                    8,
+                                                    12,
+                                                    16,
+                                                    20,
+                                                    24,
+                                                    28,
+                                                    32,
+                                                    36,
+                                                    40,
+                                                    44,
+                                                    48,
+                                                    52,
+                                                    56,
+                                                    60,
                                                     // Second ROI
-                                                    0, 4.1875, 8, 12.1875,
-                                                    16, 20.1875, 24, 28.1875,
-                                                    32, 36.1875, 40, 44.1875,
-                                                    48, 52.1875, 56, 60.1875},
-                                                    "offset_0p5"),
-        DeformablePSROIPoolingParams(1, 16, 2, 2, // batch_in, channel_in, height_in, width_in
-                                     0.0625, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 1, 2, // trans_std, part_size, rois_dim
-                                     IN_ET, true, 0, 0, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 10, 10, 20, 20,
-                                                    0, 100, 100, 200, 200},
-                                     std::vector<T>{
-                                                    // First ROI
-                                                    0.375,  4.71875,  9.0625,  13.40625, 16.375, 20.71875, 25.0625, 29.40625,
-                                                    32.375, 36.71875, 41.0625, 45.40625, 48.375, 52.71875, 57.0625, 61.40625,
+                                                    0,
+                                                    4.1875,
+                                                    8,
+                                                    12.1875,
+                                                    16,
+                                                    20.1875,
+                                                    24,
+                                                    28.1875,
+                                                    32,
+                                                    36.1875,
+                                                    40,
+                                                    44.1875,
+                                                    48,
+                                                    52.1875,
+                                                    56,
+                                                    60.1875},
+                                     "offset_0p5"),
+        DeformablePSROIPoolingParams(1,
+                                     16,
+                                     2,
+                                     2,  // batch_in, channel_in, height_in, width_in
+                                     0.0625,
+                                     2,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     1,
+                                     2,  // trans_std, part_size, rois_dim
+                                     IN_ET,
+                                     true,
+                                     0,
+                                     0,             // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    10,
+                                                    10,
+                                                    20,
+                                                    20,
+                                                    0,
+                                                    100,
+                                                    100,
+                                                    200,
+                                                    200},
+                                     std::vector<T>{// First ROI
+                                                    0.375,
+                                                    4.71875,
+                                                    9.0625,
+                                                    13.40625,
+                                                    16.375,
+                                                    20.71875,
+                                                    25.0625,
+                                                    29.40625,
+                                                    32.375,
+                                                    36.71875,
+                                                    41.0625,
+                                                    45.40625,
+                                                    48.375,
+                                                    52.71875,
+                                                    57.0625,
+                                                    61.40625,
                                                     // Second ROI
-                                                    0,      0,        0,       0,        0,      0,        0,       0,
-                                                    0,      0,        0,       0,        0,      0,        0,       0},
-                                                    "roi_oversize"),
-        DeformablePSROIPoolingParams(1, 8, 3, 3, // batch_in, channel_in, height_in, width_in
-                                     1, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 2, 1, // trans_std, part_size, rois_dim
-                                     IN_ET, true, 0, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 1, 1, 2, 2},
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0,
+                                                    0},
+                                     "roi_oversize"),
+        DeformablePSROIPoolingParams(1,
+                                     8,
+                                     3,
+                                     3,  // batch_in, channel_in, height_in, width_in
+                                     1,
+                                     2,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     2,
+                                     1,  // trans_std, part_size, rois_dim
+                                     IN_ET,
+                                     true,
+                                     0,             // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    1,
+                                                    1,
+                                                    2,
+                                                    2},
                                      std::vector<T>{2.0, 12.0, 23.0, 33.0, 38.0, 48.0, 59.0, 69.0},
-                                                    "no_offset_input"),
-        DeformablePSROIPoolingParams(1, 8, 3, 3, // batch_in, channel_in, height_in, width_in
-                                     1, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 2, 1, // trans_std, part_size, rois_dim,
-                                     IN_ET, true, 0, 0, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 1, 1, 2, 2},
+                                     "no_offset_input"),
+        DeformablePSROIPoolingParams(1,
+                                     8,
+                                     3,
+                                     3,  // batch_in, channel_in, height_in, width_in
+                                     1,
+                                     2,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     2,
+                                     1,  // trans_std, part_size, rois_dim,
+                                     IN_ET,
+                                     true,
+                                     0,
+                                     0,             // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    1,
+                                                    1,
+                                                    2,
+                                                    2},
                                      std::vector<T>{2.0, 12.0, 23.0, 33.0, 38.0, 48.0, 59.0, 69.0},
-                                                    "offset_zero"),
-        DeformablePSROIPoolingParams(1, 8, 3, 3, // batch_in, channel_in, height_in, width_in
-                                     1, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 2, 1, // trans_std, part_size, rois_dim,
-                                     IN_ET, true, 0, 0.1, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 1, 1, 2, 2},
+                                     "offset_zero"),
+        DeformablePSROIPoolingParams(1,
+                                     8,
+                                     3,
+                                     3,  // batch_in, channel_in, height_in, width_in
+                                     1,
+                                     2,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     2,
+                                     1,  // trans_std, part_size, rois_dim,
+                                     IN_ET,
+                                     true,
+                                     0,
+                                     0.1,           // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    1,
+                                                    1,
+                                                    2,
+                                                    2},
                                      std::vector<T>{2.8, 12.8, 23.8, 33.8, 38.8, 48.8, 59.8, 69.8},
-                                                    "offset_01"),
-        DeformablePSROIPoolingParams(1, 8, 3, 3, // batch_in, channel_in, height_in, width_in
-                                     1, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 2, 1, // trans_std, part_size, rois_dim,
-                                     IN_ET, true, 0, 0.5, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 1, 1, 2, 2},
+                                     "offset_01"),
+        DeformablePSROIPoolingParams(1,
+                                     8,
+                                     3,
+                                     3,  // batch_in, channel_in, height_in, width_in
+                                     1,
+                                     2,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     2,
+                                     1,  // trans_std, part_size, rois_dim,
+                                     IN_ET,
+                                     true,
+                                     0,
+                                     0.5,           // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    1,
+                                                    1,
+                                                    2,
+                                                    2},
                                      std::vector<T>{6., 15.5, 25.5, 35., 42., 51.5, 61.5, 71.},
-                                                    "offset_05"),
-        DeformablePSROIPoolingParams(1, 16, 2, 2, // batch_in, channel_in, height_in, width_in
-                                     0.0625, 2, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 1, 1, // trans_std, part_size, rois_dim,
-                                     IN_ET, false, 0.1, 0.1, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 10, 10, 10, 10},
-                                     std::vector<T>{0.1, 0.1, 0.1, 0.1,
-                                                    0.1, 0.1, 0.1, 0.1,
-                                                    0.1, 0.1, 0.1, 0.1,
-                                                    0.1, 0.1, 0.1, 0.1},
-                                                    "single_value"),
-        DeformablePSROIPoolingParams(1, 1024, 63, 38, // batch_in, channel_in, height_in, width_in
-                                     0.0625, 3, 1, 1, //spatial_scale, group_size, spatial_bins_x, spatial_bins_y
-                                     1, 1, 2, // trans_std, part_size, rois_dim,
-                                     IN_ET, false, 0.1, 0.0, //inputType, is_input_generation_iota, inputValue, offsetValue
-                                     std::vector<T>{
-                                                    // input_batch_id, x1, y1, x2, y2
-                                                    0, 1, 2, 4, 6,
-                                                    0, 0, 3, 10, 4},
+                                     "offset_05"),
+        DeformablePSROIPoolingParams(
+            1,
+            16,
+            2,
+            2,  // batch_in, channel_in, height_in, width_in
+            0.0625,
+            2,
+            1,
+            1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+            1,
+            1,
+            1,  // trans_std, part_size, rois_dim,
+            IN_ET,
+            false,
+            0.1,
+            0.1,           // inputType, is_input_generation_iota, inputValue, offsetValue
+            std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                           0,
+                           10,
+                           10,
+                           10,
+                           10},
+            std::vector<T>{0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1},
+            "single_value"),
+        DeformablePSROIPoolingParams(1,
+                                     1024,
+                                     63,
+                                     38,  // batch_in, channel_in, height_in, width_in
+                                     0.0625,
+                                     3,
+                                     1,
+                                     1,  // spatial_scale, group_size, spatial_bins_x, spatial_bins_y
+                                     1,
+                                     1,
+                                     2,  // trans_std, part_size, rois_dim,
+                                     IN_ET,
+                                     false,
+                                     0.1,
+                                     0.0,           // inputType, is_input_generation_iota, inputValue, offsetValue
+                                     std::vector<T>{// input_batch_id, x1, y1, x2, y2
+                                                    0,
+                                                    1,
+                                                    2,
+                                                    4,
+                                                    6,
+                                                    0,
+                                                    0,
+                                                    3,
+                                                    10,
+                                                    4},
                                      std::vector<T>{0.1},
-                                                    "single_value_big_shape")
-    };
+                                     "single_value_big_shape")};
     return deformablePSROIPoolingParams;
 }
 
 std::vector<DeformablePSROIPoolingParams> generateDeformablePSROIPoolingCombinedParams() {
-    const std::vector<std::vector<DeformablePSROIPoolingParams>> deformablePSROIPoolingTypeParams {
+    const std::vector<std::vector<DeformablePSROIPoolingParams>> deformablePSROIPoolingTypeParams{
         generateDeformablePSROIPoolingFloatParams<element::Type_t::f64>(),
         generateDeformablePSROIPoolingFloatParams<element::Type_t::f32>(),
         generateDeformablePSROIPoolingFloatParams<element::Type_t::f16>(),
-        generateDeformablePSROIPoolingFloatParams<element::Type_t::bf16>()
-        };
+        generateDeformablePSROIPoolingFloatParams<element::Type_t::bf16>()};
     std::vector<DeformablePSROIPoolingParams> combinedParams;
 
     for (const auto& params : deformablePSROIPoolingTypeParams) {
@@ -348,7 +628,9 @@ std::vector<DeformablePSROIPoolingParams> generateDeformablePSROIPoolingCombined
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_DeformablePSROIPooling_With_Hardcoded_Refs, ReferenceDeformablePSROIPoolingLayerTest,
-    testing::ValuesIn(generateDeformablePSROIPoolingCombinedParams()), ReferenceDeformablePSROIPoolingLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_DeformablePSROIPooling_With_Hardcoded_Refs,
+                         ReferenceDeformablePSROIPoolingLayerTest,
+                         testing::ValuesIn(generateDeformablePSROIPoolingCombinedParams()),
+                         ReferenceDeformablePSROIPoolingLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/depth_to_space.cpp b/src/plugins/template/tests/functional/op_reference/depth_to_space.cpp
index 6340c5665e235b..6f683ed5452765 100644
--- a/src/plugins/template/tests/functional/op_reference/depth_to_space.cpp
+++ b/src/plugins/template/tests/functional/op_reference/depth_to_space.cpp
@@ -4,18 +4,24 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct DepthToSpaceParams {
-    DepthToSpaceParams(const reference_tests::Tensor& dataTensor, const std::string mode, const int32_t blockSize,
-                       const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), mode(mode), blockSize(blockSize), expectedTensor(expectedTensor),
-        testcaseName(testcaseName) {}
+    DepthToSpaceParams(const reference_tests::Tensor& dataTensor,
+                       const std::string mode,
+                       const int32_t blockSize,
+                       const reference_tests::Tensor& expectedTensor,
+                       const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          mode(mode),
+          blockSize(blockSize),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     std::string mode;
@@ -50,11 +56,12 @@ class ReferenceDepthToSpaceLayerTest : public testing::TestWithParam<DepthToSpac
 
 private:
     static std::shared_ptr<Model> CreateFunction(const DepthToSpaceParams& params) {
-        opset1::DepthToSpace::DepthToSpaceMode mode = params.mode == "DEPTH_FIRST" ?
-            opset1::DepthToSpace::DepthToSpaceMode::DEPTH_FIRST : opset1::DepthToSpace::DepthToSpaceMode::BLOCKS_FIRST;
+        opset1::DepthToSpace::DepthToSpaceMode mode = params.mode == "DEPTH_FIRST"
+                                                          ? opset1::DepthToSpace::DepthToSpaceMode::DEPTH_FIRST
+                                                          : opset1::DepthToSpace::DepthToSpaceMode::BLOCKS_FIRST;
         const auto data = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto depthToSpace = std::make_shared<opset1::DepthToSpace>(data, mode, params.blockSize);
-        return std::make_shared<Model>(NodeVector {depthToSpace}, ParameterVector {data});
+        return std::make_shared<Model>(NodeVector{depthToSpace}, ParameterVector{data});
     }
 };
 
@@ -65,72 +72,84 @@ TEST_P(ReferenceDepthToSpaceLayerTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<DepthToSpaceParams> generateDepthToSpaceParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<DepthToSpaceParams> depthToSpaceParams {
+    std::vector<DepthToSpaceParams> depthToSpaceParams{
         // depth_to_space_block_first_K1_BS2
         DepthToSpaceParams(
-            reference_tests::Tensor({1, 8, 2}, IN_ET, std::vector<T>{0, 2, 8, 10, 16, 18, 24, 26, 1, 3, 9, 11, 17, 19, 25, 27}),
+            reference_tests::Tensor({1, 8, 2},
+                                    IN_ET,
+                                    std::vector<T>{0, 2, 8, 10, 16, 18, 24, 26, 1, 3, 9, 11, 17, 19, 25, 27}),
             "BLOCKS_FIRST",
             2,
-            reference_tests::Tensor({1, 4, 4}, IN_ET, std::vector<T>{0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27}),
+            reference_tests::Tensor({1, 4, 4},
+                                    IN_ET,
+                                    std::vector<T>{0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27}),
             "depth_to_space_block_first_K1_BS2"),
 
         // depth_to_space_block_first_K2_BS2
         DepthToSpaceParams(
             reference_tests::Tensor({1, 8, 2, 2}, IN_ET, std::vector<T>{0,  2,  8,  10, 16, 18, 24, 26, 1,  3,  9,
-                                                       11, 17, 19, 25, 27, 4,  6,  12, 14, 20, 22,
-                                                       28, 30, 5,  7,  13, 15, 21, 23, 29, 31}),
+                                                                        11, 17, 19, 25, 27, 4,  6,  12, 14, 20, 22,
+                                                                        28, 30, 5,  7,  13, 15, 21, 23, 29, 31}),
             "BLOCKS_FIRST",
             2,
-            reference_tests::Tensor({1, 2, 4, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15,
-                                                       16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
+            reference_tests::Tensor({1, 2, 4, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
+                                                                        11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
+                                                                        22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
             "depth_to_space_block_first_K2_BS2"),
 
         // depth_to_space_block_first_K2_BS4
         DepthToSpaceParams(
             reference_tests::Tensor({1, 16, 2, 1}, IN_ET, std::vector<T>{0,  16, 1,  17, 2,  18, 3,  19, 4,  20, 5,
-                                                        21, 6,  22, 7,  23, 8,  24, 9,  25, 10, 26,
-                                                        11, 27, 12, 28, 13, 29, 14, 30, 15, 31}),
+                                                                         21, 6,  22, 7,  23, 8,  24, 9,  25, 10, 26,
+                                                                         11, 27, 12, 28, 13, 29, 14, 30, 15, 31}),
             "BLOCKS_FIRST",
             4,
-            reference_tests::Tensor({1, 1, 8, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15,
-                                                       16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
+            reference_tests::Tensor({1, 1, 8, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
+                                                                        11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
+                                                                        22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
             "depth_to_space_block_first_K2_BS4"),
 
         // depth_to_space_depth_first_1K_BS2
         DepthToSpaceParams(
-            reference_tests::Tensor({1, 8, 2}, IN_ET, std::vector<T>{0, 2, 1, 3, 4, 6, 5, 7, 8, 10, 9, 11, 12, 14, 13, 15}),
+            reference_tests::Tensor({1, 8, 2},
+                                    IN_ET,
+                                    std::vector<T>{0, 2, 1, 3, 4, 6, 5, 7, 8, 10, 9, 11, 12, 14, 13, 15}),
             "DEPTH_FIRST",
             2,
-            reference_tests::Tensor({1, 4, 4}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}),
+            reference_tests::Tensor({1, 4, 4},
+                                    IN_ET,
+                                    std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}),
             "depth_to_space_depth_first_1K_BS2"),
 
         // depth_to_space_depth_first_2K_BS2
         DepthToSpaceParams(
             reference_tests::Tensor({1, 8, 2, 2}, IN_ET, std::vector<T>{0,  2,  8,  10, 16, 18, 24, 26, 1,  3,  9,
-                                                       11, 17, 19, 25, 27, 4,  6,  12, 14, 20, 22,
-                                                       28, 30, 5,  7,  13, 15, 21, 23, 29, 31}),
+                                                                        11, 17, 19, 25, 27, 4,  6,  12, 14, 20, 22,
+                                                                        28, 30, 5,  7,  13, 15, 21, 23, 29, 31}),
             "DEPTH_FIRST",
             2,
-            reference_tests::Tensor({1, 2, 4, 4}, IN_ET, std::vector<T>{0, 16, 2, 18, 1, 17, 3, 19, 8,  24, 10, 26, 9,  25, 11, 27,
-                                                       4, 20, 6, 22, 5, 21, 7, 23, 12, 28, 14, 30, 13, 29, 15, 31}),
+            reference_tests::Tensor({1, 2, 4, 4}, IN_ET, std::vector<T>{0,  16, 2,  18, 1,  17, 3,  19, 8,  24, 10,
+                                                                        26, 9,  25, 11, 27, 4,  20, 6,  22, 5,  21,
+                                                                        7,  23, 12, 28, 14, 30, 13, 29, 15, 31}),
             "depth_to_space_depth_first_2K_BS2"),
 
         // depth_to_space_depth_first_2K_BS4
         DepthToSpaceParams(
             reference_tests::Tensor({1, 16, 2, 1}, IN_ET, std::vector<T>{0,  16, 1,  17, 2,  18, 3,  19, 4,  20, 5,
-                                                        21, 6,  22, 7,  23, 8,  24, 9,  25, 10, 26,
-                                                        11, 27, 12, 28, 13, 29, 14, 30, 15, 31}),
+                                                                         21, 6,  22, 7,  23, 8,  24, 9,  25, 10, 26,
+                                                                         11, 27, 12, 28, 13, 29, 14, 30, 15, 31}),
             "DEPTH_FIRST",
             4,
-            reference_tests::Tensor({1, 1, 8, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15,
-                                                       16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
+            reference_tests::Tensor({1, 1, 8, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
+                                                                        11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
+                                                                        22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
             "depth_to_space_depth_first_2K_BS4"),
     };
     return depthToSpaceParams;
 }
 
 std::vector<DepthToSpaceParams> generateDepthToSpaceCombinedParams() {
-    const std::vector<std::vector<DepthToSpaceParams>> depthToSpaceTypeParams {
+    const std::vector<std::vector<DepthToSpaceParams>> depthToSpaceTypeParams{
         generateDepthToSpaceParams<element::Type_t::i8>(),
         generateDepthToSpaceParams<element::Type_t::i16>(),
         generateDepthToSpaceParams<element::Type_t::i32>(),
@@ -152,6 +171,8 @@ std::vector<DepthToSpaceParams> generateDepthToSpaceCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_DepthToSpace_With_Hardcoded_Refs, ReferenceDepthToSpaceLayerTest,
-    testing::ValuesIn(generateDepthToSpaceCombinedParams()), ReferenceDepthToSpaceLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_DepthToSpace_With_Hardcoded_Refs,
+                         ReferenceDepthToSpaceLayerTest,
+                         testing::ValuesIn(generateDepthToSpaceCombinedParams()),
+                         ReferenceDepthToSpaceLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/detection_output.cpp b/src/plugins/template/tests/functional/op_reference/detection_output.cpp
index 573b9c8d144904..a1809cb24a85a9 100644
--- a/src/plugins/template/tests/functional/op_reference/detection_output.cpp
+++ b/src/plugins/template/tests/functional/op_reference/detection_output.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/detection_output.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/detection_output.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -44,33 +45,34 @@ struct DetectionOutputParams {
           priorBoxesData(CreateTensor(iType, priorBoxesValues)),
           refData(CreateTensor(iType, oValues)),
           testcaseName(test_name) {
-              attrs.num_classes = num_classes;
-              attrs_v8.background_label_id = attrs.background_label_id = background_label_id;
-              attrs_v8.top_k = attrs.top_k = top_k;
-              attrs_v8.variance_encoded_in_target = attrs.variance_encoded_in_target = variance_encoded_in_target;
-              attrs_v8.keep_top_k = attrs.keep_top_k = keep_top_k;
-              attrs_v8.code_type = attrs.code_type = code_type;
-              attrs_v8.share_location = attrs.share_location = share_location;
-              attrs_v8.nms_threshold = attrs.nms_threshold = nms_threshold;
-              attrs_v8.confidence_threshold = attrs.confidence_threshold = confidence_threshold;
-              attrs_v8.clip_after_nms = attrs.clip_after_nms = clip_after_nms;
-              attrs_v8.clip_before_nms = attrs.clip_before_nms = clip_before_nms;
-              attrs_v8.decrease_label_id = attrs.decrease_label_id = decrease_label_id;
-              attrs_v8.normalized = attrs.normalized = normalized;
-              attrs_v8.input_height = attrs.input_height = input_height;
-              attrs_v8.input_width = attrs.input_width = input_width;
-              attrs_v8.objectness_score = attrs.objectness_score = objectness_score;
+        attrs.num_classes = num_classes;
+        attrs_v8.background_label_id = attrs.background_label_id = background_label_id;
+        attrs_v8.top_k = attrs.top_k = top_k;
+        attrs_v8.variance_encoded_in_target = attrs.variance_encoded_in_target = variance_encoded_in_target;
+        attrs_v8.keep_top_k = attrs.keep_top_k = keep_top_k;
+        attrs_v8.code_type = attrs.code_type = code_type;
+        attrs_v8.share_location = attrs.share_location = share_location;
+        attrs_v8.nms_threshold = attrs.nms_threshold = nms_threshold;
+        attrs_v8.confidence_threshold = attrs.confidence_threshold = confidence_threshold;
+        attrs_v8.clip_after_nms = attrs.clip_after_nms = clip_after_nms;
+        attrs_v8.clip_before_nms = attrs.clip_before_nms = clip_before_nms;
+        attrs_v8.decrease_label_id = attrs.decrease_label_id = decrease_label_id;
+        attrs_v8.normalized = attrs.normalized = normalized;
+        attrs_v8.input_height = attrs.input_height = input_height;
+        attrs_v8.input_width = attrs.input_width = input_width;
+        attrs_v8.objectness_score = attrs.objectness_score = objectness_score;
 
-              size_t num_loc_classes = attrs.share_location ? 1 : attrs.num_classes;
-              size_t prior_box_size = attrs.normalized ? 4 : 5;
+        size_t num_loc_classes = attrs.share_location ? 1 : attrs.num_classes;
+        size_t prior_box_size = attrs.normalized ? 4 : 5;
 
-              locShape = ov::Shape{num_images, num_prior_boxes * num_loc_classes * prior_box_size};
-              confShape = ov::Shape{num_images, num_prior_boxes * attrs.num_classes};
-              priorBoxesShape =
-              ov::Shape{is_priors_patch_size_1 ? 1UL : num_images, attrs.variance_encoded_in_target ? 1UL : 2UL, num_prior_boxes * prior_box_size};
-          }
+        locShape = ov::Shape{num_images, num_prior_boxes * num_loc_classes * prior_box_size};
+        confShape = ov::Shape{num_images, num_prior_boxes * attrs.num_classes};
+        priorBoxesShape = ov::Shape{is_priors_patch_size_1 ? 1UL : num_images,
+                                    attrs.variance_encoded_in_target ? 1UL : 2UL,
+                                    num_prior_boxes * prior_box_size};
+    }
 
-template <class IT>
+    template <class IT>
     DetectionOutputParams(const int num_classes,
                           const int background_label_id,
                           const int top_k,
@@ -106,33 +108,34 @@ template <class IT>
           auxLocData(CreateTensor(iType, auxLocValues)),
           auxConfData(CreateTensor(iType, auxConfValues)),
           testcaseName(test_name) {
-              attrs.num_classes = num_classes;
-              attrs_v8.background_label_id = attrs.background_label_id = background_label_id;
-              attrs_v8.top_k = attrs.top_k = top_k;
-              attrs_v8.variance_encoded_in_target = attrs.variance_encoded_in_target = variance_encoded_in_target;
-              attrs_v8.keep_top_k = attrs.keep_top_k = keep_top_k;
-              attrs_v8.code_type = attrs.code_type = code_type;
-              attrs_v8.share_location = attrs.share_location = share_location;
-              attrs_v8.nms_threshold = attrs.nms_threshold = nms_threshold;
-              attrs_v8.confidence_threshold = attrs.confidence_threshold = confidence_threshold;
-              attrs_v8.clip_after_nms = attrs.clip_after_nms = clip_after_nms;
-              attrs_v8.clip_before_nms = attrs.clip_before_nms = clip_before_nms;
-              attrs_v8.decrease_label_id = attrs.decrease_label_id = decrease_label_id;
-              attrs_v8.normalized = attrs.normalized = normalized;
-              attrs_v8.input_height = attrs.input_height = input_height;
-              attrs_v8.input_width = attrs.input_width = input_width;
-              attrs_v8.objectness_score = attrs.objectness_score = objectness_score;
+        attrs.num_classes = num_classes;
+        attrs_v8.background_label_id = attrs.background_label_id = background_label_id;
+        attrs_v8.top_k = attrs.top_k = top_k;
+        attrs_v8.variance_encoded_in_target = attrs.variance_encoded_in_target = variance_encoded_in_target;
+        attrs_v8.keep_top_k = attrs.keep_top_k = keep_top_k;
+        attrs_v8.code_type = attrs.code_type = code_type;
+        attrs_v8.share_location = attrs.share_location = share_location;
+        attrs_v8.nms_threshold = attrs.nms_threshold = nms_threshold;
+        attrs_v8.confidence_threshold = attrs.confidence_threshold = confidence_threshold;
+        attrs_v8.clip_after_nms = attrs.clip_after_nms = clip_after_nms;
+        attrs_v8.clip_before_nms = attrs.clip_before_nms = clip_before_nms;
+        attrs_v8.decrease_label_id = attrs.decrease_label_id = decrease_label_id;
+        attrs_v8.normalized = attrs.normalized = normalized;
+        attrs_v8.input_height = attrs.input_height = input_height;
+        attrs_v8.input_width = attrs.input_width = input_width;
+        attrs_v8.objectness_score = attrs.objectness_score = objectness_score;
 
-              size_t num_loc_classes = attrs.share_location ? 1 : attrs.num_classes;
-              size_t prior_box_size = attrs.normalized ? 4 : 5;
+        size_t num_loc_classes = attrs.share_location ? 1 : attrs.num_classes;
+        size_t prior_box_size = attrs.normalized ? 4 : 5;
 
-              locShape = ov::Shape{num_images, num_prior_boxes * num_loc_classes * prior_box_size};
-              confShape = ov::Shape{num_images, num_prior_boxes * attrs.num_classes};
-              priorBoxesShape =
-              ov::Shape{is_priors_patch_size_1 ? 1UL : num_images, attrs.variance_encoded_in_target ? 1UL : 2UL, num_prior_boxes * prior_box_size};
-              auxLocShape = locShape;
-              auxConfShape = confShape;
-          }
+        locShape = ov::Shape{num_images, num_prior_boxes * num_loc_classes * prior_box_size};
+        confShape = ov::Shape{num_images, num_prior_boxes * attrs.num_classes};
+        priorBoxesShape = ov::Shape{is_priors_patch_size_1 ? 1UL : num_images,
+                                    attrs.variance_encoded_in_target ? 1UL : 2UL,
+                                    num_prior_boxes * prior_box_size};
+        auxLocShape = locShape;
+        auxConfShape = confShape;
+    }
 
     ov::op::v0::DetectionOutput::Attributes attrs;
     ov::op::v8::DetectionOutput::Attributes attrs_v8;
@@ -151,7 +154,8 @@ template <class IT>
     std::string testcaseName;
 };
 
-class ReferenceDetectionOutputLayerTest : public testing::TestWithParam<DetectionOutputParams>, public CommonReferenceTest {
+class ReferenceDetectionOutputLayerTest : public testing::TestWithParam<DetectionOutputParams>,
+                                          public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -186,17 +190,19 @@ class ReferenceDetectionOutputLayerTest : public testing::TestWithParam<Detectio
         if ((params.auxLocShape.size() != 0) && (params.auxConfShape.size() != 0)) {
             const auto auxConf = std::make_shared<op::v0::Parameter>(params.inType, params.auxConfShape);
             const auto auxLoc = std::make_shared<op::v0::Parameter>(params.inType, params.auxLocShape);
-            const auto DetectionOutput = std::make_shared<op::v0::DetectionOutput>(loc, conf, priorBoxes, auxConf, auxLoc, params.attrs);
-            return std::make_shared<ov::Model>(NodeVector {DetectionOutput}, ParameterVector {loc, conf, priorBoxes, auxConf, auxLoc});
+            const auto DetectionOutput =
+                std::make_shared<op::v0::DetectionOutput>(loc, conf, priorBoxes, auxConf, auxLoc, params.attrs);
+            return std::make_shared<ov::Model>(NodeVector{DetectionOutput},
+                                               ParameterVector{loc, conf, priorBoxes, auxConf, auxLoc});
         } else {
             const auto DetectionOutput = std::make_shared<op::v0::DetectionOutput>(loc, conf, priorBoxes, params.attrs);
-            return std::make_shared<ov::Model>(NodeVector {DetectionOutput}, ParameterVector {loc, conf, priorBoxes});
+            return std::make_shared<ov::Model>(NodeVector{DetectionOutput}, ParameterVector{loc, conf, priorBoxes});
         }
     }
 };
 
 class ReferenceDetectionOutputV8LayerTest : public testing::TestWithParam<DetectionOutputParams>,
-                                          public CommonReferenceTest {
+                                            public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -234,9 +240,10 @@ class ReferenceDetectionOutputV8LayerTest : public testing::TestWithParam<Detect
             const auto DetectionOutput =
                 std::make_shared<op::v8::DetectionOutput>(loc, conf, priorBoxes, auxConf, auxLoc, params.attrs_v8);
             return std::make_shared<ov::Model>(NodeVector{DetectionOutput},
-                                                  ParameterVector{loc, conf, priorBoxes, auxConf, auxLoc});
+                                               ParameterVector{loc, conf, priorBoxes, auxConf, auxLoc});
         } else {
-            const auto DetectionOutput = std::make_shared<op::v8::DetectionOutput>(loc, conf, priorBoxes, params.attrs_v8);
+            const auto DetectionOutput =
+                std::make_shared<op::v8::DetectionOutput>(loc, conf, priorBoxes, params.attrs_v8);
             return std::make_shared<ov::Model>(NodeVector{DetectionOutput}, ParameterVector{loc, conf, priorBoxes});
         }
     }
@@ -254,7 +261,7 @@ template <element::Type_t IN_ET>
 std::vector<DetectionOutputParams> generateDetectionOutputFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DetectionOutputParams> detectionOutputParams {
+    std::vector<DetectionOutputParams> detectionOutputParams{
         DetectionOutputParams(3,
                               -1,
                               -1,
@@ -275,33 +282,87 @@ std::vector<DetectionOutputParams> generateDetectionOutputFloatParams() {
                               2,
                               true,
                               IN_ET,
-                              std::vector<T>{
-                                    // batch 0, class 0
-                                    0.1, 0.1, 0.2, 0.2, 0.0, 0.1, 0.2, 0.15,
-                                    // batch 0, class 1
-                                    0.3, 0.2, 0.5, 0.3, 0.2, 0.1, 0.42, 0.66,
-                                    // batch 0, class 2
-                                    0.05, 0.1, 0.2, 0.3, 0.2, 0.1, 0.33, 0.44,
-                                    // batch 1, class 0
-                                    0.2, 0.1, 0.4, 0.2, 0.1, 0.05, 0.2, 0.25,
-                                    // batch 1, class 1
-                                    0.1, 0.2, 0.5, 0.3, 0.1, 0.1, 0.12, 0.34,
-                                    // batch 1, class 2
-                                    0.25, 0.11, 0.4, 0.32, 0.2, 0.12, 0.38, 0.24},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.9, 0.4, 0.7, 0, 0.2,
-                                    // batch 1
-                                    0.7, 0.8, 0.42, 0.33, 0.81, 0.2},
-                              std::vector<T>{
-                                    // prior box 0
-                                    0.0, 0.5, 0.1, 0.2,
-                                    // prior box 1
-                                    0.0, 0.3, 0.1, 0.35},
-                              std::vector<T>{
-                                    0, 0, 0.7,  0.2,  0.4,  0.52, 1,    0, 1, 0.9, 0,   0.6,  0.3, 0.35,
-                                    1, 1, 0.81, 0.25, 0.41, 0.5,  0.67, 1, 1, 0.8, 0.1, 0.55, 0.3, 0.45},
-                                    "3_inputs"),
+                              std::vector<T>{// batch 0, class 0
+                                             0.1,
+                                             0.1,
+                                             0.2,
+                                             0.2,
+                                             0.0,
+                                             0.1,
+                                             0.2,
+                                             0.15,
+                                             // batch 0, class 1
+                                             0.3,
+                                             0.2,
+                                             0.5,
+                                             0.3,
+                                             0.2,
+                                             0.1,
+                                             0.42,
+                                             0.66,
+                                             // batch 0, class 2
+                                             0.05,
+                                             0.1,
+                                             0.2,
+                                             0.3,
+                                             0.2,
+                                             0.1,
+                                             0.33,
+                                             0.44,
+                                             // batch 1, class 0
+                                             0.2,
+                                             0.1,
+                                             0.4,
+                                             0.2,
+                                             0.1,
+                                             0.05,
+                                             0.2,
+                                             0.25,
+                                             // batch 1, class 1
+                                             0.1,
+                                             0.2,
+                                             0.5,
+                                             0.3,
+                                             0.1,
+                                             0.1,
+                                             0.12,
+                                             0.34,
+                                             // batch 1, class 2
+                                             0.25,
+                                             0.11,
+                                             0.4,
+                                             0.32,
+                                             0.2,
+                                             0.12,
+                                             0.38,
+                                             0.24},
+                              std::vector<T>{// batch 0
+                                             0.1,
+                                             0.9,
+                                             0.4,
+                                             0.7,
+                                             0,
+                                             0.2,
+                                             // batch 1
+                                             0.7,
+                                             0.8,
+                                             0.42,
+                                             0.33,
+                                             0.81,
+                                             0.2},
+                              std::vector<T>{// prior box 0
+                                             0.0,
+                                             0.5,
+                                             0.1,
+                                             0.2,
+                                             // prior box 1
+                                             0.0,
+                                             0.3,
+                                             0.1,
+                                             0.35},
+                              std::vector<T>{0, 0, 0.7,  0.2,  0.4,  0.52, 1,    0, 1, 0.9, 0,   0.6,  0.3, 0.35,
+                                             1, 1, 0.81, 0.25, 0.41, 0.5,  0.67, 1, 1, 0.8, 0.1, 0.55, 0.3, 0.45},
+                              "3_inputs"),
         DetectionOutputParams(3,
                               -1,
                               -1,
@@ -322,25 +383,59 @@ std::vector<DetectionOutputParams> generateDetectionOutputFloatParams() {
                               2,
                               false,
                               IN_ET,
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.1, 0.2, 0.2, 0.0, 0.1, 0.2, 0.15,
-                                    // batch 1
-                                    0.2, 0.1, 0.4, 0.2, 0.1, 0.05, 0.2, 0.25},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.9, 0.4, 0.7, 0, 0.2,
-                                    // batch 1
-                                    0.7, 0.8, 0.42, 0.33, 0.81, 0.2},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.0, 0.5, 0.1, 0.2, 0.0, 0.3, 0.1, 0.35,
-                                    // batch 1
-                                    0.33, 0.2, 0.52, 0.37, 0.22, 0.1, 0.32, 0.36},
-                              std::vector<T>{
-                                    0, 0, 0.7,  0,    0.4,  0.3,  0.5,  0, 1, 0.9, 0.1,  0.6, 0.3,  0.4,
-                                    1, 1, 0.81, 0.32, 0.15, 0.52, 0.61, 1, 1, 0.8, 0.53, 0.3, 0.92, 0.57},
-                                    "3_inputs_share_location"),
+                              std::vector<T>{// batch 0
+                                             0.1,
+                                             0.1,
+                                             0.2,
+                                             0.2,
+                                             0.0,
+                                             0.1,
+                                             0.2,
+                                             0.15,
+                                             // batch 1
+                                             0.2,
+                                             0.1,
+                                             0.4,
+                                             0.2,
+                                             0.1,
+                                             0.05,
+                                             0.2,
+                                             0.25},
+                              std::vector<T>{// batch 0
+                                             0.1,
+                                             0.9,
+                                             0.4,
+                                             0.7,
+                                             0,
+                                             0.2,
+                                             // batch 1
+                                             0.7,
+                                             0.8,
+                                             0.42,
+                                             0.33,
+                                             0.81,
+                                             0.2},
+                              std::vector<T>{// batch 0
+                                             0.0,
+                                             0.5,
+                                             0.1,
+                                             0.2,
+                                             0.0,
+                                             0.3,
+                                             0.1,
+                                             0.35,
+                                             // batch 1
+                                             0.33,
+                                             0.2,
+                                             0.52,
+                                             0.37,
+                                             0.22,
+                                             0.1,
+                                             0.32,
+                                             0.36},
+                              std::vector<T>{0, 0, 0.7,  0,    0.4,  0.3,  0.5,  0, 1, 0.9, 0.1,  0.6, 0.3,  0.4,
+                                             1, 1, 0.81, 0.32, 0.15, 0.52, 0.61, 1, 1, 0.8, 0.53, 0.3, 0.92, 0.57},
+                              "3_inputs_share_location"),
         DetectionOutputParams(3,
                               -1,
                               -1,
@@ -361,86 +456,210 @@ std::vector<DetectionOutputParams> generateDetectionOutputFloatParams() {
                               2,
                               false,
                               IN_ET,
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.1, 0.2, 0.2, 0.0, 0.1, 0.2, 0.15,
-                                    // batch 1
-                                    0.2, 0.1, 0.4, 0.2, 0.1, 0.05, 0.2, 0.25},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.9, 0.4, 0.7, 0, 0.2,
-                                    // batch 1
-                                    0.7, 0.8, 0.42, 0.33, 0.81, 0.2},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.0, 0.5, 0.1, 0.2, 0.0, 0.3, 0.1, 0.35,
-                                    // batch 1
-                                    0.33, 0.2, 0.52, 0.37, 0.22, 0.1, 0.32, 0.36},
-                              std::vector<T>{
-                                    0, 0, 0.7,  0,    0.4,  0.3,  0.5,  0, 1, 0.9, 0.1,  0.6, 0.3,  0.4,
-                                    1, 1, 0.81, 0.32, 0.15, 0.52, 0.61, 1, 1, 0.8, 0.53, 0.3, 0.92, 0.57},
-                                    "3_inputs_normalized"),
-        DetectionOutputParams(2,
-                              -1,
-                              -1,
-                              false,
-                              {-1},
-                              "caffe.PriorBoxParameter.CORNER",
-                              false,
-                              0.5,
-                              0.3,
-                              false,
-                              true,
-                              false,
-                              true,
-                              0,
-                              0,
-                              0,
-                              2,
-                              3,
-                              false,
-                              IN_ET,
-                              std::vector<T>{
-                                    // batch 0, class 0
-                                    0.1, 0.1, 0.2, 0.2, 0.0, 0.1, 0.2, 0.15,
-                                    // batch 0, class 1
-                                    0.3, 0.2, 0.5, 0.3, 0.2, 0.1, 0.42, 0.66,
-                                    // batch 1, class 0
-                                    0.05, 0.1, 0.2, 0.3, 0.2, 0.1, 0.33, 0.44,
-                                    // batch 1, class 1
-                                    0.2, 0.1, 0.4, 0.2, 0.1, 0.05, 0.2, 0.25,
-                                    // batch 2, class 0
-                                    0.1, 0.2, 0.5, 0.3, 0.1, 0.1, 0.12, 0.34,
-                                    // batch 2, class 1
-                                    0.25, 0.11, 0.4, 0.32, 0.2, 0.12, 0.38, 0.24},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.9, 0.4, 0.7,
-                                    // batch 1
-                                    0.7, 0.8, 0.42, 0.33,
-                                    // batch 1
-                                    0.1, 0.2, 0.32, 0.43},
-                              std::vector<T>{
-                                    // batch 0 priors
-                                    0.0, 0.5, 0.1, 0.2, 0.0, 0.3, 0.1, 0.35,
-                                    // batch 0 variances
-                                    0.12, 0.11, 0.32, 0.02, 0.02, 0.20, 0.09, 0.71,
-                                    // batch 1 priors
-                                    0.33, 0.2, 0.52, 0.37, 0.22, 0.1, 0.32, 0.36,
-                                    // batch 1 variances
-                                    0.01, 0.07, 0.12, 0.13, 0.41, 0.33, 0.2, 0.1,
-                                    // batch 2 priors
-                                    0.0, 0.3, 0.1, 0.35, 0.22, 0.1, 0.32, 0.36,
-                                    // batch 2 variances
-                                    0.32, 0.02, 0.13, 0.41, 0.33, 0.2, 0.02, 0.20},
-                              std::vector<T>{
-                                    0, 0, 0.4,  0.006, 0.34,   0.145,  0.563,  0,  1, 0.9,  0,      0.511, 0.164,  0.203,
-                                    0, 1, 0.7,  0.004, 0.32,   0.1378, 0.8186, 1,  0, 0.7,  0.3305, 0.207, 0.544,  0.409,
-                                    1, 0, 0.42, 0.302, 0.133,  0.4,    0.38,   1,  1, 0.8,  0.332,  0.207, 0.5596, 0.4272,
-                                    1, 1, 0.33, 0.261, 0.1165, 0.36,   0.385,  2,  0, 0.32, 0.3025, 0.122, 0.328,  0.424,
-                                    2, 1, 0.43, 0.286, 0.124,  0.3276, 0.408,  -1, 0, 0,    0,      0,     0,      0,
-                                    0, 0, 0,    0,     0,      0,      0,      0,  0, 0,    0,      0,     0,      0},
-                                    "3_inputs_keep_all_bboxes"),
+                              std::vector<T>{// batch 0
+                                             0.1,
+                                             0.1,
+                                             0.2,
+                                             0.2,
+                                             0.0,
+                                             0.1,
+                                             0.2,
+                                             0.15,
+                                             // batch 1
+                                             0.2,
+                                             0.1,
+                                             0.4,
+                                             0.2,
+                                             0.1,
+                                             0.05,
+                                             0.2,
+                                             0.25},
+                              std::vector<T>{// batch 0
+                                             0.1,
+                                             0.9,
+                                             0.4,
+                                             0.7,
+                                             0,
+                                             0.2,
+                                             // batch 1
+                                             0.7,
+                                             0.8,
+                                             0.42,
+                                             0.33,
+                                             0.81,
+                                             0.2},
+                              std::vector<T>{// batch 0
+                                             0.0,
+                                             0.5,
+                                             0.1,
+                                             0.2,
+                                             0.0,
+                                             0.3,
+                                             0.1,
+                                             0.35,
+                                             // batch 1
+                                             0.33,
+                                             0.2,
+                                             0.52,
+                                             0.37,
+                                             0.22,
+                                             0.1,
+                                             0.32,
+                                             0.36},
+                              std::vector<T>{0, 0, 0.7,  0,    0.4,  0.3,  0.5,  0, 1, 0.9, 0.1,  0.6, 0.3,  0.4,
+                                             1, 1, 0.81, 0.32, 0.15, 0.52, 0.61, 1, 1, 0.8, 0.53, 0.3, 0.92, 0.57},
+                              "3_inputs_normalized"),
+        DetectionOutputParams(
+            2,
+            -1,
+            -1,
+            false,
+            {-1},
+            "caffe.PriorBoxParameter.CORNER",
+            false,
+            0.5,
+            0.3,
+            false,
+            true,
+            false,
+            true,
+            0,
+            0,
+            0,
+            2,
+            3,
+            false,
+            IN_ET,
+            std::vector<T>{// batch 0, class 0
+                           0.1,
+                           0.1,
+                           0.2,
+                           0.2,
+                           0.0,
+                           0.1,
+                           0.2,
+                           0.15,
+                           // batch 0, class 1
+                           0.3,
+                           0.2,
+                           0.5,
+                           0.3,
+                           0.2,
+                           0.1,
+                           0.42,
+                           0.66,
+                           // batch 1, class 0
+                           0.05,
+                           0.1,
+                           0.2,
+                           0.3,
+                           0.2,
+                           0.1,
+                           0.33,
+                           0.44,
+                           // batch 1, class 1
+                           0.2,
+                           0.1,
+                           0.4,
+                           0.2,
+                           0.1,
+                           0.05,
+                           0.2,
+                           0.25,
+                           // batch 2, class 0
+                           0.1,
+                           0.2,
+                           0.5,
+                           0.3,
+                           0.1,
+                           0.1,
+                           0.12,
+                           0.34,
+                           // batch 2, class 1
+                           0.25,
+                           0.11,
+                           0.4,
+                           0.32,
+                           0.2,
+                           0.12,
+                           0.38,
+                           0.24},
+            std::vector<T>{// batch 0
+                           0.1,
+                           0.9,
+                           0.4,
+                           0.7,
+                           // batch 1
+                           0.7,
+                           0.8,
+                           0.42,
+                           0.33,
+                           // batch 1
+                           0.1,
+                           0.2,
+                           0.32,
+                           0.43},
+            std::vector<T>{// batch 0 priors
+                           0.0,
+                           0.5,
+                           0.1,
+                           0.2,
+                           0.0,
+                           0.3,
+                           0.1,
+                           0.35,
+                           // batch 0 variances
+                           0.12,
+                           0.11,
+                           0.32,
+                           0.02,
+                           0.02,
+                           0.20,
+                           0.09,
+                           0.71,
+                           // batch 1 priors
+                           0.33,
+                           0.2,
+                           0.52,
+                           0.37,
+                           0.22,
+                           0.1,
+                           0.32,
+                           0.36,
+                           // batch 1 variances
+                           0.01,
+                           0.07,
+                           0.12,
+                           0.13,
+                           0.41,
+                           0.33,
+                           0.2,
+                           0.1,
+                           // batch 2 priors
+                           0.0,
+                           0.3,
+                           0.1,
+                           0.35,
+                           0.22,
+                           0.1,
+                           0.32,
+                           0.36,
+                           // batch 2 variances
+                           0.32,
+                           0.02,
+                           0.13,
+                           0.41,
+                           0.33,
+                           0.2,
+                           0.02,
+                           0.20},
+            std::vector<T>{0, 0, 0.4,  0.006, 0.34,   0.145,  0.563,  0,  1, 0.9,  0,      0.511, 0.164,  0.203,
+                           0, 1, 0.7,  0.004, 0.32,   0.1378, 0.8186, 1,  0, 0.7,  0.3305, 0.207, 0.544,  0.409,
+                           1, 0, 0.42, 0.302, 0.133,  0.4,    0.38,   1,  1, 0.8,  0.332,  0.207, 0.5596, 0.4272,
+                           1, 1, 0.33, 0.261, 0.1165, 0.36,   0.385,  2,  0, 0.32, 0.3025, 0.122, 0.328,  0.424,
+                           2, 1, 0.43, 0.286, 0.124,  0.3276, 0.408,  -1, 0, 0,    0,      0,     0,      0,
+                           0, 0, 0,    0,     0,      0,      0,      0,  0, 0,    0,      0,     0,      0},
+            "3_inputs_keep_all_bboxes"),
         DetectionOutputParams(3,
                               -1,
                               -1,
@@ -461,35 +680,97 @@ std::vector<DetectionOutputParams> generateDetectionOutputFloatParams() {
                               2,
                               false,
                               IN_ET,
-                              std::vector<T>{
-                                    // batch 0, class 0
-                                    0.1, 0.1, 0.2, 0.2, 0.0, 0.1, 0.2, 0.15,
-                                    // batch 0, class 1
-                                    0.3, 0.2, 0.5, 0.3, 0.2, 0.1, 0.42, 0.66,
-                                    // batch 0, class 2
-                                    0.05, 0.1, 0.2, 0.3, 0.2, 0.1, 0.33, 0.44,
-                                    // batch 1, class 0
-                                    0.2, 0.1, 0.4, 0.2, 0.1, 0.05, 0.2, 0.25,
-                                    // batch 1, class 1
-                                    0.1, 0.2, 0.5, 0.3, 0.1, 0.1, 0.12, 0.34,
-                                    // batch 1, class 2
-                                    0.25, 0.11, 0.4, 0.32, 0.2, 0.12, 0.38, 0.24},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.9, 0.4, 0.7, 0, 0.2,
-                                    // batch 1
-                                    0.7, 0.8, 0.42, 0.33, 0.81, 0.2},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.0, 0.5, 0.1, 0.2, 0.0, 0.3, 0.1, 0.35,
-                                    // batch 1
-                                    0.33, 0.2, 0.52, 0.37, 0.22, 0.1, 0.32, 0.36},
-                              std::vector<T>{
-                                    0, 0, 0.7,  0,          0.28163019,  0.14609808, 0.37836978,
-                                    0, 1, 0.9,  0,          0.49427515,  0.11107014, 0.14572485,
-                                    1, 1, 0.81, 0.22040875, 0.079573378, 0.36959124, 0.4376266,
-                                    1, 1, 0.8,  0.32796675, 0.18435785,  0.56003326, 0.40264216},
-                                    "3_inputs_center_size"),
+                              std::vector<T>{// batch 0, class 0
+                                             0.1,
+                                             0.1,
+                                             0.2,
+                                             0.2,
+                                             0.0,
+                                             0.1,
+                                             0.2,
+                                             0.15,
+                                             // batch 0, class 1
+                                             0.3,
+                                             0.2,
+                                             0.5,
+                                             0.3,
+                                             0.2,
+                                             0.1,
+                                             0.42,
+                                             0.66,
+                                             // batch 0, class 2
+                                             0.05,
+                                             0.1,
+                                             0.2,
+                                             0.3,
+                                             0.2,
+                                             0.1,
+                                             0.33,
+                                             0.44,
+                                             // batch 1, class 0
+                                             0.2,
+                                             0.1,
+                                             0.4,
+                                             0.2,
+                                             0.1,
+                                             0.05,
+                                             0.2,
+                                             0.25,
+                                             // batch 1, class 1
+                                             0.1,
+                                             0.2,
+                                             0.5,
+                                             0.3,
+                                             0.1,
+                                             0.1,
+                                             0.12,
+                                             0.34,
+                                             // batch 1, class 2
+                                             0.25,
+                                             0.11,
+                                             0.4,
+                                             0.32,
+                                             0.2,
+                                             0.12,
+                                             0.38,
+                                             0.24},
+                              std::vector<T>{// batch 0
+                                             0.1,
+                                             0.9,
+                                             0.4,
+                                             0.7,
+                                             0,
+                                             0.2,
+                                             // batch 1
+                                             0.7,
+                                             0.8,
+                                             0.42,
+                                             0.33,
+                                             0.81,
+                                             0.2},
+                              std::vector<T>{// batch 0
+                                             0.0,
+                                             0.5,
+                                             0.1,
+                                             0.2,
+                                             0.0,
+                                             0.3,
+                                             0.1,
+                                             0.35,
+                                             // batch 1
+                                             0.33,
+                                             0.2,
+                                             0.52,
+                                             0.37,
+                                             0.22,
+                                             0.1,
+                                             0.32,
+                                             0.36},
+                              std::vector<T>{0, 0, 0.7,  0,          0.28163019,  0.14609808, 0.37836978,
+                                             0, 1, 0.9,  0,          0.49427515,  0.11107014, 0.14572485,
+                                             1, 1, 0.81, 0.22040875, 0.079573378, 0.36959124, 0.4376266,
+                                             1, 1, 0.8,  0.32796675, 0.18435785,  0.56003326, 0.40264216},
+                              "3_inputs_center_size"),
         DetectionOutputParams(2,
                               -1,
                               -1,
@@ -510,54 +791,130 @@ std::vector<DetectionOutputParams> generateDetectionOutputFloatParams() {
                               2,
                               false,
                               IN_ET,
-                              std::vector<T>{
-                                    // batch 0, class 0
-                                    0.1, 0.1, 0.2, 0.2, 0.0, 0.1, 0.2, 0.15,
-                                    // batch 0, class 1
-                                    0.3, 0.2, 0.5, 0.3, 0.2, 0.1, 0.42, 0.66,
-                                    // batch 1, class 0
-                                    0.2, 0.1, 0.4, 0.2, 0.1, 0.05, 0.2, 0.25,
-                                    // batch 1, class 1
-                                    0.1, 0.2, 0.5, 0.3, 0.1, 0.1, 0.12, 0.34},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.9, 0.4, 0.7,
-                                    // batch 1
-                                    0.42, 0.33, 0.81, 0.2},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.0, 0.5, 0.1, 0.2, 0.0, 0.3, 0.1, 0.35,
-                                    // batch 1
-                                    0.33, 0.2, 0.52, 0.37, 0.22, 0.1, 0.32, 0.36},
-                              std::vector<T>{
-                                    0, 0, 0.4,  0.55, 0.61, 1, 0.97, 0, 1, 0.7,  0.4,  0.52, 0.9, 1,
-                                    1, 0, 0.42, 0.83, 0.5,  1, 0.87, 1, 1, 0.33, 0.63, 0.35, 1,   1},
-                              std::vector<T>{
-                                    // batch 0, class 0
-                                    0.1, 0.2, 0.5, 0.3, 0.1, 0.1, 0.12, 0.34,
-                                    // batch 0, class 1
-                                    0.25, 0.11, 0.4, 0.32, 0.2, 0.12, 0.38, 0.24,
-                                    // batch 1, class 0
-                                    0.3, 0.2, 0.5, 0.3, 0.2, 0.1, 0.42, 0.66,
-                                    // batch 1, class 1
-                                    0.05, 0.1, 0.2, 0.3, 0.2, 0.1, 0.33, 0.44},
-                              std::vector<T>{
-                                    // batch 0
-                                    0.1, 0.3, 0.5, 0.8,
-                                    // batch 1
-                                    0.5, 0.8, 0.01, 0.1},
-                                    "5_inputs"),
+                              std::vector<T>{// batch 0, class 0
+                                             0.1,
+                                             0.1,
+                                             0.2,
+                                             0.2,
+                                             0.0,
+                                             0.1,
+                                             0.2,
+                                             0.15,
+                                             // batch 0, class 1
+                                             0.3,
+                                             0.2,
+                                             0.5,
+                                             0.3,
+                                             0.2,
+                                             0.1,
+                                             0.42,
+                                             0.66,
+                                             // batch 1, class 0
+                                             0.2,
+                                             0.1,
+                                             0.4,
+                                             0.2,
+                                             0.1,
+                                             0.05,
+                                             0.2,
+                                             0.25,
+                                             // batch 1, class 1
+                                             0.1,
+                                             0.2,
+                                             0.5,
+                                             0.3,
+                                             0.1,
+                                             0.1,
+                                             0.12,
+                                             0.34},
+                              std::vector<T>{// batch 0
+                                             0.1,
+                                             0.9,
+                                             0.4,
+                                             0.7,
+                                             // batch 1
+                                             0.42,
+                                             0.33,
+                                             0.81,
+                                             0.2},
+                              std::vector<T>{// batch 0
+                                             0.0,
+                                             0.5,
+                                             0.1,
+                                             0.2,
+                                             0.0,
+                                             0.3,
+                                             0.1,
+                                             0.35,
+                                             // batch 1
+                                             0.33,
+                                             0.2,
+                                             0.52,
+                                             0.37,
+                                             0.22,
+                                             0.1,
+                                             0.32,
+                                             0.36},
+                              std::vector<T>{0, 0, 0.4,  0.55, 0.61, 1, 0.97, 0, 1, 0.7,  0.4,  0.52, 0.9, 1,
+                                             1, 0, 0.42, 0.83, 0.5,  1, 0.87, 1, 1, 0.33, 0.63, 0.35, 1,   1},
+                              std::vector<T>{// batch 0, class 0
+                                             0.1,
+                                             0.2,
+                                             0.5,
+                                             0.3,
+                                             0.1,
+                                             0.1,
+                                             0.12,
+                                             0.34,
+                                             // batch 0, class 1
+                                             0.25,
+                                             0.11,
+                                             0.4,
+                                             0.32,
+                                             0.2,
+                                             0.12,
+                                             0.38,
+                                             0.24,
+                                             // batch 1, class 0
+                                             0.3,
+                                             0.2,
+                                             0.5,
+                                             0.3,
+                                             0.2,
+                                             0.1,
+                                             0.42,
+                                             0.66,
+                                             // batch 1, class 1
+                                             0.05,
+                                             0.1,
+                                             0.2,
+                                             0.3,
+                                             0.2,
+                                             0.1,
+                                             0.33,
+                                             0.44},
+                              std::vector<T>{// batch 0
+                                             0.1,
+                                             0.3,
+                                             0.5,
+                                             0.8,
+                                             // batch 1
+                                             0.5,
+                                             0.8,
+                                             0.01,
+                                             0.1},
+                              "5_inputs"),
     };
     return detectionOutputParams;
 }
 
 std::vector<DetectionOutputParams> generateDetectionOutputCombinedParams() {
-    const std::vector<std::vector<DetectionOutputParams>> detectionOutputTypeParams {
+    const std::vector<std::vector<DetectionOutputParams>> detectionOutputTypeParams{
         generateDetectionOutputFloatParams<element::Type_t::f64>(),
         generateDetectionOutputFloatParams<element::Type_t::f32>(),
         generateDetectionOutputFloatParams<element::Type_t::f16>(),
         generateDetectionOutputFloatParams<element::Type_t::bf16>(),
-        };
+    };
     std::vector<DetectionOutputParams> combinedParams;
 
     for (const auto& params : detectionOutputTypeParams) {
@@ -566,12 +923,14 @@ std::vector<DetectionOutputParams> generateDetectionOutputCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_DetectionOutput_With_Hardcoded_Refs, ReferenceDetectionOutputLayerTest,
-    testing::ValuesIn(generateDetectionOutputCombinedParams()), ReferenceDetectionOutputLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_DetectionOutput_With_Hardcoded_Refs,
+                         ReferenceDetectionOutputLayerTest,
+                         testing::ValuesIn(generateDetectionOutputCombinedParams()),
+                         ReferenceDetectionOutputLayerTest::getTestCaseName);
 
 INSTANTIATE_TEST_SUITE_P(smoke_DetectionOutput_With_Hardcoded_Refs,
                          ReferenceDetectionOutputV8LayerTest,
                          testing::ValuesIn(generateDetectionOutputCombinedParams()),
                          ReferenceDetectionOutputV8LayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/dft.cpp b/src/plugins/template/tests/functional/op_reference/dft.cpp
index 4537ec541d2782..5b742a3909b5f9 100644
--- a/src/plugins/template/tests/functional/op_reference/dft.cpp
+++ b/src/plugins/template/tests/functional/op_reference/dft.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/dft.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/dft.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -16,13 +17,13 @@ namespace {
 struct DFTParams {
     template <class T>
     DFTParams(const Shape& input_shape,
-                 const Shape& expected_shape,
-                 const element::Type_t& input_type,
-                 const element::Type_t& expected_type,
-                 const std::vector<T>& input_value,
-                 const std::vector<T>& expected_value,
-                 const std::shared_ptr<op::v0::Constant>& axes,
-                 const std::shared_ptr<op::v0::Constant>& signal) {
+              const Shape& expected_shape,
+              const element::Type_t& input_type,
+              const element::Type_t& expected_type,
+              const std::vector<T>& input_value,
+              const std::vector<T>& expected_value,
+              const std::shared_ptr<op::v0::Constant>& axes,
+              const std::shared_ptr<op::v0::Constant>& signal) {
         m_input_shape = input_shape;
         m_expected_shape = expected_shape;
         m_input_type = input_type;
@@ -1118,7 +1119,7 @@ static const std::vector<float> expected_dft3d_signal_size_results = {
     1.1392056,    -4.696983,   0.45275614,   1.9134089,  -3.8572056,   -2.009159,   1.6307822,   -0.9646755,
     -1.2407924,   2.6003554};
 
-template<class T>
+template <class T>
 static std::vector<T> convert(const std::vector<float>& v) {
     if (v.empty()) {
         return std::vector<T>();
@@ -1402,10 +1403,9 @@ std::vector<DFTParams> generateCombinedParamsForDFT() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_DFT_With_Hardcoded_Refs,
-    ReferenceDFTLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForDFT()),
-    ReferenceDFTLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_DFT_With_Hardcoded_Refs,
+                         ReferenceDFTLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForDFT()),
+                         ReferenceDFTLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/divide.cpp b/src/plugins/template/tests/functional/op_reference/divide.cpp
index c89b133e431832..5588bc95c9e2a2 100644
--- a/src/plugins/template/tests/functional/op_reference/divide.cpp
+++ b/src/plugins/template/tests/functional/op_reference/divide.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/divide.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/divide.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,11 +16,11 @@ namespace {
 struct DivideParams {
     template <class IT>
     DivideParams(const PartialShape& iShape1,
-              const PartialShape& iShape2,
-              const element::Type& iType,
-              const std::vector<IT>& iValues1,
-              const std::vector<IT>& iValues2,
-              const std::vector<IT>& oValues)
+                 const PartialShape& iShape2,
+                 const element::Type& iType,
+                 const std::vector<IT>& iValues1,
+                 const std::vector<IT>& iValues2,
+                 const std::vector<IT>& oValues)
         : pshape1(iShape1),
           pshape2(iShape2),
           inType(iType),
@@ -45,7 +47,8 @@ struct DivideRoundingParams : public DivideParams {
                          const std::vector<IT>& iValues2,
                          const std::vector<IT>& oValues,
                          const bool pythondiv)
-        : DivideParams(iShape1, iShape2, iType, iValues1, iValues2, oValues), pythonDivision(pythondiv) {}
+        : DivideParams(iShape1, iShape2, iType, iValues1, iValues2, oValues),
+          pythonDivision(pythondiv) {}
 
     bool pythonDivision;
 };
@@ -71,9 +74,9 @@ class ReferenceDivideLayerTest : public testing::TestWithParam<DivideParams>, pu
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto divide = std::make_shared<op::v1::Divide>(in1, in2);
@@ -81,7 +84,8 @@ class ReferenceDivideLayerTest : public testing::TestWithParam<DivideParams>, pu
     }
 };
 
-class ReferenceDivideRoundingLayerTest : public testing::TestWithParam<DivideRoundingParams>, public CommonReferenceTest {
+class ReferenceDivideRoundingLayerTest : public testing::TestWithParam<DivideRoundingParams>,
+                                         public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -102,14 +106,14 @@ class ReferenceDivideRoundingLayerTest : public testing::TestWithParam<DivideRou
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type,
-                                                    const bool pythondiv) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type,
+                                                 const bool pythondiv) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto divide = std::make_shared<op::v1::Divide>(in1, in2, pythondiv);
-        return  std::make_shared<Model>(NodeVector{divide}, ParameterVector{in1, in2});
+        return std::make_shared<Model>(NodeVector{divide}, ParameterVector{in1, in2});
     }
 };
 
@@ -125,14 +129,12 @@ template <element::Type_t IN_ET>
 std::vector<DivideParams> generateParamsForDivide() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DivideParams> params{
-        DivideParams(ov::PartialShape{2, 2},
-                     ov::PartialShape{2, 2},
-                     IN_ET,
-                     std::vector<T>{2, 4, 8, 16},
-                     std::vector<T>{1, 2, 4, 8},
-                     std::vector<T>{2, 2, 2, 2})
-    };
+    std::vector<DivideParams> params{DivideParams(ov::PartialShape{2, 2},
+                                                  ov::PartialShape{2, 2},
+                                                  IN_ET,
+                                                  std::vector<T>{2, 4, 8, 16},
+                                                  std::vector<T>{1, 2, 4, 8},
+                                                  std::vector<T>{2, 2, 2, 2})};
     return params;
 }
 
@@ -140,23 +142,21 @@ template <element::Type_t IN_ET>
 std::vector<DivideParams> generateParamsForDivideFloat32() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DivideParams> params{
-        DivideParams(ov::PartialShape{1},
-                     ov::PartialShape{1},
-                     IN_ET,
-                     std::vector<T>{18},
-                     std::vector<T>{8},
-                     std::vector<T>{2.25}),
-        DivideParams(ov::PartialShape{2, 2},
-                     ov::PartialShape{2, 2},
-                     IN_ET,
-                     std::vector<T>{2, 4, 8, 16},
-                     std::vector<T>{0, 0, 0, 0},
-                     std::vector<T>{std::numeric_limits<float>::infinity(),
-                                    std::numeric_limits<float>::infinity(),
-                                    std::numeric_limits<float>::infinity(),
-                                    std::numeric_limits<float>::infinity()})
-    };
+    std::vector<DivideParams> params{DivideParams(ov::PartialShape{1},
+                                                  ov::PartialShape{1},
+                                                  IN_ET,
+                                                  std::vector<T>{18},
+                                                  std::vector<T>{8},
+                                                  std::vector<T>{2.25}),
+                                     DivideParams(ov::PartialShape{2, 2},
+                                                  ov::PartialShape{2, 2},
+                                                  IN_ET,
+                                                  std::vector<T>{2, 4, 8, 16},
+                                                  std::vector<T>{0, 0, 0, 0},
+                                                  std::vector<T>{std::numeric_limits<float>::infinity(),
+                                                                 std::numeric_limits<float>::infinity(),
+                                                                 std::numeric_limits<float>::infinity(),
+                                                                 std::numeric_limits<float>::infinity()})};
     return params;
 }
 
@@ -164,20 +164,18 @@ template <element::Type_t IN_ET>
 std::vector<DivideParams> generateParamsForDivideInt32() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DivideParams> params{
-        DivideParams(ov::PartialShape{2, 2},
-                     ov::PartialShape{2, 2},
-                     IN_ET,
-                     std::vector<T>{0x40000140, 0x40000001, 8, 16},
-                     std::vector<T>{2, 5, 4, 8},
-                     std::vector<T>{536871072, 214748365, 2, 2}),
-        DivideParams(ov::PartialShape{1},
-                     ov::PartialShape{1},
-                     IN_ET,
-                     std::vector<T>{18},
-                     std::vector<T>{8},
-                     std::vector<T>{2})
-    };
+    std::vector<DivideParams> params{DivideParams(ov::PartialShape{2, 2},
+                                                  ov::PartialShape{2, 2},
+                                                  IN_ET,
+                                                  std::vector<T>{0x40000140, 0x40000001, 8, 16},
+                                                  std::vector<T>{2, 5, 4, 8},
+                                                  std::vector<T>{536871072, 214748365, 2, 2}),
+                                     DivideParams(ov::PartialShape{1},
+                                                  ov::PartialShape{1},
+                                                  IN_ET,
+                                                  std::vector<T>{18},
+                                                  std::vector<T>{8},
+                                                  std::vector<T>{2})};
     return params;
 }
 
@@ -191,13 +189,8 @@ std::vector<DivideParams> generateParamsForDivideBroadcast() {
                      IN_ET,
                      std::vector<T>{12, 24, 36, 48, 60, 72},
                      std::vector<T>{1, 2, 3, 4, 6, 1},
-                     std::vector<T>{12,  6,  4,  3,  2,  12,
-                                    24, 12,  8,  6,  4,  24,
-                                    36, 18, 12, 9,  6,  36,
-                                    48, 24, 16, 12, 8,  48,
-                                    60, 30, 20, 15, 10, 60,
-                                    72, 36, 24, 18, 12, 72})
-    };
+                     std::vector<T>{12, 6,  4,  3,  2, 12, 24, 12, 8,  6,  4,  24, 36, 18, 12, 9,  6,  36,
+                                    48, 24, 16, 12, 8, 48, 60, 30, 20, 15, 10, 60, 72, 36, 24, 18, 12, 72})};
     return params;
 }
 
@@ -205,14 +198,12 @@ template <element::Type_t IN_ET>
 std::vector<DivideParams> generateParamsForDividePythonRoundingInt32() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DivideParams> params{
-        DivideParams(ov::PartialShape{2, 2},
-                     ov::PartialShape{2, 2},
-                     IN_ET,
-                     std::vector<T>{-10, -10, 10, 10},
-                     std::vector<T>{-3, 3, -3, 3},
-                     std::vector<T>{3, -4, -4, 3})
-    };
+    std::vector<DivideParams> params{DivideParams(ov::PartialShape{2, 2},
+                                                  ov::PartialShape{2, 2},
+                                                  IN_ET,
+                                                  std::vector<T>{-10, -10, 10, 10},
+                                                  std::vector<T>{-3, 3, -3, 3},
+                                                  std::vector<T>{3, -4, -4, 3})};
     return params;
 }
 
@@ -220,28 +211,24 @@ template <element::Type_t IN_ET>
 std::vector<DivideRoundingParams> generateParamsForDivideCppRoundingInt32() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<DivideRoundingParams> params{
-        DivideRoundingParams(ov::PartialShape{2, 2},
-                     ov::PartialShape{2, 2},
-                     IN_ET,
-                     std::vector<T>{-10, -10, 10, 10},
-                     std::vector<T>{-3, 3, -3, 3},
-                     std::vector<T>{3, -3, -3, 3},
-                     false)
-    };
+    std::vector<DivideRoundingParams> params{DivideRoundingParams(ov::PartialShape{2, 2},
+                                                                  ov::PartialShape{2, 2},
+                                                                  IN_ET,
+                                                                  std::vector<T>{-10, -10, 10, 10},
+                                                                  std::vector<T>{-3, 3, -3, 3},
+                                                                  std::vector<T>{3, -3, -3, 3},
+                                                                  false)};
     return params;
 }
 
 std::vector<DivideParams> generateCombinedParamsForDivide() {
-    const std::vector<std::vector<DivideParams>> allTypeParams{
-        generateParamsForDivide<element::Type_t::f32>(),
-        generateParamsForDivide<element::Type_t::f16>(),
-        generateParamsForDivide<element::Type_t::bf16>(),
-        generateParamsForDivide<element::Type_t::i64>(),
-        generateParamsForDivide<element::Type_t::i32>(),
-        generateParamsForDivide<element::Type_t::u64>(),
-        generateParamsForDivide<element::Type_t::u32>()
-    };
+    const std::vector<std::vector<DivideParams>> allTypeParams{generateParamsForDivide<element::Type_t::f32>(),
+                                                               generateParamsForDivide<element::Type_t::f16>(),
+                                                               generateParamsForDivide<element::Type_t::bf16>(),
+                                                               generateParamsForDivide<element::Type_t::i64>(),
+                                                               generateParamsForDivide<element::Type_t::i32>(),
+                                                               generateParamsForDivide<element::Type_t::u64>(),
+                                                               generateParamsForDivide<element::Type_t::u32>()};
 
     std::vector<DivideParams> combinedParams;
 
@@ -253,9 +240,7 @@ std::vector<DivideParams> generateCombinedParamsForDivide() {
 }
 
 std::vector<DivideParams> generateCombinedParamsForDivideFloat32() {
-    const std::vector<std::vector<DivideParams>> allTypeParams{
-        generateParamsForDivideFloat32<element::Type_t::f32>()
-    };
+    const std::vector<std::vector<DivideParams>> allTypeParams{generateParamsForDivideFloat32<element::Type_t::f32>()};
 
     std::vector<DivideParams> combinedParams;
 
@@ -267,9 +252,7 @@ std::vector<DivideParams> generateCombinedParamsForDivideFloat32() {
 }
 
 std::vector<DivideParams> generateCombinedParamsForDivideInt32() {
-    const std::vector<std::vector<DivideParams>> allTypeParams{
-        generateParamsForDivideInt32<element::Type_t::i32>()
-    };
+    const std::vector<std::vector<DivideParams>> allTypeParams{generateParamsForDivideInt32<element::Type_t::i32>()};
 
     std::vector<DivideParams> combinedParams;
 
@@ -283,8 +266,7 @@ std::vector<DivideParams> generateCombinedParamsForDivideInt32() {
 std::vector<DivideParams> generateCombinedParamsForDivideBroadcast() {
     const std::vector<std::vector<DivideParams>> allTypeParams{
         generateParamsForDivideBroadcast<element::Type_t::f32>(),
-        generateParamsForDivideBroadcast<element::Type_t::i32>()
-    };
+        generateParamsForDivideBroadcast<element::Type_t::i32>()};
 
     std::vector<DivideParams> combinedParams;
 
@@ -297,8 +279,7 @@ std::vector<DivideParams> generateCombinedParamsForDivideBroadcast() {
 
 std::vector<DivideParams> generateCombinedParamsForDividePythonRoundingInt32() {
     const std::vector<std::vector<DivideParams>> allTypeParams{
-        generateParamsForDividePythonRoundingInt32<element::Type_t::i32>()
-    };
+        generateParamsForDividePythonRoundingInt32<element::Type_t::i32>()};
 
     std::vector<DivideParams> combinedParams;
 
@@ -311,8 +292,7 @@ std::vector<DivideParams> generateCombinedParamsForDividePythonRoundingInt32() {
 
 std::vector<DivideRoundingParams> generateCombinedParamsForDivideCppRoundingInt32() {
     const std::vector<std::vector<DivideRoundingParams>> allTypeParams{
-        generateParamsForDivideCppRoundingInt32<element::Type_t::i32>()
-    };
+        generateParamsForDivideCppRoundingInt32<element::Type_t::i32>()};
 
     std::vector<DivideRoundingParams> combinedParams;
 
@@ -323,40 +303,34 @@ std::vector<DivideRoundingParams> generateCombinedParamsForDivideCppRoundingInt3
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Divide_With_Hardcoded_Refs,
-    ReferenceDivideLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForDivide()),
-    ReferenceDivideLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Divide_Float32_With_Hardcoded_Refs,
-    ReferenceDivideLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForDivideFloat32()),
-    ReferenceDivideLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Divide_Int32_With_Hardcoded_Refs,
-    ReferenceDivideLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForDivideInt32()),
-    ReferenceDivideLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Divide_Broadcast_With_Hardcoded_Refs,
-    ReferenceDivideLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForDivideBroadcast()),
-    ReferenceDivideLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Divide_Python_Rounding_Int32_With_Hardcoded_Refs,
-    ReferenceDivideLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForDividePythonRoundingInt32()),
-    ReferenceDivideLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Divide_Cpp_Rounding_Int32_With_Hardcoded_Refs,
-    ReferenceDivideRoundingLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForDivideCppRoundingInt32()),
-    ReferenceDivideRoundingLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Divide_With_Hardcoded_Refs,
+                         ReferenceDivideLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForDivide()),
+                         ReferenceDivideLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Divide_Float32_With_Hardcoded_Refs,
+                         ReferenceDivideLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForDivideFloat32()),
+                         ReferenceDivideLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Divide_Int32_With_Hardcoded_Refs,
+                         ReferenceDivideLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForDivideInt32()),
+                         ReferenceDivideLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Divide_Broadcast_With_Hardcoded_Refs,
+                         ReferenceDivideLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForDivideBroadcast()),
+                         ReferenceDivideLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Divide_Python_Rounding_Int32_With_Hardcoded_Refs,
+                         ReferenceDivideLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForDividePythonRoundingInt32()),
+                         ReferenceDivideLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Divide_Cpp_Rounding_Int32_With_Hardcoded_Refs,
+                         ReferenceDivideRoundingLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForDivideCppRoundingInt32()),
+                         ReferenceDivideRoundingLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/einsum.cpp b/src/plugins/template/tests/functional/op_reference/einsum.cpp
index d3aeb727b60ce7..400fdc445c5387 100644
--- a/src/plugins/template/tests/functional/op_reference/einsum.cpp
+++ b/src/plugins/template/tests/functional/op_reference/einsum.cpp
@@ -4,9 +4,9 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset7.hpp"
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
+#include "openvino/opsets/opset7.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -73,37 +73,33 @@ TEST_P(ReferenceEinsumTest, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<EinsumParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<EinsumParams> params {
-        Builder {}
+    std::vector<EinsumParams> params{
+        Builder{}
             .inputs({{ET, {1, 2}, std::vector<T>{1, 2}},
-                     {ET, {3, 4}, std::vector<T>{3, 4, 5, 6,
-                                                 7, 8, 9, 10,
-                                                 11, 12, 13, 14}}})
+                     {ET, {3, 4}, std::vector<T>{3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14}}})
             .equation("ab,cd->abcd")
-            .expectedResult({ET, {1, 2, 3, 4}, std::vector<T>{3,  4,  5,  6,  7,  8,  9,  10,
-                                                              11, 12, 13, 14, 6,  8,  10, 12,
-                                                              14, 16, 18, 20, 22, 24, 26, 28}})
+            .expectedResult({ET, {1, 2, 3, 4}, std::vector<T>{3, 4, 5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                              6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28}})
             .testcaseName("einsum_no_reduction"),
-        Builder {}
+        Builder{}
             .inputs({{ET, {1, 2, 3}, std::vector<T>{1, 2, 3, 4, 5, 6}}})
             .equation("ijk->kij")
             .expectedResult({ET, {3, 1, 2}, std::vector<T>{1, 4, 2, 5, 3, 6}})
             .testcaseName("einsum_transpose"),
 
-        Builder {}
+        Builder{}
             .inputs({{ET, {2, 3}, std::vector<T>{1, 2, 3, 4, 5, 6}}})
             .equation("ab->a")
             .expectedResult({ET, {2}, std::vector<T>{6, 15}})
             .testcaseName("einsum_reduce"),
 
-        Builder {}
-            .inputs({{ET, {2, 3}, std::vector<T>{1, 2, 3, 4, 5, 6}},
-                     {ET, {3, 2}, std::vector<T>{1, 2, 3, 4, 5, 6}}})
+        Builder{}
+            .inputs({{ET, {2, 3}, std::vector<T>{1, 2, 3, 4, 5, 6}}, {ET, {3, 2}, std::vector<T>{1, 2, 3, 4, 5, 6}}})
             .equation("ab,bc->ac")
             .expectedResult({ET, {2, 2}, std::vector<T>{22, 28, 49, 64}})
             .testcaseName("einsum_matrix_multiplication"),
 
-        Builder {}
+        Builder{}
             .inputs({{ET, {2, 4}, std::vector<T>{1, 3, 2, 7, 5, 6, 0, 1}},
                      {ET, {4, 3, 1}, std::vector<T>{1, 2, 3, 4, 5, 6, 5, 7, 3, 7, 9, 1}},
                      {ET, {4, 3}, std::vector<T>{4, 3, 1, 6, 4, 2, 2, 5, 3, 1, 9, 4}}})
@@ -111,50 +107,47 @@ std::vector<EinsumParams> generateParams() {
             .expectedResult({ET, {3, 2}, std::vector<T>{145, 171, 703, 231, 85, 91}})
             .testcaseName("einsum_multiple_multiplication"),
 
-        Builder {}
+        Builder{}
             .inputs({{ET, {2, 2, 3}, std::vector<T>{1, 3, 2, 7, 5, 6, 3, 5, 2, 1, 0, 7}}})
             .equation("a...->...")
             .expectedResult({ET, {2, 3}, std::vector<T>{4, 8, 4, 8, 5, 13}})
             .testcaseName("einsum_ellipsis_one_input_reduction"),
 
-        Builder {}
+        Builder{}
             .inputs({{ET, {2, 2, 3}, std::vector<T>{1, 3, 2, 7, 5, 6, 3, 5, 2, 1, 0, 7}}})
             .equation("a...->...a")
             .expectedResult({ET, {2, 3, 2}, std::vector<T>{1, 3, 3, 5, 2, 2, 7, 1, 5, 0, 6, 7}})
             .testcaseName("einsum_ellipsis_one_input_transpose"),
 
-        Builder {}
-            .inputs({{ET, {2, 2, 3}, std::vector<T>{1, 3, 2, 7, 5, 6, 3, 5, 2, 1, 0, 7}},
-                     {ET, {1}, std::vector<T>{2}}})
+        Builder{}
+            .inputs({{ET, {2, 2, 3}, std::vector<T>{1, 3, 2, 7, 5, 6, 3, 5, 2, 1, 0, 7}}, {ET, {1}, std::vector<T>{2}}})
             .equation("ab...,...->ab...")
             .expectedResult({ET, {2, 2, 3}, std::vector<T>{2, 6, 4, 14, 10, 12, 6, 10, 4, 2, 0, 14}})
             .testcaseName("einsum_ellipsis_mul_by_1dscalar"),
 
-        Builder {}
+        Builder{}
             .inputs({{ET, {1, 1, 4, 3}, std::vector<T>{1, 3, 2, 7, 5, 6, 3, 5, 2, 1, 0, 7}},
                      {ET, {3, 4, 2, 1}, std::vector<T>{3, 1, 6, 2, 3, 10, 9,  8, 2, 9, 3, 2,
                                                        4, 2, 3, 1, 9, 1,  11, 4, 7, 2, 3, 1}}})
             .equation("a...j,j...->a...")
-            .expectedResult({ET, {1, 4, 2, 4}, std::vector<T>{27, 85,  37, 66, 30, 58, 50, 8,
-                                                              37, 123, 55, 83, 16, 48, 24, 30,
-                                                              29, 83,  43, 52, 20, 92, 44, 24,
-                                                              24, 96,  48, 30, 13, 67, 31, 15}})
+            .expectedResult(
+                {ET, {1, 4, 2, 4}, std::vector<T>{27, 85, 37, 66, 30, 58, 50, 8,  37, 123, 55, 83, 16, 48, 24, 30,
+                                                  29, 83, 43, 52, 20, 92, 44, 24, 24, 96,  48, 30, 13, 67, 31, 15}})
             .testcaseName("einsum_ellipsis_complex_mul"),
 
-        Builder {}
+        Builder{}
             .inputs({{ET, {1, 3, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9}}})
             .equation("kii->ki")
             .expectedResult({ET, {1, 3}, std::vector<T>{1, 5, 9}})
             .testcaseName("einsum_diagonal"),
 
-        Builder {}
-            .inputs({{ET, {2, 3, 3, 2, 4}, std::vector<T>{4, 2, 5, 4, 5, 5, 1, 1, 3, 3, 1, 1, 2, 2, 4, 1, 3, 4,
-                                                          4, 5, 1, 3, 1, 3, 1, 4, 3, 5, 4, 4, 5, 4, 4, 5, 4, 2,
-                                                          2, 2, 3, 3, 1, 1, 4, 3, 4, 2, 2, 1, 1, 2, 3, 1, 1, 4,
-                                                          2, 3, 1, 3, 4, 2, 5, 5, 3, 4, 3, 4, 5, 4, 4, 5, 1, 3,
-                                                          4, 4, 5, 3, 1, 3, 2, 5, 3, 2, 5, 4, 4, 2, 4, 4, 1, 4,
-                                                          4, 5, 4, 4, 4, 2, 3, 3, 4, 2, 4, 2, 5, 1, 3, 2, 4, 3,
-                                                          5, 1, 2, 3, 1, 1, 2, 5, 1, 1, 2, 1, 4, 5, 3, 4, 1, 3,
+        Builder{}
+            .inputs({{ET, {2, 3, 3, 2, 4}, std::vector<T>{4, 2, 5, 4, 5, 5, 1, 1, 3, 3, 1, 1, 2, 2, 4, 1, 3, 4, 4, 5, 1,
+                                                          3, 1, 3, 1, 4, 3, 5, 4, 4, 5, 4, 4, 5, 4, 2, 2, 2, 3, 3, 1, 1,
+                                                          4, 3, 4, 2, 2, 1, 1, 2, 3, 1, 1, 4, 2, 3, 1, 3, 4, 2, 5, 5, 3,
+                                                          4, 3, 4, 5, 4, 4, 5, 1, 3, 4, 4, 5, 3, 1, 3, 2, 5, 3, 2, 5, 4,
+                                                          4, 2, 4, 4, 1, 4, 4, 5, 4, 4, 4, 2, 3, 3, 4, 2, 4, 2, 5, 1, 3,
+                                                          2, 4, 3, 5, 1, 2, 3, 1, 1, 2, 5, 1, 1, 2, 1, 4, 5, 3, 4, 1, 3,
                                                           3, 1, 3, 2, 4, 5, 1, 1, 5, 4, 5, 2, 2, 3, 3, 1, 2, 4}},
                      {ET, {3, 2, 1}, std::vector<T>{1, 4, 4, 5, 3, 3}}})
             .equation("abbac,bad->ad")
@@ -165,7 +158,7 @@ std::vector<EinsumParams> generateParams() {
 }
 
 std::vector<EinsumParams> generateCombinedParams() {
-    const std::vector<std::vector<EinsumParams>> generatedParams {
+    const std::vector<std::vector<EinsumParams>> generatedParams{
         generateParams<element::Type_t::i32>(),
         generateParams<element::Type_t::f32>(),
     };
@@ -177,6 +170,8 @@ std::vector<EinsumParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Einsum_With_Hardcoded_Refs, ReferenceEinsumTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceEinsumTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Einsum_With_Hardcoded_Refs,
+                         ReferenceEinsumTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceEinsumTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/elu.cpp b/src/plugins/template/tests/functional/op_reference/elu.cpp
index ccb5112e709bee..dc057a9ffeb788 100644
--- a/src/plugins/template/tests/functional/op_reference/elu.cpp
+++ b/src/plugins/template/tests/functional/op_reference/elu.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/elu.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/elu.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,8 +14,11 @@ using namespace ov;
 namespace {
 struct EluParams {
     template <class IT>
-    EluParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
-                const double alpha)
+    EluParams(const ov::PartialShape& shape,
+              const ov::element::Type& iType,
+              const std::vector<IT>& iValues,
+              const std::vector<IT>& oValues,
+              const double alpha)
         : alpha(alpha),
           pshape(shape),
           inType(iType),
@@ -50,11 +54,13 @@ class ReferenceEluLayerTest : public testing::TestWithParam<EluParams>, public C
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type, const double alpha) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type,
+                                                 const double alpha) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Elu = std::make_shared<op::v0::Elu>(in, alpha);
-        return std::make_shared<ov::Model>(NodeVector {Elu}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Elu}, ParameterVector{in});
     }
 };
 
@@ -66,18 +72,17 @@ template <element::Type_t IN_ET>
 std::vector<EluParams> generateEluFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<EluParams> eluParams {
-        EluParams(ov::PartialShape {3, 2},
-                    IN_ET,
-                    std::vector<T>{-2.f, 3.f, -2.f, 1.f, -1.f, 0.f},
-                    std::vector<T>{-0.432332358f, 3.f, -0.432332358f, 1.f, -0.316060279f, 0.f},
-                    0.5f),
-        EluParams(ov::PartialShape {3, 2},
-                    IN_ET,
-                    std::vector<T>{-2.f, 3.f, -2.f, 1.f, -1.f, 0.f},
-                    std::vector<T>{0.864664717f, 3.f, 0.864664717f, 1.f, 0.632120559f, 0.f},
-                    -1.f)
-    };
+    std::vector<EluParams> eluParams{
+        EluParams(ov::PartialShape{3, 2},
+                  IN_ET,
+                  std::vector<T>{-2.f, 3.f, -2.f, 1.f, -1.f, 0.f},
+                  std::vector<T>{-0.432332358f, 3.f, -0.432332358f, 1.f, -0.316060279f, 0.f},
+                  0.5f),
+        EluParams(ov::PartialShape{3, 2},
+                  IN_ET,
+                  std::vector<T>{-2.f, 3.f, -2.f, 1.f, -1.f, 0.f},
+                  std::vector<T>{0.864664717f, 3.f, 0.864664717f, 1.f, 0.632120559f, 0.f},
+                  -1.f)};
     return eluParams;
 }
 
@@ -85,18 +90,16 @@ template <element::Type_t IN_ET>
 std::vector<EluParams> generateEluIntParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<EluParams> eluParams {
-        EluParams(ov::PartialShape {3, 2},
-                    IN_ET,
-                    std::vector<T>{-2, 3, -2, 1, -1, 0},
-                    std::vector<T>{0, 3, 0, 1, 0, 0},
-                    0.5f),
-        EluParams(ov::PartialShape {3, 2},
-                    IN_ET,
-                    std::vector<T>{-2, 3, -2, 1, -1, 0},
-                    std::vector<T>{0, 3, 0, 1, 0, 0},
-                    -1.f)
-    };
+    std::vector<EluParams> eluParams{EluParams(ov::PartialShape{3, 2},
+                                               IN_ET,
+                                               std::vector<T>{-2, 3, -2, 1, -1, 0},
+                                               std::vector<T>{0, 3, 0, 1, 0, 0},
+                                               0.5f),
+                                     EluParams(ov::PartialShape{3, 2},
+                                               IN_ET,
+                                               std::vector<T>{-2, 3, -2, 1, -1, 0},
+                                               std::vector<T>{0, 3, 0, 1, 0, 0},
+                                               -1.f)};
     return eluParams;
 }
 
@@ -104,34 +107,30 @@ template <element::Type_t IN_ET>
 std::vector<EluParams> generateEluUintParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<EluParams> eluParams {
-        EluParams(ov::PartialShape {3, 2},
-                    IN_ET,
-                    std::vector<T>{5, 4, 3, 2, 1, 0},
-                    std::vector<T>{5, 4, 3, 2, 1, 0},
-                    0.5f),
-        EluParams(ov::PartialShape {3, 2},
-                    IN_ET,
-                    std::vector<T>{5, 4, 3, 2, 1, 0},
-                    std::vector<T>{5, 4, 3, 2, 1, 0},
-                    -1.f)
-    };
+    std::vector<EluParams> eluParams{EluParams(ov::PartialShape{3, 2},
+                                               IN_ET,
+                                               std::vector<T>{5, 4, 3, 2, 1, 0},
+                                               std::vector<T>{5, 4, 3, 2, 1, 0},
+                                               0.5f),
+                                     EluParams(ov::PartialShape{3, 2},
+                                               IN_ET,
+                                               std::vector<T>{5, 4, 3, 2, 1, 0},
+                                               std::vector<T>{5, 4, 3, 2, 1, 0},
+                                               -1.f)};
     return eluParams;
 }
 std::vector<EluParams> generateEluCombinedParams() {
-    const std::vector<std::vector<EluParams>> eluTypeParams {
-        generateEluFloatParams<element::Type_t::f32>(),
-        generateEluFloatParams<element::Type_t::f16>(),
-        generateEluFloatParams<element::Type_t::bf16>(),
-        generateEluIntParams<element::Type_t::i8>(),
-        generateEluIntParams<element::Type_t::i16>(),
-        generateEluIntParams<element::Type_t::i32>(),
-        generateEluIntParams<element::Type_t::i64>(),
-        generateEluUintParams<element::Type_t::u8>(),
-        generateEluUintParams<element::Type_t::u16>(),
-        generateEluUintParams<element::Type_t::u32>(),
-        generateEluUintParams<element::Type_t::u64>()
-        };
+    const std::vector<std::vector<EluParams>> eluTypeParams{generateEluFloatParams<element::Type_t::f32>(),
+                                                            generateEluFloatParams<element::Type_t::f16>(),
+                                                            generateEluFloatParams<element::Type_t::bf16>(),
+                                                            generateEluIntParams<element::Type_t::i8>(),
+                                                            generateEluIntParams<element::Type_t::i16>(),
+                                                            generateEluIntParams<element::Type_t::i32>(),
+                                                            generateEluIntParams<element::Type_t::i64>(),
+                                                            generateEluUintParams<element::Type_t::u8>(),
+                                                            generateEluUintParams<element::Type_t::u16>(),
+                                                            generateEluUintParams<element::Type_t::u32>(),
+                                                            generateEluUintParams<element::Type_t::u64>()};
     std::vector<EluParams> combinedParams;
 
     for (const auto& params : eluTypeParams) {
@@ -140,7 +139,9 @@ std::vector<EluParams> generateEluCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Elu_With_Hardcoded_Refs, ReferenceEluLayerTest,
-    testing::ValuesIn(generateEluCombinedParams()), ReferenceEluLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Elu_With_Hardcoded_Refs,
+                         ReferenceEluLayerTest,
+                         testing::ValuesIn(generateEluCombinedParams()),
+                         ReferenceEluLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/embedding_segments_sum.cpp b/src/plugins/template/tests/functional/op_reference/embedding_segments_sum.cpp
index 1097aa85620f61..d308d2c2a5d69f 100644
--- a/src/plugins/template/tests/functional/op_reference/embedding_segments_sum.cpp
+++ b/src/plugins/template/tests/functional/op_reference/embedding_segments_sum.cpp
@@ -79,14 +79,13 @@ class ReferenceEmbeddingSegmentsSumLayerTest : public testing::TestWithParam<Emb
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(
-        const PartialShape& input_shape,
-        const element::Type& input_type,
-        const std::shared_ptr<ov::op::v0::Constant> indices,
-        const std::shared_ptr<ov::op::v0::Constant> segment_ids,
-        const std::shared_ptr<ov::op::v0::Constant> num_segments,
-        const std::shared_ptr<ov::op::v0::Constant> default_index,
-        const std::shared_ptr<ov::op::v0::Constant> per_sample_weights) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const std::shared_ptr<ov::op::v0::Constant> indices,
+                                                 const std::shared_ptr<ov::op::v0::Constant> segment_ids,
+                                                 const std::shared_ptr<ov::op::v0::Constant> num_segments,
+                                                 const std::shared_ptr<ov::op::v0::Constant> default_index,
+                                                 const std::shared_ptr<ov::op::v0::Constant> per_sample_weights) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
 
         if (default_index) {
@@ -133,8 +132,8 @@ INSTANTIATE_TEST_SUITE_P(
             std::make_shared<ov::op::v0::Constant>(element::i32, ov::Shape(), std::vector<int32_t>{3}),
             std::make_shared<ov::op::v0::Constant>(element::i32, ov::Shape(), std::vector<int32_t>{0}),
             std::make_shared<ov::op::v0::Constant>(element::f32,
-                                                       ov::Shape({4}),
-                                                       std::vector<float>{0.5, 0.5, 0.5, 0.5})),
+                                                   ov::Shape({4}),
+                                                   std::vector<float>{0.5, 0.5, 0.5, 0.5})),
         EmbeddingSegmentsSumParams(
             ov::PartialShape{5, 2},
             ov::element::f64,
diff --git a/src/plugins/template/tests/functional/op_reference/embeddingbag_offsetssum.cpp b/src/plugins/template/tests/functional/op_reference/embeddingbag_offsetssum.cpp
index d4d7c5c492c7ec..f7e7bdcafaa7f0 100644
--- a/src/plugins/template/tests/functional/op_reference/embeddingbag_offsetssum.cpp
+++ b/src/plugins/template/tests/functional/op_reference/embeddingbag_offsetssum.cpp
@@ -74,13 +74,12 @@ class ReferenceEmbeddingBagOffsetsSumLayerTest : public testing::TestWithParam<E
     }
 
 private:
-    static std::shared_ptr<ov::Model> CreateFunction(
-        const PartialShape& input_shape,
-        const element::Type& input_type,
-        const std::shared_ptr<ov::op::v0::Constant> indices,
-        const std::shared_ptr<ov::op::v0::Constant> offsets,
-        const std::shared_ptr<ov::op::v0::Constant> default_index,
-        const std::shared_ptr<ov::op::v0::Constant> per_sample_weights) {
+    static std::shared_ptr<ov::Model> CreateFunction(const PartialShape& input_shape,
+                                                     const element::Type& input_type,
+                                                     const std::shared_ptr<ov::op::v0::Constant> indices,
+                                                     const std::shared_ptr<ov::op::v0::Constant> offsets,
+                                                     const std::shared_ptr<ov::op::v0::Constant> default_index,
+                                                     const std::shared_ptr<ov::op::v0::Constant> per_sample_weights) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
 
         if (default_index) {
@@ -121,8 +120,8 @@ INSTANTIATE_TEST_SUITE_P(
             std::make_shared<ov::op::v0::Constant>(element::i32, ov::Shape({3}), std::vector<int32_t>{0, 2, 2}),
             std::make_shared<ov::op::v0::Constant>(element::i32, ov::Shape(), std::vector<int32_t>{0}),
             std::make_shared<ov::op::v0::Constant>(element::f32,
-                                                       ov::Shape({4}),
-                                                       std::vector<float>{0.5, 0.5, 0.5, 0.5})),
+                                                   ov::Shape({4}),
+                                                   std::vector<float>{0.5, 0.5, 0.5, 0.5})),
         EmbeddingBagOffsetsSumParams(
             ov::PartialShape{5, 2},
             ov::element::f64,
diff --git a/src/plugins/template/tests/functional/op_reference/embeddingbag_packedsum.cpp b/src/plugins/template/tests/functional/op_reference/embeddingbag_packedsum.cpp
index f81acb2d4e23d2..80af12d4053c8f 100644
--- a/src/plugins/template/tests/functional/op_reference/embeddingbag_packedsum.cpp
+++ b/src/plugins/template/tests/functional/op_reference/embeddingbag_packedsum.cpp
@@ -63,11 +63,10 @@ class ReferenceEmbeddingBagPackedSumLayerTest : public testing::TestWithParam<Em
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(
-        const PartialShape& input_shape,
-        const element::Type& input_type,
-        const std::shared_ptr<ov::op::v0::Constant> indices,
-        const std::shared_ptr<ov::op::v0::Constant> per_sample_weights) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const std::shared_ptr<ov::op::v0::Constant> indices,
+                                                 const std::shared_ptr<ov::op::v0::Constant> per_sample_weights) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
 
         if (per_sample_weights) {
@@ -86,7 +85,7 @@ TEST_P(ReferenceEmbeddingBagPackedSumLayerTest, CompareWithRefs) {
 
 template <class T>
 inline std::shared_ptr<ov::op::v0::Constant> CreateConstant(const std::vector<std::vector<T>>& val,
-                                                                  const ov::element::Type& element_type) {
+                                                            const ov::element::Type& element_type) {
     if (val.size() > 0) {
         ov::Shape i_shape({val.size(), val[0].size()});
 
diff --git a/src/plugins/template/tests/functional/op_reference/equal.cpp b/src/plugins/template/tests/functional/op_reference/equal.cpp
index 6bed3aa52e5523..574cc95c25e13e 100644
--- a/src/plugins/template/tests/functional/op_reference/equal.cpp
+++ b/src/plugins/template/tests/functional/op_reference/equal.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/equal.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/equal.hpp"
 #include "comparison.hpp"
 
 using namespace ov;
@@ -16,43 +17,43 @@ namespace {
 template <element::Type_t IN_ET>
 std::vector<RefComparisonParams> generateComparisonParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RefComparisonParams> compParams {
+    std::vector<RefComparisonParams> compParams{
         // 1D // 2D // 3D // 4D
-        Builder {}
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .input2({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {1, 1, 1, 1}}),
-        Builder {}
+            .input1({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .input2({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{1, 1, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{2, 3}, type, std::vector<T> {0, 6, 45, 1, 21, 21}})
-            .input2({{2, 3}, type, std::vector<T> {1, 18, 23, 1, 19, 21}})
-            .expected({{2, 3}, element::boolean, std::vector<char> {0, 0, 0, 1, 0, 1}}),
-        Builder {}
+            .input1({{2, 3}, type, std::vector<T>{0, 6, 45, 1, 21, 21}})
+            .input2({{2, 3}, type, std::vector<T>{1, 18, 23, 1, 19, 21}})
+            .expected({{2, 3}, element::boolean, std::vector<char>{0, 0, 0, 1, 0, 1}}),
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{1}, type, std::vector<T> {53}})
-            .input2({{1}, type, std::vector<T> {53}})
-            .expected({{1}, element::boolean, std::vector<char> {1}}),
-        Builder {}
+            .input1({{1}, type, std::vector<T>{53}})
+            .input2({{1}, type, std::vector<T>{53}})
+            .expected({{1}, element::boolean, std::vector<char>{1}}),
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 1, 5, 11, 8}})
-            .input2({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 10, 5, 11, 8}})
-            .expected({{2, 4}, element::boolean, std::vector<char> {1, 1, 1, 1, 0, 1, 1, 1}}),
-        Builder {}
+            .input1({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 1, 5, 11, 8}})
+            .input2({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 10, 5, 11, 8}})
+            .expected({{2, 4}, element::boolean, std::vector<char>{1, 1, 1, 1, 0, 1, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{3, 1, 2}, type, std::vector<T> {2, 1, 4, 1, 3, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{3, 2, 2}, element::boolean, std::vector<char> {0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1}}),
-        Builder {}
+            .input1({{3, 1, 2}, type, std::vector<T>{2, 1, 4, 1, 3, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{3, 2, 2}, element::boolean, std::vector<char>{0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1}}),
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{2, 1, 2, 1}, type, std::vector<T> {2, 1, 4, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {0, 1, 0, 1}})};
+            .input1({{2, 1, 2, 1}, type, std::vector<T>{2, 1, 4, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{0, 1, 0, 1}})};
     return compParams;
 }
 
 std::vector<RefComparisonParams> generateComparisonCombinedParams() {
-    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams{
         generateComparisonParams<element::Type_t::f32>(element::f32),
         generateComparisonParams<element::Type_t::f16>(element::f16),
         generateComparisonParams<element::Type_t::i32>(element::i32),
@@ -66,38 +67,47 @@ std::vector<RefComparisonParams> generateComparisonCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateComparisonCombinedParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs,
+                         ReferenceComparisonLayerTest,
+                         ::testing::ValuesIn(generateComparisonCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
 
 template <element::Type_t IN_ET>
 std::vector<RefComparisonParams> generateNumericParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RefComparisonParams> compParams {
-        Builder {}
+    std::vector<RefComparisonParams> compParams{
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{4}, type, std::vector<T> {-2.5f, 25.5f, 2.25f, NAN}})
-            .input2({{4}, type, std::vector<T> {10.0f, 5.0f, 2.25f, 10.0f}})
-            .expected({{4}, element::boolean, std::vector<char> {0, 0, 1, 0, }}),
-        Builder {}
+            .input1({{4}, type, std::vector<T>{-2.5f, 25.5f, 2.25f, NAN}})
+            .input2({{4}, type, std::vector<T>{10.0f, 5.0f, 2.25f, 10.0f}})
+            .expected({{4},
+                       element::boolean,
+                       std::vector<char>{
+                           0,
+                           0,
+                           1,
+                           0,
+                       }}),
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{2, 3}, type, std::vector<T> {0.0f, NAN, NAN, 1.0f, 21.0f, -INFINITY}})
-            .input2({{2, 3}, type, std::vector<T> {1.0f, NAN, 23.0f, 1.0f, 19.0f, 21.0f}})
-            .expected({{2, 3}, element::boolean, std::vector<char> {0, 0, 0, 1, 0, 0}}),
-        Builder {}
+            .input1({{2, 3}, type, std::vector<T>{0.0f, NAN, NAN, 1.0f, 21.0f, -INFINITY}})
+            .input2({{2, 3}, type, std::vector<T>{1.0f, NAN, 23.0f, 1.0f, 19.0f, 21.0f}})
+            .expected({{2, 3}, element::boolean, std::vector<char>{0, 0, 0, 1, 0, 0}}),
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{1}, type, std::vector<T> {INFINITY}})
-            .input2({{1}, type, std::vector<T> {INFINITY}})
-            .expected({{1}, element::boolean, std::vector<char> {1}}),
-        Builder {}
+            .input1({{1}, type, std::vector<T>{INFINITY}})
+            .input2({{1}, type, std::vector<T>{INFINITY}})
+            .expected({{1}, element::boolean, std::vector<char>{1}}),
+        Builder{}
             .compType(ComparisonTypes::EQUAL)
-            .input1({{5}, type, std::vector<T> {-2.5f, 25.5f, 2.25f, INFINITY, 6.0f}})
-            .input2({{5}, type, std::vector<T> {10.0f, 5.0f, 2.25f, 10.0f, -INFINITY}})
-            .expected({{5}, element::boolean, std::vector<char> {0, 0, 1, 0, 0}})};
+            .input1({{5}, type, std::vector<T>{-2.5f, 25.5f, 2.25f, INFINITY, 6.0f}})
+            .input2({{5}, type, std::vector<T>{10.0f, 5.0f, 2.25f, 10.0f, -INFINITY}})
+            .expected({{5}, element::boolean, std::vector<char>{0, 0, 1, 0, 0}})};
     return compParams;
 }
 
 std::vector<RefComparisonParams> generateNumericCombinedParams() {
-    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams{
         generateNumericParams<element::Type_t::f16>(element::f16),
         generateNumericParams<element::Type_t::f32>(element::f32)};
     std::vector<RefComparisonParams> combinedParams;
@@ -108,8 +118,10 @@ std::vector<RefComparisonParams> generateNumericCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Numeric_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateNumericCombinedParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_Numeric_With_Hardcoded_Refs,
+                         ReferenceComparisonLayerTest,
+                         ::testing::ValuesIn(generateNumericCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
-} // namespace
-} // namespace ComparisonOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace
+}  // namespace ComparisonOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/erf.cpp b/src/plugins/template/tests/functional/op_reference/erf.cpp
index 9f658d78573129..a386abfb2fbf5b 100644
--- a/src/plugins/template/tests/functional/op_reference/erf.cpp
+++ b/src/plugins/template/tests/functional/op_reference/erf.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/erf.hpp"
+
 #include <gtest/gtest.h>
-#include "functional_test_utils/skip_tests_config.hpp"
 
-#include "openvino/op/erf.hpp"
 #include "base_reference_test.hpp"
+#include "functional_test_utils/skip_tests_config.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -14,7 +15,10 @@ using namespace ov;
 struct ErfParams {
     template <class IT>
     ErfParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues)
-        : pshape(shape), inType(iType), outType(iType), inputData(CreateTensor(iType, iValues)) {
+        : pshape(shape),
+          inType(iType),
+          outType(iType),
+          inputData(CreateTensor(iType, iValues)) {
         std::vector<IT> oValues;
         std::vector<double> output;
         for (auto element : iValues)
@@ -60,11 +64,12 @@ class ReferenceErfLayerTest : public testing::TestWithParam<ErfParams>, public C
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto erf = std::make_shared<op::v0::Erf>(in);
-        return std::make_shared<ov::Model>(NodeVector {erf}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{erf}, ParameterVector{in});
     }
 };
 
@@ -73,17 +78,37 @@ TEST_P(ReferenceErfLayerTest, CompareWithRefs) {
 }
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Erf_With_Hardcoded_Refs, ReferenceErfLayerTest,
-    ::testing::Values(ErfParams(ov::PartialShape {2, 5}, ov::element::f32,
-                                std::vector<float> {-INFINITY, -4.0f, -3.0f, -2.0f, -1.0f, 0.0f, 1.0f, 2.0f, 3.0f, INFINITY}),
-                      ErfParams(ov::PartialShape {2, 5}, ov::element::f16,
-                                std::vector<float16> {-INFINITY, -4.0f, -3.0f, -2.0f, -1.0f, 0.0f, 1.0f, 2.0f, 3.0f, INFINITY}),
-                      ErfParams(ov::PartialShape {2, 3}, ov::element::i32,
-                                std::vector<int32_t> {std::numeric_limits<int32_t>::min(), -2, -1, 1, 2, std::numeric_limits<int32_t>::max()}),
-                      ErfParams(ov::PartialShape {2, 3}, ov::element::u32,
-                                std::vector<uint32_t> {std::numeric_limits<uint32_t>::min(), 0, 1, 2, 3, std::numeric_limits<uint32_t>::max()}),
-                      ErfParams(ov::PartialShape {2, 3}, ov::element::i64,
-                                std::vector<int64_t> {std::numeric_limits<int64_t>::min(), -2, -1, 1, 2, std::numeric_limits<int64_t>::max()}),
-                      ErfParams(ov::PartialShape {2, 3}, ov::element::u64,
-                                std::vector<uint64_t> {std::numeric_limits<uint64_t>::min(), 0, 1, 2, 3, std::numeric_limits<uint64_t>::max()})),
+    smoke_Erf_With_Hardcoded_Refs,
+    ReferenceErfLayerTest,
+    ::testing::Values(
+        ErfParams(ov::PartialShape{2, 5},
+                  ov::element::f32,
+                  std::vector<float>{-INFINITY, -4.0f, -3.0f, -2.0f, -1.0f, 0.0f, 1.0f, 2.0f, 3.0f, INFINITY}),
+        ErfParams(ov::PartialShape{2, 5},
+                  ov::element::f16,
+                  std::vector<float16>{-INFINITY, -4.0f, -3.0f, -2.0f, -1.0f, 0.0f, 1.0f, 2.0f, 3.0f, INFINITY}),
+        ErfParams(ov::PartialShape{2, 3},
+                  ov::element::i32,
+                  std::vector<
+                      int32_t>{std::numeric_limits<int32_t>::min(), -2, -1, 1, 2, std::numeric_limits<int32_t>::max()}),
+        ErfParams(ov::PartialShape{2, 3},
+                  ov::element::u32,
+                  std::vector<uint32_t>{std::numeric_limits<uint32_t>::min(),
+                                        0,
+                                        1,
+                                        2,
+                                        3,
+                                        std::numeric_limits<uint32_t>::max()}),
+        ErfParams(ov::PartialShape{2, 3},
+                  ov::element::i64,
+                  std::vector<
+                      int64_t>{std::numeric_limits<int64_t>::min(), -2, -1, 1, 2, std::numeric_limits<int64_t>::max()}),
+        ErfParams(ov::PartialShape{2, 3},
+                  ov::element::u64,
+                  std::vector<uint64_t>{std::numeric_limits<uint64_t>::min(),
+                                        0,
+                                        1,
+                                        2,
+                                        3,
+                                        std::numeric_limits<uint64_t>::max()})),
     ReferenceErfLayerTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/op_reference/exp.cpp b/src/plugins/template/tests/functional/op_reference/exp.cpp
index 9b15a9cf970890..4e06b1dc2a8be5 100644
--- a/src/plugins/template/tests/functional/op_reference/exp.cpp
+++ b/src/plugins/template/tests/functional/op_reference/exp.cpp
@@ -2,11 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/exp.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/exp.hpp"
 #include "base_reference_test.hpp"
-
 #include "functional_test_utils/skip_tests_config.hpp"
 
 using namespace reference_tests;
@@ -16,7 +16,10 @@ using namespace InferenceEngine;
 namespace {
 struct ExpParams {
     template <class IT>
-    ExpParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    ExpParams(const ov::PartialShape& shape,
+              const ov::element::Type& iType,
+              const std::vector<IT>& iValues,
+              const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -49,11 +52,12 @@ class ReferenceExpLayerTest : public testing::TestWithParam<ExpParams>, public C
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Exp = std::make_shared<op::v0::Exp>(in);
-        return std::make_shared<ov::Model>(NodeVector {Exp}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Exp}, ParameterVector{in});
     }
 };
 
@@ -75,12 +79,13 @@ class ReferenceExpInPlaceLayerTest : public testing::TestWithParam<ExpParams>, p
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Exp = std::make_shared<op::v0::Exp>(in);
         const auto ExpInPlace = std::make_shared<op::v0::Exp>(Exp);
-        return std::make_shared<ov::Model>(NodeVector {ExpInPlace}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{ExpInPlace}, ParameterVector{in});
     }
 };
 
@@ -96,16 +101,12 @@ template <element::Type_t IN_ET>
 std::vector<ExpParams> generateExpFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ExpParams> expParams {
-        ExpParams(ov::PartialShape {8},
-                    IN_ET,
-                    std::vector<T>{-4, -3, -2, -1, 0, 1, 2, 3},
-                    std::vector<T>{expf(-4), expf(-3), expf(-2), expf(-1), expf(0), expf(1), expf(2), expf(3)}),
-        ExpParams(ov::PartialShape {1},
-                    IN_ET,
-                    std::vector<T>{13},
-                    std::vector<T>{expf(13)})
-    };
+    std::vector<ExpParams> expParams{
+        ExpParams(ov::PartialShape{8},
+                  IN_ET,
+                  std::vector<T>{-4, -3, -2, -1, 0, 1, 2, 3},
+                  std::vector<T>{expf(-4), expf(-3), expf(-2), expf(-1), expf(0), expf(1), expf(2), expf(3)}),
+        ExpParams(ov::PartialShape{1}, IN_ET, std::vector<T>{13}, std::vector<T>{expf(13)})};
     return expParams;
 }
 
@@ -113,17 +114,19 @@ template <element::Type_t IN_ET>
 std::vector<ExpParams> generateExpIntParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ExpParams> expParams {
-        ExpParams(ov::PartialShape {8},
-                    IN_ET,
-                    std::vector<T>{-4, -3, -2, -1, 0, 1, 2, 3},
-                    std::vector<T>{static_cast<T>(expf(-4)), static_cast<T>(expf(-3)), static_cast<T>(expf(-2)), static_cast<T>(expf(-1)),
-                                   static_cast<T>(expf(0)), static_cast<T>(expf(1)), static_cast<T>(expf(2)), static_cast<T>(expf(3))}),
-        ExpParams(ov::PartialShape {1},
-                    IN_ET,
-                    std::vector<T>{13},
-                    std::vector<T>{static_cast<T>(expf(13))})
-    };
+    std::vector<ExpParams> expParams{
+        ExpParams(ov::PartialShape{8},
+                  IN_ET,
+                  std::vector<T>{-4, -3, -2, -1, 0, 1, 2, 3},
+                  std::vector<T>{static_cast<T>(expf(-4)),
+                                 static_cast<T>(expf(-3)),
+                                 static_cast<T>(expf(-2)),
+                                 static_cast<T>(expf(-1)),
+                                 static_cast<T>(expf(0)),
+                                 static_cast<T>(expf(1)),
+                                 static_cast<T>(expf(2)),
+                                 static_cast<T>(expf(3))}),
+        ExpParams(ov::PartialShape{1}, IN_ET, std::vector<T>{13}, std::vector<T>{static_cast<T>(expf(13))})};
     return expParams;
 }
 
@@ -131,17 +134,19 @@ template <element::Type_t IN_ET>
 std::vector<ExpParams> generateExpUintParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ExpParams> expParams {
-        ExpParams(ov::PartialShape {8},
-                    IN_ET,
-                    std::vector<T>{0, 1, 2, 3, 4, 5, 10, 100},
-                    std::vector<T>{static_cast<T>(expf(0)), static_cast<T>(expf(1)), static_cast<T>(expf(2)), static_cast<T>(expf(3)),
-                                   static_cast<T>(expf(4)), static_cast<T>(expf(5)), static_cast<T>(expf(10)), static_cast<T>(expf(100))}),
-        ExpParams(ov::PartialShape {1},
-                    IN_ET,
-                    std::vector<T>{13},
-                    std::vector<T>{static_cast<T>(expf(13))})
-    };
+    std::vector<ExpParams> expParams{
+        ExpParams(ov::PartialShape{8},
+                  IN_ET,
+                  std::vector<T>{0, 1, 2, 3, 4, 5, 10, 100},
+                  std::vector<T>{static_cast<T>(expf(0)),
+                                 static_cast<T>(expf(1)),
+                                 static_cast<T>(expf(2)),
+                                 static_cast<T>(expf(3)),
+                                 static_cast<T>(expf(4)),
+                                 static_cast<T>(expf(5)),
+                                 static_cast<T>(expf(10)),
+                                 static_cast<T>(expf(100))}),
+        ExpParams(ov::PartialShape{1}, IN_ET, std::vector<T>{13}, std::vector<T>{static_cast<T>(expf(13))})};
     return expParams;
 }
 
@@ -149,22 +154,16 @@ template <element::Type_t IN_ET>
 std::vector<ExpParams> generateExpInPlaceFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ExpParams> expParams {
-        ExpParams(ov::PartialShape {2},
-                    IN_ET,
-                    std::vector<T>{1, 3},
-                    std::vector<T>{expf(expf(1)), expf(expf(3))})
-    };
+    std::vector<ExpParams> expParams{
+        ExpParams(ov::PartialShape{2}, IN_ET, std::vector<T>{1, 3}, std::vector<T>{expf(expf(1)), expf(expf(3))})};
     return expParams;
 }
 
 std::vector<ExpParams> generateExpCombinedParams() {
-    const std::vector<std::vector<ExpParams>> expTypeParams {
-        generateExpFloatParams<element::Type_t::f32>(),
-        generateExpFloatParams<element::Type_t::f16>(),
-        generateExpIntParams<element::Type_t::i32>(),
-        generateExpIntParams<element::Type_t::i64>()
-        };
+    const std::vector<std::vector<ExpParams>> expTypeParams{generateExpFloatParams<element::Type_t::f32>(),
+                                                            generateExpFloatParams<element::Type_t::f16>(),
+                                                            generateExpIntParams<element::Type_t::i32>(),
+                                                            generateExpIntParams<element::Type_t::i64>()};
     std::vector<ExpParams> combinedParams;
 
     for (const auto& params : expTypeParams) {
@@ -174,10 +173,8 @@ std::vector<ExpParams> generateExpCombinedParams() {
 }
 
 std::vector<ExpParams> generateExpInPlaceCombinedParams() {
-    const std::vector<std::vector<ExpParams>> expTypeParams {
-        generateExpInPlaceFloatParams<element::Type_t::f16>(),
-        generateExpInPlaceFloatParams<element::Type_t::f32>()
-        };
+    const std::vector<std::vector<ExpParams>> expTypeParams{generateExpInPlaceFloatParams<element::Type_t::f16>(),
+                                                            generateExpInPlaceFloatParams<element::Type_t::f32>()};
     std::vector<ExpParams> combinedParams;
 
     for (const auto& params : expTypeParams) {
@@ -186,10 +183,14 @@ std::vector<ExpParams> generateExpInPlaceCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Exp_With_Hardcoded_Refs, ReferenceExpLayerTest,
-    testing::ValuesIn(generateExpCombinedParams()), ReferenceExpLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Exp_With_Hardcoded_Refs,
+                         ReferenceExpLayerTest,
+                         testing::ValuesIn(generateExpCombinedParams()),
+                         ReferenceExpLayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Exp_In_Place_With_Hardcoded_Refs, ReferenceExpInPlaceLayerTest,
-    testing::ValuesIn(generateExpInPlaceCombinedParams()), ReferenceExpInPlaceLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Exp_In_Place_With_Hardcoded_Refs,
+                         ReferenceExpInPlaceLayerTest,
+                         testing::ValuesIn(generateExpInPlaceCombinedParams()),
+                         ReferenceExpInPlaceLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/experimental_detectron_detection_output.cpp b/src/plugins/template/tests/functional/op_reference/experimental_detectron_detection_output.cpp
index f602aed2f02e1a..c1c719babd8a72 100644
--- a/src/plugins/template/tests/functional/op_reference/experimental_detectron_detection_output.cpp
+++ b/src/plugins/template/tests/functional/op_reference/experimental_detectron_detection_output.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/experimental_detectron_detection_output.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/experimental_detectron_detection_output.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -18,9 +19,13 @@ struct ExperimentalDOParams {
     ExperimentalDOParams(const Attrs& attrs,
                          const size_t num_rois,
                          const element::Type& iType,
-                         const std::vector<IT>& roisValues, const std::vector<IT>& deltasValues,
-                         const std::vector<IT>& scoresValues, const std::vector<IT>& imageSizeInfoValues,
-                         const std::vector<IT>& refBoxesValues, const std::vector<int32_t>& refClassesValues, const std::vector<IT>& refScoresValues,
+                         const std::vector<IT>& roisValues,
+                         const std::vector<IT>& deltasValues,
+                         const std::vector<IT>& scoresValues,
+                         const std::vector<IT>& imageSizeInfoValues,
+                         const std::vector<IT>& refBoxesValues,
+                         const std::vector<int32_t>& refClassesValues,
+                         const std::vector<IT>& refScoresValues,
                          const std::string& testcaseName = "")
         : attrs(attrs),
           inType(iType),
@@ -33,11 +38,11 @@ struct ExperimentalDOParams {
           refClassesData(CreateTensor(ov::element::i32, refClassesValues)),
           refScoresData(CreateTensor(iType, refScoresValues)),
           testcaseName(testcaseName) {
-              roisShape = Shape{num_rois, 4};
-              deltasShape = Shape{num_rois, static_cast<size_t>(attrs.num_classes * 4)};
-              scoresShape = Shape{num_rois, static_cast<size_t>(attrs.num_classes)};
-              imageSizeInfoShape = Shape{1, 3};
-          }
+        roisShape = Shape{num_rois, 4};
+        deltasShape = Shape{num_rois, static_cast<size_t>(attrs.num_classes * 4)};
+        scoresShape = Shape{num_rois, static_cast<size_t>(attrs.num_classes)};
+        imageSizeInfoShape = Shape{1, 3};
+    }
 
     Attrs attrs;
     PartialShape roisShape;
@@ -56,7 +61,8 @@ struct ExperimentalDOParams {
     std::string testcaseName;
 };
 
-class ReferenceExperimentalDOLayerTest : public testing::TestWithParam<ExperimentalDOParams>, public CommonReferenceTest {
+class ReferenceExperimentalDOLayerTest : public testing::TestWithParam<ExperimentalDOParams>,
+                                         public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -84,12 +90,9 @@ class ReferenceExperimentalDOLayerTest : public testing::TestWithParam<Experimen
         const auto deltas = std::make_shared<op::v0::Parameter>(params.inType, params.deltasShape);
         const auto scores = std::make_shared<op::v0::Parameter>(params.inType, params.scoresShape);
         const auto im_info = std::make_shared<op::v0::Parameter>(params.inType, params.imageSizeInfoShape);
-        const auto ExperimentalDO = std::make_shared<op::v6::ExperimentalDetectronDetectionOutput>(rois,
-                                                                    deltas,
-                                                                    scores,
-                                                                    im_info,
-                                                                    params.attrs);
-        return std::make_shared<ov::Model>(ExperimentalDO->outputs(), ParameterVector {rois, deltas, scores, im_info});
+        const auto ExperimentalDO =
+            std::make_shared<op::v6::ExperimentalDetectronDetectionOutput>(rois, deltas, scores, im_info, params.attrs);
+        return std::make_shared<ov::Model>(ExperimentalDO->outputs(), ParameterVector{rois, deltas, scores, im_info});
     }
 };
 
@@ -101,68 +104,71 @@ template <element::Type_t IN_ET>
 std::vector<ExperimentalDOParams> generateExperimentalDOFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ExperimentalDOParams> experimentalDOParams {
-        ExperimentalDOParams(Attrs{0.01000000074505806f, // score_threshold
-                              0.2f, // nms_threshold
-                              2.0f, // max_delta_log_wh
-                              2, // num_classes
-                              500, // post_nms_count
-                              5, // max_detections_per_image
-                              true, // class_agnostic_box_regression
-                              {10.0f, 10.0f, 5.0f, 5.0f} // deltas_weights
-                              },
-                              16,
-                              IN_ET,
-                              std::vector<T>{1.0f, 1.0f, 10.0f, 10.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f,  4.0f,  1.0f, 8.0f, 5.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f,  1.0f,  1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f,  1.0f,  1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f,  1.0f,  1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
-                              std::vector<T>{5.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 4.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 8.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
-                              std::vector<T>{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
-                              std::vector<T>{1.0f, 1.0f, 1.0f},
-                              std::vector<T>{0.8929862f,
-                                             0.892986297607421875,
-                                             12.10701370239257812,
-                                             12.10701370239257812,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0f,
-                                             0.0},
-                              std::vector<int32_t>{1, 0, 0, 0, 0},
-                              std::vector<T>{1.0f, 0.0f, 0.0f, 0.0f, 0.0f}),
+    std::vector<ExperimentalDOParams> experimentalDOParams{
+        ExperimentalDOParams(
+            Attrs{
+                0.01000000074505806f,       // score_threshold
+                0.2f,                       // nms_threshold
+                2.0f,                       // max_delta_log_wh
+                2,                          // num_classes
+                500,                        // post_nms_count
+                5,                          // max_detections_per_image
+                true,                       // class_agnostic_box_regression
+                {10.0f, 10.0f, 5.0f, 5.0f}  // deltas_weights
+            },
+            16,
+            IN_ET,
+            std::vector<T>{1.0f, 1.0f, 10.0f, 10.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                           1.0f, 1.0f, 1.0f,  4.0f,  1.0f, 8.0f, 5.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                           1.0f, 1.0f, 1.0f,  1.0f,  1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                           1.0f, 1.0f, 1.0f,  1.0f,  1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                           1.0f, 1.0f, 1.0f,  1.0f,  1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
+            std::vector<T>{
+                5.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 4.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 8.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
+            std::vector<T>{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                           1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                           1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
+            std::vector<T>{1.0f, 1.0f, 1.0f},
+            std::vector<T>{0.8929862f,
+                           0.892986297607421875,
+                           12.10701370239257812,
+                           12.10701370239257812,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0f,
+                           0.0},
+            std::vector<int32_t>{1, 0, 0, 0, 0},
+            std::vector<T>{1.0f, 0.0f, 0.0f, 0.0f, 0.0f}),
     };
     return experimentalDOParams;
 }
 
 std::vector<ExperimentalDOParams> generateExperimentalDOCombinedParams() {
-    const std::vector<std::vector<ExperimentalDOParams>> ExperimentalDOTypeParams {
+    const std::vector<std::vector<ExperimentalDOParams>> ExperimentalDOTypeParams{
         generateExperimentalDOFloatParams<element::Type_t::f32>(),
         generateExperimentalDOFloatParams<element::Type_t::f16>(),
         generateExperimentalDOFloatParams<element::Type_t::bf16>(),
-        };
+    };
     std::vector<ExperimentalDOParams> combinedParams;
 
     for (const auto& params : ExperimentalDOTypeParams) {
@@ -171,6 +177,8 @@ std::vector<ExperimentalDOParams> generateExperimentalDOCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ExperimentalDetectronDetectionOutput_With_Hardcoded_Refs, ReferenceExperimentalDOLayerTest,
-    testing::ValuesIn(generateExperimentalDOCombinedParams()), ReferenceExperimentalDOLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_ExperimentalDetectronDetectionOutput_With_Hardcoded_Refs,
+                         ReferenceExperimentalDOLayerTest,
+                         testing::ValuesIn(generateExperimentalDOCombinedParams()),
+                         ReferenceExperimentalDOLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/experimental_detectron_detection_prior_grid.cpp b/src/plugins/template/tests/functional/op_reference/experimental_detectron_detection_prior_grid.cpp
index a82d111e6bb0ed..abca08c733f33a 100644
--- a/src/plugins/template/tests/functional/op_reference/experimental_detectron_detection_prior_grid.cpp
+++ b/src/plugins/template/tests/functional/op_reference/experimental_detectron_detection_prior_grid.cpp
@@ -4,8 +4,8 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/op/experimental_detectron_prior_grid_generator.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/experimental_detectron_prior_grid_generator.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -16,14 +16,14 @@ namespace {
 struct ExperimentalPGGParams {
     template <class IT>
     ExperimentalPGGParams(const Attrs& attrs,
-                         const PartialShape& priorsShape,
-                         const PartialShape& featureMapShape,
-                         const PartialShape& imageSizeInfoShape,
-                         const Shape& outRefShape,
-                         const element::Type& iType,
-                         const std::vector<IT>& priorsValues,
-                         const std::vector<IT>& refValues,
-                         const std::string& testcaseName = "")
+                          const PartialShape& priorsShape,
+                          const PartialShape& featureMapShape,
+                          const PartialShape& imageSizeInfoShape,
+                          const Shape& outRefShape,
+                          const element::Type& iType,
+                          const std::vector<IT>& priorsValues,
+                          const std::vector<IT>& refValues,
+                          const std::string& testcaseName = "")
         : attrs(attrs),
           priorsShape(priorsShape),
           featureMapShape(featureMapShape),
@@ -34,19 +34,19 @@ struct ExperimentalPGGParams {
           priorsData(CreateTensor(iType, priorsValues)),
           refData(CreateTensor(outRefShape, iType, refValues)),
           testcaseName(testcaseName) {
-              std::vector<IT> featureMapValues(shape_size(featureMapShape.get_shape()));
-              std::iota(featureMapValues.begin(), featureMapValues.end(), 0.f);
-              featureMapData = CreateTensor(iType, featureMapValues);
-
-              std::vector<IT> imageSizeInfoValues(shape_size(imageSizeInfoShape.get_shape()));
-              std::iota(imageSizeInfoValues.begin(), imageSizeInfoValues.end(), 0.f);
-              imageSizeInfoData = CreateTensor(iType, imageSizeInfoValues);
-
-              if (shape_size(outRefShape) > refValues.size())
-                  actualComparisonSize = refValues.size();
-              else
-                  actualComparisonSize = 0;
-          }
+        std::vector<IT> featureMapValues(shape_size(featureMapShape.get_shape()));
+        std::iota(featureMapValues.begin(), featureMapValues.end(), 0.f);
+        featureMapData = CreateTensor(iType, featureMapValues);
+
+        std::vector<IT> imageSizeInfoValues(shape_size(imageSizeInfoShape.get_shape()));
+        std::iota(imageSizeInfoValues.begin(), imageSizeInfoValues.end(), 0.f);
+        imageSizeInfoData = CreateTensor(iType, imageSizeInfoValues);
+
+        if (shape_size(outRefShape) > refValues.size())
+            actualComparisonSize = refValues.size();
+        else
+            actualComparisonSize = 0;
+    }
 
     Attrs attrs;
     PartialShape priorsShape;
@@ -63,7 +63,8 @@ struct ExperimentalPGGParams {
     std::string testcaseName;
 };
 
-class ReferenceExperimentalPGGLayerTest : public testing::TestWithParam<ExperimentalPGGParams>, public CommonReferenceTest {
+class ReferenceExperimentalPGGLayerTest : public testing::TestWithParam<ExperimentalPGGParams>,
+                                          public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -98,10 +99,10 @@ class ReferenceExperimentalPGGLayerTest : public testing::TestWithParam<Experime
         const auto featureMap = std::make_shared<op::v0::Parameter>(params.inType, params.featureMapShape);
         const auto im_info = std::make_shared<op::v0::Parameter>(params.inType, params.imageSizeInfoShape);
         const auto ExperimentalPGG = std::make_shared<op::v6::ExperimentalDetectronPriorGridGenerator>(priors,
-                                                                    featureMap,
-                                                                    im_info,
-                                                                    params.attrs);
-        return std::make_shared<ov::Model>(NodeVector {ExperimentalPGG}, ParameterVector {priors, featureMap, im_info});
+                                                                                                       featureMap,
+                                                                                                       im_info,
+                                                                                                       params.attrs);
+        return std::make_shared<ov::Model>(NodeVector{ExperimentalPGG}, ParameterVector{priors, featureMap, im_info});
     }
 };
 
@@ -113,106 +114,119 @@ template <element::Type_t IN_ET>
 std::vector<ExperimentalPGGParams> generateExperimentalPGGFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ExperimentalPGGParams> experimentalPGGParams {
-        ExperimentalPGGParams(Attrs{true, 0, 0, 4.0f, 4.0f},
-                              {3, 4},
-                              {1, 16, 4, 5},
-                              {1, 3, 100, 200},
-                              {60, 4},
-                              IN_ET,
-                              std::vector<T>{-24.5, -12.5, 24.5, 12.5, -16.5, -16.5, 16.5, 16.5, -12.5, -24.5, 12.5, 24.5},
-                              std::vector<T>{-22.5, -10.5, 26.5, 14.5, -14.5, -14.5, 18.5, 18.5, -10.5, -22.5, 14.5, 26.5, -18.5, -10.5, 30.5, 14.5,
-                                             -10.5, -14.5, 22.5, 18.5, -6.5,  -22.5, 18.5, 26.5, -14.5, -10.5, 34.5, 14.5, -6.5,  -14.5, 26.5, 18.5,
-                                             -2.5,  -22.5, 22.5, 26.5, -10.5, -10.5, 38.5, 14.5, -2.5,  -14.5, 30.5, 18.5, 1.5,   -22.5, 26.5, 26.5,
-                                             -6.5,  -10.5, 42.5, 14.5, 1.5,   -14.5, 34.5, 18.5, 5.5,   -22.5, 30.5, 26.5, -22.5, -6.5,  26.5, 18.5,
-                                             -14.5, -10.5, 18.5, 22.5, -10.5, -18.5, 14.5, 30.5, -18.5, -6.5,  30.5, 18.5, -10.5, -10.5, 22.5, 22.5,
-                                             -6.5,  -18.5, 18.5, 30.5, -14.5, -6.5,  34.5, 18.5, -6.5,  -10.5, 26.5, 22.5, -2.5,  -18.5, 22.5, 30.5,
-                                             -10.5, -6.5,  38.5, 18.5, -2.5,  -10.5, 30.5, 22.5, 1.5,   -18.5, 26.5, 30.5, -6.5,  -6.5,  42.5, 18.5,
-                                             1.5,   -10.5, 34.5, 22.5, 5.5,   -18.5, 30.5, 30.5, -22.5, -2.5,  26.5, 22.5, -14.5, -6.5,  18.5, 26.5,
-                                             -10.5, -14.5, 14.5, 34.5, -18.5, -2.5,  30.5, 22.5, -10.5, -6.5,  22.5, 26.5, -6.5,  -14.5, 18.5, 34.5,
-                                             -14.5, -2.5,  34.5, 22.5, -6.5,  -6.5,  26.5, 26.5, -2.5,  -14.5, 22.5, 34.5, -10.5, -2.5,  38.5, 22.5,
-                                             -2.5,  -6.5,  30.5, 26.5, 1.5,   -14.5, 26.5, 34.5, -6.5,  -2.5,  42.5, 22.5, 1.5,   -6.5,  34.5, 26.5,
-                                             5.5,   -14.5, 30.5, 34.5, -22.5, 1.5,   26.5, 26.5, -14.5, -2.5,  18.5, 30.5, -10.5, -10.5, 14.5, 38.5,
-                                             -18.5, 1.5,   30.5, 26.5, -10.5, -2.5,  22.5, 30.5, -6.5,  -10.5, 18.5, 38.5, -14.5, 1.5,   34.5, 26.5,
-                                             -6.5,  -2.5,  26.5, 30.5, -2.5,  -10.5, 22.5, 38.5, -10.5, 1.5,   38.5, 26.5, -2.5,  -2.5,  30.5, 30.5,
-                                             1.5,   -10.5, 26.5, 38.5, -6.5,  1.5,   42.5, 26.5, 1.5,   -2.5,  34.5, 30.5, 5.5,   -10.5, 30.5, 38.5}),
-        ExperimentalPGGParams(Attrs{false, 0, 0, 8.0f, 8.0f},
-                              {3, 4},
-                              {1, 16, 3, 7},
-                              {1, 3, 100, 200},
-                              {3, 7, 3, 4},
-                              IN_ET,
-                              std::vector<T>{-44.5, -24.5, 44.5, 24.5, -32.5, -32.5, 32.5, 32.5, -24.5, -44.5, 24.5, 44.5},
-                              std::vector<T>{-40.5, -20.5, 48.5, 28.5, -28.5, -28.5, 36.5, 36.5, -20.5, -40.5, 28.5, 48.5, -32.5, -20.5, 56.5, 28.5,
-                                             -20.5, -28.5, 44.5, 36.5, -12.5, -40.5, 36.5, 48.5, -24.5, -20.5, 64.5, 28.5, -12.5, -28.5, 52.5, 36.5,
-                                             -4.5,  -40.5, 44.5, 48.5, -16.5, -20.5, 72.5, 28.5, -4.5,  -28.5, 60.5, 36.5, 3.5,   -40.5, 52.5, 48.5,
-                                             -8.5,  -20.5, 80.5, 28.5, 3.5,   -28.5, 68.5, 36.5, 11.5,  -40.5, 60.5, 48.5, -0.5,  -20.5, 88.5, 28.5,
-                                             11.5,  -28.5, 76.5, 36.5, 19.5,  -40.5, 68.5, 48.5, 7.5,   -20.5, 96.5, 28.5, 19.5,  -28.5, 84.5, 36.5,
-                                             27.5,  -40.5, 76.5, 48.5, -40.5, -12.5, 48.5, 36.5, -28.5, -20.5, 36.5, 44.5, -20.5, -32.5, 28.5, 56.5,
-                                             -32.5, -12.5, 56.5, 36.5, -20.5, -20.5, 44.5, 44.5, -12.5, -32.5, 36.5, 56.5, -24.5, -12.5, 64.5, 36.5,
-                                             -12.5, -20.5, 52.5, 44.5, -4.5,  -32.5, 44.5, 56.5, -16.5, -12.5, 72.5, 36.5, -4.5,  -20.5, 60.5, 44.5,
-                                             3.5,   -32.5, 52.5, 56.5, -8.5,  -12.5, 80.5, 36.5, 3.5,   -20.5, 68.5, 44.5, 11.5,  -32.5, 60.5, 56.5,
-                                             -0.5,  -12.5, 88.5, 36.5, 11.5,  -20.5, 76.5, 44.5, 19.5,  -32.5, 68.5, 56.5, 7.5,   -12.5, 96.5, 36.5,
-                                             19.5,  -20.5, 84.5, 44.5, 27.5,  -32.5, 76.5, 56.5, -40.5, -4.5,  48.5, 44.5, -28.5, -12.5, 36.5, 52.5,
-                                             -20.5, -24.5, 28.5, 64.5, -32.5, -4.5,  56.5, 44.5, -20.5, -12.5, 44.5, 52.5, -12.5, -24.5, 36.5, 64.5,
-                                             -24.5, -4.5,  64.5, 44.5, -12.5, -12.5, 52.5, 52.5, -4.5,  -24.5, 44.5, 64.5, -16.5, -4.5,  72.5, 44.5,
-                                             -4.5,  -12.5, 60.5, 52.5, 3.5,   -24.5, 52.5, 64.5, -8.5,  -4.5,  80.5, 44.5, 3.5,   -12.5, 68.5, 52.5,
-                                             11.5,  -24.5, 60.5, 64.5, -0.5,  -4.5,  88.5, 44.5, 11.5,  -12.5, 76.5, 52.5, 19.5,  -24.5, 68.5, 64.5,
-                                             7.5,   -4.5,  96.5, 44.5, 19.5,  -12.5, 84.5, 52.5, 27.5,  -24.5, 76.5, 64.5}),
-        ExperimentalPGGParams(Attrs{true, 3, 6, 64.0f, 64.0f},
-                              {3, 4},
-                              {1, 16, 100, 100},
-                              {1, 3, 100, 200},
-                              {30000, 4},
-                              IN_ET,
-                              std::vector<T>{-364.5, -184.5, 364.5, 184.5, -256.5, -256.5, 256.5, 256.5, -180.5, -360.5, 180.5, 360.5},
-                              std::vector<T>{-332.5, -152.5, 396.5,  216.5,  -224.5, -224.5, 288.5,  288.5,  -148.5, -328.5, 212.5,  392.5,  -268.5, -152.5,
-                                             460.5,  216.5,  -160.5, -224.5, 352.5,  288.5,  -84.5,  -328.5, 276.5,  392.5,  -204.5, -152.5, 524.5,  216.5,
-                                             -96.5,  -224.5, 416.5,  288.5,  -20.5,  -328.5, 340.5,  392.5,  -140.5, -152.5, 588.5,  216.5,  -32.5,  -224.5,
-                                             480.5,  288.5,  43.5,   -328.5, 404.5,  392.5,  -76.5,  -152.5, 652.5,  216.5,  31.5,   -224.5, 544.5,  288.5,
-                                             107.5,  -328.5, 468.5,  392.5,  -12.5,  -152.5, 716.5,  216.5,  95.5,   -224.5, 608.5,  288.5,  171.5,  -328.5,
-                                             532.5,  392.5,  -332.5, -88.5,  396.5,  280.5,  -224.5, -160.5, 288.5,  352.5,  -148.5, -264.5, 212.5,  456.5,
-                                             -268.5, -88.5,  460.5,  280.5,  -160.5, -160.5, 352.5,  352.5,  -84.5,  -264.5, 276.5,  456.5,  -204.5, -88.5,
-                                             524.5,  280.5,  -96.5,  -160.5, 416.5,  352.5,  -20.5,  -264.5, 340.5,  456.5,  -140.5, -88.5,  588.5,  280.5,
-                                             -32.5,  -160.5, 480.5,  352.5,  43.5,   -264.5, 404.5,  456.5,  -76.5,  -88.5,  652.5,  280.5,  31.5,   -160.5,
-                                             544.5,  352.5,  107.5,  -264.5, 468.5,  456.5,  -12.5,  -88.5,  716.5,  280.5,  95.5,   -160.5, 608.5,  352.5,
-                                             171.5,  -264.5, 532.5,  456.5,  -332.5, -24.5,  396.5,  344.5,  -224.5, -96.5,  288.5,  416.5,  -148.5, -200.5,
-                                             212.5,  520.5,  -268.5, -24.5,  460.5,  344.5,  -160.5, -96.5,  352.5,  416.5,  -84.5,  -200.5, 276.5,  520.5,
-                                             -204.5, -24.5,  524.5,  344.5,  -96.5,  -96.5,  416.5,  416.5,  -20.5,  -200.5, 340.5,  520.5,  -140.5, -24.5,
-                                             588.5,  344.5,  -32.5,  -96.5,  480.5,  416.5,  43.5,   -200.5, 404.5,  520.5,  -76.5,  -24.5,  652.5,  344.5,
-                                             31.5,   -96.5,  544.5,  416.5,  107.5,  -200.5, 468.5,  520.5,  -12.5,  -24.5,  716.5,  344.5,  95.5,   -96.5,
-                                             608.5,  416.5,  171.5,  -200.5, 532.5,  520.5}),
-        ExperimentalPGGParams(Attrs{false, 5, 3, 32.0f, 32.0f},
-                              {3, 4},
-                              {1, 16, 100, 100},
-                              {1, 3, 100, 200},
-                              {100, 100, 3, 4},
-                              IN_ET,
-                              std::vector<T>{-180.5, -88.5, 180.5, 88.5, -128.5, -128.5, 128.5, 128.5, -92.5, -184.5, 92.5, 184.5},
-                              std::vector<T>{-164.5, -72.5,  196.5,  104.5,  -112.5, -112.5, 144.5,  144.5,  -76.5,  -168.5, 108.5,  200.5,  -132.5, -72.5,
-                                             228.5,  104.5,  -80.5,  -112.5, 176.5,  144.5,  -44.5,  -168.5, 140.5,  200.5,  -100.5, -72.5,  260.5,  104.5,
-                                             -48.5,  -112.5, 208.5,  144.5,  -12.5,  -168.5, 172.5,  200.5,  -164.5, -40.5,  196.5,  136.5,  -112.5, -80.5,
-                                             144.5,  176.5,  -76.5,  -136.5, 108.5,  232.5,  -132.5, -40.5,  228.5,  136.5,  -80.5,  -80.5,  176.5,  176.5,
-                                             -44.5,  -136.5, 140.5,  232.5,  -100.5, -40.5,  260.5,  136.5,  -48.5,  -80.5,  208.5,  176.5,  -12.5,  -136.5,
-                                             172.5,  232.5,  -164.5, -8.5,   196.5,  168.5,  -112.5, -48.5,  144.5,  208.5,  -76.5,  -104.5, 108.5,  264.5,
-                                             -132.5, -8.5,   228.5,  168.5,  -80.5,  -48.5,  176.5,  208.5,  -44.5,  -104.5, 140.5,  264.5,  -100.5, -8.5,
-                                             260.5,  168.5,  -48.5,  -48.5,  208.5,  208.5,  -12.5,  -104.5, 172.5,  264.5,  -164.5, 23.5,   196.5,  200.5,
-                                             -112.5, -16.5,  144.5,  240.5,  -76.5,  -72.5,  108.5,  296.5,  -132.5, 23.5,   228.5,  200.5,  -80.5,  -16.5,
-                                             176.5,  240.5,  -44.5,  -72.5,  140.5,  296.5,  -100.5, 23.5,   260.5,  200.5,  -48.5,  -16.5,  208.5,  240.5,
-                                             -12.5,  -72.5,  172.5,  296.5,  -164.5, 55.5,   196.5,  232.5,  -112.5, 15.5,   144.5,  272.5,  -76.5,  -40.5,
-                                             108.5,  328.5,  -132.5, 55.5,   228.5,  232.5,  -80.5,  15.5,   176.5,  272.5,  -44.5,  -40.5,  140.5,  328.5,
-                                             -100.5, 55.5,   260.5,  232.5,  -48.5,  15.5,   208.5,  272.5,  -12.5,  -40.5,  172.5,  328.5}),
+    std::vector<ExperimentalPGGParams> experimentalPGGParams{
+        ExperimentalPGGParams(
+            Attrs{true, 0, 0, 4.0f, 4.0f},
+            {3, 4},
+            {1, 16, 4, 5},
+            {1, 3, 100, 200},
+            {60, 4},
+            IN_ET,
+            std::vector<T>{-24.5, -12.5, 24.5, 12.5, -16.5, -16.5, 16.5, 16.5, -12.5, -24.5, 12.5, 24.5},
+            std::vector<T>{-22.5, -10.5, 26.5,  14.5,  -14.5, -14.5, 18.5,  18.5,  -10.5, -22.5, 14.5,  26.5,  -18.5,
+                           -10.5, 30.5,  14.5,  -10.5, -14.5, 22.5,  18.5,  -6.5,  -22.5, 18.5,  26.5,  -14.5, -10.5,
+                           34.5,  14.5,  -6.5,  -14.5, 26.5,  18.5,  -2.5,  -22.5, 22.5,  26.5,  -10.5, -10.5, 38.5,
+                           14.5,  -2.5,  -14.5, 30.5,  18.5,  1.5,   -22.5, 26.5,  26.5,  -6.5,  -10.5, 42.5,  14.5,
+                           1.5,   -14.5, 34.5,  18.5,  5.5,   -22.5, 30.5,  26.5,  -22.5, -6.5,  26.5,  18.5,  -14.5,
+                           -10.5, 18.5,  22.5,  -10.5, -18.5, 14.5,  30.5,  -18.5, -6.5,  30.5,  18.5,  -10.5, -10.5,
+                           22.5,  22.5,  -6.5,  -18.5, 18.5,  30.5,  -14.5, -6.5,  34.5,  18.5,  -6.5,  -10.5, 26.5,
+                           22.5,  -2.5,  -18.5, 22.5,  30.5,  -10.5, -6.5,  38.5,  18.5,  -2.5,  -10.5, 30.5,  22.5,
+                           1.5,   -18.5, 26.5,  30.5,  -6.5,  -6.5,  42.5,  18.5,  1.5,   -10.5, 34.5,  22.5,  5.5,
+                           -18.5, 30.5,  30.5,  -22.5, -2.5,  26.5,  22.5,  -14.5, -6.5,  18.5,  26.5,  -10.5, -14.5,
+                           14.5,  34.5,  -18.5, -2.5,  30.5,  22.5,  -10.5, -6.5,  22.5,  26.5,  -6.5,  -14.5, 18.5,
+                           34.5,  -14.5, -2.5,  34.5,  22.5,  -6.5,  -6.5,  26.5,  26.5,  -2.5,  -14.5, 22.5,  34.5,
+                           -10.5, -2.5,  38.5,  22.5,  -2.5,  -6.5,  30.5,  26.5,  1.5,   -14.5, 26.5,  34.5,  -6.5,
+                           -2.5,  42.5,  22.5,  1.5,   -6.5,  34.5,  26.5,  5.5,   -14.5, 30.5,  34.5,  -22.5, 1.5,
+                           26.5,  26.5,  -14.5, -2.5,  18.5,  30.5,  -10.5, -10.5, 14.5,  38.5,  -18.5, 1.5,   30.5,
+                           26.5,  -10.5, -2.5,  22.5,  30.5,  -6.5,  -10.5, 18.5,  38.5,  -14.5, 1.5,   34.5,  26.5,
+                           -6.5,  -2.5,  26.5,  30.5,  -2.5,  -10.5, 22.5,  38.5,  -10.5, 1.5,   38.5,  26.5,  -2.5,
+                           -2.5,  30.5,  30.5,  1.5,   -10.5, 26.5,  38.5,  -6.5,  1.5,   42.5,  26.5,  1.5,   -2.5,
+                           34.5,  30.5,  5.5,   -10.5, 30.5,  38.5}),
+        ExperimentalPGGParams(
+            Attrs{false, 0, 0, 8.0f, 8.0f},
+            {3, 4},
+            {1, 16, 3, 7},
+            {1, 3, 100, 200},
+            {3, 7, 3, 4},
+            IN_ET,
+            std::vector<T>{-44.5, -24.5, 44.5, 24.5, -32.5, -32.5, 32.5, 32.5, -24.5, -44.5, 24.5, 44.5},
+            std::vector<T>{
+                -40.5, -20.5, 48.5, 28.5, -28.5, -28.5, 36.5, 36.5, -20.5, -40.5, 28.5, 48.5, -32.5, -20.5, 56.5, 28.5,
+                -20.5, -28.5, 44.5, 36.5, -12.5, -40.5, 36.5, 48.5, -24.5, -20.5, 64.5, 28.5, -12.5, -28.5, 52.5, 36.5,
+                -4.5,  -40.5, 44.5, 48.5, -16.5, -20.5, 72.5, 28.5, -4.5,  -28.5, 60.5, 36.5, 3.5,   -40.5, 52.5, 48.5,
+                -8.5,  -20.5, 80.5, 28.5, 3.5,   -28.5, 68.5, 36.5, 11.5,  -40.5, 60.5, 48.5, -0.5,  -20.5, 88.5, 28.5,
+                11.5,  -28.5, 76.5, 36.5, 19.5,  -40.5, 68.5, 48.5, 7.5,   -20.5, 96.5, 28.5, 19.5,  -28.5, 84.5, 36.5,
+                27.5,  -40.5, 76.5, 48.5, -40.5, -12.5, 48.5, 36.5, -28.5, -20.5, 36.5, 44.5, -20.5, -32.5, 28.5, 56.5,
+                -32.5, -12.5, 56.5, 36.5, -20.5, -20.5, 44.5, 44.5, -12.5, -32.5, 36.5, 56.5, -24.5, -12.5, 64.5, 36.5,
+                -12.5, -20.5, 52.5, 44.5, -4.5,  -32.5, 44.5, 56.5, -16.5, -12.5, 72.5, 36.5, -4.5,  -20.5, 60.5, 44.5,
+                3.5,   -32.5, 52.5, 56.5, -8.5,  -12.5, 80.5, 36.5, 3.5,   -20.5, 68.5, 44.5, 11.5,  -32.5, 60.5, 56.5,
+                -0.5,  -12.5, 88.5, 36.5, 11.5,  -20.5, 76.5, 44.5, 19.5,  -32.5, 68.5, 56.5, 7.5,   -12.5, 96.5, 36.5,
+                19.5,  -20.5, 84.5, 44.5, 27.5,  -32.5, 76.5, 56.5, -40.5, -4.5,  48.5, 44.5, -28.5, -12.5, 36.5, 52.5,
+                -20.5, -24.5, 28.5, 64.5, -32.5, -4.5,  56.5, 44.5, -20.5, -12.5, 44.5, 52.5, -12.5, -24.5, 36.5, 64.5,
+                -24.5, -4.5,  64.5, 44.5, -12.5, -12.5, 52.5, 52.5, -4.5,  -24.5, 44.5, 64.5, -16.5, -4.5,  72.5, 44.5,
+                -4.5,  -12.5, 60.5, 52.5, 3.5,   -24.5, 52.5, 64.5, -8.5,  -4.5,  80.5, 44.5, 3.5,   -12.5, 68.5, 52.5,
+                11.5,  -24.5, 60.5, 64.5, -0.5,  -4.5,  88.5, 44.5, 11.5,  -12.5, 76.5, 52.5, 19.5,  -24.5, 68.5, 64.5,
+                7.5,   -4.5,  96.5, 44.5, 19.5,  -12.5, 84.5, 52.5, 27.5,  -24.5, 76.5, 64.5}),
+        ExperimentalPGGParams(
+            Attrs{true, 3, 6, 64.0f, 64.0f},
+            {3, 4},
+            {1, 16, 100, 100},
+            {1, 3, 100, 200},
+            {30000, 4},
+            IN_ET,
+            std::vector<T>{-364.5, -184.5, 364.5, 184.5, -256.5, -256.5, 256.5, 256.5, -180.5, -360.5, 180.5, 360.5},
+            std::vector<T>{-332.5, -152.5, 396.5, 216.5, -224.5, -224.5, 288.5, 288.5, -148.5, -328.5, 212.5, 392.5,
+                           -268.5, -152.5, 460.5, 216.5, -160.5, -224.5, 352.5, 288.5, -84.5,  -328.5, 276.5, 392.5,
+                           -204.5, -152.5, 524.5, 216.5, -96.5,  -224.5, 416.5, 288.5, -20.5,  -328.5, 340.5, 392.5,
+                           -140.5, -152.5, 588.5, 216.5, -32.5,  -224.5, 480.5, 288.5, 43.5,   -328.5, 404.5, 392.5,
+                           -76.5,  -152.5, 652.5, 216.5, 31.5,   -224.5, 544.5, 288.5, 107.5,  -328.5, 468.5, 392.5,
+                           -12.5,  -152.5, 716.5, 216.5, 95.5,   -224.5, 608.5, 288.5, 171.5,  -328.5, 532.5, 392.5,
+                           -332.5, -88.5,  396.5, 280.5, -224.5, -160.5, 288.5, 352.5, -148.5, -264.5, 212.5, 456.5,
+                           -268.5, -88.5,  460.5, 280.5, -160.5, -160.5, 352.5, 352.5, -84.5,  -264.5, 276.5, 456.5,
+                           -204.5, -88.5,  524.5, 280.5, -96.5,  -160.5, 416.5, 352.5, -20.5,  -264.5, 340.5, 456.5,
+                           -140.5, -88.5,  588.5, 280.5, -32.5,  -160.5, 480.5, 352.5, 43.5,   -264.5, 404.5, 456.5,
+                           -76.5,  -88.5,  652.5, 280.5, 31.5,   -160.5, 544.5, 352.5, 107.5,  -264.5, 468.5, 456.5,
+                           -12.5,  -88.5,  716.5, 280.5, 95.5,   -160.5, 608.5, 352.5, 171.5,  -264.5, 532.5, 456.5,
+                           -332.5, -24.5,  396.5, 344.5, -224.5, -96.5,  288.5, 416.5, -148.5, -200.5, 212.5, 520.5,
+                           -268.5, -24.5,  460.5, 344.5, -160.5, -96.5,  352.5, 416.5, -84.5,  -200.5, 276.5, 520.5,
+                           -204.5, -24.5,  524.5, 344.5, -96.5,  -96.5,  416.5, 416.5, -20.5,  -200.5, 340.5, 520.5,
+                           -140.5, -24.5,  588.5, 344.5, -32.5,  -96.5,  480.5, 416.5, 43.5,   -200.5, 404.5, 520.5,
+                           -76.5,  -24.5,  652.5, 344.5, 31.5,   -96.5,  544.5, 416.5, 107.5,  -200.5, 468.5, 520.5,
+                           -12.5,  -24.5,  716.5, 344.5, 95.5,   -96.5,  608.5, 416.5, 171.5,  -200.5, 532.5, 520.5}),
+        ExperimentalPGGParams(
+            Attrs{false, 5, 3, 32.0f, 32.0f},
+            {3, 4},
+            {1, 16, 100, 100},
+            {1, 3, 100, 200},
+            {100, 100, 3, 4},
+            IN_ET,
+            std::vector<T>{-180.5, -88.5, 180.5, 88.5, -128.5, -128.5, 128.5, 128.5, -92.5, -184.5, 92.5, 184.5},
+            std::vector<T>{-164.5, -72.5, 196.5, 104.5, -112.5, -112.5, 144.5, 144.5, -76.5, -168.5, 108.5, 200.5,
+                           -132.5, -72.5, 228.5, 104.5, -80.5,  -112.5, 176.5, 144.5, -44.5, -168.5, 140.5, 200.5,
+                           -100.5, -72.5, 260.5, 104.5, -48.5,  -112.5, 208.5, 144.5, -12.5, -168.5, 172.5, 200.5,
+                           -164.5, -40.5, 196.5, 136.5, -112.5, -80.5,  144.5, 176.5, -76.5, -136.5, 108.5, 232.5,
+                           -132.5, -40.5, 228.5, 136.5, -80.5,  -80.5,  176.5, 176.5, -44.5, -136.5, 140.5, 232.5,
+                           -100.5, -40.5, 260.5, 136.5, -48.5,  -80.5,  208.5, 176.5, -12.5, -136.5, 172.5, 232.5,
+                           -164.5, -8.5,  196.5, 168.5, -112.5, -48.5,  144.5, 208.5, -76.5, -104.5, 108.5, 264.5,
+                           -132.5, -8.5,  228.5, 168.5, -80.5,  -48.5,  176.5, 208.5, -44.5, -104.5, 140.5, 264.5,
+                           -100.5, -8.5,  260.5, 168.5, -48.5,  -48.5,  208.5, 208.5, -12.5, -104.5, 172.5, 264.5,
+                           -164.5, 23.5,  196.5, 200.5, -112.5, -16.5,  144.5, 240.5, -76.5, -72.5,  108.5, 296.5,
+                           -132.5, 23.5,  228.5, 200.5, -80.5,  -16.5,  176.5, 240.5, -44.5, -72.5,  140.5, 296.5,
+                           -100.5, 23.5,  260.5, 200.5, -48.5,  -16.5,  208.5, 240.5, -12.5, -72.5,  172.5, 296.5,
+                           -164.5, 55.5,  196.5, 232.5, -112.5, 15.5,   144.5, 272.5, -76.5, -40.5,  108.5, 328.5,
+                           -132.5, 55.5,  228.5, 232.5, -80.5,  15.5,   176.5, 272.5, -44.5, -40.5,  140.5, 328.5,
+                           -100.5, 55.5,  260.5, 232.5, -48.5,  15.5,   208.5, 272.5, -12.5, -40.5,  172.5, 328.5}),
     };
     return experimentalPGGParams;
 }
 
 std::vector<ExperimentalPGGParams> generateExperimentalPGGCombinedParams() {
-    const std::vector<std::vector<ExperimentalPGGParams>> experimentalPGGTypeParams {
+    const std::vector<std::vector<ExperimentalPGGParams>> experimentalPGGTypeParams{
         generateExperimentalPGGFloatParams<element::Type_t::f64>(),
         generateExperimentalPGGFloatParams<element::Type_t::f32>(),
         generateExperimentalPGGFloatParams<element::Type_t::f16>(),
         generateExperimentalPGGFloatParams<element::Type_t::bf16>(),
-        };
+    };
     std::vector<ExperimentalPGGParams> combinedParams;
 
     for (const auto& params : experimentalPGGTypeParams) {
@@ -221,6 +235,8 @@ std::vector<ExperimentalPGGParams> generateExperimentalPGGCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ExperimentalDetectronPriorGridGenerator_With_Hardcoded_Refs, ReferenceExperimentalPGGLayerTest,
-    testing::ValuesIn(generateExperimentalPGGCombinedParams()), ReferenceExperimentalPGGLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_ExperimentalDetectronPriorGridGenerator_With_Hardcoded_Refs,
+                         ReferenceExperimentalPGGLayerTest,
+                         testing::ValuesIn(generateExperimentalPGGCombinedParams()),
+                         ReferenceExperimentalPGGLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/experimental_detectron_generate_proposals.cpp b/src/plugins/template/tests/functional/op_reference/experimental_detectron_generate_proposals.cpp
index 1a3ff42b53e1d2..f0320d7b411cc5 100644
--- a/src/plugins/template/tests/functional/op_reference/experimental_detectron_generate_proposals.cpp
+++ b/src/plugins/template/tests/functional/op_reference/experimental_detectron_generate_proposals.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/experimental_detectron_generate_proposals.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/experimental_detectron_generate_proposals.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -16,11 +17,16 @@ namespace {
 struct ExperimentalGPParams {
     template <class IT>
     ExperimentalGPParams(const Attrs& attrs,
-                         const size_t number_of_channels, const size_t height, const size_t width,
+                         const size_t number_of_channels,
+                         const size_t height,
+                         const size_t width,
                          const element::Type& iType,
-                         const std::vector<IT>& imageSizeInfoValues, const std::vector<IT>& anchorsValues,
-                         const std::vector<IT>& deltasValues, const std::vector<IT>& scoresValues,
-                         const std::vector<IT>& refRoisValues, const std::vector<IT>& refScoresValues,
+                         const std::vector<IT>& imageSizeInfoValues,
+                         const std::vector<IT>& anchorsValues,
+                         const std::vector<IT>& deltasValues,
+                         const std::vector<IT>& scoresValues,
+                         const std::vector<IT>& refRoisValues,
+                         const std::vector<IT>& refScoresValues,
                          const std::string& testcaseName = "")
         : attrs(attrs),
           inType(iType),
@@ -32,11 +38,11 @@ struct ExperimentalGPParams {
           refRoisData(CreateTensor(iType, refRoisValues)),
           refScoresData(CreateTensor(iType, refScoresValues)),
           testcaseName(testcaseName) {
-              imageSizeInfoShape = Shape{3};
-              anchorsShape = Shape{height * width * number_of_channels, 4};
-              deltasShape = Shape{number_of_channels * 4, height, width};
-              scoresShape = Shape{number_of_channels, height, width};
-          }
+        imageSizeInfoShape = Shape{3};
+        anchorsShape = Shape{height * width * number_of_channels, 4};
+        deltasShape = Shape{number_of_channels * 4, height, width};
+        scoresShape = Shape{number_of_channels, height, width};
+    }
 
     Attrs attrs;
     PartialShape imageSizeInfoShape;
@@ -54,7 +60,8 @@ struct ExperimentalGPParams {
     std::string testcaseName;
 };
 
-class ReferenceExperimentalGPLayerTest : public testing::TestWithParam<ExperimentalGPParams>, public CommonReferenceTest {
+class ReferenceExperimentalGPLayerTest : public testing::TestWithParam<ExperimentalGPParams>,
+                                         public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -82,12 +89,14 @@ class ReferenceExperimentalGPLayerTest : public testing::TestWithParam<Experimen
         const auto anchors = std::make_shared<op::v0::Parameter>(params.inType, params.anchorsShape);
         const auto deltas = std::make_shared<op::v0::Parameter>(params.inType, params.deltasShape);
         const auto scores = std::make_shared<op::v0::Parameter>(params.inType, params.scoresShape);
-        const auto ExperimentalGP = std::make_shared<op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(im_info,
-                                                                    anchors,
-                                                                    deltas,
-                                                                    scores,
-                                                                    params.attrs);
-        return std::make_shared<ov::Model>(ExperimentalGP->outputs(), ParameterVector {im_info, anchors, deltas, scores});
+        const auto ExperimentalGP =
+            std::make_shared<op::v6::ExperimentalDetectronGenerateProposalsSingleImage>(im_info,
+                                                                                        anchors,
+                                                                                        deltas,
+                                                                                        scores,
+                                                                                        params.attrs);
+        return std::make_shared<ov::Model>(ExperimentalGP->outputs(),
+                                           ParameterVector{im_info, anchors, deltas, scores});
     }
 };
 
@@ -99,104 +108,118 @@ template <element::Type_t IN_ET>
 std::vector<ExperimentalGPParams> generateExperimentalGPFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ExperimentalGPParams> experimentalGPParams {
-        ExperimentalGPParams(Attrs{0, // min_size
-                              0.699999988079071, // nms_threshold
-                              6, // post_nms_count
-                              1000 // pre_nms_count
-                              },
-                              3,
-                              2,
-                              6,
-                              IN_ET,
-                              std::vector<T>{1.0f, 1.0f, 1.0f},
-                              std::vector<T>{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
-                              std::vector<T>{1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
-                              std::vector<T>{5.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 4.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 8.0f, 1.0f},
-                              std::vector<T>{0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
-                                             0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f},
-                              std::vector<T>{8.0f, 5.0f, 4.0f, 1.0f, 1.0f, 1.0f},
-                              "eval"),
-        ExperimentalGPParams(Attrs{0, // min_size
-                              0.699999988079071, // nms_threshold
-                              6, // post_nms_count
-                              1000 // pre_nms_count
-                              },
-                              3,
-                              2,
-                              6,
-                              IN_ET,
-                              std::vector<T>{150.0, 150.0, 1.0},
-                              std::vector<T>{12.0, 68.0, 102.0, 123.0, 46.0, 80.0,  79.0,  128.0, 33.0, 71.0, 127.0, 86.0,  33.0, 56.0, 150.0, 73.0,
-                                             5.0,  41.0, 93.0,  150.0, 74.0, 66.0,  106.0, 115.0, 17.0, 37.0, 87.0,  150.0, 31.0, 27.0, 150.0, 39.0,
-                                             29.0, 23.0, 112.0, 123.0, 41.0, 37.0,  103.0, 150.0, 8.0,  46.0, 98.0,  111.0, 7.0,  69.0, 114.0, 150.0,
-                                             70.0, 21.0, 150.0, 125.0, 54.0, 19.0,  132.0, 68.0,  62.0, 8.0,  150.0, 101.0, 57.0, 81.0, 150.0, 97.0,
-                                             79.0, 29.0, 109.0, 130.0, 12.0, 63.0,  100.0, 150.0, 17.0, 33.0, 113.0, 150.0, 90.0, 78.0, 150.0, 111.0,
-                                             47.0, 68.0, 150.0, 71.0,  66.0, 103.0, 111.0, 150.0, 4.0,  17.0, 112.0, 94.0,  12.0, 8.0,  119.0, 98.0,
-                                             54.0, 56.0, 120.0, 150.0, 56.0, 29.0,  150.0, 31.0,  42.0, 3.0,  139.0, 92.0,  41.0, 65.0, 150.0, 130.0,
-                                             49.0, 13.0, 143.0, 30.0,  40.0, 60.0,  150.0, 150.0, 23.0, 73.0, 24.0,  115.0, 56.0, 84.0, 107.0, 108.0,
-                                             63.0, 8.0,  142.0, 125.0, 78.0, 37.0,  93.0,  144.0, 40.0, 34.0, 150.0, 46.0,  30.0, 21.0, 150.0, 120.0},
-                              std::vector<T>{9.062256,   10.883133, 9.8441105,   12.694285,   0.41781136, 8.749107,      14.990341,  6.587644,  1.4206103,
-                                             13.299262,  12.432549, 2.736371,    0.22732796,  6.3361835,  12.268727,     2.1009045,  4.771589,  2.5131326,
-                                             5.610736,   9.3604145, 4.27379,     8.317948,    0.60510135, 6.7446275,     1.0207708,  1.1352817, 1.5785321,
-                                             1.718335,   1.8093798, 0.99247587,  1.3233583,   1.7432803,  1.8534478,     1.2593061,  1.7394226, 1.7686696,
-                                             1.647999,   1.7611449, 1.3119122,   0.03007332,  1.1106564,  0.55669737,    0.2546148,  1.9181818, 0.7134989,
-                                             2.0407224,  1.7211134, 1.8565536,   14.562747,   2.8786168,  0.5927796,     0.2064463,  7.6794515, 8.672126,
-                                             10.139171,  8.002429,  7.002932,    12.6314945,  10.550842,  0.15784842,    0.3194304,  10.752157, 3.709805,
-                                             11.628928,  0.7136225, 14.619964,   15.177284,   2.2824087,  15.381494,     0.16618137, 7.507227,  11.173228,
-                                             0.4923559,  1.8227729, 1.4749299,   1.7833921,   1.2363617,  -0.23659119,   1.5737582,  1.779316,  1.9828427,
-                                             1.0482665,  1.4900246, 1.3563544,   1.5341306,   0.7634312,  4.6216766e-05, 1.6161222,  1.7512476, 1.9363779,
-                                             0.9195784,  1.4906164, -0.03244795, 0.681073,    0.6192401,  1.8033613,     14.146055,  3.4043705, 15.292292,
-                                             3.5295358,  11.138999, 9.952057,    5.633434,    12.114562,  9.427372,      12.384038,  9.583308,  8.427233,
-                                             15.293704,  3.288159,  11.64898,    9.350885,    2.0037227,  13.523184,     4.4176426,  6.1057625, 14.400079,
-                                             8.248259,   11.815807, 15.713364,   1.0023532,   1.3203261,  1.7100681,     0.7407832,  1.09448,   1.7188418,
-                                             1.4412547,  1.4862992, 0.74790007,  0.31571656,  0.6398838,  2.0236106,     1.1869069,  1.7265586, 1.2624544,
-                                             0.09934269, 1.3508598, 0.85212964,  -0.38968498, 1.7059708,  1.6533034,     1.7400402,  1.8123854, -0.43063712},
-                              std::vector<T>{0.7719922,  0.35906568, 0.29054508, 0.18124384, 0.5604661,  0.84750974, 0.98948747, 0.009793862, 0.7184191,
-                                             0.5560748,  0.6952493,  0.6732593,  0.3306898,  0.6790913,  0.41128764, 0.34593266, 0.94296855,  0.7348507,
-                                             0.24478768, 0.94024557, 0.05405676, 0.06466125, 0.36244348, 0.07942984, 0.10619422, 0.09412837,  0.9053611,
-                                             0.22870538, 0.9237487,  0.20986171, 0.5067282,  0.29709867, 0.53138554, 0.189101,   0.4786443,   0.88421875},
-                              std::vector<T>{149, 149, 149, 149, 149, 0,   149, 149, 149, 60.87443542480469, 149, 149, 149, 61.89498901367188, 149,
-                                             149, 149, 149, 149, 149, 149, 149, 149, 149},
-                              std::vector<T>{0.9894874691963196,
-                                             0.9429685473442078,
-                                             0.9402455687522888,
-                                             0.9237486720085144,
-                                             0.9053611159324646,
-                                             0.8842187523841858},
-                              "eval_2"),
+    std::vector<ExperimentalGPParams> experimentalGPParams{
+        ExperimentalGPParams(
+            Attrs{
+                0,                  // min_size
+                0.699999988079071,  // nms_threshold
+                6,                  // post_nms_count
+                1000                // pre_nms_count
+            },
+            3,
+            2,
+            6,
+            IN_ET,
+            std::vector<T>{1.0f, 1.0f, 1.0f},
+            std::vector<T>{
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
+            std::vector<T>{
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+
+                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f},
+            std::vector<T>{5.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                           1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 4.0f, 1.0f, 1.0f, 1.0f,
+                           1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 8.0f, 1.0f},
+            std::vector<T>{0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+                           0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f},
+            std::vector<T>{8.0f, 5.0f, 4.0f, 1.0f, 1.0f, 1.0f},
+            "eval"),
+        ExperimentalGPParams(
+            Attrs{
+                0,                  // min_size
+                0.699999988079071,  // nms_threshold
+                6,                  // post_nms_count
+                1000                // pre_nms_count
+            },
+            3,
+            2,
+            6,
+            IN_ET,
+            std::vector<T>{150.0, 150.0, 1.0},
+            std::vector<T>{
+                12.0,  68.0,  102.0, 123.0, 46.0,  80.0,  79.0,  128.0, 33.0,  71.0,  127.0, 86.0,  33.0,  56.0,  150.0,
+                73.0,  5.0,   41.0,  93.0,  150.0, 74.0,  66.0,  106.0, 115.0, 17.0,  37.0,  87.0,  150.0, 31.0,  27.0,
+                150.0, 39.0,  29.0,  23.0,  112.0, 123.0, 41.0,  37.0,  103.0, 150.0, 8.0,   46.0,  98.0,  111.0, 7.0,
+                69.0,  114.0, 150.0, 70.0,  21.0,  150.0, 125.0, 54.0,  19.0,  132.0, 68.0,  62.0,  8.0,   150.0, 101.0,
+                57.0,  81.0,  150.0, 97.0,  79.0,  29.0,  109.0, 130.0, 12.0,  63.0,  100.0, 150.0, 17.0,  33.0,  113.0,
+                150.0, 90.0,  78.0,  150.0, 111.0, 47.0,  68.0,  150.0, 71.0,  66.0,  103.0, 111.0, 150.0, 4.0,   17.0,
+                112.0, 94.0,  12.0,  8.0,   119.0, 98.0,  54.0,  56.0,  120.0, 150.0, 56.0,  29.0,  150.0, 31.0,  42.0,
+                3.0,   139.0, 92.0,  41.0,  65.0,  150.0, 130.0, 49.0,  13.0,  143.0, 30.0,  40.0,  60.0,  150.0, 150.0,
+                23.0,  73.0,  24.0,  115.0, 56.0,  84.0,  107.0, 108.0, 63.0,  8.0,   142.0, 125.0, 78.0,  37.0,  93.0,
+                144.0, 40.0,  34.0,  150.0, 46.0,  30.0,  21.0,  150.0, 120.0},
+            std::vector<T>{
+                9.062256,   10.883133,  9.8441105,   12.694285,  0.41781136,  8.749107,    14.990341,     6.587644,
+                1.4206103,  13.299262,  12.432549,   2.736371,   0.22732796,  6.3361835,   12.268727,     2.1009045,
+                4.771589,   2.5131326,  5.610736,    9.3604145,  4.27379,     8.317948,    0.60510135,    6.7446275,
+                1.0207708,  1.1352817,  1.5785321,   1.718335,   1.8093798,   0.99247587,  1.3233583,     1.7432803,
+                1.8534478,  1.2593061,  1.7394226,   1.7686696,  1.647999,    1.7611449,   1.3119122,     0.03007332,
+                1.1106564,  0.55669737, 0.2546148,   1.9181818,  0.7134989,   2.0407224,   1.7211134,     1.8565536,
+                14.562747,  2.8786168,  0.5927796,   0.2064463,  7.6794515,   8.672126,    10.139171,     8.002429,
+                7.002932,   12.6314945, 10.550842,   0.15784842, 0.3194304,   10.752157,   3.709805,      11.628928,
+                0.7136225,  14.619964,  15.177284,   2.2824087,  15.381494,   0.16618137,  7.507227,      11.173228,
+                0.4923559,  1.8227729,  1.4749299,   1.7833921,  1.2363617,   -0.23659119, 1.5737582,     1.779316,
+                1.9828427,  1.0482665,  1.4900246,   1.3563544,  1.5341306,   0.7634312,   4.6216766e-05, 1.6161222,
+                1.7512476,  1.9363779,  0.9195784,   1.4906164,  -0.03244795, 0.681073,    0.6192401,     1.8033613,
+                14.146055,  3.4043705,  15.292292,   3.5295358,  11.138999,   9.952057,    5.633434,      12.114562,
+                9.427372,   12.384038,  9.583308,    8.427233,   15.293704,   3.288159,    11.64898,      9.350885,
+                2.0037227,  13.523184,  4.4176426,   6.1057625,  14.400079,   8.248259,    11.815807,     15.713364,
+                1.0023532,  1.3203261,  1.7100681,   0.7407832,  1.09448,     1.7188418,   1.4412547,     1.4862992,
+                0.74790007, 0.31571656, 0.6398838,   2.0236106,  1.1869069,   1.7265586,   1.2624544,     0.09934269,
+                1.3508598,  0.85212964, -0.38968498, 1.7059708,  1.6533034,   1.7400402,   1.8123854,     -0.43063712},
+            std::vector<T>{0.7719922,  0.35906568,  0.29054508, 0.18124384, 0.5604661,  0.84750974,
+                           0.98948747, 0.009793862, 0.7184191,  0.5560748,  0.6952493,  0.6732593,
+                           0.3306898,  0.6790913,   0.41128764, 0.34593266, 0.94296855, 0.7348507,
+                           0.24478768, 0.94024557,  0.05405676, 0.06466125, 0.36244348, 0.07942984,
+                           0.10619422, 0.09412837,  0.9053611,  0.22870538, 0.9237487,  0.20986171,
+                           0.5067282,  0.29709867,  0.53138554, 0.189101,   0.4786443,  0.88421875},
+            std::vector<T>{
+                149, 149, 149, 149, 149, 0,   149, 149, 149, 60.87443542480469, 149, 149, 149, 61.89498901367188, 149,
+                149, 149, 149, 149, 149, 149, 149, 149, 149},
+            std::vector<T>{0.9894874691963196,
+                           0.9429685473442078,
+                           0.9402455687522888,
+                           0.9237486720085144,
+                           0.9053611159324646,
+                           0.8842187523841858},
+            "eval_2"),
     };
     return experimentalGPParams;
 }
 
 std::vector<ExperimentalGPParams> generateExperimentalGPCombinedParams() {
-    const std::vector<std::vector<ExperimentalGPParams>> experimentalGPTypeParams {
+    const std::vector<std::vector<ExperimentalGPParams>> experimentalGPTypeParams{
         generateExperimentalGPFloatParams<element::Type_t::f32>(),
         generateExperimentalGPFloatParams<element::Type_t::f16>(),
         generateExperimentalGPFloatParams<element::Type_t::bf16>(),
-        };
+    };
     std::vector<ExperimentalGPParams> combinedParams;
 
     for (const auto& params : experimentalGPTypeParams) {
@@ -205,6 +228,8 @@ std::vector<ExperimentalGPParams> generateExperimentalGPCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ExperimentalDetectronGenerateProposalsSingleImage_With_Hardcoded_Refs, ReferenceExperimentalGPLayerTest,
-    testing::ValuesIn(generateExperimentalGPCombinedParams()), ReferenceExperimentalGPLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_ExperimentalDetectronGenerateProposalsSingleImage_With_Hardcoded_Refs,
+                         ReferenceExperimentalGPLayerTest,
+                         testing::ValuesIn(generateExperimentalGPCombinedParams()),
+                         ReferenceExperimentalGPLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/experimental_detectron_roi_feature_extractor.cpp b/src/plugins/template/tests/functional/op_reference/experimental_detectron_roi_feature_extractor.cpp
index 10f5f7e4e10135..f187a79a8fc86b 100644
--- a/src/plugins/template/tests/functional/op_reference/experimental_detectron_roi_feature_extractor.cpp
+++ b/src/plugins/template/tests/functional/op_reference/experimental_detectron_roi_feature_extractor.cpp
@@ -4,8 +4,8 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/op/experimental_detectron_roi_feature.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/experimental_detectron_roi_feature.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -23,7 +23,8 @@ struct ExperimentalROIParams {
     std::string test_case_name;
 };
 
-class ReferenceExperimentalROILayerTest : public testing::TestWithParam<ExperimentalROIParams>, public CommonReferenceTest {
+class ReferenceExperimentalROILayerTest : public testing::TestWithParam<ExperimentalROIParams>,
+                                          public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -76,149 +77,67 @@ INSTANTIATE_TEST_SUITE_P(
     ReferenceExperimentalROILayerTest,
     ::testing::Values(
         ExperimentalROIParams(
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{2, 4},
-                                       ov::element::f32,
-                                       std::vector<float>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2, 3},
-                                       ov::element::f32,
-                                       std::vector<float>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{2, 2, 3, 3},
-                                       ov::element::f32,
-                                       std::vector<float>{1.416667,
-                                                          1.75,
-                                                          2.083333,
-                                                          2.416667,
-                                                          2.75,
-                                                          3.083333,
-                                                          3.166667,
-                                                          3.5,
-                                                          3.833333,
-                                                          7.416667,
-                                                          7.75,
-                                                          8.083333,
-                                                          8.416667,
-                                                          8.75,
-                                                          9.083334,
-                                                          9.166666,
-                                                          9.5,
-                                                          9.833334,
-                                                          4.166667,
-                                                          4.5,
-                                                          4.833333,
-                                                          4.166667,
-                                                          4.5,
-                                                          4.833333,
-                                                          2.083333,
-                                                          2.25,
-                                                          2.416667,
-                                                          10.16667,
-                                                          10.5,
-                                                          10.83333,
-                                                          10.16667,
-                                                          10.5,
-                                                          10.83333,
-                                                          5.083333,
-                                                          5.25,
-                                                          5.416667}),
-                                reference_tests::Tensor(Shape{2, 4},
-                                       ov::element::f32,
-                                       std::vector<float>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0})},
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(Shape{2, 4},
+                                        ov::element::f32,
+                                        std::vector<float>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0}),
+                reference_tests::Tensor(
+                    Shape{1, 2, 2, 3},
+                    ov::element::f32,
+                    std::vector<float>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0})},
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(
+                    Shape{2, 2, 3, 3},
+                    ov::element::f32,
+                    std::vector<float>{1.416667, 1.75, 2.083333, 2.416667, 2.75, 3.083333, 3.166667, 3.5,  3.833333,
+                                       7.416667, 7.75, 8.083333, 8.416667, 8.75, 9.083334, 9.166666, 9.5,  9.833334,
+                                       4.166667, 4.5,  4.833333, 4.166667, 4.5,  4.833333, 2.083333, 2.25, 2.416667,
+                                       10.16667, 10.5, 10.83333, 10.16667, 10.5, 10.83333, 5.083333, 5.25, 5.416667}),
+                reference_tests::Tensor(Shape{2, 4},
+                                        ov::element::f32,
+                                        std::vector<float>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0})},
             "experimental_detectron_roi_feature_eval_f32"),
         ExperimentalROIParams(
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{2, 4},
-                                       ov::element::f16,
-                                       std::vector<ov::float16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2, 3},
-                                       ov::element::f16,
-                                       std::vector<ov::float16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{2, 2, 3, 3},
-                                       ov::element::f16,
-                                       std::vector<ov::float16>{1.416667,
-                                                                    1.75,
-                                                                    2.083333,
-                                                                    2.416667,
-                                                                    2.75,
-                                                                    3.083333,
-                                                                    3.166667,
-                                                                    3.5,
-                                                                    3.833333,
-                                                                    7.416667,
-                                                                    7.75,
-                                                                    8.083333,
-                                                                    8.416667,
-                                                                    8.75,
-                                                                    9.083334,
-                                                                    9.166666,
-                                                                    9.5,
-                                                                    9.833334,
-                                                                    4.166667,
-                                                                    4.5,
-                                                                    4.833333,
-                                                                    4.166667,
-                                                                    4.5,
-                                                                    4.833333,
-                                                                    2.083333,
-                                                                    2.25,
-                                                                    2.416667,
-                                                                    10.16667,
-                                                                    10.5,
-                                                                    10.83333,
-                                                                    10.16667,
-                                                                    10.5,
-                                                                    10.83333,
-                                                                    5.083333,
-                                                                    5.25,
-                                                                    5.416667}),
-                                reference_tests::Tensor(Shape{2, 4},
-                                       ov::element::f16,
-                                       std::vector<ov::float16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0})},
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(Shape{2, 4},
+                                        ov::element::f16,
+                                        std::vector<ov::float16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0}),
+                reference_tests::Tensor(
+                    Shape{1, 2, 2, 3},
+                    ov::element::f16,
+                    std::vector<ov::float16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0})},
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(Shape{2, 2, 3, 3},
+                                        ov::element::f16,
+                                        std::vector<ov::float16>{1.416667, 1.75, 2.083333, 2.416667, 2.75, 3.083333,
+                                                                 3.166667, 3.5,  3.833333, 7.416667, 7.75, 8.083333,
+                                                                 8.416667, 8.75, 9.083334, 9.166666, 9.5,  9.833334,
+                                                                 4.166667, 4.5,  4.833333, 4.166667, 4.5,  4.833333,
+                                                                 2.083333, 2.25, 2.416667, 10.16667, 10.5, 10.83333,
+                                                                 10.16667, 10.5, 10.83333, 5.083333, 5.25, 5.416667}),
+                reference_tests::Tensor(Shape{2, 4},
+                                        ov::element::f16,
+                                        std::vector<ov::float16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0})},
             "experimental_detectron_roi_feature_eval_f16"),
         ExperimentalROIParams(
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{2, 4},
-                                       ov::element::bf16,
-                                       std::vector<ov::bfloat16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2, 3},
-                                       ov::element::bf16,
-                                       std::vector<ov::bfloat16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{2, 2, 3, 3},
-                                       ov::element::bf16,
-                                       std::vector<ov::bfloat16>{1.416667,
-                                                                     1.75,
-                                                                     2.083333,
-                                                                     2.416667,
-                                                                     2.75,
-                                                                     3.083333,
-                                                                     3.166667,
-                                                                     3.5,
-                                                                     3.833333,
-                                                                     7.416667,
-                                                                     7.75,
-                                                                     8.083333,
-                                                                     8.416667,
-                                                                     8.75,
-                                                                     9.083334,
-                                                                     9.166666,
-                                                                     9.5,
-                                                                     9.833334,
-                                                                     4.166667,
-                                                                     4.5,
-                                                                     4.833333,
-                                                                     4.166667,
-                                                                     4.5,
-                                                                     4.833333,
-                                                                     2.083333,
-                                                                     2.25,
-                                                                     2.416667,
-                                                                     10.16667,
-                                                                     10.5,
-                                                                     10.83333,
-                                                                     10.16667,
-                                                                     10.5,
-                                                                     10.83333,
-                                                                     5.083333,
-                                                                     5.25,
-                                                                     5.416667}),
-                                reference_tests::Tensor(Shape{2, 4},
-                                       ov::element::bf16,
-                                       std::vector<ov::bfloat16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0})},
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(Shape{2, 4},
+                                        ov::element::bf16,
+                                        std::vector<ov::bfloat16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0}),
+                reference_tests::Tensor(
+                    Shape{1, 2, 2, 3},
+                    ov::element::bf16,
+                    std::vector<ov::bfloat16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0})},
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(Shape{2, 2, 3, 3},
+                                        ov::element::bf16,
+                                        std::vector<ov::bfloat16>{1.416667, 1.75, 2.083333, 2.416667, 2.75, 3.083333,
+                                                                  3.166667, 3.5,  3.833333, 7.416667, 7.75, 8.083333,
+                                                                  8.416667, 8.75, 9.083334, 9.166666, 9.5,  9.833334,
+                                                                  4.166667, 4.5,  4.833333, 4.166667, 4.5,  4.833333,
+                                                                  2.083333, 2.25, 2.416667, 10.16667, 10.5, 10.83333,
+                                                                  10.16667, 10.5, 10.83333, 5.083333, 5.25, 5.416667}),
+                reference_tests::Tensor(Shape{2, 4},
+                                        ov::element::bf16,
+                                        std::vector<ov::bfloat16>{0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0})},
             "experimental_detectron_roi_feature_eval_bf16")));
diff --git a/src/plugins/template/tests/functional/op_reference/experimental_detectron_topkrois.cpp b/src/plugins/template/tests/functional/op_reference/experimental_detectron_topkrois.cpp
index 0096a4bf212f68..d41d0983481b46 100644
--- a/src/plugins/template/tests/functional/op_reference/experimental_detectron_topkrois.cpp
+++ b/src/plugins/template/tests/functional/op_reference/experimental_detectron_topkrois.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/experimental_detectron_topkrois.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/experimental_detectron_topkrois.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,11 +13,16 @@ using namespace ov;
 
 namespace {
 struct ExperimentalDetectronTopKROIsParams {
-    ExperimentalDetectronTopKROIsParams(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& probsTensor, const int32_t numRois,
-        const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), probsTensor(probsTensor), numRois(numRois),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    ExperimentalDetectronTopKROIsParams(const reference_tests::Tensor& dataTensor,
+                                        const reference_tests::Tensor& probsTensor,
+                                        const int32_t numRois,
+                                        const reference_tests::Tensor& expectedTensor,
+                                        const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          probsTensor(probsTensor),
+          numRois(numRois),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor probsTensor;
@@ -25,7 +31,8 @@ struct ExperimentalDetectronTopKROIsParams {
     std::string testcaseName;
 };
 
-class ReferenceExperimentalDetectronTopKROIsTest : public testing::TestWithParam<ExperimentalDetectronTopKROIsParams>, public CommonReferenceTest {
+class ReferenceExperimentalDetectronTopKROIsTest : public testing::TestWithParam<ExperimentalDetectronTopKROIsParams>,
+                                                   public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -70,7 +77,7 @@ TEST_P(ReferenceExperimentalDetectronTopKROIsTest, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ExperimentalDetectronTopKROIsParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ExperimentalDetectronTopKROIsParams> params {
+    std::vector<ExperimentalDetectronTopKROIsParams> params{
         ExperimentalDetectronTopKROIsParams(
             reference_tests::Tensor(ET, {2, 4}, std::vector<T>{1.0f, 1.0f, 3.0f, 4.0f, 2.0f, 1.0f, 5.0f, 7.0f}),
             reference_tests::Tensor(ET, {2}, std::vector<T>{0.5f, 0.3f}),
@@ -78,8 +85,24 @@ std::vector<ExperimentalDetectronTopKROIsParams> generateParams() {
             reference_tests::Tensor(ET, {1, 4}, std::vector<T>{1.0, 1.0, 3.0, 4.0}),
             "experimental_detectron_topk_rois_eval"),
         ExperimentalDetectronTopKROIsParams(
-            reference_tests::Tensor(ET, {4, 4}, std::vector<T>{1.0f,  1.0f,  4.0f,  5.0f,  3.0f,  2.0f,  7.0f,  9.0f,
-                                              10.0f, 15.0f, 13.0f, 17.0f, 13.0f, 10.0f, 18.0f, 15.0f}),
+            reference_tests::Tensor(ET,
+                                    {4, 4},
+                                    std::vector<T>{1.0f,
+                                                   1.0f,
+                                                   4.0f,
+                                                   5.0f,
+                                                   3.0f,
+                                                   2.0f,
+                                                   7.0f,
+                                                   9.0f,
+                                                   10.0f,
+                                                   15.0f,
+                                                   13.0f,
+                                                   17.0f,
+                                                   13.0f,
+                                                   10.0f,
+                                                   18.0f,
+                                                   15.0f}),
             reference_tests::Tensor(ET, {4}, std::vector<T>{0.1f, 0.7f, 0.5f, 0.9f}),
             2,
             reference_tests::Tensor(ET, {2, 4}, std::vector<T>{13.0f, 10.0f, 18.0f, 15.0f, 3.0f, 2.0f, 7.0f, 9.0f}),
@@ -89,7 +112,7 @@ std::vector<ExperimentalDetectronTopKROIsParams> generateParams() {
 }
 
 std::vector<ExperimentalDetectronTopKROIsParams> generateCombinedParams() {
-    const std::vector<std::vector<ExperimentalDetectronTopKROIsParams>> generatedParams {
+    const std::vector<std::vector<ExperimentalDetectronTopKROIsParams>> generatedParams{
         generateParams<element::Type_t::bf16>(),
         generateParams<element::Type_t::f16>(),
         generateParams<element::Type_t::f32>(),
@@ -103,6 +126,8 @@ std::vector<ExperimentalDetectronTopKROIsParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ExperimentalDetectronTopKROIs_With_Hardcoded_Refs, ReferenceExperimentalDetectronTopKROIsTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceExperimentalDetectronTopKROIsTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_ExperimentalDetectronTopKROIs_With_Hardcoded_Refs,
+                         ReferenceExperimentalDetectronTopKROIsTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceExperimentalDetectronTopKROIsTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/extract_image_patches.cpp b/src/plugins/template/tests/functional/op_reference/extract_image_patches.cpp
index 49f24595eb58e6..62fc41dbea9b2c 100644
--- a/src/plugins/template/tests/functional/op_reference/extract_image_patches.cpp
+++ b/src/plugins/template/tests/functional/op_reference/extract_image_patches.cpp
@@ -4,9 +4,9 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset3.hpp"
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
+#include "openvino/opsets/opset3.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -32,7 +32,8 @@ struct Builder : ParamsBuilder<ExtractImagePatchesParams> {
     REFERENCE_TESTS_ADD_SET_PARAM(Builder, testcaseName);
 };
 
-class ReferenceExtractImagePatchesTest : public testing::TestWithParam<ExtractImagePatchesParams>, public CommonReferenceTest {
+class ReferenceExtractImagePatchesTest : public testing::TestWithParam<ExtractImagePatchesParams>,
+                                         public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -78,148 +79,89 @@ TEST_P(ReferenceExtractImagePatchesTest, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<ExtractImagePatchesParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<ExtractImagePatchesParams> params {
-        Builder {}
-            .data({ET, {1, 1, 10, 10}, std::vector<T>{
-                1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
-                11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
-                21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
-                31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
-                41, 42, 43, 44, 45, 46, 47, 48, 49, 50,
-                51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
-                61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
-                71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
-                81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
-                91, 92, 93, 94, 95, 96, 97, 98, 99, 100}})
+    std::vector<ExtractImagePatchesParams> params{
+        Builder{}
+            .data({ET,
+                   {1, 1, 10, 10},
+                   std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
+                                  21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
+                                  41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
+                                  61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
+                                  81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100}})
             .sizes({3, 3})
             .strides({5, 5})
             .rates({1, 1})
             .autoPad(op::PadType::VALID)
-            .expectedResult({ET, {1, 9, 2, 2}, std::vector<T>{
-                1,  6,  51, 56,
-                2,  7,  52, 57,
-                3,  8,  53, 58,
-                11, 16, 61, 66,
-                12, 17, 62, 67,
-                13, 18, 63, 68,
-                21, 26, 71, 76,
-                22, 27, 72, 77,
-                23, 28, 73, 78}}),
-
-        Builder {}
-            .data({ET, {1, 1, 10, 10}, std::vector<T>{
-                1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
-                11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
-                21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
-                31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
-                41, 42, 43, 44, 45, 46, 47, 48, 49, 50,
-                51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
-                61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
-                71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
-                81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
-                91, 92, 93, 94, 95, 96, 97, 98, 99, 100}})
+            .expectedResult({ET, {1, 9, 2, 2}, std::vector<T>{1,  6,  51, 56, 2,  7,  52, 57, 3,  8,  53, 58,
+                                                              11, 16, 61, 66, 12, 17, 62, 67, 13, 18, 63, 68,
+                                                              21, 26, 71, 76, 22, 27, 72, 77, 23, 28, 73, 78}}),
+
+        Builder{}
+            .data({ET,
+                   {1, 1, 10, 10},
+                   std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
+                                  21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
+                                  41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
+                                  61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
+                                  81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100}})
             .sizes({4, 4})
             .strides({8, 8})
             .rates({1, 1})
             .autoPad(op::PadType::VALID)
-            .expectedResult({ET, {1, 16, 1, 1}, std::vector<T>{
-                1,  2,  3,  4,
-                11, 12, 13, 14,
-                21, 22, 23, 24,
-                31, 32, 33, 34}}),
-
-        Builder {}
-            .data({ET, {1, 1, 10, 10}, std::vector<T>{
-                1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
-                11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
-                21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
-                31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
-                41, 42, 43, 44, 45, 46, 47, 48, 49, 50,
-                51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
-                61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
-                71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
-                81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
-                91, 92, 93, 94, 95, 96, 97, 98, 99, 100}})
+            .expectedResult(
+                {ET, {1, 16, 1, 1}, std::vector<T>{1, 2, 3, 4, 11, 12, 13, 14, 21, 22, 23, 24, 31, 32, 33, 34}}),
+
+        Builder{}
+            .data({ET,
+                   {1, 1, 10, 10},
+                   std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
+                                  21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
+                                  41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
+                                  61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
+                                  81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100}})
             .sizes({4, 4})
             .strides({9, 9})
             .rates({1, 1})
             .autoPad(op::PadType::SAME_UPPER)
-            .expectedResult({ET, {1, 16, 2, 2}, std::vector<T>{
-                0,  0,  0,  89,
-                0,  0,  81, 90,
-                0,  0,  82, 0,
-                0,  0,  83, 0,
-                0,  9,  0,  99,
-                1,  10, 91, 100,
-                2,  0,  92, 0,
-                3,  0,  93, 0,
-                0,  19, 0,  0,
-                11, 20, 0,  0,
-                12, 0,  0,  0,
-                13, 0,  0,  0,
-                0,  29, 0,  0,
-                21, 30, 0,  0,
-                22, 0,  0,  0,
-                23, 0,  0,  0}}),
-
-        Builder {}
-            .data({ET, {1, 1, 10, 10}, std::vector<T>{
-                1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
-                11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
-                21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
-                31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
-                41, 42, 43, 44, 45, 46, 47, 48, 49, 50,
-                51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
-                61, 62, 63, 64, 65, 66, 67, 68, 69, 70,
-                71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
-                81, 82, 83, 84, 85, 86, 87, 88, 89, 90,
-                91, 92, 93, 94, 95, 96, 97, 98, 99, 100}})
+            .expectedResult(
+                {ET, {1, 16, 2, 2}, std::vector<T>{0, 0,  0, 89, 0,  0,  81, 90,  0,  0, 82, 0, 0,  0, 83, 0,
+                                                   0, 9,  0, 99, 1,  10, 91, 100, 2,  0, 92, 0, 3,  0, 93, 0,
+                                                   0, 19, 0, 0,  11, 20, 0,  0,   12, 0, 0,  0, 13, 0, 0,  0,
+                                                   0, 29, 0, 0,  21, 30, 0,  0,   22, 0, 0,  0, 23, 0, 0,  0}}),
+
+        Builder{}
+            .data({ET,
+                   {1, 1, 10, 10},
+                   std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
+                                  21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40,
+                                  41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60,
+                                  61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
+                                  81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100}})
             .sizes({3, 3})
             .strides({5, 5})
             .rates({2, 2})
             .autoPad(op::PadType::VALID)
-            .expectedResult({ET, {1, 9, 2, 2}, std::vector<T>{
-                1,  6,  51, 56,
-                3,  8,  53, 58,
-                5,  10, 55, 60,
-                21, 26, 71, 76,
-                23, 28, 73, 78,
-                25, 30, 75, 80,
-                41, 46, 91, 96,
-                43, 48, 93, 98,
-                45, 50, 95, 100}}),
-
-        Builder {}
-            .data({ET, {1, 2, 5, 5}, std::vector<T>{
-                1,  2,  3,  4,  5,
-                6,  7,  8,  9,  10,
-                11, 12, 13, 14, 15,
-                16, 17, 18, 19, 20,
-                21, 22, 23, 24, 25,
-                26, 27, 28, 29, 30,
-                31, 32, 33, 34, 35,
-                36, 37, 38, 39, 40,
-                41, 42, 43, 44, 45,
-                46, 47, 48, 49, 50}})
+            .expectedResult({ET, {1, 9, 2, 2}, std::vector<T>{1,  6,  51, 56, 3,  8,  53, 58, 5,  10, 55, 60,
+                                                              21, 26, 71, 76, 23, 28, 73, 78, 25, 30, 75, 80,
+                                                              41, 46, 91, 96, 43, 48, 93, 98, 45, 50, 95, 100}}),
+
+        Builder{}
+            .data({ET, {1, 2, 5, 5}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17,
+                                                    18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34,
+                                                    35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50}})
             .sizes({2, 2})
             .strides({3, 3})
             .rates({1, 1})
             .autoPad(op::PadType::VALID)
-            .expectedResult({ET, {1, 8, 2, 2}, std::vector<T>{
-                1,  4,  16, 19,
-                26, 29, 41, 44,
-                2,  5,  17, 20,
-                27, 30, 42, 45,
-                6,  9,  21, 24,
-                31, 34, 46, 49,
-                7,  10, 22, 25,
-                32, 35, 47, 50}}),
+            .expectedResult(
+                {ET, {1, 8, 2, 2}, std::vector<T>{1, 4, 16, 19, 26, 29, 41, 44, 2, 5,  17, 20, 27, 30, 42, 45,
+                                                  6, 9, 21, 24, 31, 34, 46, 49, 7, 10, 22, 25, 32, 35, 47, 50}}),
     };
     return params;
 }
 
 std::vector<ExtractImagePatchesParams> generateCombinedParams() {
-    const std::vector<std::vector<ExtractImagePatchesParams>> generatedParams {
+    const std::vector<std::vector<ExtractImagePatchesParams>> generatedParams{
         generateParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
         generateParams<element::Type_t::i32>(),
@@ -241,6 +183,8 @@ std::vector<ExtractImagePatchesParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ExtractImagePatches_With_Hardcoded_Refs, ReferenceExtractImagePatchesTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceExtractImagePatchesTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_ExtractImagePatches_With_Hardcoded_Refs,
+                         ReferenceExtractImagePatchesTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceExtractImagePatchesTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/eye.cpp b/src/plugins/template/tests/functional/op_reference/eye.cpp
index 23037edaebcb40..714dbdee8e61b4 100644
--- a/src/plugins/template/tests/functional/op_reference/eye.cpp
+++ b/src/plugins/template/tests/functional/op_reference/eye.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/eye.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/eye.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -20,13 +22,13 @@ struct EyeParams {
               const reference_tests::Tensor& expected_tensor,
               const std::string& test_case_name,
               bool is_dyn_shape_test = false)
-              : num_rows(num_rows),
-              num_columns(num_columns),
-              diagonal_index(diagonal_index),
-              output_type(output_type),
-              expected_tensor(expected_tensor),
-              test_case_name(test_case_name),
-              set_dynamic_shape(is_dyn_shape_test) {}
+        : num_rows(num_rows),
+          num_columns(num_columns),
+          diagonal_index(diagonal_index),
+          output_type(output_type),
+          expected_tensor(expected_tensor),
+          test_case_name(test_case_name),
+          set_dynamic_shape(is_dyn_shape_test) {}
 
     reference_tests::Tensor num_rows;
     reference_tests::Tensor num_columns;
@@ -46,14 +48,14 @@ struct EyeBatchShapeParams {
                         const reference_tests::Tensor& expected_tensor,
                         const std::string& test_case_name,
                         bool is_dyn_shape_test = false)
-                        : num_rows(num_rows),
-                        num_columns(num_columns),
-                        diagonal_index(diagonal_index),
-                        batch_shape(batch_shape),
-                        output_type(output_type),
-                        expected_tensor(expected_tensor),
-                        test_case_name(test_case_name),
-                        set_dynamic_shape(is_dyn_shape_test) {}
+        : num_rows(num_rows),
+          num_columns(num_columns),
+          diagonal_index(diagonal_index),
+          batch_shape(batch_shape),
+          output_type(output_type),
+          expected_tensor(expected_tensor),
+          test_case_name(test_case_name),
+          set_dynamic_shape(is_dyn_shape_test) {}
 
     reference_tests::Tensor num_rows;
     reference_tests::Tensor num_columns;
@@ -88,9 +90,15 @@ class ReferenceEyeLayerTest : public testing::TestWithParam<EyeParams>, public C
                                                  const reference_tests::Tensor& diagonal_index,
                                                  const element::Type& output_type,
                                                  bool set_dynamic_shape = false) {
-        const auto in1 = std::make_shared<op::v0::Parameter>(num_rows.type, set_dynamic_shape ? PartialShape::dynamic() : num_rows.shape);
-        const auto in2 = std::make_shared<op::v0::Parameter>(num_columns.type, set_dynamic_shape ? PartialShape::dynamic() : num_columns.shape);
-        const auto in3 = std::make_shared<op::v0::Parameter>(diagonal_index.type, set_dynamic_shape ? PartialShape::dynamic() : diagonal_index.shape);
+        const auto in1 =
+            std::make_shared<op::v0::Parameter>(num_rows.type,
+                                                set_dynamic_shape ? PartialShape::dynamic() : num_rows.shape);
+        const auto in2 =
+            std::make_shared<op::v0::Parameter>(num_columns.type,
+                                                set_dynamic_shape ? PartialShape::dynamic() : num_columns.shape);
+        const auto in3 =
+            std::make_shared<op::v0::Parameter>(diagonal_index.type,
+                                                set_dynamic_shape ? PartialShape::dynamic() : diagonal_index.shape);
         const auto Eye = std::make_shared<op::v9::Eye>(in1, in2, in3, output_type);
         return std::make_shared<Model>(NodeVector{Eye}, ParameterVector{in1, in2, in3});
     }
@@ -106,7 +114,10 @@ class ReferenceEyeBatchShapeLayerTest : public testing::TestWithParam<EyeBatchSh
                                   params.batch_shape,
                                   params.output_type,
                                   params.set_dynamic_shape);
-        inputData = {params.num_rows.data, params.num_columns.data, params.diagonal_index.data, params.batch_shape.data};
+        inputData = {params.num_rows.data,
+                     params.num_columns.data,
+                     params.diagonal_index.data,
+                     params.batch_shape.data};
         refOutData = {params.expected_tensor.data};
     }
 
@@ -121,252 +132,213 @@ class ReferenceEyeBatchShapeLayerTest : public testing::TestWithParam<EyeBatchSh
                                                  const reference_tests::Tensor& batch_shape,
                                                  const element::Type& output_type,
                                                  bool set_dynamic_shape = false) {
-        const auto in1 = std::make_shared<op::v0::Parameter>(num_rows.type, set_dynamic_shape ? PartialShape::dynamic() : num_rows.shape);
-        const auto in2 = std::make_shared<op::v0::Parameter>(num_columns.type, set_dynamic_shape ? PartialShape::dynamic() : num_columns.shape);
-        const auto in3 = std::make_shared<op::v0::Parameter>(diagonal_index.type, set_dynamic_shape ? PartialShape::dynamic() : diagonal_index.shape);
-        const auto in4 = std::make_shared<op::v0::Parameter>(batch_shape.type, set_dynamic_shape ? PartialShape::dynamic() : batch_shape.shape);
+        const auto in1 =
+            std::make_shared<op::v0::Parameter>(num_rows.type,
+                                                set_dynamic_shape ? PartialShape::dynamic() : num_rows.shape);
+        const auto in2 =
+            std::make_shared<op::v0::Parameter>(num_columns.type,
+                                                set_dynamic_shape ? PartialShape::dynamic() : num_columns.shape);
+        const auto in3 =
+            std::make_shared<op::v0::Parameter>(diagonal_index.type,
+                                                set_dynamic_shape ? PartialShape::dynamic() : diagonal_index.shape);
+        const auto in4 =
+            std::make_shared<op::v0::Parameter>(batch_shape.type,
+                                                set_dynamic_shape ? PartialShape::dynamic() : batch_shape.shape);
         const auto Eye = std::make_shared<op::v9::Eye>(in1, in2, in3, in4, output_type);
         return std::make_shared<Model>(NodeVector{Eye}, ParameterVector{in1, in2, in3, in4});
     }
 };
 
 std::vector<EyeParams> generateEyeParams(bool is_dyn_shape_test = false) {
-    std::vector<EyeParams> test_params {
+    std::vector<EyeParams> test_params{
         EyeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                    reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                    reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
-                    element::Type_t::f32,
-                    reference_tests::Tensor{{3, 2}, element::f32, std::vector<float>{1, 0,
-                                                                                    0, 1,
-                                                                                    0, 0}},
-                    "float32_default_3x2", is_dyn_shape_test),
+                  reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+                  reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
+                  element::Type_t::f32,
+                  reference_tests::Tensor{{3, 2}, element::f32, std::vector<float>{1, 0, 0, 1, 0, 0}},
+                  "float32_default_3x2",
+                  is_dyn_shape_test),
         EyeParams(reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{2}},
-                    reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{4}},
-                    reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{2}},
-                    element::Type_t::i8,
-                    reference_tests::Tensor{{2, 4}, element::i8, std::vector<int8_t>{0, 0, 1, 0,
-                                                                                    0, 0, 0, 1}},
-                    "int8_diag=2_2x4", is_dyn_shape_test),
+                  reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{4}},
+                  reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{2}},
+                  element::Type_t::i8,
+                  reference_tests::Tensor{{2, 4}, element::i8, std::vector<int8_t>{0, 0, 1, 0, 0, 0, 0, 1}},
+                  "int8_diag=2_2x4",
+                  is_dyn_shape_test),
         EyeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                    reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                    reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{-3}},
-                    element::Type_t::i64,
-                    reference_tests::Tensor{{4, 2}, element::i64, std::vector<int64_t>{0, 0,
-                                                                                        0, 0,
-                                                                                        0, 0,
-                                                                                        1, 0}},
-                    "int64_diag=-3_4x2", is_dyn_shape_test),
+                  reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+                  reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{-3}},
+                  element::Type_t::i64,
+                  reference_tests::Tensor{{4, 2}, element::i64, std::vector<int64_t>{0, 0, 0, 0, 0, 0, 1, 0}},
+                  "int64_diag=-3_4x2",
+                  is_dyn_shape_test),
         EyeParams(reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{1}},
-                    reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{4}},
-                    reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{10}},
-                    element::Type_t::i8,
-                    reference_tests::Tensor{{1, 4}, element::i8, std::vector<int8_t>{0, 0, 0, 0}},
-                    "int8_empty_1x4", is_dyn_shape_test)};
+                  reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{4}},
+                  reference_tests::Tensor{{}, element::i32, std::vector<int32_t>{10}},
+                  element::Type_t::i8,
+                  reference_tests::Tensor{{1, 4}, element::i8, std::vector<int8_t>{0, 0, 0, 0}},
+                  "int8_empty_1x4",
+                  is_dyn_shape_test)};
     return test_params;
 }
 
 std::vector<EyeBatchShapeParams> generateEyeBatchShapeParams(bool is_dyn_shape_test = false) {
-    std::vector<EyeBatchShapeParams> test_params {
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::f32,
-                            reference_tests::Tensor{{2, 3, 3}, element::f32, std::vector<float>{1, 0, 0,
-                                                                                                0, 1, 0,
-                                                                                                0, 0, 1,
-                                                                                                1, 0, 0,
-                                                                                                0, 1, 0,
-                                                                                                0, 0, 1}},
-                            "f32_2x3x3_diag0", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::f32,
-                            reference_tests::Tensor{{2, 3, 3}, element::f32, std::vector<float>{1, 0, 0, 0,
-                                                                                                0, 1, 0, 0,
-                                                                                                0, 0, 1, 0,
-                                                                                                0, 0, 0, 1,
-                                                                                                1, 0, 0, 0,
-                                                                                                0, 1, 0, 0,
-                                                                                                0, 0, 1, 0,
-                                                                                                0, 0, 0, 1}},
-                            "f32_2x4x4_diag0", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::f32,
-                            reference_tests::Tensor{{2, 3, 4}, element::f32, std::vector<float>{1, 0, 0, 0,
-                                                                                                0, 1, 0, 0,
-                                                                                                0, 0, 1, 0,
-                                                                                                1, 0, 0, 0,
-                                                                                                0, 1, 0, 0,
-                                                                                                0, 0, 1, 0}},
-                            "f32_2x3x4_diag0", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::i8,
-                            reference_tests::Tensor{{2, 4, 3}, element::i8, std::vector<int8_t>{1, 0, 0,
-                                                                                                0, 1, 0,
-                                                                                                0, 0, 1,
-                                                                                                0, 0, 0,
-                                                                                                1, 0, 0,
-                                                                                                0, 1, 0,
-                                                                                                0, 0, 1,
-                                                                                                0, 0, 0}},
-                            "f32_2x4x3_diag0", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{1}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::f32,
-                            reference_tests::Tensor{{2, 3, 4}, element::f32, std::vector<float>{0, 1, 0, 0,
-                                                                                                0, 0, 1, 0,
-                                                                                                0, 0, 0, 1,
-                                                                                                0, 1, 0, 0,
-                                                                                                0, 0, 1, 0,
-                                                                                                0, 0, 0, 1}},
-                            "f32_2x3x4_diag1", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{1}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::f32,
-                            reference_tests::Tensor{{2, 4, 3}, element::f32, std::vector<float>{0, 1, 0,
-                                                                                                0, 0, 1,
-                                                                                                0, 0, 0,
-                                                                                                0, 0, 0,
-                                                                                                0, 1, 0,
-                                                                                                0, 0, 1,
-                                                                                                0, 0, 0,
-                                                                                                0, 0, 0}},
-                            "f32_2x4x3_diag1", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::i8,
-                            reference_tests::Tensor{{2, 3, 4}, element::i8, std::vector<int8_t>{0, 0, 1, 0,
-                                                                                                0, 0, 0, 1,
-                                                                                                0, 0, 0, 0,
-                                                                                                0, 0, 1, 0,
-                                                                                                0, 0, 0, 1,
-                                                                                                0, 0, 0, 0}},
-                            "i8_2x3x4_diag2", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::i8,
-                            reference_tests::Tensor{{2, 4, 3}, element::i8, std::vector<int8_t>{0, 0, 1,
-                                                                                                0, 0, 0,
-                                                                                                0, 0, 0,
-                                                                                                0, 0, 0,
-                                                                                                0, 0, 1,
-                                                                                                0, 0, 0,
-                                                                                                0, 0, 0,
-                                                                                                0, 0, 0}},
-                            "i8_2x4x3_diag2", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-1}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::i8,
-                            reference_tests::Tensor{{2, 3, 4}, element::i8, std::vector<int8_t>{0, 0, 0, 0,
-                                                                                                1, 0, 0, 0,
-                                                                                                0, 1, 0, 0,
-                                                                                                0, 0, 0, 0,
-                                                                                                1, 0, 0, 0,
-                                                                                                0, 1, 0, 0}},
-                            "i8_2x3x4_diag-1", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-1}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::i8,
-                            reference_tests::Tensor{{2, 4, 3}, element::i8, std::vector<int8_t>{0, 0, 0,
-                                                                                                1, 0, 0,
-                                                                                                0, 1, 0,
-                                                                                                0, 0, 1,
-                                                                                                0, 0, 0,
-                                                                                                1, 0, 0,
-                                                                                                0, 1, 0,
-                                                                                                0, 0, 1}},
-                            "i8_2x4x3_diag-1", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-2}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::i8,
-                            reference_tests::Tensor{{2, 3, 4}, element::i8, std::vector<int8_t>{0, 0, 0, 0,
-                                                                                                0, 0, 0, 0,
-                                                                                                1, 0, 0, 0,
-                                                                                                0, 0, 0, 0,
-                                                                                                0, 0, 0, 0,
-                                                                                                1, 0, 0, 0}},
-                            "i8_2x3x4_diag-2", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-2}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::i8,
-                            reference_tests::Tensor{{2, 4, 3}, element::i8, std::vector<int8_t>{0, 0, 0,
-                                                                                                0, 0, 0,
-                                                                                                1, 0, 0,
-                                                                                                0, 1, 0,
-                                                                                                0, 0, 0,
-                                                                                                0, 0, 0,
-                                                                                                1, 0, 0,
-                                                                                                0, 1, 0}},
-                            "i8_2x4x3_diag-2", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{6}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{5}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{1}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            element::Type_t::i32,
-                            reference_tests::Tensor{{2, 6, 5}, element::i32, std::vector<int32_t>{0, 1, 0, 0, 0,
-                                                                                                  0, 0, 1, 0, 0,
-                                                                                                  0, 0, 0, 1, 0,
-                                                                                                  0, 0, 0, 0, 1,
-                                                                                                  0, 0, 0, 0, 0,
-                                                                                                  0, 0, 0, 0, 0,
-                                                                                                  0, 1, 0, 0, 0,
-                                                                                                  0, 0, 1, 0, 0,
-                                                                                                  0, 0, 0, 1, 0,
-                                                                                                  0, 0, 0, 0, 1,
-                                                                                                  0, 0, 0, 0, 0,
-                                                                                                  0, 0, 0, 0, 0}},
-                            "int32_2x6x5_diag1", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            reference_tests::Tensor{{2}, element::i32, std::vector<int32_t>{2, 2}},
-                            element::Type_t::i64,
-                            reference_tests::Tensor{{2, 2, 4, 2}, element::i64, std::vector<int64_t>{0, 0, 1, 0,
-                                                                                                     0, 0, 0, 1,
-                                                                                                     0, 0, 1, 0,
-                                                                                                     0, 0, 0, 1,
-                                                                                                     0, 0, 1, 0,
-                                                                                                     0, 0, 0, 1,
-                                                                                                     0, 0, 1, 0,
-                                                                                                     0, 0, 0, 1}},
-                            "int64_2x2x3x3", is_dyn_shape_test),
-        EyeBatchShapeParams(reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
-                            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
-                            reference_tests::Tensor{{2}, element::i32, std::vector<int32_t>{1, 3}},
-                            element::Type_t::u8,
-                            reference_tests::Tensor{{2, 3, 3}, element::u8, std::vector<uint8_t>{0, 0,
-                                                                                                 0, 0,
-                                                                                                 0, 0,
-                                                                                                 0, 0,
-                                                                                                 0, 0,
-                                                                                                 0, 0}},
-                        "uint8_1x3x2x2", is_dyn_shape_test)};
+    std::vector<EyeBatchShapeParams> test_params{
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::f32,
+            reference_tests::Tensor{{2, 3, 3},
+                                    element::f32,
+                                    std::vector<float>{1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1}},
+            "f32_2x3x3_diag0",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::f32,
+            reference_tests::Tensor{{2, 3, 3}, element::f32, std::vector<float>{1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1,
+                                                                                0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1,
+                                                                                0, 0, 0, 0, 1, 0, 0, 0, 0, 1}},
+            "f32_2x4x4_diag0",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::f32,
+            reference_tests::Tensor{{2, 3, 4}, element::f32, std::vector<float>{1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0,
+                                                                                1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0}},
+            "f32_2x3x4_diag0",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{0}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::i8,
+            reference_tests::Tensor{{2, 4, 3}, element::i8, std::vector<int8_t>{1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0,
+                                                                                1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0}},
+            "f32_2x4x3_diag0",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{1}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::f32,
+            reference_tests::Tensor{{2, 3, 4}, element::f32, std::vector<float>{0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1,
+                                                                                0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1}},
+            "f32_2x3x4_diag1",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{1}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::f32,
+            reference_tests::Tensor{{2, 4, 3}, element::f32, std::vector<float>{0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
+                                                                                0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0}},
+            "f32_2x4x3_diag1",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::i8,
+            reference_tests::Tensor{{2, 3, 4}, element::i8, std::vector<int8_t>{0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0,
+                                                                                0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0}},
+            "i8_2x3x4_diag2",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::i8,
+            reference_tests::Tensor{{2, 4, 3}, element::i8, std::vector<int8_t>{0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                                                0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0}},
+            "i8_2x4x3_diag2",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-1}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::i8,
+            reference_tests::Tensor{{2, 3, 4}, element::i8, std::vector<int8_t>{0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0,
+                                                                                0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0}},
+            "i8_2x3x4_diag-1",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-1}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::i8,
+            reference_tests::Tensor{{2, 4, 3}, element::i8, std::vector<int8_t>{0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1,
+                                                                                0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1}},
+            "i8_2x4x3_diag-1",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-2}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::i8,
+            reference_tests::Tensor{{2, 3, 4}, element::i8, std::vector<int8_t>{0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,
+                                                                                0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0}},
+            "i8_2x3x4_diag-2",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-2}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::i8,
+            reference_tests::Tensor{{2, 4, 3}, element::i8, std::vector<int8_t>{0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0,
+                                                                                0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0}},
+            "i8_2x4x3_diag-2",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{6}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{5}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{1}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            element::Type_t::i32,
+            reference_tests::Tensor{{2, 6, 5},
+                                    element::i32,
+                                    std::vector<int32_t>{0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1,
+                                                         0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0,
+                                                         0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}},
+            "int32_2x6x5_diag1",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{4}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            reference_tests::Tensor{{2}, element::i32, std::vector<int32_t>{2, 2}},
+            element::Type_t::i64,
+            reference_tests::Tensor{{2, 2, 4, 2}, element::i64, std::vector<int64_t>{0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1,
+                                                                                     0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0,
+                                                                                     0, 1, 0, 0, 1, 0, 0, 0, 0, 1}},
+            "int64_2x2x3x3",
+            is_dyn_shape_test),
+        EyeBatchShapeParams(
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{2}},
+            reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{3}},
+            reference_tests::Tensor{{2}, element::i32, std::vector<int32_t>{1, 3}},
+            element::Type_t::u8,
+            reference_tests::Tensor{{2, 3, 3}, element::u8, std::vector<uint8_t>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}},
+            "uint8_1x3x2x2",
+            is_dyn_shape_test)};
     return test_params;
 }
 
@@ -394,18 +366,16 @@ TEST_P(ReferenceEyeBatchShapeLayerTest, EyeRectangleBatchShapeWithHardcodedRefs)
 
 }  // namespace
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_Eye_With_Hardcoded_Refs,
-        ReferenceEyeLayerTest,
-        // Generate params (3 inputs) with static and dynamic shapes
-        ::testing::ValuesIn(generateEyeCombinedParams()),
-        ReferenceEyeLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Eye_With_Hardcoded_Refs,
+                         ReferenceEyeLayerTest,
+                         // Generate params (3 inputs) with static and dynamic shapes
+                         ::testing::ValuesIn(generateEyeCombinedParams()),
+                         ReferenceEyeLayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_EyeBatchShape_With_Hardcoded_Refs,
-        ReferenceEyeBatchShapeLayerTest,
-        // Generate params (4 inputs) with static and dynamic shapes
-        ::testing::ValuesIn(generateEyeBatchShapeCombinedParams()),
-        ReferenceEyeBatchShapeLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_EyeBatchShape_With_Hardcoded_Refs,
+                         ReferenceEyeBatchShapeLayerTest,
+                         // Generate params (4 inputs) with static and dynamic shapes
+                         ::testing::ValuesIn(generateEyeBatchShapeCombinedParams()),
+                         ReferenceEyeBatchShapeLayerTest::getTestCaseName);
 
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/fake_quantize.cpp b/src/plugins/template/tests/functional/op_reference/fake_quantize.cpp
index 5f42a477da270f..418d02c23c5d08 100644
--- a/src/plugins/template/tests/functional/op_reference/fake_quantize.cpp
+++ b/src/plugins/template/tests/functional/op_reference/fake_quantize.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/fake_quantize.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/fake_quantize.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -16,17 +17,17 @@ namespace {
 struct FakeQuantizeParams {
     template <class IT>
     FakeQuantizeParams(const Shape& input_shape,
-                const Shape& expected_shape,
-                const element::Type& input_type,
-                const element::Type& expected_type,
-                const std::vector<IT>& input_data,
-                const std::vector<IT>& expected_data,
-                const std::shared_ptr<op::v0::Constant>& input_low,
-                const std::shared_ptr<op::v0::Constant>& input_high,
-                const std::shared_ptr<op::v0::Constant>& output_low,
-                const std::shared_ptr<op::v0::Constant>& output_high,
-                const std::size_t& levels,
-                const op::AutoBroadcastSpec& broadcast = op::AutoBroadcastType::NONE)
+                       const Shape& expected_shape,
+                       const element::Type& input_type,
+                       const element::Type& expected_type,
+                       const std::vector<IT>& input_data,
+                       const std::vector<IT>& expected_data,
+                       const std::shared_ptr<op::v0::Constant>& input_low,
+                       const std::shared_ptr<op::v0::Constant>& input_high,
+                       const std::shared_ptr<op::v0::Constant>& output_low,
+                       const std::shared_ptr<op::v0::Constant>& output_high,
+                       const std::size_t& levels,
+                       const op::AutoBroadcastSpec& broadcast = op::AutoBroadcastType::NONE)
         : m_input_shape(input_shape),
           m_expected_shape(expected_shape),
           m_input_type(input_type),
@@ -90,24 +91,26 @@ class ReferenceFakeQuantizeLayerTest : public testing::TestWithParam<FakeQuantiz
 
 private:
     static std::shared_ptr<Model> CreateFunction(const Shape& input_shape,
-                                                    const Shape& expected_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_type,
-                                                    const std::shared_ptr<op::v0::Constant>& input_low,
-                                                    const std::shared_ptr<op::v0::Constant>& input_high,
-                                                    const std::shared_ptr<op::v0::Constant>& output_low,
-                                                    const std::shared_ptr<op::v0::Constant>& output_high,
-                                                    const std::size_t& levels,
-                                                    const op::AutoBroadcastSpec& broadcast) {
+                                                 const Shape& expected_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_type,
+                                                 const std::shared_ptr<op::v0::Constant>& input_low,
+                                                 const std::shared_ptr<op::v0::Constant>& input_high,
+                                                 const std::shared_ptr<op::v0::Constant>& output_low,
+                                                 const std::shared_ptr<op::v0::Constant>& output_high,
+                                                 const std::size_t& levels,
+                                                 const op::AutoBroadcastSpec& broadcast) {
         auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         if (broadcast == op::AutoBroadcastType::NONE) {
             return std::make_shared<Model>(
-                NodeVector{std::make_shared<op::v0::FakeQuantize>(in, input_low, input_high, output_low, output_high, levels)},
+                NodeVector{
+                    std::make_shared<op::v0::FakeQuantize>(in, input_low, input_high, output_low, output_high, levels)},
                 ParameterVector{in});
 
         } else {
             return std::make_shared<Model>(
-                NodeVector{std::make_shared<op::v0::FakeQuantize>(in, input_low, input_high, output_low, output_high, levels, broadcast)},
+                NodeVector{std::make_shared<
+                    op::v0::FakeQuantize>(in, input_low, input_high, output_low, output_high, levels, broadcast)},
                 ParameterVector{in});
         }
     }
@@ -128,21 +131,22 @@ template <element::Type_t IN_ET>
 std::vector<FakeQuantizeParams> generateParamsForFakeQuantize() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<FakeQuantizeParams> params {
-        FakeQuantizeParams(ov::Shape{1, 2, 3, 4},
-                           ov::Shape{1, 2, 3, 4},
-                           IN_ET,
-                           IN_ET,
-                           iota_vector<T>(shape_size(ov::Shape{1, 2, 3, 4})),
-                           std::vector<T>{2.f,          2.f,          2.f,          2.f,          6.6666669f,   6.6666669f,
-                                          6.6666669f,   6.6666669f,   6.6666669f,   6.6666669f,   6.6666669f,   6.6666669f,
-                                          11.33333301f, 11.33333301f, 11.33333301f, 11.33333301f, 11.33333301f, 11.33333301f,
-                                          11.33333301f, 11.33333301f, 16.f,         16.f,         16.f,         16.f},
-                           op::v0::Constant::create(IN_ET, Shape{}, {0.f}),
-                           op::v0::Constant::create(IN_ET, Shape{}, {23.f}),
-                           op::v0::Constant::create(IN_ET, Shape{}, {2.f}),
-                           op::v0::Constant::create(IN_ET, Shape{}, {16.f}),
-                           4),
+    std::vector<FakeQuantizeParams> params{
+        FakeQuantizeParams(
+            ov::Shape{1, 2, 3, 4},
+            ov::Shape{1, 2, 3, 4},
+            IN_ET,
+            IN_ET,
+            iota_vector<T>(shape_size(ov::Shape{1, 2, 3, 4})),
+            std::vector<T>{2.f,          2.f,          2.f,          2.f,          6.6666669f,   6.6666669f,
+                           6.6666669f,   6.6666669f,   6.6666669f,   6.6666669f,   6.6666669f,   6.6666669f,
+                           11.33333301f, 11.33333301f, 11.33333301f, 11.33333301f, 11.33333301f, 11.33333301f,
+                           11.33333301f, 11.33333301f, 16.f,         16.f,         16.f,         16.f},
+            op::v0::Constant::create(IN_ET, Shape{}, {0.f}),
+            op::v0::Constant::create(IN_ET, Shape{}, {23.f}),
+            op::v0::Constant::create(IN_ET, Shape{}, {2.f}),
+            op::v0::Constant::create(IN_ET, Shape{}, {16.f}),
+            4),
         FakeQuantizeParams(ov::Shape{1, 2, 3, 4},
                            ov::Shape{1, 2, 3, 4},
                            IN_ET,
@@ -155,61 +159,98 @@ std::vector<FakeQuantizeParams> generateParamsForFakeQuantize() {
                            op::v0::Constant::create(IN_ET, Shape{}, {2.f}),
                            op::v0::Constant::create(IN_ET, Shape{}, {16.f}),
                            5),
-        FakeQuantizeParams(ov::Shape{1, 2, 5, 5},
-                           ov::Shape{1, 2, 5, 5},
-                           IN_ET,
-                           IN_ET,
-                           iota_vector<T>(shape_size(Shape{1, 2, 5, 5})),
-                           std::vector<T>{0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  5.0f,  10.0f, 10.0f, 15.0f, 20.0f, 20.0f, 20.0f,
-                                          20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 50.0f,
-                                          50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 55.0f, 55.0f, 60.0f, 60.0f, 60.0f, 65.0f, 65.0f,
-                                          70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f},
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {5.f, 30.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {10.f, 40.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {0.f, 50.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {20.f, 70.f}),
-                           5),
-        FakeQuantizeParams(ov::Shape{1, 2, 5, 5},
-                           ov::Shape{1, 2, 5, 5},
-                           IN_ET,
-                           IN_ET,
-                           iota_vector<T>(shape_size(Shape{1, 2, 5, 5})),
-                           std::vector<T>{0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  5.0f,  10.0f, 10.0f, 15.0f, 20.0f, 20.0f, 20.0f,
-                                          20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 50.0f,
-                                          50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 55.0f, 55.0f, 60.0f, 60.0f, 60.0f, 65.0f, 65.0f,
-                                          70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f},
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {5.f, 30.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {10.f, 40.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {0.f, 50.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {20.f, 70.f}),
-                           5,
-                           op::AutoBroadcastSpec(op::AutoBroadcastType::PDPD, 1)),
-        FakeQuantizeParams(ov::Shape{1, 2, 5, 5},
-                           ov::Shape{1, 2, 5, 5},
-                           IN_ET,
-                           IN_ET,
-                           iota_vector<T>(shape_size(Shape{1, 2, 5, 5})),
-                           std::vector<T>{0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  5.0f,  10.0f, 10.0f, 15.0f, 20.0f, 20.0f, 20.0f,
-                                          20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 50.0f,
-                                          50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 55.0f, 55.0f, 60.0f, 60.0f, 60.0f, 65.0f, 65.0f,
-                                          70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f},
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {5.f, 30.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {10.f, 40.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {0.f, 50.f}),
-                           op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {20.f, 70.f}),
-                           5,
-                           op::AutoBroadcastSpec(op::AutoBroadcastType::PDPD, -1)),
+        FakeQuantizeParams(
+            ov::Shape{1, 2, 5, 5},
+            ov::Shape{1, 2, 5, 5},
+            IN_ET,
+            IN_ET,
+            iota_vector<T>(shape_size(Shape{1, 2, 5, 5})),
+            std::vector<T>{0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  5.0f,  10.0f, 10.0f, 15.0f, 20.0f, 20.0f, 20.0f,
+                           20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 50.0f,
+                           50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 55.0f, 55.0f, 60.0f, 60.0f, 60.0f, 65.0f, 65.0f,
+                           70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f},
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {5.f, 30.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {10.f, 40.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {0.f, 50.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {20.f, 70.f}),
+            5),
+        FakeQuantizeParams(
+            ov::Shape{1, 2, 5, 5},
+            ov::Shape{1, 2, 5, 5},
+            IN_ET,
+            IN_ET,
+            iota_vector<T>(shape_size(Shape{1, 2, 5, 5})),
+            std::vector<T>{0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  5.0f,  10.0f, 10.0f, 15.0f, 20.0f, 20.0f, 20.0f,
+                           20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 50.0f,
+                           50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 55.0f, 55.0f, 60.0f, 60.0f, 60.0f, 65.0f, 65.0f,
+                           70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f},
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {5.f, 30.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {10.f, 40.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {0.f, 50.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {20.f, 70.f}),
+            5,
+            op::AutoBroadcastSpec(op::AutoBroadcastType::PDPD, 1)),
+        FakeQuantizeParams(
+            ov::Shape{1, 2, 5, 5},
+            ov::Shape{1, 2, 5, 5},
+            IN_ET,
+            IN_ET,
+            iota_vector<T>(shape_size(Shape{1, 2, 5, 5})),
+            std::vector<T>{0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  0.0f,  5.0f,  10.0f, 10.0f, 15.0f, 20.0f, 20.0f, 20.0f,
+                           20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 20.0f, 50.0f,
+                           50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 50.0f, 55.0f, 55.0f, 60.0f, 60.0f, 60.0f, 65.0f, 65.0f,
+                           70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f, 70.0f},
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {5.f, 30.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {10.f, 40.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {0.f, 50.f}),
+            op::v0::Constant::create(IN_ET, Shape{2, 1, 1}, {20.f, 70.f}),
+            5,
+            op::AutoBroadcastSpec(op::AutoBroadcastType::PDPD, -1)),
         FakeQuantizeParams(ov::Shape{1, 2, 3, 3},
                            ov::Shape{1, 2, 3, 3},
                            IN_ET,
                            IN_ET,
                            iota_vector<T>(shape_size(Shape{1, 2, 3, 3})),
-                           std::vector<T>{5.0f, 9.0f, 13.0f, 17.0f, 21.0f, 25.0f, 25.0f, 25.0f, 25.0f,
-                                          25.0f, 25.0f, 25.0f, 25.0f, 25.0f, 25.0f, 25.0f, 25.0f, 25.0f,},
-                           op::v0::Constant::create(IN_ET, Shape{1, 1, 3, 3}, {0.f,}),
-                           op::v0::Constant::create(IN_ET, Shape{1, 1, 3, 3}, {5.f,}),
-                           op::v0::Constant::create(IN_ET, Shape{1, 2, 3, 1}, {5.f,}),
-                           op::v0::Constant::create(IN_ET, Shape{1, 2, 1, 3}, {25.f,}),
+                           std::vector<T>{
+                               5.0f,
+                               9.0f,
+                               13.0f,
+                               17.0f,
+                               21.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                               25.0f,
+                           },
+                           op::v0::Constant::create(IN_ET,
+                                                    Shape{1, 1, 3, 3},
+                                                    {
+                                                        0.f,
+                                                    }),
+                           op::v0::Constant::create(IN_ET,
+                                                    Shape{1, 1, 3, 3},
+                                                    {
+                                                        5.f,
+                                                    }),
+                           op::v0::Constant::create(IN_ET,
+                                                    Shape{1, 2, 3, 1},
+                                                    {
+                                                        5.f,
+                                                    }),
+                           op::v0::Constant::create(IN_ET,
+                                                    Shape{1, 2, 1, 3},
+                                                    {
+                                                        25.f,
+                                                    }),
                            16,
                            op::AutoBroadcastSpec(op::AutoBroadcastType::NUMPY)),
     };
@@ -219,8 +260,7 @@ std::vector<FakeQuantizeParams> generateParamsForFakeQuantize() {
 std::vector<FakeQuantizeParams> generateCombinedParamsForFakeQuantize() {
     const std::vector<std::vector<FakeQuantizeParams>> allTypeParams{
         generateParamsForFakeQuantize<element::Type_t::f32>(),
-        generateParamsForFakeQuantize<element::Type_t::f16>()
-    };
+        generateParamsForFakeQuantize<element::Type_t::f16>()};
 
     std::vector<FakeQuantizeParams> combinedParams;
 
@@ -231,10 +271,9 @@ std::vector<FakeQuantizeParams> generateCombinedParamsForFakeQuantize() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_FakeQuantize_With_Hardcoded_Refs,
-    ReferenceFakeQuantizeLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForFakeQuantize()),
-    ReferenceFakeQuantizeLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_FakeQuantize_With_Hardcoded_Refs,
+                         ReferenceFakeQuantizeLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForFakeQuantize()),
+                         ReferenceFakeQuantizeLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/floor.cpp b/src/plugins/template/tests/functional/op_reference/floor.cpp
index 59da7069139dbc..861c1c197e1955 100644
--- a/src/plugins/template/tests/functional/op_reference/floor.cpp
+++ b/src/plugins/template/tests/functional/op_reference/floor.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/floor.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/floor.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,9 +16,9 @@ namespace {
 struct FloorParams {
     template <class IT>
     FloorParams(const PartialShape& shape,
-                   const element::Type& iType,
-                   const std::vector<IT>& iValues,
-                   const std::vector<IT>& oValues)
+                const element::Type& iType,
+                const std::vector<IT>& iValues,
+                const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -50,8 +52,8 @@ class ReferenceFloorLayerTest : public testing::TestWithParam<FloorParams>, publ
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto floor = std::make_shared<op::v0::Floor>(in);
         return std::make_shared<Model>(NodeVector{floor}, ParameterVector{in});
@@ -66,12 +68,10 @@ template <element::Type_t IN_ET>
 std::vector<FloorParams> generateParamsForFloorFloat() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<FloorParams> params{
-        FloorParams(ov::PartialShape{4},
-                    IN_ET,
-                    std::vector<T>{-2.5f, -2.0f, 0.3f, 4.8f},
-                    std::vector<T>{-3.0f, -2.0f, 0.0f, 4.0f})
-    };
+    std::vector<FloorParams> params{FloorParams(ov::PartialShape{4},
+                                                IN_ET,
+                                                std::vector<T>{-2.5f, -2.0f, 0.3f, 4.8f},
+                                                std::vector<T>{-3.0f, -2.0f, 0.0f, 4.0f})};
     return params;
 }
 
@@ -79,26 +79,21 @@ template <element::Type_t IN_ET>
 std::vector<FloorParams> generateParamsForFloorInt64() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<FloorParams> params{
-        FloorParams(ov::PartialShape{3},
-                    IN_ET,
-                    std::vector<T>{0, 1, 0x4000000000000001},
-                    std::vector<T>{0, 1, 0x4000000000000001})
-    };
+    std::vector<FloorParams> params{FloorParams(ov::PartialShape{3},
+                                                IN_ET,
+                                                std::vector<T>{0, 1, 0x4000000000000001},
+                                                std::vector<T>{0, 1, 0x4000000000000001})};
     return params;
 }
 
-
 template <element::Type_t IN_ET>
 std::vector<FloorParams> generateParamsForFloorInt32() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<FloorParams> params{
-        FloorParams(ov::PartialShape{4},
-                    IN_ET,
-                    std::vector<T>{2, 136314888, 0x40000010, 0x40000001},
-                    std::vector<T>{2, 136314888, 0x40000010, 0x40000001})
-    };
+    std::vector<FloorParams> params{FloorParams(ov::PartialShape{4},
+                                                IN_ET,
+                                                std::vector<T>{2, 136314888, 0x40000010, 0x40000001},
+                                                std::vector<T>{2, 136314888, 0x40000010, 0x40000001})};
     return params;
 }
 
@@ -107,27 +102,21 @@ std::vector<FloorParams> generateParamsForFloorInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     std::vector<FloorParams> params{
-        FloorParams(ov::PartialShape{4},
-                    IN_ET,
-                    std::vector<T>{2, 64, 0x40, 0x01},
-                    std::vector<T>{2, 64, 0x40, 0x01})
-    };
+        FloorParams(ov::PartialShape{4}, IN_ET, std::vector<T>{2, 64, 0x40, 0x01}, std::vector<T>{2, 64, 0x40, 0x01})};
     return params;
 }
 
 std::vector<FloorParams> generateCombinedParamsForFloor() {
-    const std::vector<std::vector<FloorParams>> allTypeParams{
-        generateParamsForFloorFloat<element::Type_t::f32>(),
-        generateParamsForFloorFloat<element::Type_t::f16>(),
-        generateParamsForFloorInt64<element::Type_t::i64>(),
-        generateParamsForFloorInt32<element::Type_t::i32>(),
-        generateParamsForFloorInt<element::Type_t::i16>(),
-        generateParamsForFloorInt<element::Type_t::i8>(),
-        generateParamsForFloorInt<element::Type_t::u64>(),
-        generateParamsForFloorInt<element::Type_t::u32>(),
-        generateParamsForFloorInt<element::Type_t::u16>(),
-        generateParamsForFloorInt<element::Type_t::u8>()
-    };
+    const std::vector<std::vector<FloorParams>> allTypeParams{generateParamsForFloorFloat<element::Type_t::f32>(),
+                                                              generateParamsForFloorFloat<element::Type_t::f16>(),
+                                                              generateParamsForFloorInt64<element::Type_t::i64>(),
+                                                              generateParamsForFloorInt32<element::Type_t::i32>(),
+                                                              generateParamsForFloorInt<element::Type_t::i16>(),
+                                                              generateParamsForFloorInt<element::Type_t::i8>(),
+                                                              generateParamsForFloorInt<element::Type_t::u64>(),
+                                                              generateParamsForFloorInt<element::Type_t::u32>(),
+                                                              generateParamsForFloorInt<element::Type_t::u16>(),
+                                                              generateParamsForFloorInt<element::Type_t::u8>()};
 
     std::vector<FloorParams> combinedParams;
 
@@ -138,11 +127,9 @@ std::vector<FloorParams> generateCombinedParamsForFloor() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Floor_With_Hardcoded_Refs,
-    ReferenceFloorLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForFloor()),
-    ReferenceFloorLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Floor_With_Hardcoded_Refs,
+                         ReferenceFloorLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForFloor()),
+                         ReferenceFloorLayerTest::getTestCaseName);
 
 }  // namespace
-
diff --git a/src/plugins/template/tests/functional/op_reference/floor_mod.cpp b/src/plugins/template/tests/functional/op_reference/floor_mod.cpp
index 497bea5f9e8621..5eb6433a67f0ef 100644
--- a/src/plugins/template/tests/functional/op_reference/floor_mod.cpp
+++ b/src/plugins/template/tests/functional/op_reference/floor_mod.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/floor_mod.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/floor_mod.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,11 +16,11 @@ namespace {
 struct FloorModParams {
     template <class IT>
     FloorModParams(const PartialShape& iShape1,
-              const PartialShape& iShape2,
-              const element::Type& iType,
-              const std::vector<IT>& iValues1,
-              const std::vector<IT>& iValues2,
-              const std::vector<IT>& oValues)
+                   const PartialShape& iShape2,
+                   const element::Type& iType,
+                   const std::vector<IT>& iValues1,
+                   const std::vector<IT>& iValues2,
+                   const std::vector<IT>& oValues)
         : pshape1(iShape1),
           pshape2(iShape2),
           inType(iType),
@@ -57,9 +59,9 @@ class ReferenceFloorModLayerTest : public testing::TestWithParam<FloorModParams>
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto floormod = std::make_shared<op::v1::FloorMod>(in1, in2);
@@ -76,14 +78,12 @@ template <element::Type_t IN_ET>
 std::vector<FloorModParams> generateParamsForFloorMod() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<FloorModParams> params{
-        FloorModParams(ov::PartialShape{4},
-                       ov::PartialShape{4},
-                       IN_ET,
-                       std::vector<T>{7, -7, 7, -7},
-                       std::vector<T>{3, 3, -3, -3},
-                       std::vector<T>{1, 2, -2, -1})
-    };
+    std::vector<FloorModParams> params{FloorModParams(ov::PartialShape{4},
+                                                      ov::PartialShape{4},
+                                                      IN_ET,
+                                                      std::vector<T>{7, -7, 7, -7},
+                                                      std::vector<T>{3, 3, -3, -3},
+                                                      std::vector<T>{1, 2, -2, -1})};
     return params;
 }
 
@@ -129,14 +129,12 @@ std::vector<FloorModParams> generateParamsForFloorModNonIntegerDivisor() {
 }
 
 std::vector<FloorModParams> generateCombinedParamsForFloorMod() {
-    const std::vector<std::vector<FloorModParams>> allTypeParams{
-        generateParamsForFloorMod<element::Type_t::f32>(),
-        generateParamsForFloorMod<element::Type_t::f16>(),
-        generateParamsForFloorMod<element::Type_t::bf16>(),
-        generateParamsForFloorMod<element::Type_t::i64>(),
-        generateParamsForFloorMod<element::Type_t::i32>(),
-        generateParamsForFloorMod<element::Type_t::i8>()
-    };
+    const std::vector<std::vector<FloorModParams>> allTypeParams{generateParamsForFloorMod<element::Type_t::f32>(),
+                                                                 generateParamsForFloorMod<element::Type_t::f16>(),
+                                                                 generateParamsForFloorMod<element::Type_t::bf16>(),
+                                                                 generateParamsForFloorMod<element::Type_t::i64>(),
+                                                                 generateParamsForFloorMod<element::Type_t::i32>(),
+                                                                 generateParamsForFloorMod<element::Type_t::i8>()};
 
     std::vector<FloorModParams> combinedParams;
 
@@ -150,8 +148,7 @@ std::vector<FloorModParams> generateCombinedParamsForFloorMod() {
 std::vector<FloorModParams> generateCombinedParamsForFloorModBroadcast() {
     const std::vector<std::vector<FloorModParams>> allTypeParams{
         generateParamsForFloorModBroadcast<element::Type_t::f32>(),
-        generateParamsForFloorModBroadcast<element::Type_t::f16>()
-    };
+        generateParamsForFloorModBroadcast<element::Type_t::f16>()};
 
     std::vector<FloorModParams> combinedParams;
 
@@ -172,8 +169,7 @@ std::vector<FloorModParams> generateCombinedParamsForFloorModScalar() {
         generateParamsForFloorModScalar<element::Type_t::i8>(),
         generateParamsForFloorModScalar<element::Type_t::u64>(),
         generateParamsForFloorModScalar<element::Type_t::u32>(),
-        generateParamsForFloorModScalar<element::Type_t::u8>()
-    };
+        generateParamsForFloorModScalar<element::Type_t::u8>()};
 
     std::vector<FloorModParams> combinedParams;
 
@@ -188,28 +184,24 @@ std::vector<FloorModParams> generateCombinedParamsForFloorModNonIntegerDivisor()
     return generateParamsForFloorModNonIntegerDivisor<element::Type_t::f32>();
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_FloorMod_With_Hardcoded_Refs,
-    ReferenceFloorModLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForFloorMod()),
-    ReferenceFloorModLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_FloorMod_Broadcast_With_Hardcoded_Refs,
-    ReferenceFloorModLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForFloorModBroadcast()),
-    ReferenceFloorModLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_FloorMod_Scalar_With_Hardcoded_Refs,
-    ReferenceFloorModLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForFloorModScalar()),
-    ReferenceFloorModLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_FloorMod_NonInteger_Divisor,
-    ReferenceFloorModLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForFloorModNonIntegerDivisor()),
-    ReferenceFloorModLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_FloorMod_With_Hardcoded_Refs,
+                         ReferenceFloorModLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForFloorMod()),
+                         ReferenceFloorModLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_FloorMod_Broadcast_With_Hardcoded_Refs,
+                         ReferenceFloorModLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForFloorModBroadcast()),
+                         ReferenceFloorModLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_FloorMod_Scalar_With_Hardcoded_Refs,
+                         ReferenceFloorModLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForFloorModScalar()),
+                         ReferenceFloorModLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_FloorMod_NonInteger_Divisor,
+                         ReferenceFloorModLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForFloorModNonIntegerDivisor()),
+                         ReferenceFloorModLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/gather.cpp b/src/plugins/template/tests/functional/op_reference/gather.cpp
index d158a8b38e3bf1..916cee50407836 100644
--- a/src/plugins/template/tests/functional/op_reference/gather.cpp
+++ b/src/plugins/template/tests/functional/op_reference/gather.cpp
@@ -4,21 +4,26 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset8.hpp"
-#include "openvino/opsets/opset7.hpp"
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
+#include "openvino/opsets/opset7.hpp"
+#include "openvino/opsets/opset8.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct GatherParams {
-    GatherParams(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& indicesTensor, const reference_tests::Tensor& axisTensor,
-        const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), indicesTensor(indicesTensor), axisTensor(axisTensor),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    GatherParams(const reference_tests::Tensor& dataTensor,
+                 const reference_tests::Tensor& indicesTensor,
+                 const reference_tests::Tensor& axisTensor,
+                 const reference_tests::Tensor& expectedTensor,
+                 const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          indicesTensor(indicesTensor),
+          axisTensor(axisTensor),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor indicesTensor;
@@ -59,8 +64,8 @@ class ReferenceGatherTest : public testing::TestWithParam<GatherParams>, public
     static std::shared_ptr<Model> CreateFunction(const GatherParams& params) {
         const auto P = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto I = std::make_shared<opset1::Parameter>(params.indicesTensor.type, params.indicesTensor.shape);
-        const auto A = opset1::Constant::create(params.axisTensor.type, params.axisTensor.shape,
-                                                params.axisTensor.data.data());
+        const auto A =
+            opset1::Constant::create(params.axisTensor.type, params.axisTensor.shape, params.axisTensor.data.data());
         const auto G = std::make_shared<opset1::Gather>(P, I, A);
         const auto f = std::make_shared<Model>(G, ParameterVector{P, I});
         return f;
@@ -72,11 +77,18 @@ TEST_P(ReferenceGatherTest, CompareWithRefs) {
 }
 
 struct GatherParamsV7 {
-    GatherParamsV7(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& indicesTensor, const reference_tests::Tensor& axisTensor, int64_t batchDims,
-        const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), indicesTensor(indicesTensor), axisTensor(axisTensor), batchDims(batchDims),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    GatherParamsV7(const reference_tests::Tensor& dataTensor,
+                   const reference_tests::Tensor& indicesTensor,
+                   const reference_tests::Tensor& axisTensor,
+                   int64_t batchDims,
+                   const reference_tests::Tensor& expectedTensor,
+                   const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          indicesTensor(indicesTensor),
+          axisTensor(axisTensor),
+          batchDims(batchDims),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor indicesTensor;
@@ -119,8 +131,8 @@ class ReferenceGatherTestV7 : public testing::TestWithParam<GatherParamsV7>, pub
     static std::shared_ptr<Model> CreateFunction(const GatherParamsV7& params) {
         const auto P = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto I = std::make_shared<opset1::Parameter>(params.indicesTensor.type, params.indicesTensor.shape);
-        const auto A = opset1::Constant::create(params.axisTensor.type, params.axisTensor.shape,
-                                                params.axisTensor.data.data());
+        const auto A =
+            opset1::Constant::create(params.axisTensor.type, params.axisTensor.shape, params.axisTensor.data.data());
         const auto G = std::make_shared<opset7::Gather>(P, I, A, params.batchDims);
         const auto f = std::make_shared<Model>(G, ParameterVector{P, I});
         return f;
@@ -136,8 +148,8 @@ class ReferenceGatherTestV8 : public ReferenceGatherTestV7 {
     static std::shared_ptr<Model> CreateFunction(const GatherParamsV7& params) {
         const auto P = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto I = std::make_shared<opset1::Parameter>(params.indicesTensor.type, params.indicesTensor.shape);
-        const auto A = opset1::Constant::create(params.axisTensor.type, params.axisTensor.shape,
-                                                params.axisTensor.data.data());
+        const auto A =
+            opset1::Constant::create(params.axisTensor.type, params.axisTensor.shape, params.axisTensor.data.data());
         const auto G = std::make_shared<opset8::Gather>(P, I, A, params.batchDims);
         const auto f = std::make_shared<Model>(G, ParameterVector{P, I});
         return f;
@@ -153,29 +165,27 @@ std::vector<GatherParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
     using T_I = typename element_type_traits<ET_I>::value_type;
     using T_A = typename element_type_traits<ET_A>::value_type;
-    std::vector<GatherParams> params {
-        GatherParams(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                10, 11, 20, 21, 30, 31}),
-            reference_tests::Tensor(ET_I, {2, 2, 3, 4}, std::vector<T_I>{
-                0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
-                0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            reference_tests::Tensor(ET, {2, 2, 3, 4, 2}, std::vector<T>{
-                10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31,
-                10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31,
-                10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31,
-                10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31}),
-            "gather_4d_indices_axis_0"),
-        GatherParams(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                10, 11, 20, 21, 30, 31}),
-            reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{
-                0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                10, 11, 20, 21, 20, 21, 30, 31}),
-            "gather_axis_0"),
+    std::vector<GatherParams> params{
+        GatherParams(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{10, 11, 20, 21, 30, 31}),
+                     reference_tests::Tensor(ET_I, {2, 2, 3, 4}, std::vector<T_I>{0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
+                                                                                  0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
+                                                                                  0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
+                                                                                  0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}),
+                     reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                     reference_tests::Tensor(
+                         ET,
+                         {2, 2, 3, 4, 2},
+                         std::vector<T>{10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21,
+                                        20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31,
+                                        10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21,
+                                        20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31,
+                                        10, 11, 20, 21, 20, 21, 30, 31, 10, 11, 20, 21, 20, 21, 30, 31}),
+                     "gather_4d_indices_axis_0"),
+        GatherParams(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{10, 11, 20, 21, 30, 31}),
+                     reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{0, 1, 1, 2}),
+                     reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                     reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{10, 11, 20, 21, 20, 21, 30, 31}),
+                     "gather_axis_0"),
     };
     return params;
 }
@@ -185,251 +195,139 @@ std::vector<GatherParams> generateParamsFloatValue() {
     using T = typename element_type_traits<ET>::value_type;
     using T_I = typename element_type_traits<ET_I>::value_type;
     using T_A = typename element_type_traits<ET_A>::value_type;
-    std::vector<GatherParams> params {
-        GatherParams(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {2, 2, 3, 4}, std::vector<T_I>{
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-
-
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            reference_tests::Tensor(ET, {2, 2, 3, 4, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+    std::vector<GatherParams> params{
+        GatherParams(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+                     reference_tests::Tensor(ET_I, {2, 2, 3, 4}, std::vector<T_I>{0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
 
+                                                                                  0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                                                  0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                                                  0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}),
+                     reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                     reference_tests::Tensor(ET,
+                                             {2, 2, 3, 4, 2},
+                                             std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            "gather_4d_indices_axis_0_2d_input"),
-        GatherParams(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {2, 3, 4}, std::vector<T_I>{
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            reference_tests::Tensor(ET, {2, 3, 4, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            "gather_3d_indices_axis_0_2d_input"),
+                                                            1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+                     "gather_4d_indices_axis_0_2d_input"),
         GatherParams(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{
-                0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
+            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+            reference_tests::Tensor(ET_I, {2, 3, 4}, std::vector<T_I>{0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
 
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            "gather_2d_indices_axis_0_2d_input"),
-        GatherParams(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{
-                0, -2, 1, 2}),
+                                                                      0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
+            reference_tests::Tensor(ET, {2, 3, 4, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            "gather_2d_negative_and_positive_indices_axis_0_2d_input"),
-        GatherParams(
-            reference_tests::Tensor(ET, {3}, std::vector<T>{
-                1.0f, 2.0f, 3.0f}),
-            reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{
-                1, 0}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            reference_tests::Tensor(ET, {2}, std::vector<T>{
-                2.0f, 1.0f}),
-            "gather_1d_indices_axis_0_1d_input"),
-        GatherParams(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {}, std::vector<T_I>{1}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            reference_tests::Tensor(ET, {2}, std::vector<T>{
-                2.0f, 2.1f}),
-            "gather_scalar_indices_axis_0_2d_input"),
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
+
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
+
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
+
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
+
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+            "gather_3d_indices_axis_0_2d_input"),
+        GatherParams(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+                     reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{0, 1, 1, 2}),
+                     reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                     reference_tests::Tensor(ET,
+                                             {2, 2, 2},
+                                             std::vector<T>{1.0f,
+                                                            1.1f,
+                                                            2.0f,
+                                                            2.1f,
+
+                                                            2.0f,
+                                                            2.1f,
+                                                            3.0f,
+                                                            3.1f}),
+                     "gather_2d_indices_axis_0_2d_input"),
+        GatherParams(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+                     reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{0, -2, 1, 2}),
+                     reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                     reference_tests::Tensor(ET,
+                                             {2, 2, 2},
+                                             std::vector<T>{1.0f,
+                                                            1.1f,
+                                                            2.0f,
+                                                            2.1f,
+
+                                                            2.0f,
+                                                            2.1f,
+                                                            3.0f,
+                                                            3.1f}),
+                     "gather_2d_negative_and_positive_indices_axis_0_2d_input"),
+        GatherParams(reference_tests::Tensor(ET, {3}, std::vector<T>{1.0f, 2.0f, 3.0f}),
+                     reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{1, 0}),
+                     reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                     reference_tests::Tensor(ET, {2}, std::vector<T>{2.0f, 1.0f}),
+                     "gather_1d_indices_axis_0_1d_input"),
+        GatherParams(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+                     reference_tests::Tensor(ET_I, {}, std::vector<T_I>{1}),
+                     reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                     reference_tests::Tensor(ET, {2}, std::vector<T>{2.0f, 2.1f}),
+                     "gather_scalar_indices_axis_0_2d_input"),
         GatherParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1.0f, 1.1f, 1.2f,
-                2.0f, 2.1f, 2.2f,
-                3.0f, 3.1f, 3.2f}),
-            reference_tests::Tensor(ET_I, {1, 2}, std::vector<T_I>{
-                0, 2}),
+            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}),
+            reference_tests::Tensor(ET_I, {1, 2}, std::vector<T_I>{0, 2}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
-            reference_tests::Tensor(ET, {3, 1, 2}, std::vector<T>{
-                1.0f, 1.2f,
-                2.0f, 2.2f,
-                3.0f, 3.2f}),
+            reference_tests::Tensor(ET, {3, 1, 2}, std::vector<T>{1.0f, 1.2f, 2.0f, 2.2f, 3.0f, 3.2f}),
             "gather_2d_indices_axis_1_2d_input"),
         GatherParams(
-            reference_tests::Tensor(ET, {2, 2, 3, 3}, std::vector<T>{
-                1.0f,   1.1f,   1.2f,
-                2.0f,   2.1f,   2.2f,
-                3.0f,   3.1f,   3.2f,
-
-                11.0f,  11.1f,  11.2f,
-                12.0f,  12.1f,  12.2f,
-                13.0f,  13.1f,  13.2f,
+            reference_tests::Tensor(
+                ET,
+                {2, 2, 3, 3},
+                std::vector<T>{1.0f,   1.1f,   1.2f,   2.0f,   2.1f,   2.2f,   3.0f,   3.1f,   3.2f,
 
+                               11.0f,  11.1f,  11.2f,  12.0f,  12.1f,  12.2f,  13.0f,  13.1f,  13.2f,
 
-                101.0f, 101.1f, 101.2f,
-                102.0f, 102.1f, 102.2f,
-                103.0f, 103.1f, 103.2f,
+                               101.0f, 101.1f, 101.2f, 102.0f, 102.1f, 102.2f, 103.0f, 103.1f, 103.2f,
 
-                111.0f, 111.1f, 111.2f,
-                112.0f, 112.1f, 112.2f,
-                113.0f, 113.1f, 113.2f}),
-            reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{
-                0, 2}),
+                               111.0f, 111.1f, 111.2f, 112.0f, 112.1f, 112.2f, 113.0f, 113.1f, 113.2f}),
+            reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{0, 2}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{2}),
-            reference_tests::Tensor(ET, {2, 2, 2, 3}, std::vector<T>{
-                1.0f,   1.1f,   1.2f,
-                3.0f,   3.1f,   3.2f,
+            reference_tests::Tensor(ET, {2, 2, 2, 3}, std::vector<T>{1.0f,   1.1f,   1.2f,   3.0f,   3.1f,   3.2f,
 
-                11.0f,  11.1f,  11.2f,
-                13.0f,  13.1f,  13.2f,
+                                                                     11.0f,  11.1f,  11.2f,  13.0f,  13.1f,  13.2f,
 
+                                                                     101.0f, 101.1f, 101.2f, 103.0f, 103.1f, 103.2f,
 
-                101.0f, 101.1f, 101.2f,
-                103.0f, 103.1f, 103.2f,
-
-                111.0f, 111.1f, 111.2f,
-                113.0f, 113.1f, 113.2f}),
+                                                                     111.0f, 111.1f, 111.2f, 113.0f, 113.1f, 113.2f}),
             "gather_1d_indices_axis_2_4d_input"),
         GatherParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}),
+            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}),
             reference_tests::Tensor(ET_I, {}, std::vector<T_I>{0}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
-            reference_tests::Tensor(ET, {3}, std::vector<T>{
-                1.0f, 2.0f, 3.0f}),
+            reference_tests::Tensor(ET, {3}, std::vector<T>{1.0f, 2.0f, 3.0f}),
             "gather_scalar_indices_axis_1_2d_input"),
     };
     return params;
 }
 
 std::vector<GatherParams> generateCombinedParams() {
-    const std::vector<std::vector<GatherParams>> generatedParams {
+    const std::vector<std::vector<GatherParams>> generatedParams{
         generateParams<element::Type_t::i8, element::Type_t::i32, element::Type_t::i64>(),
         generateParams<element::Type_t::i16, element::Type_t::i32, element::Type_t::i64>(),
         generateParams<element::Type_t::i32, element::Type_t::i32, element::Type_t::i64>(),
@@ -451,106 +349,79 @@ std::vector<GatherParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Gather_With_Hardcoded_Refs, ReferenceGatherTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceGatherTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Gather_With_Hardcoded_Refs,
+                         ReferenceGatherTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceGatherTest::getTestCaseName);
 
 template <element::Type_t ET, element::Type_t ET_I, element::Type_t ET_A>
 std::vector<GatherParamsV7> generateParamsV7() {
     using T = typename element_type_traits<ET>::value_type;
     using T_I = typename element_type_traits<ET_I>::value_type;
     using T_A = typename element_type_traits<ET_A>::value_type;
-    std::vector<GatherParamsV7> params {
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {3}, std::vector<T>{
-                1, 2, 3}),
-            reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{
-                2, 0}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            0,
-            reference_tests::Tensor(ET, {2}, std::vector<T>{
-                3, 1}),
-            "gather_v7_1d"),
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                10, 11, 20, 21, 30, 31}),
-            reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{
-                0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            0,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                10, 11, 20, 21, 20, 21, 30, 31}),
-            "gather_v7_axis_0"),
+    std::vector<GatherParamsV7> params{
+        GatherParamsV7(reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
+                       reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{2, 0}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET, {2}, std::vector<T>{3, 1}),
+                       "gather_v7_1d"),
+        GatherParamsV7(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{10, 11, 20, 21, 30, 31}),
+                       reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{0, 1, 1, 2}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{10, 11, 20, 21, 20, 21, 30, 31}),
+                       "gather_v7_axis_0"),
+        GatherParamsV7(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                       reference_tests::Tensor(ET_I,
+                                               {2, 2, 2},
+                                               std::vector<T_I>{0,
+                                                                1,
+                                                                1,
+                                                                2,
+
+                                                                2,
+                                                                0,
+                                                                1,
+                                                                2}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
+                       1,
+                       reference_tests::Tensor(ET,
+                                               {2, 2, 2},
+                                               std::vector<T>{1,
+                                                              2,
+                                                              2,
+                                                              3,
+
+                                                              6,
+                                                              4,
+                                                              5,
+                                                              6}),
+                       "gather_v7_data_int32_3d_indices_axis_1_batch_dims_1"),
+        GatherParamsV7(reference_tests::Tensor(ET, {2, 5}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}),
+                       reference_tests::Tensor(ET_I, {2, 3}, std::vector<T_I>{0, 0, 4, 4, 0, 0}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
+                       1,
+                       reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1, 1, 5, 10, 6, 6}),
+                       "gather_v7_data_int32_2d_indices_axis_1_batch_dims_1"),
+        GatherParamsV7(reference_tests::Tensor(ET, {2, 5}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}),
+                       reference_tests::Tensor(ET_I, {2, 3}, std::vector<T_I>{0, 0, 4, 4, 0, 0}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
+                       -1,
+                       reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1, 1, 5, 10, 6, 6}),
+                       "gather_v7_data_int32_2d_indices_axis_1_negative_batch_dims"),
         GatherParamsV7(
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6}),
-            reference_tests::Tensor(ET_I, {2, 2, 2}, std::vector<T_I>{
-                0, 1,
-                1, 2,
-
-                2, 0,
-                1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
-            1,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                1, 2,
-                2, 3,
+            reference_tests::Tensor(ET, {2, 1, 5, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
+                                                                     11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
 
-                6, 4,
-                5, 6}),
-            "gather_v7_data_int32_3d_indices_axis_1_batch_dims_1"),
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {2, 5}, std::vector<T>{
-                1, 2, 3, 4, 5,
-                6, 7, 8, 9, 10}),
-            reference_tests::Tensor(ET_I, {2, 3}, std::vector<T_I>{
-                0, 0, 4,
-                4, 0, 0}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
-            1,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                1,  1, 5,
-                10, 6, 6}),
-            "gather_v7_data_int32_2d_indices_axis_1_batch_dims_1"),
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {2, 5}, std::vector<T>{
-                1, 2, 3, 4, 5,
-                6, 7, 8, 9, 10}),
-            reference_tests::Tensor(ET_I, {2, 3}, std::vector<T_I>{
-                0, 0, 4,
-                4, 0, 0}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
-            -1,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                1,  1, 5,
-                10, 6, 6}),
-            "gather_v7_data_int32_2d_indices_axis_1_negative_batch_dims"),
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {2, 1, 5, 4}, std::vector<T>{
-                1,  2,  3,  4,
-                5,  6,  7,  8,
-                9,  10, 11, 12,
-                13, 14, 15, 16,
-                17, 18, 19, 20,
-
-                21, 22, 23, 24,
-                25, 26, 27, 28,
-                29, 30, 31, 32,
-                33, 34, 35, 36,
-                37, 38, 39, 40}),
-            reference_tests::Tensor(ET_I, {2, 3}, std::vector<T_I>{
-                1, 2, 4,
-                4, 3, 2}),
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
+                                                                     31, 32, 33, 34, 35, 36, 37, 38, 39, 40}),
+            reference_tests::Tensor(ET_I, {2, 3}, std::vector<T_I>{1, 2, 4, 4, 3, 2}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{2}),
             1,
-            reference_tests::Tensor(ET, {2, 1, 3, 4}, std::vector<T>{
-                5,  6,  7,  8,
-                9,  10, 11, 12,
-                17, 18, 19, 20,
-
-                37, 38, 39, 40,
-                33, 34, 35, 36,
-                29, 30, 31, 32}),
+            reference_tests::Tensor(ET, {2, 1, 3, 4}, std::vector<T>{5,  6,  7,  8,  9,  10, 11, 12, 17, 18, 19, 20,
+
+                                                                     37, 38, 39, 40, 33, 34, 35, 36, 29, 30, 31, 32}),
             "gather_v7_4d_data_axis_2_batch_dims_1_int32"),
     };
     return params;
@@ -558,17 +429,13 @@ std::vector<GatherParamsV7> generateParamsV7() {
 
 template <>
 std::vector<GatherParamsV7> generateParamsV7<element::boolean, element::i32, element::i64>() {
-    std::vector<GatherParamsV7> params {
-        GatherParamsV7(
-            reference_tests::Tensor(element::boolean, {3, 2}, std::vector<char>{
-                1, 1, 1, 0, 0, 1}),
-            reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{
-                0, 1, 1, 2}),
-            reference_tests::Tensor(element::i64, {}, std::vector<int64_t>{0}),
-            0,
-            reference_tests::Tensor(element::boolean, {2, 2, 2}, std::vector<char>{
-                1, 1, 1, 0, 1, 0, 0, 1}),
-            "gather_v7_axis_0_bool"),
+    std::vector<GatherParamsV7> params{
+        GatherParamsV7(reference_tests::Tensor(element::boolean, {3, 2}, std::vector<char>{1, 1, 1, 0, 0, 1}),
+                       reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 1, 2}),
+                       reference_tests::Tensor(element::i64, {}, std::vector<int64_t>{0}),
+                       0,
+                       reference_tests::Tensor(element::boolean, {2, 2, 2}, std::vector<char>{1, 1, 1, 0, 1, 0, 0, 1}),
+                       "gather_v7_axis_0_bool"),
     };
     return params;
 }
@@ -578,299 +445,180 @@ std::vector<GatherParamsV7> generateParamsFloatValueV7() {
     using T = typename element_type_traits<ET>::value_type;
     using T_I = typename element_type_traits<ET_I>::value_type;
     using T_A = typename element_type_traits<ET_A>::value_type;
-    std::vector<GatherParamsV7> params {
+    std::vector<GatherParamsV7> params{
         GatherParamsV7(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {2, 2, 3, 4}, std::vector<T_I>{
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-
-
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            0,
-            reference_tests::Tensor(ET, {2, 2, 3, 4, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+            reference_tests::Tensor(ET_I, {2, 2, 3, 4}, std::vector<T_I>{0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                                         0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
 
+                                                                         0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                                         0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}),
+            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+            0,
+            reference_tests::Tensor(ET,
+                                    {2, 2, 3, 4, 2},
+                                    std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
+                                                   1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
             "gather_v7_4d_indices_axis_0_2d_input"),
         GatherParamsV7(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {2, 3, 4}, std::vector<T_I>{
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-
-                0, 1, 1, 2,
-                0, 1, 1, 2,
-                0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            0,
-            reference_tests::Tensor(ET, {2, 3, 4, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f,
-
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            "gather_v7_3d_indices_axis_0_2d_input"),
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{
-                0, 1, 1, 2}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            0,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
+            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+            reference_tests::Tensor(ET_I, {2, 3, 4}, std::vector<T_I>{0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2,
 
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            "gather_v7_2d_indices_axis_0_2d_input"),
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{
-                0, -2, 1, 2}),
+                                                                      0, 1, 1, 2, 0, 1, 1, 2, 0, 1, 1, 2}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
             0,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                1.0f, 1.1f,
-                2.0f, 2.1f,
+            reference_tests::Tensor(ET, {2, 3, 4, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
 
-                2.0f, 2.1f,
-                3.0f, 3.1f}),
-            "gather_v7_2d_negative_and_positive_indices_axis_0_2d_input"),
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {3}, std::vector<T>{
-                1.0f, 2.0f, 3.0f}),
-            reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{
-                1, 0}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            0,
-            reference_tests::Tensor(ET, {2}, std::vector<T>{
-                2.0f, 1.0f}),
-            "gather_v7_1d_indices_axis_0_1d_input"),
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {3, 2}, std::vector<T>{
-                1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
-            reference_tests::Tensor(ET_I, {}, std::vector<T_I>{1}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            0,
-            reference_tests::Tensor(ET, {2}, std::vector<T>{
-                2.0f, 2.1f}),
-            "gather_v7_scalar_indices_axis_0_2d_input"),
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
+
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
+
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
+
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f,
+
+                                                                     1.0f, 1.1f, 2.0f, 2.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+            "gather_v7_3d_indices_axis_0_2d_input"),
+        GatherParamsV7(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+                       reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{0, 1, 1, 2}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET,
+                                               {2, 2, 2},
+                                               std::vector<T>{1.0f,
+                                                              1.1f,
+                                                              2.0f,
+                                                              2.1f,
+
+                                                              2.0f,
+                                                              2.1f,
+                                                              3.0f,
+                                                              3.1f}),
+                       "gather_v7_2d_indices_axis_0_2d_input"),
+        GatherParamsV7(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+                       reference_tests::Tensor(ET_I, {2, 2}, std::vector<T_I>{0, -2, 1, 2}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET,
+                                               {2, 2, 2},
+                                               std::vector<T>{1.0f,
+                                                              1.1f,
+                                                              2.0f,
+                                                              2.1f,
+
+                                                              2.0f,
+                                                              2.1f,
+                                                              3.0f,
+                                                              3.1f}),
+                       "gather_v7_2d_negative_and_positive_indices_axis_0_2d_input"),
+        GatherParamsV7(reference_tests::Tensor(ET, {3}, std::vector<T>{1.0f, 2.0f, 3.0f}),
+                       reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{1, 0}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET, {2}, std::vector<T>{2.0f, 1.0f}),
+                       "gather_v7_1d_indices_axis_0_1d_input"),
+        GatherParamsV7(reference_tests::Tensor(ET, {3, 2}, std::vector<T>{1.0f, 1.1f, 2.0f, 2.1f, 3.0f, 3.1f}),
+                       reference_tests::Tensor(ET_I, {}, std::vector<T_I>{1}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET, {2}, std::vector<T>{2.0f, 2.1f}),
+                       "gather_v7_scalar_indices_axis_0_2d_input"),
         GatherParamsV7(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1.0f, 1.1f, 1.2f,
-                2.0f, 2.1f, 2.2f,
-                3.0f, 3.1f, 3.2f}),
-            reference_tests::Tensor(ET_I, {1, 2}, std::vector<T_I>{
-                0, 2}),
+            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}),
+            reference_tests::Tensor(ET_I, {1, 2}, std::vector<T_I>{0, 2}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
             0,
-            reference_tests::Tensor(ET, {3, 1, 2}, std::vector<T>{
-                1.0f, 1.2f,
-                2.0f, 2.2f,
-                3.0f, 3.2f}),
+            reference_tests::Tensor(ET, {3, 1, 2}, std::vector<T>{1.0f, 1.2f, 2.0f, 2.2f, 3.0f, 3.2f}),
             "gather_v7_2d_indices_axis_1_2d_input"),
         GatherParamsV7(
-            reference_tests::Tensor(ET, {2, 2, 3, 3}, std::vector<T>{
-                1.0f,   1.1f,   1.2f,
-                2.0f,   2.1f,   2.2f,
-                3.0f,   3.1f,   3.2f,
-
-                11.0f,  11.1f,  11.2f,
-                12.0f,  12.1f,  12.2f,
-                13.0f,  13.1f,  13.2f,
+            reference_tests::Tensor(
+                ET,
+                {2, 2, 3, 3},
+                std::vector<T>{1.0f,   1.1f,   1.2f,   2.0f,   2.1f,   2.2f,   3.0f,   3.1f,   3.2f,
 
+                               11.0f,  11.1f,  11.2f,  12.0f,  12.1f,  12.2f,  13.0f,  13.1f,  13.2f,
 
-                101.0f, 101.1f, 101.2f,
-                102.0f, 102.1f, 102.2f,
-                103.0f, 103.1f, 103.2f,
+                               101.0f, 101.1f, 101.2f, 102.0f, 102.1f, 102.2f, 103.0f, 103.1f, 103.2f,
 
-                111.0f, 111.1f, 111.2f,
-                112.0f, 112.1f, 112.2f,
-                113.0f, 113.1f, 113.2f}),
-            reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{
-                0, 2}),
+                               111.0f, 111.1f, 111.2f, 112.0f, 112.1f, 112.2f, 113.0f, 113.1f, 113.2f}),
+            reference_tests::Tensor(ET_I, {2}, std::vector<T_I>{0, 2}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{2}),
             0,
-            reference_tests::Tensor(ET, {2, 2, 2, 3}, std::vector<T>{
-                1.0f,   1.1f,   1.2f,
-                3.0f,   3.1f,   3.2f,
+            reference_tests::Tensor(ET, {2, 2, 2, 3}, std::vector<T>{1.0f,   1.1f,   1.2f,   3.0f,   3.1f,   3.2f,
 
-                11.0f,  11.1f,  11.2f,
-                13.0f,  13.1f,  13.2f,
+                                                                     11.0f,  11.1f,  11.2f,  13.0f,  13.1f,  13.2f,
 
+                                                                     101.0f, 101.1f, 101.2f, 103.0f, 103.1f, 103.2f,
 
-                101.0f, 101.1f, 101.2f,
-                103.0f, 103.1f, 103.2f,
-
-                111.0f, 111.1f, 111.2f,
-                113.0f, 113.1f, 113.2f}),
+                                                                     111.0f, 111.1f, 111.2f, 113.0f, 113.1f, 113.2f}),
             "gather_v7_1d_indices_axis_2_4d_input"),
         GatherParamsV7(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}),
+            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{1.0f, 1.1f, 1.2f, 2.0f, 2.1f, 2.2f, 3.0f, 3.1f, 3.2f}),
             reference_tests::Tensor(ET_I, {}, std::vector<T_I>{0}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
             0,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{
-                1.0f, 2.0f, 3.0f}),
+            reference_tests::Tensor(ET, {3}, std::vector<T>{1.0f, 2.0f, 3.0f}),
             "gather_v7_scalar_indices_axis_1_2d_input"),
         GatherParamsV7(
-            reference_tests::Tensor(ET, {2, 5, 2}, std::vector<T>{
-                1.0f, 2.0f,
-                3.0f, 4.0f,
-                5.0f, 6.0f,
-                7.0f, 8.0f,
-                9.0f, 10.0f,
-
-                11.0f, 12.0f,
-                13.0f, 14.0f,
-                15.0f, 16.0f,
-                17.0f, 18.0f,
-                19.0f, 20.0f}),
-            reference_tests::Tensor(ET_I, {2, 2, 3}, std::vector<T_I>{
-                0, 0, 4,
-                4, 0, 0,
-
-                1, 2, 4,
-                4, 3, 2}),
+            reference_tests::Tensor(ET, {2, 5, 2}, std::vector<T>{1.0f,  2.0f,  3.0f,  4.0f,  5.0f,
+                                                                  6.0f,  7.0f,  8.0f,  9.0f,  10.0f,
+
+                                                                  11.0f, 12.0f, 13.0f, 14.0f, 15.0f,
+                                                                  16.0f, 17.0f, 18.0f, 19.0f, 20.0f}),
+            reference_tests::Tensor(ET_I,
+                                    {2, 2, 3},
+                                    std::vector<T_I>{0,
+                                                     0,
+                                                     4,
+                                                     4,
+                                                     0,
+                                                     0,
+
+                                                     1,
+                                                     2,
+                                                     4,
+                                                     4,
+                                                     3,
+                                                     2}),
             reference_tests::Tensor(ET_A, {}, std::vector<T_A>{1}),
             1,
-            reference_tests::Tensor(ET, {2, 2, 3, 2}, std::vector<T>{
-                1.0f, 2.0f,
-                1.0f, 2.0f,
-                9.0f, 10.0f,
-
-                9.0f, 10.0f,
-                1.0f, 2.0f,
-                1.0f, 2.0f,
+            reference_tests::Tensor(ET, {2, 2, 3, 2}, std::vector<T>{1.0f,  2.0f,  1.0f,  2.0f,  9.0f,  10.0f,
 
+                                                                     9.0f,  10.0f, 1.0f,  2.0f,  1.0f,  2.0f,
 
-                13.0f, 14.0f,
-                15.0f, 16.0f,
-                19.0f, 20.0f,
+                                                                     13.0f, 14.0f, 15.0f, 16.0f, 19.0f, 20.0f,
 
-                19.0f, 20.0f,
-                17.0f, 18.0f,
-                15.0f, 16.0f}),
+                                                                     19.0f, 20.0f, 17.0f, 18.0f, 15.0f, 16.0f}),
             "gather_v7_3d_indices_axis_1_batch_dims_1"),
     };
     return params;
 }
 
 std::vector<GatherParamsV7> generateCombinedParamsV7() {
-    const std::vector<std::vector<GatherParamsV7>> generatedParams {
+    const std::vector<std::vector<GatherParamsV7>> generatedParams{
         generateParamsV7<element::Type_t::boolean, element::Type_t::i32, element::Type_t::i64>(),
         generateParamsV7<element::Type_t::i8, element::Type_t::i32, element::Type_t::i64>(),
         generateParamsV7<element::Type_t::i16, element::Type_t::i32, element::Type_t::i64>(),
@@ -893,79 +641,55 @@ std::vector<GatherParamsV7> generateCombinedParamsV7() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Gather_With_Hardcoded_Refs, ReferenceGatherTestV7,
-    testing::ValuesIn(generateCombinedParamsV7()), ReferenceGatherTestV7::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Gather_With_Hardcoded_Refs,
+                         ReferenceGatherTestV7,
+                         testing::ValuesIn(generateCombinedParamsV7()),
+                         ReferenceGatherTestV7::getTestCaseName);
 
 template <element::Type_t ET, element::Type_t ET_I, element::Type_t ET_A>
 std::vector<GatherParamsV7> generateParamsV8() {
     using T = typename element_type_traits<ET>::value_type;
     using T_I = typename element_type_traits<ET_I>::value_type;
     using T_A = typename element_type_traits<ET_A>::value_type;
-    std::vector<GatherParamsV7> params {
-        GatherParamsV7(
-            reference_tests::Tensor(ET, {5}, std::vector<T>{
-                1, 2, 3, 4, 5}),
-            reference_tests::Tensor(ET_I, {3}, std::vector<T_I>{
-                0, -2, -1}),
-            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-            0,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{
-                1, 4, 5}),
-            "gather_v8_1d_negative_indices"),
+    std::vector<GatherParamsV7> params{
+        GatherParamsV7(reference_tests::Tensor(ET, {5}, std::vector<T>{1, 2, 3, 4, 5}),
+                       reference_tests::Tensor(ET_I, {3}, std::vector<T_I>{0, -2, -1}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET, {3}, std::vector<T>{1, 4, 5}),
+                       "gather_v8_1d_negative_indices"),
         // zeros are not present in the original data but appear because of the out of bound values
+        GatherParamsV7(reference_tests::Tensor(ET, {5}, std::vector<T>{1, 2, 3, 4, 5}),
+                       reference_tests::Tensor(ET_I, {3}, std::vector<T_I>{0, 20, 4}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET, {3}, std::vector<T>{1, 0, 5}),
+                       "gather_v8_out_of_bound_indices_1"),
         GatherParamsV7(
-                reference_tests::Tensor(ET, {5}, std::vector<T>{
-                        1, 2, 3, 4, 5}),
-                reference_tests::Tensor(ET_I, {3}, std::vector<T_I>{
-                        0, 20, 4}),
-                reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-                0,
-                reference_tests::Tensor(ET, {3}, std::vector<T>{
-                        1, 0, 5}),
-                "gather_v8_out_of_bound_indices_1"),
-        GatherParamsV7(
-                reference_tests::Tensor(ET, {2, 1, 5, 4}, std::vector<T>{
-                        1,  2,  3,  4,
-                        5,  6,  7,  8,
-                        9,  10, 11, 12,
-                        13, 14, 15, 16,
-                        17, 18, 19, 20,
-
-                        21, 22, 23, 24,
-                        25, 26, 27, 28,
-                        29, 30, 31, 32,
-                        33, 34, 35, 36,
-                        37, 38, 39, 40}),
-                reference_tests::Tensor(ET_I, {2, 3}, std::vector<T_I>{
-                        1, 2, 200,
-                        4, 200, 2}),
-                reference_tests::Tensor(ET_A, {}, std::vector<T_A>{2}),
-                1,
-                reference_tests::Tensor(ET, {2, 1, 3, 4}, std::vector<T>{
-                        5,  6,  7,  8,
-                        9,  10, 11, 12,
-                        0, 0, 0, 0,
-
-                        37, 38, 39, 40,
-                        0, 0, 0, 0,
-                        29, 30, 31, 32}),
-                "gather_v8_4d_data_axis_2_batch_dims_1_out_of_bound_indices_2"),
-        GatherParamsV7(
-                reference_tests::Tensor(ET, {5}, std::vector<T>{
-                        1, 2, 3, 4, 5}),
-                reference_tests::Tensor(ET_I, {3}, std::vector<T_I>{
-                        0, -200, 4}),
-                reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
-                0,
-                reference_tests::Tensor(ET, {3}, std::vector<T>{
-                        1, 0, 5}),
-                "gather_v8_out_of_bound_negative_index"),
+            reference_tests::Tensor(ET, {2, 1, 5, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
+                                                                     11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
+
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
+                                                                     31, 32, 33, 34, 35, 36, 37, 38, 39, 40}),
+            reference_tests::Tensor(ET_I, {2, 3}, std::vector<T_I>{1, 2, 200, 4, 200, 2}),
+            reference_tests::Tensor(ET_A, {}, std::vector<T_A>{2}),
+            1,
+            reference_tests::Tensor(ET, {2, 1, 3, 4}, std::vector<T>{5,  6,  7,  8,  9, 10, 11, 12, 0,  0,  0,  0,
+
+                                                                     37, 38, 39, 40, 0, 0,  0,  0,  29, 30, 31, 32}),
+            "gather_v8_4d_data_axis_2_batch_dims_1_out_of_bound_indices_2"),
+        GatherParamsV7(reference_tests::Tensor(ET, {5}, std::vector<T>{1, 2, 3, 4, 5}),
+                       reference_tests::Tensor(ET_I, {3}, std::vector<T_I>{0, -200, 4}),
+                       reference_tests::Tensor(ET_A, {}, std::vector<T_A>{0}),
+                       0,
+                       reference_tests::Tensor(ET, {3}, std::vector<T>{1, 0, 5}),
+                       "gather_v8_out_of_bound_negative_index"),
     };
     return params;
 }
 
 std::vector<GatherParamsV7> generateCombinedParamsV8() {
-    const std::vector<std::vector<GatherParamsV7>> generatedParams {
+    const std::vector<std::vector<GatherParamsV7>> generatedParams{
         generateParamsV7<element::Type_t::boolean, element::Type_t::i32, element::Type_t::i64>(),
         generateParamsV7<element::Type_t::i8, element::Type_t::i32, element::Type_t::i64>(),
         generateParamsV7<element::Type_t::i16, element::Type_t::i32, element::Type_t::i64>(),
@@ -1001,6 +725,8 @@ std::vector<GatherParamsV7> generateCombinedParamsV8() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Gather_With_Hardcoded_Refs, ReferenceGatherTestV8,
-    testing::ValuesIn(generateCombinedParamsV8()), ReferenceGatherTestV8::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Gather_With_Hardcoded_Refs,
+                         ReferenceGatherTestV8,
+                         testing::ValuesIn(generateCombinedParamsV8()),
+                         ReferenceGatherTestV8::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/gather_elements.cpp b/src/plugins/template/tests/functional/op_reference/gather_elements.cpp
index e7cddb376cfd87..303f520d924412 100644
--- a/src/plugins/template/tests/functional/op_reference/gather_elements.cpp
+++ b/src/plugins/template/tests/functional/op_reference/gather_elements.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/gather_elements.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/gather_elements.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,11 +13,16 @@ using namespace ov;
 
 namespace {
 struct GatherElementsParams {
-    GatherElementsParams(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& indicesTensor, int64_t axis,
-        const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), indicesTensor(indicesTensor), axis(axis),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    GatherElementsParams(const reference_tests::Tensor& dataTensor,
+                         const reference_tests::Tensor& indicesTensor,
+                         int64_t axis,
+                         const reference_tests::Tensor& expectedTensor,
+                         const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          indicesTensor(indicesTensor),
+          axis(axis),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor indicesTensor;
@@ -55,18 +61,17 @@ class ReferenceGatherElementsTest : public testing::TestWithParam<GatherElements
 private:
     static std::shared_ptr<Model> CreateFunction(const GatherElementsParams& params) {
         std::shared_ptr<Model> function;
-        const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type,
-                                                              PartialShape{params.dataTensor.shape});
-        const auto indices = std::make_shared<op::v0::Parameter>(params.indicesTensor.type,
-                                                                 PartialShape{params.indicesTensor.shape});
+        const auto data =
+            std::make_shared<op::v0::Parameter>(params.dataTensor.type, PartialShape{params.dataTensor.shape});
+        const auto indices =
+            std::make_shared<op::v0::Parameter>(params.indicesTensor.type, PartialShape{params.indicesTensor.shape});
         const auto gatherElement = std::make_shared<op::v6::GatherElements>(data, indices, params.axis);
-        function = std::make_shared<ov::Model>(NodeVector {gatherElement}, ParameterVector {data, indices});
+        function = std::make_shared<ov::Model>(NodeVector{gatherElement}, ParameterVector{data, indices});
         return function;
     }
 };
 
-class ReferenceGatherElementsTestNegative : public ReferenceGatherElementsTest {
-};
+class ReferenceGatherElementsTestNegative : public ReferenceGatherElementsTest {};
 
 TEST_P(ReferenceGatherElementsTest, CompareWithRefs) {
     Exec();
@@ -85,37 +90,32 @@ TEST_P(ReferenceGatherElementsTestNegative, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<GatherElementsParams> generateParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<GatherElementsParams> params {
-        GatherElementsParams(
-            reference_tests::Tensor(IN_ET, {3}, std::vector<T>{1, 2, 3}),
-            reference_tests::Tensor(element::i32, {7}, std::vector<int32_t>{1, 2, 0, 2, 0, 0, 2}),
-            0,
-            reference_tests::Tensor(IN_ET, {7}, std::vector<T>{2, 3, 1, 3, 1, 1, 3}),
-            "evaluate_1D_gather_elements_3_indices_int32"),
-        GatherElementsParams(
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
-            reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 0, 0}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 4, 1, 2}),
-            "evaluate_2D_gather_elements_2x2_indices_int32_axis_0"),
-        GatherElementsParams(
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
-            reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 0, 0}),
-            1,
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 3}),
-            "evaluate_2D_gather_elements_2x2_indices_int32_axis_1"),
-        GatherElementsParams(
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
-            reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 0, 0}),
-            -1,
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 3}),
-            "evaluate_2D_gather_elements_2x2_indices_int32_axis_minus_1"),
-        GatherElementsParams(
-            reference_tests::Tensor(IN_ET, {3, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9}),
-            reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{1, 2, 0, 2, 0, 0}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 3}, std::vector<T>{4, 8, 3, 7, 2, 3}),
-            "evaluate_2D_gather_elements_2x3_indices_int32"),
+    std::vector<GatherElementsParams> params{
+        GatherElementsParams(reference_tests::Tensor(IN_ET, {3}, std::vector<T>{1, 2, 3}),
+                             reference_tests::Tensor(element::i32, {7}, std::vector<int32_t>{1, 2, 0, 2, 0, 0, 2}),
+                             0,
+                             reference_tests::Tensor(IN_ET, {7}, std::vector<T>{2, 3, 1, 3, 1, 1, 3}),
+                             "evaluate_1D_gather_elements_3_indices_int32"),
+        GatherElementsParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
+                             reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 0, 0}),
+                             0,
+                             reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 4, 1, 2}),
+                             "evaluate_2D_gather_elements_2x2_indices_int32_axis_0"),
+        GatherElementsParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
+                             reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 0, 0}),
+                             1,
+                             reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 3}),
+                             "evaluate_2D_gather_elements_2x2_indices_int32_axis_1"),
+        GatherElementsParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 4}),
+                             reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 0, 0}),
+                             -1,
+                             reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{1, 2, 3, 3}),
+                             "evaluate_2D_gather_elements_2x2_indices_int32_axis_minus_1"),
+        GatherElementsParams(reference_tests::Tensor(IN_ET, {3, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9}),
+                             reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{1, 2, 0, 2, 0, 0}),
+                             0,
+                             reference_tests::Tensor(IN_ET, {2, 3}, std::vector<T>{4, 8, 3, 7, 2, 3}),
+                             "evaluate_2D_gather_elements_2x3_indices_int32"),
         GatherElementsParams(
             reference_tests::Tensor(IN_ET, {3, 2, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
             reference_tests::Tensor(element::i32, {3, 2, 2}, std::vector<int32_t>{1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1}),
@@ -124,34 +124,31 @@ std::vector<GatherElementsParams> generateParams() {
             "evaluate_3D_gather_elements_3x2x2_indices_int32"),
         GatherElementsParams(
             reference_tests::Tensor(IN_ET, {3, 2, 2, 2}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
-                                                       9,  10, 11, 12, 13, 14, 15, 16,
-                                                       17, 18, 19, 20, 21, 22, 23, 24}),
-            reference_tests::Tensor(element::i32, {3, 2, 2, 4}, std::vector<int32_t>{1, 0, 0, 0, 0, 1, 1, 0,
-                                                                    1, 1, 1, 1, 1, 0, 0, 1,
-                                                                    0, 0, 0, 1, 1, 1, 1, 0,
-                                                                    0, 0, 0, 0, 1, 0, 1, 0,
-                                                                    1, 1, 1, 1, 1, 0, 1, 0,
-                                                                    1, 0, 0, 1, 0, 0, 0, 0}),
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor(
+                element::i32,
+                {3, 2, 2, 4},
+                std::vector<int32_t>{1, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0,
+                                     0, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0}),
             -1,
-            reference_tests::Tensor(IN_ET, {3, 2, 2, 4}, std::vector<T>{2,  1,  1,  1,  3,  4,  4,  3,
-                                                       6,  6,  6,  6,  8,  7,  7,  8,
-                                                       9,  9,  9,  10, 12, 12, 12, 11,
-                                                       13, 13, 13, 13, 16, 15, 16, 15,
-                                                       18, 18, 18, 18, 20, 19, 20, 19,
-                                                       22, 21, 21, 22, 23, 23, 23, 23}),
+            reference_tests::Tensor(IN_ET,
+                                    {3, 2, 2, 4},
+                                    std::vector<T>{2,  1,  1,  1,  3,  4,  4,  3,  6,  6,  6,  6,  8,  7,  7,  8,
+                                                   9,  9,  9,  10, 12, 12, 12, 11, 13, 13, 13, 13, 16, 15, 16, 15,
+                                                   18, 18, 18, 18, 20, 19, 20, 19, 22, 21, 21, 22, 23, 23, 23, 23}),
             "evaluate_4D_gather_elements_3x2x2x2_indices_int64"),
         GatherElementsParams(
-            reference_tests::Tensor(IN_ET, {3, 2, 2}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8, 9,  10, 11, 12}),
+            reference_tests::Tensor(IN_ET, {3, 2, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
             reference_tests::Tensor(element::i32, {3, 2, 2}, std::vector<int32_t>{1, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1}),
             -1,
             reference_tests::Tensor(IN_ET, {3, 2, 2}, std::vector<T>{2, 1, 3, 4, 6, 6, 8, 7, 9, 9, 12, 12}),
             "evaluate_3D_gather_elements_3x2x2_indices_int64"),
-        GatherElementsParams(
-            reference_tests::Tensor(IN_ET, {3, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9}),
-            reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{1, 2, 0, 2, 0, 0}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 3}, std::vector<T>{4, 8, 3, 7, 2, 3}),
-            "evaluate_2D_gather_elements_2x3_data_float32"),
+        GatherElementsParams(reference_tests::Tensor(IN_ET, {3, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9}),
+                             reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{1, 2, 0, 2, 0, 0}),
+                             0,
+                             reference_tests::Tensor(IN_ET, {2, 3}, std::vector<T>{4, 8, 3, 7, 2, 3}),
+                             "evaluate_2D_gather_elements_2x3_data_float32"),
         GatherElementsParams(
             reference_tests::Tensor(IN_ET, {2, 2, 1}, std::vector<T>{5, 4, 1, 4}),
             reference_tests::Tensor(element::i32, {4, 2, 1}, std::vector<int32_t>{0, 0, 1, 1, 1, 1, 0, 1}),
@@ -164,7 +161,7 @@ std::vector<GatherElementsParams> generateParams() {
 
 template <>
 std::vector<GatherElementsParams> generateParams<element::Type_t::boolean>() {
-    std::vector<GatherElementsParams> params {
+    std::vector<GatherElementsParams> params{
         GatherElementsParams(
             reference_tests::Tensor(element::boolean, {3, 2}, std::vector<char>{true, false, true, true, false, false}),
             reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 0, 2}),
@@ -176,13 +173,12 @@ std::vector<GatherElementsParams> generateParams<element::Type_t::boolean>() {
 }
 
 std::vector<GatherElementsParams> generateParamsNegative() {
-    std::vector<GatherElementsParams> params {
-        GatherElementsParams(
-            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{1, 2, 3}),
-            reference_tests::Tensor(element::i32, {7}, std::vector<int32_t>{1, 2, 0, 2, 0, 0, 8}),
-            0,
-            reference_tests::Tensor(element::i32, {7}, std::vector<int32_t>{2, 3, 1, 3, 1, 1, 3}),
-            "evaluate_1D_gather_elements_negative_test"),
+    std::vector<GatherElementsParams> params{
+        GatherElementsParams(reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{1, 2, 3}),
+                             reference_tests::Tensor(element::i32, {7}, std::vector<int32_t>{1, 2, 0, 2, 0, 0, 8}),
+                             0,
+                             reference_tests::Tensor(element::i32, {7}, std::vector<int32_t>{2, 3, 1, 3, 1, 1, 3}),
+                             "evaluate_1D_gather_elements_negative_test"),
         GatherElementsParams(
             reference_tests::Tensor(element::i32, {3, 3}, std::vector<int32_t>{1, 2, 3, 4, 5, 6, 7, 8, 9}),
             reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{1, 3, 0, 2, 0, 0}),
@@ -194,7 +190,7 @@ std::vector<GatherElementsParams> generateParamsNegative() {
 }
 
 std::vector<GatherElementsParams> generateCombinedParams() {
-    const std::vector<std::vector<GatherElementsParams>> generatedParams {
+    const std::vector<std::vector<GatherElementsParams>> generatedParams{
         generateParams<element::Type_t::boolean>(),
         generateParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
@@ -217,9 +213,13 @@ std::vector<GatherElementsParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GatherElements_With_Hardcoded_Refs, ReferenceGatherElementsTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceGatherElementsTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_GatherElements_With_Hardcoded_Refs,
+                         ReferenceGatherElementsTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceGatherElementsTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_GatherElements_With_Hardcoded_Refs, ReferenceGatherElementsTestNegative,
-    testing::ValuesIn(generateParamsNegative()), ReferenceGatherElementsTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_GatherElements_With_Hardcoded_Refs,
+                         ReferenceGatherElementsTestNegative,
+                         testing::ValuesIn(generateParamsNegative()),
+                         ReferenceGatherElementsTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/gather_nd.cpp b/src/plugins/template/tests/functional/op_reference/gather_nd.cpp
index 9ff1507be4f230..bbb7fb07026a2e 100644
--- a/src/plugins/template/tests/functional/op_reference/gather_nd.cpp
+++ b/src/plugins/template/tests/functional/op_reference/gather_nd.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/gather_nd.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/gather_nd.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,11 +13,16 @@ using namespace ov;
 
 namespace {
 struct GatherNDParams {
-    GatherNDParams(
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& indicesTensor, int64_t batchDims,
-        const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), indicesTensor(indicesTensor), batchDims(static_cast<int32_t>(batchDims)),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    GatherNDParams(const reference_tests::Tensor& dataTensor,
+                   const reference_tests::Tensor& indicesTensor,
+                   int64_t batchDims,
+                   const reference_tests::Tensor& expectedTensor,
+                   const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          indicesTensor(indicesTensor),
+          batchDims(static_cast<int32_t>(batchDims)),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor indicesTensor;
@@ -55,17 +61,17 @@ class ReferenceGatherND5Test : public testing::TestWithParam<GatherNDParams>, pu
 private:
     static std::shared_ptr<Model> CreateFunction(const GatherNDParams& params) {
         std::shared_ptr<Model> function;
-        const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type,
-                                                              PartialShape{params.dataTensor.shape});
-        const auto indices = std::make_shared<op::v0::Parameter>(params.indicesTensor.type,
-                                                                 PartialShape{params.indicesTensor.shape});
+        const auto data =
+            std::make_shared<op::v0::Parameter>(params.dataTensor.type, PartialShape{params.dataTensor.shape});
+        const auto indices =
+            std::make_shared<op::v0::Parameter>(params.indicesTensor.type, PartialShape{params.indicesTensor.shape});
         std::shared_ptr<op::v5::GatherND> gatherND;
         if (params.batchDims == 0) {
             gatherND = std::make_shared<op::v5::GatherND>(data, indices);
         } else {
             gatherND = std::make_shared<op::v5::GatherND>(data, indices, params.batchDims);
         }
-        function = std::make_shared<ov::Model>(NodeVector {gatherND}, ParameterVector {data, indices});
+        function = std::make_shared<ov::Model>(NodeVector{gatherND}, ParameterVector{data, indices});
         return function;
     }
 };
@@ -77,101 +83,94 @@ TEST_P(ReferenceGatherND5Test, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<GatherNDParams> generateParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<GatherNDParams> params {
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {3, 3}, std::vector<T>{10, 11, 12, 13, 14, 15, 16, 17, 18}),
-            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 2}),
-            0,
-            reference_tests::Tensor(IN_ET, {}, std::vector<T>{15}),
-            "gather_nd_single_indices"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
-            reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 0, 1, 1}),
-            0,
-            reference_tests::Tensor(IN_ET, {2}, std::vector<T>{10, 13}),
-            "gather_nd_scalar_from_2d"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
-            reference_tests::Tensor(element::i32, {2, 1}, std::vector<int32_t>{1, 0}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{12, 13, 10, 11}),
-            "gather_nd_1d_from_2d"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-            reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{0, 0, 1, 1, 0, 1}),
-            0,
-            reference_tests::Tensor(IN_ET, {2}, std::vector<T>{11, 21}),
-            "gather_nd_scalar_from_3d"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-            reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 1, 0}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{12, 13, 20, 21}),
-            "gather_nd_1d_from_3d"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-            reference_tests::Tensor(element::i32, {1, 1}, std::vector<int32_t>{1}),
-            0,
-            reference_tests::Tensor(IN_ET, {1, 2, 2}, std::vector<T>{20, 21, 22, 23}),
-            "gather_nd_2d_from_3d"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
-            reference_tests::Tensor(element::i32, {2, 1, 2}, std::vector<int32_t>{0, 0, 0, 1}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 1}, std::vector<T>{10, 11}),
-            "gather_nd_batch_scalar_from_2d"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
-            reference_tests::Tensor(element::i32, {2, 1, 1}, std::vector<int32_t>{1, 0}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 1, 2}, std::vector<T>{12, 13, 10, 11}),
-            "gather_nd_batch_1d_from_2d"),
+    std::vector<GatherNDParams> params{
+        GatherNDParams(reference_tests::Tensor(IN_ET, {3, 3}, std::vector<T>{10, 11, 12, 13, 14, 15, 16, 17, 18}),
+                       reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 2}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {}, std::vector<T>{15}),
+                       "gather_nd_single_indices"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
+                       reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 0, 1, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2}, std::vector<T>{10, 13}),
+                       "gather_nd_scalar_from_2d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
+                       reference_tests::Tensor(element::i32, {2, 1}, std::vector<int32_t>{1, 0}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{12, 13, 10, 11}),
+                       "gather_nd_1d_from_2d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{0, 0, 1, 1, 0, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2}, std::vector<T>{11, 21}),
+                       "gather_nd_scalar_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 1, 0}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{12, 13, 20, 21}),
+                       "gather_nd_1d_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {1, 1}, std::vector<int32_t>{1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {1, 2, 2}, std::vector<T>{20, 21, 22, 23}),
+                       "gather_nd_2d_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
+                       reference_tests::Tensor(element::i32, {2, 1, 2}, std::vector<int32_t>{0, 0, 0, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 1}, std::vector<T>{10, 11}),
+                       "gather_nd_batch_scalar_from_2d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
+                       reference_tests::Tensor(element::i32, {2, 1, 1}, std::vector<int32_t>{1, 0}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 1, 2}, std::vector<T>{12, 13, 10, 11}),
+                       "gather_nd_batch_1d_from_2d"),
         GatherNDParams(
             reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
             reference_tests::Tensor(element::i32, {2, 2, 3}, std::vector<int32_t>{0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0}),
             0,
             reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{11, 21, 13, 22}),
             "gather_nd_batch_scalar_from_3d"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-            reference_tests::Tensor(element::i32, {2, 2, 2}, std::vector<int32_t>{0, 1, 1, 0, 0, 0, 1, 1}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{12, 13, 20, 21, 10, 11, 22, 23}),
-            "gather_nd_batch_1d_from_3d"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-            reference_tests::Tensor(element::i32, {2, 2, 2}, std::vector<int32_t>{0, -1, -1, 0, 0, 0, 1, 1}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{12, 13, 20, 21, 10, 11, 22, 23}),
-            "gather_nd_batch_1d_from_3d_negative"),
-        GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-            reference_tests::Tensor(element::i32, {2, 1, 1}, std::vector<int32_t>{1, 0}),
-            0,
-            reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{20, 21, 22, 23, 10, 11, 12, 13}),
-            "gather_nd_batch_2d_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 2, 2}, std::vector<int32_t>{0, 1, 1, 0, 0, 0, 1, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{12, 13, 20, 21, 10, 11, 22, 23}),
+                       "gather_nd_batch_1d_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 2, 2}, std::vector<int32_t>{0, -1, -1, 0, 0, 0, 1, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{12, 13, 20, 21, 10, 11, 22, 23}),
+                       "gather_nd_batch_1d_from_3d_negative"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 1, 1}, std::vector<int32_t>{1, 0}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{20, 21, 22, 23, 10, 11, 12, 13}),
+                       "gather_nd_batch_2d_from_3d"),
         GatherNDParams(
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                    13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
+                                                                     13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor(element::i32, {2, 1}, std::vector<int32_t>{1, 0}),
             1,
             reference_tests::Tensor(IN_ET, {2, 4}, std::vector<T>{5, 6, 7, 8, 13, 14, 15, 16}),
             "gather_nd_batch_dims1"),
         GatherNDParams(
-            reference_tests::Tensor(IN_ET, {2, 3, 4, 2}, std::vector<T>{
-                1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16,
-                17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
-                33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48}),
-            reference_tests::Tensor(element::i32, {2, 3, 3, 2}, std::vector<int32_t>{
-                1, 0, 3, 1, 2, 1, 0, 1, 1, 1, 2, 0, 3, 0, 3, 1, 2, 1,
-                2, 0, 1, 1, 3, 1, 1, 1, 2, 0, 2, 0, 0, 0, 3, 1, 3, 1}),
+            reference_tests::Tensor(IN_ET,
+                                    {2, 3, 4, 2},
+                                    std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16,
+                                                   17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
+                                                   33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48}),
+            reference_tests::Tensor(element::i32,
+                                    {2, 3, 3, 2},
+                                    std::vector<int32_t>{1, 0, 3, 1, 2, 1, 0, 1, 1, 1, 2, 0, 3, 0, 3, 1, 2, 1,
+                                                         2, 0, 1, 1, 3, 1, 1, 1, 2, 0, 2, 0, 0, 0, 3, 1, 3, 1}),
             2,
-            reference_tests::Tensor(IN_ET, {6, 3}, std::vector<T>{
-                3, 8, 6, 10, 12, 13, 23, 24, 22, 29, 28, 32, 36, 37, 37, 41, 48, 48}),
+            reference_tests::Tensor(
+                IN_ET,
+                {6, 3},
+                std::vector<T>{3, 8, 6, 10, 12, 13, 23, 24, 22, 29, 28, 32, 36, 37, 37, 41, 48, 48}),
             "gather_nd_batch_dims2"),
         GatherNDParams(
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                    13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
+                                                                     13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor(element::i32, {2, 3, 1, 1}, std::vector<int32_t>{1, 0, 2, 0, 2, 2}),
             2,
             reference_tests::Tensor(IN_ET, {6, 1}, std::vector<T>{2, 5, 11, 13, 19, 23}),
@@ -181,7 +180,7 @@ std::vector<GatherNDParams> generateParams() {
 }
 
 std::vector<GatherNDParams> generateCombinedParams() {
-    const std::vector<std::vector<GatherNDParams>> generatedParams {
+    const std::vector<std::vector<GatherNDParams>> generatedParams{
         generateParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
         generateParams<element::Type_t::i32>(),
@@ -203,9 +202,10 @@ std::vector<GatherNDParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GatherND_With_Hardcoded_Refs, ReferenceGatherND5Test,
-    testing::ValuesIn(generateCombinedParams()), ReferenceGatherND5Test::getTestCaseName);
-
+INSTANTIATE_TEST_SUITE_P(smoke_GatherND_With_Hardcoded_Refs,
+                         ReferenceGatherND5Test,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceGatherND5Test::getTestCaseName);
 
 class ReferenceGatherND8Test : public testing::TestWithParam<GatherNDParams>, public CommonReferenceTest {
 public:
@@ -237,17 +237,17 @@ class ReferenceGatherND8Test : public testing::TestWithParam<GatherNDParams>, pu
 private:
     static std::shared_ptr<Model> CreateFunction(const GatherNDParams& params) {
         std::shared_ptr<Model> function;
-        const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type,
-                                                              PartialShape{params.dataTensor.shape});
-        const auto indices = std::make_shared<op::v0::Parameter>(params.indicesTensor.type,
-                                                                 PartialShape{params.indicesTensor.shape});
+        const auto data =
+            std::make_shared<op::v0::Parameter>(params.dataTensor.type, PartialShape{params.dataTensor.shape});
+        const auto indices =
+            std::make_shared<op::v0::Parameter>(params.indicesTensor.type, PartialShape{params.indicesTensor.shape});
         std::shared_ptr<op::v8::GatherND> gatherND;
         if (params.batchDims == 0) {
             gatherND = std::make_shared<op::v8::GatherND>(data, indices);
         } else {
             gatherND = std::make_shared<op::v8::GatherND>(data, indices, params.batchDims);
         }
-        function = std::make_shared<ov::Model>(NodeVector {gatherND}, ParameterVector {data, indices});
+        function = std::make_shared<ov::Model>(NodeVector{gatherND}, ParameterVector{data, indices});
         return function;
     }
 };
@@ -259,142 +259,139 @@ TEST_P(ReferenceGatherND8Test, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<GatherNDParams> generateParams_v8() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<GatherNDParams> params {
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {3, 3}, std::vector<T>{10, 11, 12, 13, 14, 15, 16, 17, 18}),
-                    reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 2}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {}, std::vector<T>{15}),
-                    "gather_nd_8_single_indices"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
-                    reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 0, 1, 1}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2}, std::vector<T>{10, 13}),
-                    "gather_nd_8_scalar_from_2d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
-                    reference_tests::Tensor(element::i32, {2, 1}, std::vector<int32_t>{1, 0}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{12, 13, 10, 11}),
-                    "gather_nd_8_1d_from_2d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-                    reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{0, 0, 1, 1, 0, 1}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2}, std::vector<T>{11, 21}),
-                    "gather_nd_8_scalar_from_3d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-                    reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 1, 0}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{12, 13, 20, 21}),
-                    "gather_nd_8_1d_from_3d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-                    reference_tests::Tensor(element::i32, {1, 1}, std::vector<int32_t>{1}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {1, 2, 2}, std::vector<T>{20, 21, 22, 23}),
-                    "gather_nd_8_2d_from_3d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
-                    reference_tests::Tensor(element::i32, {2, 1, 2}, std::vector<int32_t>{0, 0, 0, 1}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2, 1}, std::vector<T>{10, 11}),
-                    "gather_nd_8_batch_scalar_from_2d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
-                    reference_tests::Tensor(element::i32, {2, 1, 1}, std::vector<int32_t>{1, 0}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2, 1, 2}, std::vector<T>{12, 13, 10, 11}),
-                    "gather_nd_8_batch_1d_from_2d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-                    reference_tests::Tensor(element::i32, {2, 2, 3}, std::vector<int32_t>{0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{11, 21, 13, 22}),
-                    "gather_nd_8_batch_scalar_from_3d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-                    reference_tests::Tensor(element::i32, {2, 2, 2}, std::vector<int32_t>{0, 1, 1, 0, 0, 0, 1, 1}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{12, 13, 20, 21, 10, 11, 22, 23}),
-                    "gather_nd_8_batch_1d_from_3d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-                    reference_tests::Tensor(element::i32, {2, 2, 2}, std::vector<int32_t>{0, -1, -1, 0, 0, 0, 1, 1}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{12, 13, 20, 21, 10, 11, 22, 23}),
-                    "gather_nd_8_batch_1d_from_3d_negative"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
-                    reference_tests::Tensor(element::i32, {2, 1, 1}, std::vector<int32_t>{1, 0}),
-                    0,
-                    reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{20, 21, 22, 23, 10, 11, 12, 13}),
-                    "gather_nd_8_batch_2d_from_3d"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                            13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
-                    reference_tests::Tensor(element::i32, {2, 1}, std::vector<int32_t>{1, 0}),
-                    1,
-                    reference_tests::Tensor(IN_ET, {2, 4}, std::vector<T>{5, 6, 7, 8, 13, 14, 15, 16}),
-                    "gather_nd_8_batch_dims1"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 3, 4, 2}, std::vector<T>{
-                            1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16,
-                            17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
-                            33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48}),
-                    reference_tests::Tensor(element::i32, {2, 3, 3, 2}, std::vector<int32_t>{
-                            1, 0, 3, 1, 2, 1, 0, 1, 1, 1, 2, 0, 3, 0, 3, 1, 2, 1,
-                            2, 0, 1, 1, 3, 1, 1, 1, 2, 0, 2, 0, 0, 0, 3, 1, 3, 1}),
-                    2,
-                    reference_tests::Tensor(IN_ET, {2, 3, 3}, std::vector<T>{
-                            3, 8, 6, 10, 12, 13, 23, 24, 22, 29, 28, 32, 36, 37, 37, 41, 48, 48}),
-                    "gather_8_nd_batch_dims2"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                            13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
-                    reference_tests::Tensor(element::i32, {2, 3, 1, 1}, std::vector<int32_t>{1, 0, 2, 0, 2, 2}),
-                    2,
-                    reference_tests::Tensor(IN_ET, {2, 3, 1}, std::vector<T>{2, 5, 11, 13, 19, 23}),
-                    "gather_8_nd_batch_dims2_lead_dims"),
-            GatherNDParams(
-                    reference_tests::Tensor(IN_ET, {2, 3, 4, 5}, std::vector<T>{
-                            1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16,
-                            17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
-                            33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,
-                            49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64,
-                            65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
-                            81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96,
-                            97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110,
-                            111, 112, 113, 114, 115, 116, 117, 118, 119, 120}),
-                    reference_tests::Tensor(element::i32, {2, 3, 2, 1}, std::vector<int32_t>{
-                            1, 0, 2, 0, 2, 0, 1, 0, 2, 0, 2, 0}),
-                    2,
-                    reference_tests::Tensor(IN_ET, {2, 3, 2, 5}, std::vector<T>{
-                            6, 7, 8, 9, 10, 1, 2, 3, 4, 5, 31, 32, 33, 34, 35, 21, 22, 23,
-                            24, 25, 51, 52, 53, 54, 55, 41, 42, 43, 44, 45, 66, 67, 68, 69,
-                            70, 61, 62, 63, 64, 65, 91, 92, 93, 94, 95, 81, 82, 83, 84, 85,
-                            111, 112, 113, 114, 115, 101, 102, 103, 104, 105}),
-                    "gather_8_nd_batch_dims2_non_scalar_slices"),
+    std::vector<GatherNDParams> params{
+        GatherNDParams(reference_tests::Tensor(IN_ET, {3, 3}, std::vector<T>{10, 11, 12, 13, 14, 15, 16, 17, 18}),
+                       reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 2}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {}, std::vector<T>{15}),
+                       "gather_nd_8_single_indices"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
+                       reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 0, 1, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2}, std::vector<T>{10, 13}),
+                       "gather_nd_8_scalar_from_2d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
+                       reference_tests::Tensor(element::i32, {2, 1}, std::vector<int32_t>{1, 0}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{12, 13, 10, 11}),
+                       "gather_nd_8_1d_from_2d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 3}, std::vector<int32_t>{0, 0, 1, 1, 0, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2}, std::vector<T>{11, 21}),
+                       "gather_nd_8_scalar_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 2}, std::vector<int32_t>{0, 1, 1, 0}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{12, 13, 20, 21}),
+                       "gather_nd_8_1d_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {1, 1}, std::vector<int32_t>{1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {1, 2, 2}, std::vector<T>{20, 21, 22, 23}),
+                       "gather_nd_8_2d_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
+                       reference_tests::Tensor(element::i32, {2, 1, 2}, std::vector<int32_t>{0, 0, 0, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 1}, std::vector<T>{10, 11}),
+                       "gather_nd_8_batch_scalar_from_2d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{10, 11, 12, 13}),
+                       reference_tests::Tensor(element::i32, {2, 1, 1}, std::vector<int32_t>{1, 0}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 1, 2}, std::vector<T>{12, 13, 10, 11}),
+                       "gather_nd_8_batch_1d_from_2d"),
+        GatherNDParams(
+            reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+            reference_tests::Tensor(element::i32, {2, 2, 3}, std::vector<int32_t>{0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0}),
+            0,
+            reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{11, 21, 13, 22}),
+            "gather_nd_8_batch_scalar_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 2, 2}, std::vector<int32_t>{0, 1, 1, 0, 0, 0, 1, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{12, 13, 20, 21, 10, 11, 22, 23}),
+                       "gather_nd_8_batch_1d_from_3d"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 2, 2}, std::vector<int32_t>{0, -1, -1, 0, 0, 0, 1, 1}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{12, 13, 20, 21, 10, 11, 22, 23}),
+                       "gather_nd_8_batch_1d_from_3d_negative"),
+        GatherNDParams(reference_tests::Tensor(IN_ET, {2, 2, 2}, std::vector<T>{10, 11, 12, 13, 20, 21, 22, 23}),
+                       reference_tests::Tensor(element::i32, {2, 1, 1}, std::vector<int32_t>{1, 0}),
+                       0,
+                       reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{20, 21, 22, 23, 10, 11, 12, 13}),
+                       "gather_nd_8_batch_2d_from_3d"),
+        GatherNDParams(
+            reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                     13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor(element::i32, {2, 1}, std::vector<int32_t>{1, 0}),
+            1,
+            reference_tests::Tensor(IN_ET, {2, 4}, std::vector<T>{5, 6, 7, 8, 13, 14, 15, 16}),
+            "gather_nd_8_batch_dims1"),
+        GatherNDParams(
+            reference_tests::Tensor(IN_ET,
+                                    {2, 3, 4, 2},
+                                    std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16,
+                                                   17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
+                                                   33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48}),
+            reference_tests::Tensor(element::i32,
+                                    {2, 3, 3, 2},
+                                    std::vector<int32_t>{1, 0, 3, 1, 2, 1, 0, 1, 1, 1, 2, 0, 3, 0, 3, 1, 2, 1,
+                                                         2, 0, 1, 1, 3, 1, 1, 1, 2, 0, 2, 0, 0, 0, 3, 1, 3, 1}),
+            2,
+            reference_tests::Tensor(
+                IN_ET,
+                {2, 3, 3},
+                std::vector<T>{3, 8, 6, 10, 12, 13, 23, 24, 22, 29, 28, 32, 36, 37, 37, 41, 48, 48}),
+            "gather_8_nd_batch_dims2"),
+        GatherNDParams(
+            reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                     13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor(element::i32, {2, 3, 1, 1}, std::vector<int32_t>{1, 0, 2, 0, 2, 2}),
+            2,
+            reference_tests::Tensor(IN_ET, {2, 3, 1}, std::vector<T>{2, 5, 11, 13, 19, 23}),
+            "gather_8_nd_batch_dims2_lead_dims"),
+        GatherNDParams(
+            reference_tests::Tensor(
+                IN_ET,
+                {2, 3, 4, 5},
+                std::vector<T>{1,   2,   3,   4,   5,   6,   7,   8,   9,   10,  11,  12,  13,  14,  15,  16,  17,  18,
+                               19,  20,  21,  22,  23,  24,  25,  26,  27,  28,  29,  30,  31,  32,  33,  34,  35,  36,
+                               37,  38,  39,  40,  41,  42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,  54,
+                               55,  56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,  70,  71,  72,
+                               73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,  84,  85,  86,  87,  88,  89,  90,
+                               91,  92,  93,  94,  95,  96,  97,  98,  99,  100, 101, 102, 103, 104, 105, 106, 107, 108,
+                               109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120}),
+            reference_tests::Tensor(element::i32,
+                                    {2, 3, 2, 1},
+                                    std::vector<int32_t>{1, 0, 2, 0, 2, 0, 1, 0, 2, 0, 2, 0}),
+            2,
+            reference_tests::Tensor(
+                IN_ET,
+                {2, 3, 2, 5},
+                std::vector<T>{6,  7,  8,  9,  10, 1,   2,   3,   4,   5,   31,  32,  33,  34,  35,
+                               21, 22, 23, 24, 25, 51,  52,  53,  54,  55,  41,  42,  43,  44,  45,
+                               66, 67, 68, 69, 70, 61,  62,  63,  64,  65,  91,  92,  93,  94,  95,
+                               81, 82, 83, 84, 85, 111, 112, 113, 114, 115, 101, 102, 103, 104, 105}),
+            "gather_8_nd_batch_dims2_non_scalar_slices"),
     };
     return params;
 }
 
 std::vector<GatherNDParams> generateCombinedParams_v8() {
-    const std::vector<std::vector<GatherNDParams>> generatedParams {
-            generateParams_v8<element::Type_t::i8>(),
-            generateParams_v8<element::Type_t::i16>(),
-            generateParams_v8<element::Type_t::i32>(),
-            generateParams_v8<element::Type_t::i64>(),
-            generateParams_v8<element::Type_t::u8>(),
-            generateParams_v8<element::Type_t::u16>(),
-            generateParams_v8<element::Type_t::u32>(),
-            generateParams_v8<element::Type_t::u64>(),
-            generateParams_v8<element::Type_t::bf16>(),
-            generateParams_v8<element::Type_t::f16>(),
-            generateParams_v8<element::Type_t::f32>(),
-            generateParams_v8<element::Type_t::f64>(),
+    const std::vector<std::vector<GatherNDParams>> generatedParams{
+        generateParams_v8<element::Type_t::i8>(),
+        generateParams_v8<element::Type_t::i16>(),
+        generateParams_v8<element::Type_t::i32>(),
+        generateParams_v8<element::Type_t::i64>(),
+        generateParams_v8<element::Type_t::u8>(),
+        generateParams_v8<element::Type_t::u16>(),
+        generateParams_v8<element::Type_t::u32>(),
+        generateParams_v8<element::Type_t::u64>(),
+        generateParams_v8<element::Type_t::bf16>(),
+        generateParams_v8<element::Type_t::f16>(),
+        generateParams_v8<element::Type_t::f32>(),
+        generateParams_v8<element::Type_t::f64>(),
     };
     std::vector<GatherNDParams> combinedParams;
 
@@ -404,6 +401,8 @@ std::vector<GatherNDParams> generateCombinedParams_v8() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GatherND_With_Hardcoded_Refs, ReferenceGatherND8Test,
-        testing::ValuesIn(generateCombinedParams_v8()), ReferenceGatherND8Test::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_GatherND_With_Hardcoded_Refs,
+                         ReferenceGatherND8Test,
+                         testing::ValuesIn(generateCombinedParams_v8()),
+                         ReferenceGatherND8Test::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/gather_tree.cpp b/src/plugins/template/tests/functional/op_reference/gather_tree.cpp
index e79917a1826467..696820760e8fea 100644
--- a/src/plugins/template/tests/functional/op_reference/gather_tree.cpp
+++ b/src/plugins/template/tests/functional/op_reference/gather_tree.cpp
@@ -4,8 +4,8 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -64,7 +64,8 @@ class ReferenceGatherTreeTest : public testing::TestWithParam<GatherTreeParams>,
         const auto max_seq_len = std::make_shared<opset1::Parameter>(params.maxSeqLen.type, params.maxSeqLen.shape);
         const auto end_token = std::make_shared<opset1::Parameter>(params.endToken.type, params.endToken.shape);
         const auto gather_tree = std::make_shared<opset1::GatherTree>(step_ids, parent_idx, max_seq_len, end_token);
-        const auto f = std::make_shared<Model>(gather_tree, ParameterVector{step_ids, parent_idx, max_seq_len, end_token});
+        const auto f =
+            std::make_shared<Model>(gather_tree, ParameterVector{step_ids, parent_idx, max_seq_len, end_token});
         return f;
     }
 };
@@ -76,84 +77,72 @@ TEST_P(ReferenceGatherTreeTest, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<GatherTreeParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<GatherTreeParams> params {
-        Builder {}
-        .stepIds(reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{
-            1, 4, 9, 7, 9, 1, 2, 3, 9, 9}))
-        .parentIdx(reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{
-            1, 4, 9, 7, 9, 1, 2, 3, 9, 9}))
-        .maxSeqLen(reference_tests::Tensor(ET, {1}, std::vector<T>{9}))
-        .endToken(reference_tests::Tensor(ET, {}, std::vector<T>{9}))
-        .finalIdx(reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{
-            1, 4, 9, 7, 9, 1, 2, 3, 9, 9}))
-        .testcaseName("gather_tree_1"),
+    std::vector<GatherTreeParams> params{
+        Builder{}
+            .stepIds(reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{1, 4, 9, 7, 9, 1, 2, 3, 9, 9}))
+            .parentIdx(reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{1, 4, 9, 7, 9, 1, 2, 3, 9, 9}))
+            .maxSeqLen(reference_tests::Tensor(ET, {1}, std::vector<T>{9}))
+            .endToken(reference_tests::Tensor(ET, {}, std::vector<T>{9}))
+            .finalIdx(reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{1, 4, 9, 7, 9, 1, 2, 3, 9, 9}))
+            .testcaseName("gather_tree_1"),
 
-        Builder {}
-        .stepIds(reference_tests::Tensor(ET, {5, 1, 10}, std::vector<T>{
-            1, 4, 9, 7, 9, 1, 2, 3, 9, 2,
-            3, 1, 4, 2, 4, 4, 7, 4, 9, 5,
-            8, 4, 3, 7, 5, 2, 4, 8, 3, 1,
-            5, 7, 9, 4, 5, 6, 4, 2, 9, 2,
-            8, 8, 7, 9, 8, 3, 1, 7, 5, 9}))
-        .parentIdx(reference_tests::Tensor(ET, {5, 1, 10}, std::vector<T>{
-            1, 4, 9, 7, 9, 1, 2, 3, 9, 2,
-            3, 1, 4, 2, 4, 4, 7, 4, 9, 5,
-            8, 4, 3, 7, 5, 2, 4, 8, 3, 1,
-            5, 7, 9, 4, 5, 6, 4, 2, 9, 2,
-            8, 8, 7, 9, 8, 3, 1, 7, 5, 9}))
-        .maxSeqLen(reference_tests::Tensor(ET, {1}, std::vector<T>{9}))
-        .endToken(reference_tests::Tensor(ET, {}, std::vector<T>{9}))
-        .finalIdx(reference_tests::Tensor(ET, {5, 1, 10}, std::vector<T>{
-            4, 4, 9, 9, 4, 9, 2, 9, 9, 9,
-            1, 1, 9, 9, 1, 9, 9, 9, 9, 9,
-            1, 1, 9, 9, 1, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9}))
-        .testcaseName("gather_tree_5"),
+        Builder{}
+            .stepIds(reference_tests::Tensor(ET, {5, 1, 10}, std::vector<T>{1, 4, 9, 7, 9, 1, 2, 3, 9, 2, 3, 1, 4,
+                                                                            2, 4, 4, 7, 4, 9, 5, 8, 4, 3, 7, 5, 2,
+                                                                            4, 8, 3, 1, 5, 7, 9, 4, 5, 6, 4, 2, 9,
+                                                                            2, 8, 8, 7, 9, 8, 3, 1, 7, 5, 9}))
+            .parentIdx(reference_tests::Tensor(ET, {5, 1, 10}, std::vector<T>{1, 4, 9, 7, 9, 1, 2, 3, 9, 2, 3, 1, 4,
+                                                                              2, 4, 4, 7, 4, 9, 5, 8, 4, 3, 7, 5, 2,
+                                                                              4, 8, 3, 1, 5, 7, 9, 4, 5, 6, 4, 2, 9,
+                                                                              2, 8, 8, 7, 9, 8, 3, 1, 7, 5, 9}))
+            .maxSeqLen(reference_tests::Tensor(ET, {1}, std::vector<T>{9}))
+            .endToken(reference_tests::Tensor(ET, {}, std::vector<T>{9}))
+            .finalIdx(reference_tests::Tensor(ET, {5, 1, 10}, std::vector<T>{4, 4, 9, 9, 4, 9, 2, 9, 9, 9, 1, 1, 9,
+                                                                             9, 1, 9, 9, 9, 9, 9, 1, 1, 9, 9, 1, 9,
+                                                                             9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
+                                                                             9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9}))
+            .testcaseName("gather_tree_5"),
 
-        Builder {}
-        .stepIds(reference_tests::Tensor(ET, {20, 1, 10}, std::vector<T>{
-            1, 4, 9, 7, 9, 1, 2, 3, 9, 2, 3, 1, 4, 2, 4, 4, 7, 4, 9, 5,
-            8, 4, 3, 7, 5, 2, 4, 8, 3, 1, 5, 7, 9, 4, 5, 6, 4, 2, 9, 2,
-            8, 8, 7, 9, 8, 3, 1, 7, 5, 8, 8, 9, 8, 1, 8, 1, 3, 2, 1, 8,
-            7, 1, 6, 4, 7, 9, 4, 5, 2, 7, 3, 3, 2, 7, 8, 8, 4, 1, 1, 7,
-            6, 9, 6, 7, 3, 3, 5, 8, 2, 1, 1, 5, 5, 9, 1, 3, 9, 3, 2, 2,
-            5, 1, 1, 7, 9, 2, 9, 3, 3, 5, 6, 1, 6, 6, 6, 2, 9, 6, 3, 7,
-            3, 1, 5, 4, 9, 7, 5, 4, 5, 1, 7, 5, 1, 6, 2, 5, 8, 9, 1, 6,
-            8, 9, 5, 2, 5, 2, 9, 8, 4, 4, 5, 2, 6, 9, 4, 4, 6, 7, 6, 7,
-            2, 8, 7, 6, 6, 7, 4, 4, 7, 3, 4, 9, 7, 4, 8, 9, 1, 6, 5, 6,
-            1, 2, 8, 9, 1, 5, 4, 6, 9, 4, 4, 3, 7, 9, 7, 6, 3, 1, 7, 9}))
-        .parentIdx(reference_tests::Tensor(ET, {20, 1, 10}, std::vector<T>{
-            1, 4, 9, 7, 9, 1, 2, 3, 9, 2, 3, 1, 4, 2, 4, 4, 7, 4, 9, 5,
-            8, 4, 3, 7, 5, 2, 4, 8, 3, 1, 5, 7, 9, 4, 5, 6, 4, 2, 9, 2,
-            8, 8, 7, 9, 8, 3, 1, 7, 5, 8, 8, 9, 8, 1, 8, 1, 3, 2, 1, 8,
-            7, 1, 6, 4, 7, 9, 4, 5, 2, 7, 3, 3, 2, 7, 8, 8, 4, 1, 1, 7,
-            6, 9, 6, 7, 3, 3, 5, 8, 2, 1, 1, 5, 5, 9, 1, 3, 9, 3, 2, 2,
-            5, 1, 1, 7, 9, 2, 9, 3, 3, 5, 6, 1, 6, 6, 6, 2, 9, 6, 3, 7,
-            3, 1, 5, 4, 9, 7, 5, 4, 5, 1, 7, 5, 1, 6, 2, 5, 8, 9, 1, 6,
-            8, 9, 5, 2, 5, 2, 9, 8, 4, 4, 5, 2, 6, 9, 4, 4, 6, 7, 6, 7,
-            2, 8, 7, 6, 6, 7, 4, 4, 7, 3, 4, 9, 7, 4, 8, 9, 1, 6, 5, 6,
-            1, 2, 8, 9, 1, 5, 4, 6, 9, 4, 4, 3, 7, 9, 7, 6, 3, 1, 7, 9}))
-        .maxSeqLen(reference_tests::Tensor(ET, {1}, std::vector<T>{9}))
-        .endToken(reference_tests::Tensor(ET, {}, std::vector<T>{9}))
-        .finalIdx(reference_tests::Tensor(ET, {20, 1, 10}, std::vector<T>{
-            9, 4, 9, 4, 4, 4, 9, 4, 9, 9, 9, 1, 9, 1, 1, 1, 9, 1, 9, 9,
-            9, 1, 9, 1, 1, 1, 9, 1, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
-            9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9}))
-        .testcaseName("gather_tree_10"),
+        Builder{}
+            .stepIds(reference_tests::Tensor(
+                ET,
+                {20, 1, 10},
+                std::vector<T>{1, 4, 9, 7, 9, 1, 2, 3, 9, 2, 3, 1, 4, 2, 4, 4, 7, 4, 9, 5, 8, 4, 3, 7, 5, 2, 4, 8, 3,
+                               1, 5, 7, 9, 4, 5, 6, 4, 2, 9, 2, 8, 8, 7, 9, 8, 3, 1, 7, 5, 8, 8, 9, 8, 1, 8, 1, 3, 2,
+                               1, 8, 7, 1, 6, 4, 7, 9, 4, 5, 2, 7, 3, 3, 2, 7, 8, 8, 4, 1, 1, 7, 6, 9, 6, 7, 3, 3, 5,
+                               8, 2, 1, 1, 5, 5, 9, 1, 3, 9, 3, 2, 2, 5, 1, 1, 7, 9, 2, 9, 3, 3, 5, 6, 1, 6, 6, 6, 2,
+                               9, 6, 3, 7, 3, 1, 5, 4, 9, 7, 5, 4, 5, 1, 7, 5, 1, 6, 2, 5, 8, 9, 1, 6, 8, 9, 5, 2, 5,
+                               2, 9, 8, 4, 4, 5, 2, 6, 9, 4, 4, 6, 7, 6, 7, 2, 8, 7, 6, 6, 7, 4, 4, 7, 3, 4, 9, 7, 4,
+                               8, 9, 1, 6, 5, 6, 1, 2, 8, 9, 1, 5, 4, 6, 9, 4, 4, 3, 7, 9, 7, 6, 3, 1, 7, 9}))
+            .parentIdx(reference_tests::Tensor(
+                ET,
+                {20, 1, 10},
+                std::vector<T>{1, 4, 9, 7, 9, 1, 2, 3, 9, 2, 3, 1, 4, 2, 4, 4, 7, 4, 9, 5, 8, 4, 3, 7, 5, 2, 4, 8, 3,
+                               1, 5, 7, 9, 4, 5, 6, 4, 2, 9, 2, 8, 8, 7, 9, 8, 3, 1, 7, 5, 8, 8, 9, 8, 1, 8, 1, 3, 2,
+                               1, 8, 7, 1, 6, 4, 7, 9, 4, 5, 2, 7, 3, 3, 2, 7, 8, 8, 4, 1, 1, 7, 6, 9, 6, 7, 3, 3, 5,
+                               8, 2, 1, 1, 5, 5, 9, 1, 3, 9, 3, 2, 2, 5, 1, 1, 7, 9, 2, 9, 3, 3, 5, 6, 1, 6, 6, 6, 2,
+                               9, 6, 3, 7, 3, 1, 5, 4, 9, 7, 5, 4, 5, 1, 7, 5, 1, 6, 2, 5, 8, 9, 1, 6, 8, 9, 5, 2, 5,
+                               2, 9, 8, 4, 4, 5, 2, 6, 9, 4, 4, 6, 7, 6, 7, 2, 8, 7, 6, 6, 7, 4, 4, 7, 3, 4, 9, 7, 4,
+                               8, 9, 1, 6, 5, 6, 1, 2, 8, 9, 1, 5, 4, 6, 9, 4, 4, 3, 7, 9, 7, 6, 3, 1, 7, 9}))
+            .maxSeqLen(reference_tests::Tensor(ET, {1}, std::vector<T>{9}))
+            .endToken(reference_tests::Tensor(ET, {}, std::vector<T>{9}))
+            .finalIdx(reference_tests::Tensor(
+                ET,
+                {20, 1, 10},
+                std::vector<T>{9, 4, 9, 4, 4, 4, 9, 4, 9, 9, 9, 1, 9, 1, 1, 1, 9, 1, 9, 9, 9, 1, 9, 1, 1, 1, 9, 1, 9,
+                               9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
+                               9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
+                               9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
+                               9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
+                               9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9,
+                               9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9}))
+            .testcaseName("gather_tree_10"),
     };
     return params;
 }
 
 std::vector<GatherTreeParams> generateCombinedParams() {
-    const std::vector<std::vector<GatherTreeParams>> generatedParams {
+    const std::vector<std::vector<GatherTreeParams>> generatedParams{
         generateParams<element::Type_t::i32>(),
         generateParams<element::Type_t::f32>(),
     };
@@ -165,6 +154,8 @@ std::vector<GatherTreeParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GatherTree_With_Hardcoded_Refs, ReferenceGatherTreeTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceGatherTreeTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_GatherTree_With_Hardcoded_Refs,
+                         ReferenceGatherTreeTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceGatherTreeTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/gelu.cpp b/src/plugins/template/tests/functional/op_reference/gelu.cpp
index 49593aa8b9a108..08624796c06658 100644
--- a/src/plugins/template/tests/functional/op_reference/gelu.cpp
+++ b/src/plugins/template/tests/functional/op_reference/gelu.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/gelu.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/gelu.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -14,8 +15,11 @@ using namespace InferenceEngine;
 namespace {
 struct GeluParams {
     template <class IT>
-    GeluParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
-                const ov::op::GeluApproximationMode mode)
+    GeluParams(const ov::PartialShape& shape,
+               const ov::element::Type& iType,
+               const std::vector<IT>& iValues,
+               const std::vector<IT>& oValues,
+               const ov::op::GeluApproximationMode mode)
         : mode(mode),
           pshape(shape),
           inType(iType),
@@ -49,11 +53,13 @@ class ReferenceGeluV0LayerTest : public testing::TestWithParam<GeluParams>, publ
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type, const op::GeluApproximationMode mode) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type,
+                                                 const op::GeluApproximationMode mode) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Gelu = std::make_shared<op::v0::Gelu>(in);
-        return std::make_shared<ov::Model>(NodeVector {Gelu}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Gelu}, ParameterVector{in});
     }
 };
 
@@ -76,11 +82,13 @@ class ReferenceGeluV7LayerTest : public testing::TestWithParam<GeluParams>, publ
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type, const op::GeluApproximationMode mode) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type,
+                                                 const op::GeluApproximationMode mode) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Gelu = std::make_shared<op::v7::Gelu>(in, mode);
-        return std::make_shared<ov::Model>(NodeVector {Gelu}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Gelu}, ParameterVector{in});
     }
 };
 
@@ -95,18 +103,19 @@ template <element::Type_t IN_ET>
 std::vector<GeluParams> generateGeluV0FloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<GeluParams> geluParams {
-        GeluParams(ov::PartialShape {8},
-                    IN_ET,
-                    std::vector<T>{-4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0},
-                    std::vector<T>{-0.00012636185, -0.0040495098, -0.04550028, -0.15865529, 0.0, 0.8413447, 1.9544997, 2.9959507},
-                    op::GeluApproximationMode::ERF),
-        GeluParams(ov::PartialShape {3},
-                    IN_ET,
-                    std::vector<T>{-0.5, 0.1, 0.4},
-                    std::vector<T>{-0.15426877, 0.05398279, 0.2621686},
-                    op::GeluApproximationMode::ERF)
-    };
+    std::vector<GeluParams> geluParams{
+        GeluParams(
+            ov::PartialShape{8},
+            IN_ET,
+            std::vector<T>{-4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0},
+            std::vector<
+                T>{-0.00012636185, -0.0040495098, -0.04550028, -0.15865529, 0.0, 0.8413447, 1.9544997, 2.9959507},
+            op::GeluApproximationMode::ERF),
+        GeluParams(ov::PartialShape{3},
+                   IN_ET,
+                   std::vector<T>{-0.5, 0.1, 0.4},
+                   std::vector<T>{-0.15426877, 0.05398279, 0.2621686},
+                   op::GeluApproximationMode::ERF)};
     return geluParams;
 }
 
@@ -114,36 +123,37 @@ template <element::Type_t IN_ET>
 std::vector<GeluParams> generateGeluV7FloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<GeluParams> geluParams {
-        GeluParams(ov::PartialShape {8},
-                    IN_ET,
-                    std::vector<T>{-4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0},
-                    std::vector<T>{-0.00012636185, -0.0040495098, -0.04550028, -0.15865529, 0.0, 0.8413447, 1.9544997, 2.9959507},
-                    op::GeluApproximationMode::ERF),
-        GeluParams(ov::PartialShape {8},
-                    IN_ET,
-                    std::vector<T>{-4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0},
-                    std::vector<T>{-0.00012636185, -0.0040495098, -0.04550028, -0.15865529, 0.0, 0.8413447, 1.9544997, 2.9959507},
-                    op::GeluApproximationMode::TANH),
-        GeluParams(ov::PartialShape {3},
-                    IN_ET,
-                    std::vector<T>{-0.5, 0.1, 0.4},
-                    std::vector<T>{-0.15426877, 0.05398279, 0.2621686},
-                    op::GeluApproximationMode::ERF),
-        GeluParams(ov::PartialShape {3},
-                    IN_ET,
-                    std::vector<T>{-0.5, 0.1, 0.4},
-                    std::vector<T>{-0.15428599, 0.053982753, 0.262161165},
-                    op::GeluApproximationMode::TANH)
-    };
+    std::vector<GeluParams> geluParams{
+        GeluParams(
+            ov::PartialShape{8},
+            IN_ET,
+            std::vector<T>{-4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0},
+            std::vector<
+                T>{-0.00012636185, -0.0040495098, -0.04550028, -0.15865529, 0.0, 0.8413447, 1.9544997, 2.9959507},
+            op::GeluApproximationMode::ERF),
+        GeluParams(
+            ov::PartialShape{8},
+            IN_ET,
+            std::vector<T>{-4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0},
+            std::vector<
+                T>{-0.00012636185, -0.0040495098, -0.04550028, -0.15865529, 0.0, 0.8413447, 1.9544997, 2.9959507},
+            op::GeluApproximationMode::TANH),
+        GeluParams(ov::PartialShape{3},
+                   IN_ET,
+                   std::vector<T>{-0.5, 0.1, 0.4},
+                   std::vector<T>{-0.15426877, 0.05398279, 0.2621686},
+                   op::GeluApproximationMode::ERF),
+        GeluParams(ov::PartialShape{3},
+                   IN_ET,
+                   std::vector<T>{-0.5, 0.1, 0.4},
+                   std::vector<T>{-0.15428599, 0.053982753, 0.262161165},
+                   op::GeluApproximationMode::TANH)};
     return geluParams;
 }
 
 std::vector<GeluParams> generateGeluV0CombinedParams() {
-    const std::vector<std::vector<GeluParams>> geluTypeParams {
-        generateGeluV0FloatParams<element::Type_t::f32>(),
-        generateGeluV0FloatParams<element::Type_t::f16>()
-        };
+    const std::vector<std::vector<GeluParams>> geluTypeParams{generateGeluV0FloatParams<element::Type_t::f32>(),
+                                                              generateGeluV0FloatParams<element::Type_t::f16>()};
     std::vector<GeluParams> combinedParams;
 
     for (const auto& params : geluTypeParams) {
@@ -153,10 +163,8 @@ std::vector<GeluParams> generateGeluV0CombinedParams() {
 }
 
 std::vector<GeluParams> generateGeluV7CombinedParams() {
-    const std::vector<std::vector<GeluParams>> geluTypeParams {
-        generateGeluV7FloatParams<element::Type_t::f32>(),
-        generateGeluV7FloatParams<element::Type_t::f16>()
-        };
+    const std::vector<std::vector<GeluParams>> geluTypeParams{generateGeluV7FloatParams<element::Type_t::f32>(),
+                                                              generateGeluV7FloatParams<element::Type_t::f16>()};
     std::vector<GeluParams> combinedParams;
 
     for (const auto& params : geluTypeParams) {
@@ -165,10 +173,14 @@ std::vector<GeluParams> generateGeluV7CombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Gelu_v2_With_Hardcoded_Refs, ReferenceGeluV0LayerTest,
-    testing::ValuesIn(generateGeluV0CombinedParams()), ReferenceGeluV0LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Gelu_v2_With_Hardcoded_Refs,
+                         ReferenceGeluV0LayerTest,
+                         testing::ValuesIn(generateGeluV0CombinedParams()),
+                         ReferenceGeluV0LayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Gelu_v7_With_Hardcoded_Refs, ReferenceGeluV7LayerTest,
-    testing::ValuesIn(generateGeluV7CombinedParams()), ReferenceGeluV7LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Gelu_v7_With_Hardcoded_Refs,
+                         ReferenceGeluV7LayerTest,
+                         testing::ValuesIn(generateGeluV7CombinedParams()),
+                         ReferenceGeluV7LayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/generate_proposals.cpp b/src/plugins/template/tests/functional/op_reference/generate_proposals.cpp
index 6c51d76b94e5d8..e53b0cc78b55cf 100644
--- a/src/plugins/template/tests/functional/op_reference/generate_proposals.cpp
+++ b/src/plugins/template/tests/functional/op_reference/generate_proposals.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/generate_proposals.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/generate_proposals.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -16,13 +17,20 @@ namespace {
 struct GPParams {
     template <class IT, class RT>
     GPParams(const Attrs& attrs,
-                         const size_t batch, const size_t number_of_channels, const size_t height, const size_t width,
-                         const element::Type& iType, const element::Type& roiNumType,
-                         const std::vector<IT>& imageSizeInfoValues, const std::vector<IT>& anchorsValues,
-                         const std::vector<IT>& deltasValues, const std::vector<IT>& scoresValues,
-                         const std::vector<IT>& refRoisValues, const std::vector<IT>& refScoresValues,
-                         const std::vector<RT>& refRoiNumValues,
-                         const std::string& testcaseName = "")
+             const size_t batch,
+             const size_t number_of_channels,
+             const size_t height,
+             const size_t width,
+             const element::Type& iType,
+             const element::Type& roiNumType,
+             const std::vector<IT>& imageSizeInfoValues,
+             const std::vector<IT>& anchorsValues,
+             const std::vector<IT>& deltasValues,
+             const std::vector<IT>& scoresValues,
+             const std::vector<IT>& refRoisValues,
+             const std::vector<IT>& refScoresValues,
+             const std::vector<RT>& refRoiNumValues,
+             const std::string& testcaseName = "")
         : attrs(attrs),
           inType(iType),
           outType(iType),
@@ -35,11 +43,11 @@ struct GPParams {
           refScoresData(CreateTensor(iType, refScoresValues)),
           refRoiNumData(CreateTensor(roiNumType, refRoiNumValues)),
           testcaseName(testcaseName) {
-              imageSizeInfoShape = Shape{batch, 3};
-              anchorsShape = Shape{height, width, number_of_channels, 4};
-              deltasShape = Shape{batch, number_of_channels * 4, height, width};
-              scoresShape = Shape{batch, number_of_channels, height, width};
-          }
+        imageSizeInfoShape = Shape{batch, 3};
+        anchorsShape = Shape{height, width, number_of_channels, 4};
+        deltasShape = Shape{batch, number_of_channels * 4, height, width};
+        scoresShape = Shape{batch, number_of_channels, height, width};
+    }
 
     Attrs attrs;
     PartialShape imageSizeInfoShape;
@@ -88,13 +96,11 @@ class ReferenceGPLayerTest : public testing::TestWithParam<GPParams>, public Com
         const auto anchors = std::make_shared<op::v0::Parameter>(params.inType, params.anchorsShape);
         const auto deltas = std::make_shared<op::v0::Parameter>(params.inType, params.deltasShape);
         const auto scores = std::make_shared<op::v0::Parameter>(params.inType, params.scoresShape);
-        const auto GenerateProposal = std::make_shared<op::v9::GenerateProposals>(im_info,
-                                                                    anchors,
-                                                                    deltas,
-                                                                    scores,
-                                                                    params.attrs);
+        const auto GenerateProposal =
+            std::make_shared<op::v9::GenerateProposals>(im_info, anchors, deltas, scores, params.attrs);
         GenerateProposal->set_roi_num_type(params.roiNumType);
-        return std::make_shared<ov::Model>(GenerateProposal->outputs(), ParameterVector {im_info, anchors, deltas, scores});
+        return std::make_shared<ov::Model>(GenerateProposal->outputs(),
+                                           ParameterVector{im_info, anchors, deltas, scores});
     }
 };
 
@@ -115,185 +121,194 @@ std::vector<GPParams> generateGPFloatParams() {
     attrs.nms_eta = 1.0;
     attrs.normalized = true;
 
-    std::vector<GPParams> generateProposalParams {
+    std::vector<GPParams> generateProposalParams{
         GPParams(attrs,
-                              1,
-                              3,    // A
-                              2,    // H
-                              6,    // W
-                              IN_ET,
-                              OUT_RT,
-                              std::vector<T>{1.0f, 1.0f, 0.0f},
-                              std::vector<T>(144, 1.0f),                                                                // anchors  [H, W, A, 4]
-                              std::vector<T>(144, 1.0f),                                                                // deltas   [N, A * 4, H, W]
-                              std::vector<T>{5.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 4.0f, 1.0f, 1.0f, 1.0f,
-                                             1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 8.0f, 1.0f},   // scores   [N, A, H, W]
-                              std::vector<T>(24, 1.0f),                                                                 // ref rois
-                              std::vector<T>{8.0f, 5.0f, 4.0f, 1.0f, 1.0f, 1.0f},                                       // ref scores
-                              std::vector<RT>{6},                                                                       // ref roiNum
-                              "eval"),
+                 1,
+                 3,  // A
+                 2,  // H
+                 6,  // W
+                 IN_ET,
+                 OUT_RT,
+                 std::vector<T>{1.0f, 1.0f, 0.0f},
+                 std::vector<T>(144, 1.0f),  // anchors  [H, W, A, 4]
+                 std::vector<T>(144, 1.0f),  // deltas   [N, A * 4, H, W]
+                 std::vector<T>{5.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 4.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f,
+                                1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 8.0f, 1.0f},  // scores   [N, A, H, W]
+                 std::vector<T>(24, 1.0f),                                                    // ref rois
+                 std::vector<T>{8.0f, 5.0f, 4.0f, 1.0f, 1.0f, 1.0f},                          // ref scores
+                 std::vector<RT>{6},                                                          // ref roiNum
+                 "eval"),
+        GPParams(
+            attrs,
+            2,
+            3,
+            2,
+            6,
+            IN_ET,
+            OUT_RT,
+            std::vector<T>{150.0, 150.0, 0.0, 150.0, 150.0, 0.0},
+            std::vector<T>{
+                12.0,  68.0,  102.0, 123.0, 46.0,  80.0,  79.0,  128.0, 33.0,  71.0,  127.0, 86.0,  33.0,  56.0,  150.0,
+                73.0,  5.0,   41.0,  93.0,  150.0, 74.0,  66.0,  106.0, 115.0, 17.0,  37.0,  87.0,  150.0, 31.0,  27.0,
+                150.0, 39.0,  29.0,  23.0,  112.0, 123.0, 41.0,  37.0,  103.0, 150.0, 8.0,   46.0,  98.0,  111.0, 7.0,
+                69.0,  114.0, 150.0, 70.0,  21.0,  150.0, 125.0, 54.0,  19.0,  132.0, 68.0,  62.0,  8.0,   150.0, 101.0,
+                57.0,  81.0,  150.0, 97.0,  79.0,  29.0,  109.0, 130.0, 12.0,  63.0,  100.0, 150.0, 17.0,  33.0,  113.0,
+                150.0, 90.0,  78.0,  150.0, 111.0, 47.0,  68.0,  150.0, 71.0,  66.0,  103.0, 111.0, 150.0, 4.0,   17.0,
+                112.0, 94.0,  12.0,  8.0,   119.0, 98.0,  54.0,  56.0,  120.0, 150.0, 56.0,  29.0,  150.0, 31.0,  42.0,
+                3.0,   139.0, 92.0,  41.0,  65.0,  150.0, 130.0, 49.0,  13.0,  143.0, 30.0,  40.0,  60.0,  150.0, 150.0,
+                23.0,  73.0,  24.0,  115.0, 56.0,  84.0,  107.0, 108.0, 63.0,  8.0,   142.0, 125.0, 78.0,  37.0,  93.0,
+                144.0, 40.0,  34.0,  150.0, 46.0,  30.0,  21.0,  150.0, 120.0},
+            std::vector<T>{
+                9.062256,   10.883133,  9.8441105,   12.694285,  0.41781136,  8.749107,    14.990341,     6.587644,
+                1.4206103,  13.299262,  12.432549,   2.736371,   0.22732796,  6.3361835,   12.268727,     2.1009045,
+                4.771589,   2.5131326,  5.610736,    9.3604145,  4.27379,     8.317948,    0.60510135,    6.7446275,
+                1.0207708,  1.1352817,  1.5785321,   1.718335,   1.8093798,   0.99247587,  1.3233583,     1.7432803,
+                1.8534478,  1.2593061,  1.7394226,   1.7686696,  1.647999,    1.7611449,   1.3119122,     0.03007332,
+                1.1106564,  0.55669737, 0.2546148,   1.9181818,  0.7134989,   2.0407224,   1.7211134,     1.8565536,
+                14.562747,  2.8786168,  0.5927796,   0.2064463,  7.6794515,   8.672126,    10.139171,     8.002429,
+                7.002932,   12.6314945, 10.550842,   0.15784842, 0.3194304,   10.752157,   3.709805,      11.628928,
+                0.7136225,  14.619964,  15.177284,   2.2824087,  15.381494,   0.16618137,  7.507227,      11.173228,
+                0.4923559,  1.8227729,  1.4749299,   1.7833921,  1.2363617,   -0.23659119, 1.5737582,     1.779316,
+                1.9828427,  1.0482665,  1.4900246,   1.3563544,  1.5341306,   0.7634312,   4.6216766e-05, 1.6161222,
+                1.7512476,  1.9363779,  0.9195784,   1.4906164,  -0.03244795, 0.681073,    0.6192401,     1.8033613,
+                14.146055,  3.4043705,  15.292292,   3.5295358,  11.138999,   9.952057,    5.633434,      12.114562,
+                9.427372,   12.384038,  9.583308,    8.427233,   15.293704,   3.288159,    11.64898,      9.350885,
+                2.0037227,  13.523184,  4.4176426,   6.1057625,  14.400079,   8.248259,    11.815807,     15.713364,
+                1.0023532,  1.3203261,  1.7100681,   0.7407832,  1.09448,     1.7188418,   1.4412547,     1.4862992,
+                0.74790007, 0.31571656, 0.6398838,   2.0236106,  1.1869069,   1.7265586,   1.2624544,     0.09934269,
+                1.3508598,  0.85212964, -0.38968498, 1.7059708,  1.6533034,   1.7400402,   1.8123854,     -0.43063712,
+                9.062256,   10.883133,  9.8441105,   12.694285,  0.41781136,  8.749107,    14.990341,     6.587644,
+                1.4206103,  13.299262,  12.432549,   2.736371,   0.22732796,  6.3361835,   12.268727,     2.1009045,
+                4.771589,   2.5131326,  5.610736,    9.3604145,  4.27379,     8.317948,    0.60510135,    6.7446275,
+                1.0207708,  1.1352817,  1.5785321,   1.718335,   1.8093798,   0.99247587,  1.3233583,     1.7432803,
+                1.8534478,  1.2593061,  1.7394226,   1.7686696,  1.647999,    1.7611449,   1.3119122,     0.03007332,
+                1.1106564,  0.55669737, 0.2546148,   1.9181818,  0.7134989,   2.0407224,   1.7211134,     1.8565536,
+                14.562747,  2.8786168,  0.5927796,   0.2064463,  7.6794515,   8.672126,    10.139171,     8.002429,
+                7.002932,   12.6314945, 10.550842,   0.15784842, 0.3194304,   10.752157,   3.709805,      11.628928,
+                0.7136225,  14.619964,  15.177284,   2.2824087,  15.381494,   0.16618137,  7.507227,      11.173228,
+                0.4923559,  1.8227729,  1.4749299,   1.7833921,  1.2363617,   -0.23659119, 1.5737582,     1.779316,
+                1.9828427,  1.0482665,  1.4900246,   1.3563544,  1.5341306,   0.7634312,   4.6216766e-05, 1.6161222,
+                1.7512476,  1.9363779,  0.9195784,   1.4906164,  -0.03244795, 0.681073,    0.6192401,     1.8033613,
+                14.146055,  3.4043705,  15.292292,   3.5295358,  11.138999,   9.952057,    5.633434,      12.114562,
+                9.427372,   12.384038,  9.583308,    8.427233,   15.293704,   3.288159,    11.64898,      9.350885,
+                2.0037227,  13.523184,  4.4176426,   6.1057625,  14.400079,   8.248259,    11.815807,     15.713364,
+                1.0023532,  1.3203261,  1.7100681,   0.7407832,  1.09448,     1.7188418,   1.4412547,     1.4862992,
+                0.74790007, 0.31571656, 0.6398838,   2.0236106,  1.1869069,   1.7265586,   1.2624544,     0.09934269,
+                1.3508598,  0.85212964, -0.38968498, 1.7059708,  1.6533034,   1.7400402,   1.8123854,     -0.43063712},
+            std::vector<T>{
+                0.7719922,  0.35906568, 0.29054508, 0.18124384,  0.5604661,  0.84750974, 0.98948747, 0.009793862,
+                0.7184191,  0.5560748,  0.6952493,  0.6732593,   0.3306898,  0.6790913,  0.41128764, 0.34593266,
+                0.94296855, 0.7348507,  0.24478768, 0.94024557,  0.05405676, 0.06466125, 0.36244348, 0.07942984,
+                0.10619422, 0.09412837, 0.9053611,  0.22870538,  0.9237487,  0.20986171, 0.5067282,  0.29709867,
+                0.53138554, 0.189101,   0.4786443,  0.88421875,  0.7719922,  0.35906568, 0.29054508, 0.18124384,
+                0.5604661,  0.84750974, 0.98948747, 0.009793862, 0.7184191,  0.5560748,  0.6952493,  0.6732593,
+                0.3306898,  0.6790913,  0.41128764, 0.34593266,  0.94296855, 0.7348507,  0.24478768, 0.94024557,
+                0.05405676, 0.06466125, 0.36244348, 0.07942984,  0.10619422, 0.09412837, 0.9053611,  0.22870538,
+                0.9237487,  0.20986171, 0.5067282,  0.29709867,  0.53138554, 0.189101,   0.4786443,  0.88421875},
+            std::vector<T>{149, 149,
+                           149, 149,
+                           149, 0,
+                           149, 149,
+                           149, 60.87443542480469,
+                           149, 149,
+                           149, 61.89498901367188,
+                           149, 149,
+                           149, 149,
+                           149, 149,
+                           149, 149,
+                           149, 149,
+                           149, 149,
+                           149, 149,
+                           149, 0,
+                           149, 149,
+                           149, 60.87443542480469,
+                           149, 149,
+                           149, 61.89498901367188,
+                           149, 149,
+                           149, 149,
+                           149, 149,
+                           149, 149,
+                           149, 149},
+            std::vector<T>{0.9894874691963196,
+                           0.9429685473442078,
+                           0.9402455687522888,
+                           0.9237486720085144,
+                           0.9053611159324646,
+                           0.8842187523841858,
+                           0.9894874691963196,
+                           0.9429685473442078,
+                           0.9402455687522888,
+                           0.9237486720085144,
+                           0.9053611159324646,
+                           0.8842187523841858},
+            std::vector<RT>{6, 6},
+            "batch_2"),
         GPParams(attrs,
-                              2,
-                              3,
-                              2,
-                              6,
-                              IN_ET,
-                              OUT_RT,
-                              std::vector<T>{150.0, 150.0, 0.0, 150.0, 150.0, 0.0},
-                              std::vector<T>{12.0, 68.0, 102.0, 123.0, 46.0, 80.0,  79.0,  128.0, 33.0, 71.0, 127.0, 86.0,  33.0, 56.0, 150.0, 73.0,
-                                             5.0,  41.0, 93.0,  150.0, 74.0, 66.0,  106.0, 115.0, 17.0, 37.0, 87.0,  150.0, 31.0, 27.0, 150.0, 39.0,
-                                             29.0, 23.0, 112.0, 123.0, 41.0, 37.0,  103.0, 150.0, 8.0,  46.0, 98.0,  111.0, 7.0,  69.0, 114.0, 150.0,
-                                             70.0, 21.0, 150.0, 125.0, 54.0, 19.0,  132.0, 68.0,  62.0, 8.0,  150.0, 101.0, 57.0, 81.0, 150.0, 97.0,
-                                             79.0, 29.0, 109.0, 130.0, 12.0, 63.0,  100.0, 150.0, 17.0, 33.0, 113.0, 150.0, 90.0, 78.0, 150.0, 111.0,
-                                             47.0, 68.0, 150.0, 71.0,  66.0, 103.0, 111.0, 150.0, 4.0,  17.0, 112.0, 94.0,  12.0, 8.0,  119.0, 98.0,
-                                             54.0, 56.0, 120.0, 150.0, 56.0, 29.0,  150.0, 31.0,  42.0, 3.0,  139.0, 92.0,  41.0, 65.0, 150.0, 130.0,
-                                             49.0, 13.0, 143.0, 30.0,  40.0, 60.0,  150.0, 150.0, 23.0, 73.0, 24.0,  115.0, 56.0, 84.0, 107.0, 108.0,
-                                             63.0, 8.0,  142.0, 125.0, 78.0, 37.0,  93.0,  144.0, 40.0, 34.0, 150.0, 46.0,  30.0, 21.0, 150.0, 120.0},
-                              std::vector<T>{9.062256,   10.883133, 9.8441105,   12.694285,   0.41781136, 8.749107,      14.990341,  6.587644,  1.4206103,
-                                             13.299262,  12.432549, 2.736371,    0.22732796,  6.3361835,  12.268727,     2.1009045,  4.771589,  2.5131326,
-                                             5.610736,   9.3604145, 4.27379,     8.317948,    0.60510135, 6.7446275,     1.0207708,  1.1352817, 1.5785321,
-                                             1.718335,   1.8093798, 0.99247587,  1.3233583,   1.7432803,  1.8534478,     1.2593061,  1.7394226, 1.7686696,
-                                             1.647999,   1.7611449, 1.3119122,   0.03007332,  1.1106564,  0.55669737,    0.2546148,  1.9181818, 0.7134989,
-                                             2.0407224,  1.7211134, 1.8565536,   14.562747,   2.8786168,  0.5927796,     0.2064463,  7.6794515, 8.672126,
-                                             10.139171,  8.002429,  7.002932,    12.6314945,  10.550842,  0.15784842,    0.3194304,  10.752157, 3.709805,
-                                             11.628928,  0.7136225, 14.619964,   15.177284,   2.2824087,  15.381494,     0.16618137, 7.507227,  11.173228,
-                                             0.4923559,  1.8227729, 1.4749299,   1.7833921,   1.2363617,  -0.23659119,   1.5737582,  1.779316,  1.9828427,
-                                             1.0482665,  1.4900246, 1.3563544,   1.5341306,   0.7634312,  4.6216766e-05, 1.6161222,  1.7512476, 1.9363779,
-                                             0.9195784,  1.4906164, -0.03244795, 0.681073,    0.6192401,  1.8033613,     14.146055,  3.4043705, 15.292292,
-                                             3.5295358,  11.138999, 9.952057,    5.633434,    12.114562,  9.427372,      12.384038,  9.583308,  8.427233,
-                                             15.293704,  3.288159,  11.64898,    9.350885,    2.0037227,  13.523184,     4.4176426,  6.1057625, 14.400079,
-                                             8.248259,   11.815807, 15.713364,   1.0023532,   1.3203261,  1.7100681,     0.7407832,  1.09448,   1.7188418,
-                                             1.4412547,  1.4862992, 0.74790007,  0.31571656,  0.6398838,  2.0236106,     1.1869069,  1.7265586, 1.2624544,
-                                             0.09934269, 1.3508598, 0.85212964,  -0.38968498, 1.7059708,  1.6533034,     1.7400402,  1.8123854, -0.43063712,
-                                             9.062256,   10.883133, 9.8441105,   12.694285,   0.41781136, 8.749107,      14.990341,  6.587644,  1.4206103,
-                                             13.299262,  12.432549, 2.736371,    0.22732796,  6.3361835,  12.268727,     2.1009045,  4.771589,  2.5131326,
-                                             5.610736,   9.3604145, 4.27379,     8.317948,    0.60510135, 6.7446275,     1.0207708,  1.1352817, 1.5785321,
-                                             1.718335,   1.8093798, 0.99247587,  1.3233583,   1.7432803,  1.8534478,     1.2593061,  1.7394226, 1.7686696,
-                                             1.647999,   1.7611449, 1.3119122,   0.03007332,  1.1106564,  0.55669737,    0.2546148,  1.9181818, 0.7134989,
-                                             2.0407224,  1.7211134, 1.8565536,   14.562747,   2.8786168,  0.5927796,     0.2064463,  7.6794515, 8.672126,
-                                             10.139171,  8.002429,  7.002932,    12.6314945,  10.550842,  0.15784842,    0.3194304,  10.752157, 3.709805,
-                                             11.628928,  0.7136225, 14.619964,   15.177284,   2.2824087,  15.381494,     0.16618137, 7.507227,  11.173228,
-                                             0.4923559,  1.8227729, 1.4749299,   1.7833921,   1.2363617,  -0.23659119,   1.5737582,  1.779316,  1.9828427,
-                                             1.0482665,  1.4900246, 1.3563544,   1.5341306,   0.7634312,  4.6216766e-05, 1.6161222,  1.7512476, 1.9363779,
-                                             0.9195784,  1.4906164, -0.03244795, 0.681073,    0.6192401,  1.8033613,     14.146055,  3.4043705, 15.292292,
-                                             3.5295358,  11.138999, 9.952057,    5.633434,    12.114562,  9.427372,      12.384038,  9.583308,  8.427233,
-                                             15.293704,  3.288159,  11.64898,    9.350885,    2.0037227,  13.523184,     4.4176426,  6.1057625, 14.400079,
-                                             8.248259,   11.815807, 15.713364,   1.0023532,   1.3203261,  1.7100681,     0.7407832,  1.09448,   1.7188418,
-                                             1.4412547,  1.4862992, 0.74790007,  0.31571656,  0.6398838,  2.0236106,     1.1869069,  1.7265586, 1.2624544,
-                                             0.09934269, 1.3508598, 0.85212964,  -0.38968498, 1.7059708,  1.6533034,     1.7400402,  1.8123854, -0.43063712},
-                              std::vector<T>{0.7719922,  0.35906568, 0.29054508, 0.18124384, 0.5604661,  0.84750974, 0.98948747, 0.009793862, 0.7184191,
-                                             0.5560748,  0.6952493,  0.6732593,  0.3306898,  0.6790913,  0.41128764, 0.34593266, 0.94296855,  0.7348507,
-                                             0.24478768, 0.94024557, 0.05405676, 0.06466125, 0.36244348, 0.07942984, 0.10619422, 0.09412837,  0.9053611,
-                                             0.22870538, 0.9237487,  0.20986171, 0.5067282,  0.29709867, 0.53138554, 0.189101,   0.4786443,   0.88421875,
-                                             0.7719922,  0.35906568, 0.29054508, 0.18124384, 0.5604661,  0.84750974, 0.98948747, 0.009793862, 0.7184191,
-                                             0.5560748,  0.6952493,  0.6732593,  0.3306898,  0.6790913,  0.41128764, 0.34593266, 0.94296855,  0.7348507,
-                                             0.24478768, 0.94024557, 0.05405676, 0.06466125, 0.36244348, 0.07942984, 0.10619422, 0.09412837,  0.9053611,
-                                             0.22870538, 0.9237487,  0.20986171, 0.5067282,  0.29709867, 0.53138554, 0.189101,   0.4786443,   0.88421875},
-                              std::vector<T>{149, 149, 149, 149, 149, 0,   149, 149, 149, 60.87443542480469, 149, 149, 149, 61.89498901367188, 149,
-                                             149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149, 0,   149, 149, 149, 60.87443542480469,
-                                             149, 149, 149, 61.89498901367188, 149, 149, 149, 149, 149, 149, 149, 149, 149, 149},
-                              std::vector<T>{0.9894874691963196, 0.9429685473442078,
-                                             0.9402455687522888, 0.9237486720085144,
-                                             0.9053611159324646, 0.8842187523841858,
-                                             0.9894874691963196, 0.9429685473442078,
-                                             0.9402455687522888, 0.9237486720085144,
-                                             0.9053611159324646, 0.8842187523841858},
-                              std::vector<RT>{6, 6},
-                              "batch_2"),
-        GPParams(attrs,
-                              1,
-                              3,    // A
-                              2,    // H
-                              6,    // W
-                              IN_ET,
-                              OUT_RT,
-                              std::vector<T>{200.0f, 200.0f, 4.0f},
-                              std::vector<T>{0.0f,  1.0f,  2.0f,  3.0f,
-                                             4.0f,  5.0f,  6.0f,  7.0f,
-                                             8.0f,  9.0f, 10.0f, 11.0f,
-                                             12.0f, 13.0f, 14.0f, 15.0f,
-                                             16.0f, 17.0f, 18.0f, 19.0f,
-                                             20.0f, 21.0f, 22.0f, 23.0f,
-                                             24.0f, 25.0f, 26.0f, 27.0f,
-                                             28.0f, 29.0f, 30.0f, 31.0f,
-                                             32.0f, 33.0f, 34.0f, 35.0f,
-                                             36.0f, 37.0f, 38.0f, 39.0f,
-                                             40.0f, 41.0f, 42.0f, 43.0f,
-                                             44.0f, 45.0f, 46.0f, 47.0f,
-                                             48.0f, 49.0f, 50.0f, 51.0f,
-                                             52.0f, 53.0f, 54.0f, 55.0f,
-                                             56.0f, 57.0f, 58.0f, 59.0f,
-                                             60.0f, 61.0f, 62.0f, 63.0f,
-                                             64.0f, 65.0f, 66.0f, 67.0f,
-                                             68.0f, 69.0f, 70.0f, 71.0f,
-                                             72.0f, 73.0f, 74.0f, 75.0f,
-                                             76.0f, 77.0f, 78.0f, 79.0f,
-                                             80.0f, 81.0f, 82.0f, 83.0f,
-                                             84.0f, 85.0f, 86.0f, 87.0f,
-                                             88.0f, 89.0f, 90.0f, 91.0f,
-                                             92.0f, 93.0f, 94.0f, 95.0f,
-                                             96.0f,  97.0f,  98.0f,  99.0f,
-                                             100.0f, 101.0f, 102.0f, 103.0f,
-                                             104.0f, 105.0f, 106.0f, 107.0f,
-                                             108.0f, 109.0f, 110.0f, 111.0f,
-                                             112.0f, 113.0f, 114.0f, 115.0f,
-                                             116.0f, 117.0f, 118.0f, 119.0f,
-                                             120.0f, 121.0f, 122.0f, 123.0f,
-                                             124.0f, 125.0f, 126.0f, 127.0f,
-                                             128.0f, 129.0f, 130.0f, 131.0f,
-                                             132.0f, 133.0f, 134.0f, 135.0f,
-                                             136.0f, 137.0f, 138.0f, 139.0f,
-                                             140.0f, 141.0f, 142.0f, 143.0f},   // anchors   H, W, A, 4
-                              std::vector<T>{0.5337073 ,0.86607957,0.55151343,0.21626699,0.4462629, 0.03985678,
-                                             0.5157072 ,0.9932138 ,0.7565954 ,0.43803605,0.802818  ,0.14834064,
-                                             0.53932905,0.14314   ,0.3817048 ,0.95075196,0.05516243,0.2567484,
-                                             0.25508744,0.77438325,0.43561   ,0.2094628 ,0.8299043 ,0.44982538,
-                                             0.95615596,0.5651084 ,0.11801951,0.05352486,0.9774733 ,0.14439464,
-                                             0.62644225,0.14370479,0.54161614,0.557915  ,0.53102225,0.0840179,
-                                             0.7249888 ,0.9843559 ,0.5490522 ,0.53788143,0.822474  ,0.3278008,
-                                             0.39688024,0.3286012 ,0.5117038 ,0.04743988,0.9408995 ,0.29885054,
-                                             0.81039643,0.85277915,0.06807619,0.86430097,0.36225632,0.16606331,
-                                             0.5401001 ,0.7541649 ,0.11998601,0.5131829 ,0.40606487,0.327888  ,
-                                             0.27721855,0.6378373 ,0.22795396,0.4961256 ,0.3215895 ,0.15607187,
-                                             0.14782153,0.8908137 ,0.8835288 ,0.834191  ,0.29907143,0.7983525 ,
-                                             0.755875  ,0.30837986,0.0839176 ,0.26624718,0.04371626,0.09472824,
-                                             0.20689541,0.37622106,0.1083321 ,0.1342548 ,0.05815459,0.7676379 ,
-                                             0.8105144 ,0.92348766,0.26761323,0.7183306 ,0.8947588 ,0.19020908,
-                                             0.42731014,0.7473663 ,0.85775334,0.9340091 ,0.3278848 ,0.755993  ,
-                                             0.05307213,0.39705503,0.21003333,0.5625373 ,0.66188884,0.80521655,
-                                             0.6125863 ,0.44678232,0.97802377,0.0204936 ,0.02686367,0.7390654 ,
-                                             0.74631   ,0.58399844,0.5988792 ,0.37413648,0.5946692 ,0.6955776 ,
-                                             0.36377597,0.7891322 ,0.40900692,0.99139464,0.50169915,0.41435778,
-                                             0.17142445,0.26761186,0.31591868,0.14249913,0.12919712,0.5418711 ,
-                                             0.6523203 ,0.50259084,0.7379765 ,0.01171071,0.94423133,0.00841132,
-                                             0.97486794,0.2921785 ,0.7633071 ,0.88477814,0.03563205,0.50833166,
-                                             0.01354555,0.535081  ,0.41366324,0.0694767 ,0.9944055 ,0.9981207},   // deltas    N, A * 4, H, W
-                              std::vector<T>{0.56637216,0.90457034,0.69827306,0.4353543, 0.47985056,0.42658508,
-                                             0.14516132,0.08081771,0.1799732 ,0.9229515 ,0.42420176,0.50857586,
-                                             0.82664067,0.4972319 ,0.3752427 ,0.56731623,0.18241242,0.33252355,
-                                             0.30608943,0.6572437 ,0.69185436,0.88646156,0.36985755,0.5590753 ,
-                                             0.5256446 ,0.03342898,0.1344396 ,0.68642473,0.37953874,0.32575172,
-                                             0.21108444,0.5661886 ,0.45378175,0.62126315,0.26799858,0.37272978},       // scores    N, A, H, W
-                              std::vector<T>{4.49132, 4.30537, 8.75027, 8.8035,
-                                             0, 1.01395, 4.66909, 5.14337,
-                                             135.501, 137.467, 139.81, 141.726,
-                                             47.2348, 47.8342, 52.5503, 52.3864,
-                                             126.483, 128.3, 131.625, 133.707},       // ref rois
-                              std::vector<T>{0.826641, 0.566372, 0.559075, 0.479851, 0.267999},   // ref scores
-                              std::vector<RT>{5},   // ref roiNum
-                              "eval_2")
-    };
+                 1,
+                 3,  // A
+                 2,  // H
+                 6,  // W
+                 IN_ET,
+                 OUT_RT,
+                 std::vector<T>{200.0f, 200.0f, 4.0f},
+                 std::vector<T>{0.0f,   1.0f,   2.0f,   3.0f,   4.0f,   5.0f,   6.0f,   7.0f,   8.0f,   9.0f,   10.0f,
+                                11.0f,  12.0f,  13.0f,  14.0f,  15.0f,  16.0f,  17.0f,  18.0f,  19.0f,  20.0f,  21.0f,
+                                22.0f,  23.0f,  24.0f,  25.0f,  26.0f,  27.0f,  28.0f,  29.0f,  30.0f,  31.0f,  32.0f,
+                                33.0f,  34.0f,  35.0f,  36.0f,  37.0f,  38.0f,  39.0f,  40.0f,  41.0f,  42.0f,  43.0f,
+                                44.0f,  45.0f,  46.0f,  47.0f,  48.0f,  49.0f,  50.0f,  51.0f,  52.0f,  53.0f,  54.0f,
+                                55.0f,  56.0f,  57.0f,  58.0f,  59.0f,  60.0f,  61.0f,  62.0f,  63.0f,  64.0f,  65.0f,
+                                66.0f,  67.0f,  68.0f,  69.0f,  70.0f,  71.0f,  72.0f,  73.0f,  74.0f,  75.0f,  76.0f,
+                                77.0f,  78.0f,  79.0f,  80.0f,  81.0f,  82.0f,  83.0f,  84.0f,  85.0f,  86.0f,  87.0f,
+                                88.0f,  89.0f,  90.0f,  91.0f,  92.0f,  93.0f,  94.0f,  95.0f,  96.0f,  97.0f,  98.0f,
+                                99.0f,  100.0f, 101.0f, 102.0f, 103.0f, 104.0f, 105.0f, 106.0f, 107.0f, 108.0f, 109.0f,
+                                110.0f, 111.0f, 112.0f, 113.0f, 114.0f, 115.0f, 116.0f, 117.0f, 118.0f, 119.0f, 120.0f,
+                                121.0f, 122.0f, 123.0f, 124.0f, 125.0f, 126.0f, 127.0f, 128.0f, 129.0f, 130.0f, 131.0f,
+                                132.0f, 133.0f, 134.0f, 135.0f, 136.0f, 137.0f, 138.0f, 139.0f, 140.0f, 141.0f, 142.0f,
+                                143.0f},  // anchors   H, W, A, 4
+                 std::vector<T>{0.5337073,  0.86607957, 0.55151343, 0.21626699, 0.4462629,  0.03985678, 0.5157072,
+                                0.9932138,  0.7565954,  0.43803605, 0.802818,   0.14834064, 0.53932905, 0.14314,
+                                0.3817048,  0.95075196, 0.05516243, 0.2567484,  0.25508744, 0.77438325, 0.43561,
+                                0.2094628,  0.8299043,  0.44982538, 0.95615596, 0.5651084,  0.11801951, 0.05352486,
+                                0.9774733,  0.14439464, 0.62644225, 0.14370479, 0.54161614, 0.557915,   0.53102225,
+                                0.0840179,  0.7249888,  0.9843559,  0.5490522,  0.53788143, 0.822474,   0.3278008,
+                                0.39688024, 0.3286012,  0.5117038,  0.04743988, 0.9408995,  0.29885054, 0.81039643,
+                                0.85277915, 0.06807619, 0.86430097, 0.36225632, 0.16606331, 0.5401001,  0.7541649,
+                                0.11998601, 0.5131829,  0.40606487, 0.327888,   0.27721855, 0.6378373,  0.22795396,
+                                0.4961256,  0.3215895,  0.15607187, 0.14782153, 0.8908137,  0.8835288,  0.834191,
+                                0.29907143, 0.7983525,  0.755875,   0.30837986, 0.0839176,  0.26624718, 0.04371626,
+                                0.09472824, 0.20689541, 0.37622106, 0.1083321,  0.1342548,  0.05815459, 0.7676379,
+                                0.8105144,  0.92348766, 0.26761323, 0.7183306,  0.8947588,  0.19020908, 0.42731014,
+                                0.7473663,  0.85775334, 0.9340091,  0.3278848,  0.755993,   0.05307213, 0.39705503,
+                                0.21003333, 0.5625373,  0.66188884, 0.80521655, 0.6125863,  0.44678232, 0.97802377,
+                                0.0204936,  0.02686367, 0.7390654,  0.74631,    0.58399844, 0.5988792,  0.37413648,
+                                0.5946692,  0.6955776,  0.36377597, 0.7891322,  0.40900692, 0.99139464, 0.50169915,
+                                0.41435778, 0.17142445, 0.26761186, 0.31591868, 0.14249913, 0.12919712, 0.5418711,
+                                0.6523203,  0.50259084, 0.7379765,  0.01171071, 0.94423133, 0.00841132, 0.97486794,
+                                0.2921785,  0.7633071,  0.88477814, 0.03563205, 0.50833166, 0.01354555, 0.535081,
+                                0.41366324, 0.0694767,  0.9944055,  0.9981207},  // deltas    N, A * 4, H, W
+                 std::vector<T>{0.56637216, 0.90457034, 0.69827306, 0.4353543,  0.47985056, 0.42658508, 0.14516132,
+                                0.08081771, 0.1799732,  0.9229515,  0.42420176, 0.50857586, 0.82664067, 0.4972319,
+                                0.3752427,  0.56731623, 0.18241242, 0.33252355, 0.30608943, 0.6572437,  0.69185436,
+                                0.88646156, 0.36985755, 0.5590753,  0.5256446,  0.03342898, 0.1344396,  0.68642473,
+                                0.37953874, 0.32575172, 0.21108444, 0.5661886,  0.45378175, 0.62126315, 0.26799858,
+                                0.37272978},  // scores    N, A, H, W
+                 std::vector<T>{4.49132, 4.30537, 8.75027, 8.8035, 0,       1.01395, 4.66909,
+                                5.14337, 135.501, 137.467, 139.81, 141.726, 47.2348, 47.8342,
+                                52.5503, 52.3864, 126.483, 128.3,  131.625, 133.707},  // ref rois
+                 std::vector<T>{0.826641, 0.566372, 0.559075, 0.479851, 0.267999},     // ref scores
+                 std::vector<RT>{5},                                                   // ref roiNum
+                 "eval_2")};
     return generateProposalParams;
 }
 
 std::vector<GPParams> generateGPCombinedParams() {
-    const std::vector<std::vector<GPParams>> GPTypeParams {
+    const std::vector<std::vector<GPParams>> GPTypeParams{
         generateGPFloatParams<element::Type_t::f32, element::Type_t::i32>(),
         generateGPFloatParams<element::Type_t::f32, element::Type_t::i64>(),
         generateGPFloatParams<element::Type_t::f16, element::Type_t::i32>(),
         generateGPFloatParams<element::Type_t::bf16, element::Type_t::i64>(),
-        };
+    };
     std::vector<GPParams> combinedParams;
 
     for (const auto& params : GPTypeParams) {
@@ -302,6 +317,8 @@ std::vector<GPParams> generateGPCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GenerateProposals_With_Hardcoded_Refs, ReferenceGPLayerTest,
-    testing::ValuesIn(generateGPCombinedParams()), ReferenceGPLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_GenerateProposals_With_Hardcoded_Refs,
+                         ReferenceGPLayerTest,
+                         testing::ValuesIn(generateGPCombinedParams()),
+                         ReferenceGPLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/greater.cpp b/src/plugins/template/tests/functional/op_reference/greater.cpp
index 7070005244a899..e74992932193ea 100644
--- a/src/plugins/template/tests/functional/op_reference/greater.cpp
+++ b/src/plugins/template/tests/functional/op_reference/greater.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/greater.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/greater.hpp"
 #include "comparison.hpp"
 
 using namespace ov;
@@ -19,43 +20,43 @@ TEST_P(ReferenceComparisonLayerTest, GreaterCompareWithHardcodedRefs) {
 template <element::Type_t IN_ET>
 std::vector<RefComparisonParams> generateComparisonParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RefComparisonParams> compParams {
+    std::vector<RefComparisonParams> compParams{
         // 1D // 2D // 3D // 4D
-        Builder {}
+        Builder{}
             .compType(ComparisonTypes::GREATER)
-            .input1({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .input2({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {0, 0, 0, 0}}),
-        Builder {}
+            .input1({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .input2({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{0, 0, 0, 0}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER)
-            .input1({{2, 3}, type, std::vector<T> {0, 6, 45, 1, 21, 21}})
-            .input2({{2, 3}, type, std::vector<T> {1, 18, 23, 1, 19, 21}})
-            .expected({{2, 3}, element::boolean, std::vector<char> {0, 0, 1, 0, 1, 0}}),
-        Builder {}
+            .input1({{2, 3}, type, std::vector<T>{0, 6, 45, 1, 21, 21}})
+            .input2({{2, 3}, type, std::vector<T>{1, 18, 23, 1, 19, 21}})
+            .expected({{2, 3}, element::boolean, std::vector<char>{0, 0, 1, 0, 1, 0}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER)
-            .input1({{1}, type, std::vector<T> {53}})
-            .input2({{1}, type, std::vector<T> {53}})
-            .expected({{1}, element::boolean, std::vector<char> {0}}),
-        Builder {}
+            .input1({{1}, type, std::vector<T>{53}})
+            .input2({{1}, type, std::vector<T>{53}})
+            .expected({{1}, element::boolean, std::vector<char>{0}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER)
-            .input1({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 1, 5, 12, 8}})
-            .input2({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 10, 5, 11, 8}})
-            .expected({{2, 4}, element::boolean, std::vector<char> {0, 0, 0, 0, 0, 0, 1, 0}}),
-        Builder {}
+            .input1({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 1, 5, 12, 8}})
+            .input2({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 10, 5, 11, 8}})
+            .expected({{2, 4}, element::boolean, std::vector<char>{0, 0, 0, 0, 0, 0, 1, 0}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER)
-            .input1({{3, 1, 2}, type, std::vector<T> {2, 1, 4, 1, 3, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{3, 2, 2}, element::boolean, std::vector<char> {1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0}}),
-        Builder {}
+            .input1({{3, 1, 2}, type, std::vector<T>{2, 1, 4, 1, 3, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{3, 2, 2}, element::boolean, std::vector<char>{1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER)
-            .input1({{2, 1, 2, 1}, type, std::vector<T> {2, 1, 4, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {1, 0, 1, 0}})};
+            .input1({{2, 1, 2, 1}, type, std::vector<T>{2, 1, 4, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{1, 0, 1, 0}})};
     return compParams;
 }
 
 std::vector<RefComparisonParams> generateComparisonCombinedParams() {
-    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams{
         generateComparisonParams<element::Type_t::f32>(element::f32),
         generateComparisonParams<element::Type_t::f16>(element::f16),
         generateComparisonParams<element::Type_t::i32>(element::i32),
@@ -71,8 +72,10 @@ std::vector<RefComparisonParams> generateComparisonCombinedParams() {
     return combinedParams;
 }
 
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateComparisonCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs,
+                         ReferenceComparisonLayerTest,
+                         ::testing::ValuesIn(generateComparisonCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
-} // namespace ComparisonOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ComparisonOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/greater_equal.cpp b/src/plugins/template/tests/functional/op_reference/greater_equal.cpp
index c8f18a3b21c7ce..cbf8781b657b61 100644
--- a/src/plugins/template/tests/functional/op_reference/greater_equal.cpp
+++ b/src/plugins/template/tests/functional/op_reference/greater_equal.cpp
@@ -4,8 +4,8 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/op/greater_eq.hpp"
 #include "comparison.hpp"
+#include "openvino/op/greater_eq.hpp"
 
 using namespace ov;
 
@@ -16,43 +16,43 @@ namespace {
 template <element::Type_t IN_ET>
 std::vector<RefComparisonParams> generateComparisonParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RefComparisonParams> compParams {
+    std::vector<RefComparisonParams> compParams{
         // 1D // 2D // 3D // 4D
-        Builder {}
+        Builder{}
             .compType(ComparisonTypes::GREATER_EQUAL)
-            .input1({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .input2({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {1, 1, 1, 1}}),
-        Builder {}
+            .input1({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .input2({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{1, 1, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER_EQUAL)
-            .input1({{2, 3}, type, std::vector<T> {0, 6, 45, 1, 21, 21}})
-            .input2({{2, 3}, type, std::vector<T> {1, 18, 23, 1, 19, 21}})
-            .expected({{2, 3}, element::boolean, std::vector<char> {0, 0, 1, 1, 1, 1}}),
-        Builder {}
+            .input1({{2, 3}, type, std::vector<T>{0, 6, 45, 1, 21, 21}})
+            .input2({{2, 3}, type, std::vector<T>{1, 18, 23, 1, 19, 21}})
+            .expected({{2, 3}, element::boolean, std::vector<char>{0, 0, 1, 1, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER_EQUAL)
-            .input1({{1}, type, std::vector<T> {53}})
-            .input2({{1}, type, std::vector<T> {53}})
-            .expected({{1}, element::boolean, std::vector<char> {1}}),
-        Builder {}
+            .input1({{1}, type, std::vector<T>{53}})
+            .input2({{1}, type, std::vector<T>{53}})
+            .expected({{1}, element::boolean, std::vector<char>{1}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER_EQUAL)
-            .input1({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 1, 5, 12, 8}})
-            .input2({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 10, 5, 11, 8}})
-            .expected({{2, 4}, element::boolean, std::vector<char> {1, 1, 1, 1, 0, 1, 1, 1}}),
-        Builder {}
+            .input1({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 1, 5, 12, 8}})
+            .input2({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 10, 5, 11, 8}})
+            .expected({{2, 4}, element::boolean, std::vector<char>{1, 1, 1, 1, 0, 1, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER_EQUAL)
-            .input1({{3, 1, 2}, type, std::vector<T> {2, 1, 4, 1, 3, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{3, 2, 2}, element::boolean, std::vector<char> {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}}),
-        Builder {}
+            .input1({{3, 1, 2}, type, std::vector<T>{2, 1, 4, 1, 3, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{3, 2, 2}, element::boolean, std::vector<char>{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::GREATER_EQUAL)
-            .input1({{2, 1, 2, 1}, type, std::vector<T> {2, 1, 4, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {1, 1, 1, 1}})};
+            .input1({{2, 1, 2, 1}, type, std::vector<T>{2, 1, 4, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{1, 1, 1, 1}})};
     return compParams;
 }
 
 std::vector<RefComparisonParams> generateComparisonCombinedParams() {
-    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams{
         generateComparisonParams<element::Type_t::f32>(element::f32),
         generateComparisonParams<element::Type_t::f16>(element::f16),
         generateComparisonParams<element::Type_t::i64>(element::i64),
@@ -68,8 +68,10 @@ std::vector<RefComparisonParams> generateComparisonCombinedParams() {
     return combinedParams;
 }
 
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateComparisonCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs,
+                         ReferenceComparisonLayerTest,
+                         ::testing::ValuesIn(generateComparisonCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
-} // namespace ComparisonOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ComparisonOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/grn.cpp b/src/plugins/template/tests/functional/op_reference/grn.cpp
index 4322da7cd3c921..c936f4d222aa83 100644
--- a/src/plugins/template/tests/functional/op_reference/grn.cpp
+++ b/src/plugins/template/tests/functional/op_reference/grn.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/grn.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/grn.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,9 +14,17 @@ using namespace ov;
 namespace {
 struct GrnParams {
     template <class IT>
-    GrnParams(const float bias, const PartialShape& shape, const element::Type& iType, const std::vector<IT>& iValues,
+    GrnParams(const float bias,
+              const PartialShape& shape,
+              const element::Type& iType,
+              const std::vector<IT>& iValues,
               const std::vector<IT>& oValues)
-        : bias(bias), pshape(shape), inType(iType), outType(iType), inputData(CreateTensor(iType, iValues)), refData(CreateTensor(iType, oValues)) {}
+        : bias(bias),
+          pshape(shape),
+          inType(iType),
+          outType(iType),
+          inputData(CreateTensor(iType, iValues)),
+          refData(CreateTensor(iType, oValues)) {}
     float bias;
     PartialShape pshape;
     element::Type inType;
@@ -43,10 +52,12 @@ class ReferenceGrnLayerTest : public testing::TestWithParam<GrnParams>, public C
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(float bias, const PartialShape& input_shape, const element::Type& input_type) {
+    static std::shared_ptr<Model> CreateFunction(float bias,
+                                                 const PartialShape& input_shape,
+                                                 const element::Type& input_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto grn = std::make_shared<op::v0::GRN>(in, bias);
-        return std::make_shared<ov::Model>(NodeVector {grn}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{grn}, ParameterVector{in});
     }
 };
 
@@ -57,50 +68,100 @@ TEST_P(ReferenceGrnLayerTest, CompareWithHardcodedRefs) {
 template <element::Type_t IN_ET>
 std::vector<GrnParams> generateGrnParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<GrnParams> grnParams {
+    std::vector<GrnParams> grnParams{
         // bias 1e-6 // 2D // 3D // 4D
-        GrnParams(1e-6f, PartialShape {3, 4}, type, std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
-                  std::vector<T> {0.182574, 0.365148, 0.547723, 0.730297, 0.379049, 0.454859, 0.530669, 0.606478, 0.426162, 0.473514, 0.520865, 0.568217}),
-        GrnParams(1e-6f, PartialShape {2, 3, 4}, type,
-                  std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
-                  std::vector<T> {0.0966737, 0.169031, 0.224231, 0.267261, 0.483368, 0.507093, 0.523205, 0.534522, 0.870063, 0.845154, 0.822179, 0.801784,
-                                  0.433574,  0.441836, 0.449215, 0.455842, 0.566982, 0.568075, 0.569005, 0.569803, 0.700389, 0.694314, 0.688796, 0.683763}),
-        GrnParams(1e-6f, PartialShape {1, 2, 3, 4}, type,
-                  std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
-                  std::vector<T> {0.0766965, 0.141421, 0.196116, 0.242536, 0.282166, 0.316228, 0.345705, 0.371391, 0.393919, 0.413803, 0.431455, 0.447214,
-                                  0.997055,  0.989949, 0.980581, 0.970143, 0.959365, 0.948683, 0.938343, 0.928477, 0.919145, 0.910366, 0.902134, 0.894427}),
-        GrnParams(1e-6f, PartialShape {2, 2, 3, 4}, type,
-                  std::vector<T> {1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,
-                                  25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48},
-                  std::vector<T> {0.0766965, 0.141421, 0.196116, 0.242536, 0.282166, 0.316228, 0.345705, 0.371391, 0.393919, 0.413803, 0.431455, 0.447214,
-                                  0.997055,  0.989949, 0.980581, 0.970143, 0.959365, 0.948683, 0.938343, 0.928477, 0.919145, 0.910366, 0.902134, 0.894427,
-                                  0.559857,  0.564684, 0.56921,  0.573462, 0.577465, 0.581238, 0.584802, 0.588172, 0.591364, 0.594391, 0.597266, 0.6,
-                                  0.828589,  0.825307, 0.822192, 0.819232, 0.816416, 0.813733, 0.811176, 0.808736, 0.806405, 0.804176, 0.802043, 0.8}),
+        GrnParams(1e-6f,
+                  PartialShape{3, 4},
+                  type,
+                  std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
+                  std::vector<T>{0.182574,
+                                 0.365148,
+                                 0.547723,
+                                 0.730297,
+                                 0.379049,
+                                 0.454859,
+                                 0.530669,
+                                 0.606478,
+                                 0.426162,
+                                 0.473514,
+                                 0.520865,
+                                 0.568217}),
+        GrnParams(1e-6f,
+                  PartialShape{2, 3, 4},
+                  type,
+                  std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
+                  std::vector<T>{0.0966737, 0.169031, 0.224231, 0.267261, 0.483368, 0.507093, 0.523205, 0.534522,
+                                 0.870063,  0.845154, 0.822179, 0.801784, 0.433574, 0.441836, 0.449215, 0.455842,
+                                 0.566982,  0.568075, 0.569005, 0.569803, 0.700389, 0.694314, 0.688796, 0.683763}),
+        GrnParams(1e-6f,
+                  PartialShape{1, 2, 3, 4},
+                  type,
+                  std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
+                  std::vector<T>{0.0766965, 0.141421, 0.196116, 0.242536, 0.282166, 0.316228, 0.345705, 0.371391,
+                                 0.393919,  0.413803, 0.431455, 0.447214, 0.997055, 0.989949, 0.980581, 0.970143,
+                                 0.959365,  0.948683, 0.938343, 0.928477, 0.919145, 0.910366, 0.902134, 0.894427}),
+        GrnParams(1e-6f,
+                  PartialShape{2, 2, 3, 4},
+                  type,
+                  std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16,
+                                 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
+                                 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48},
+                  std::vector<T>{0.0766965, 0.141421, 0.196116, 0.242536, 0.282166, 0.316228, 0.345705, 0.371391,
+                                 0.393919,  0.413803, 0.431455, 0.447214, 0.997055, 0.989949, 0.980581, 0.970143,
+                                 0.959365,  0.948683, 0.938343, 0.928477, 0.919145, 0.910366, 0.902134, 0.894427,
+                                 0.559857,  0.564684, 0.56921,  0.573462, 0.577465, 0.581238, 0.584802, 0.588172,
+                                 0.591364,  0.594391, 0.597266, 0.6,      0.828589, 0.825307, 0.822192, 0.819232,
+                                 0.816416,  0.813733, 0.811176, 0.808736, 0.806405, 0.804176, 0.802043, 0.8}),
         // bias 100.25 // 2D // 3D // 4D
-        GrnParams(100.25f, PartialShape {3, 4}, type, std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
-                  std::vector<T> {0.0876216, 0.175243, 0.262865, 0.350486, 0.301923, 0.362308, 0.422693, 0.483077, 0.385076, 0.427863, 0.470649, 0.513435}),
-        GrnParams(100.25f, PartialShape {2, 3, 4}, type,
-                  std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
-                  std::vector<T> {0.0694629, 0.129032, 0.179525, 0.222137, 0.347314, 0.387097, 0.418891, 0.444273, 0.625166, 0.645161, 0.658258, 0.66641,
-                                  0.41125,   0.421303, 0.430287, 0.438356, 0.537789, 0.541675, 0.54503,  0.547945, 0.664327, 0.662047, 0.659774, 0.657534}),
-        GrnParams(100.25f, PartialShape {1, 2, 3, 4}, type,
-                  std::vector<T> {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
-                  std::vector<T> {0.0608299, 0.115422, 0.164091, 0.207321, 0.245662, 0.279675, 0.309889, 0.336786, 0.360795, 0.38229,  0.401596, 0.418994,
-                                  0.790789,  0.807954, 0.820457, 0.829283, 0.835252, 0.839026, 0.841128, 0.841965, 0.841854, 0.841037, 0.839701, 0.837989f}),
-        GrnParams(100.25f, PartialShape {2, 2, 3, 4}, type,
-                  std::vector<T> {1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24,
-                                  25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48},
-                  std::vector<T> {0.0608299, 0.115422, 0.164091, 0.207321, 0.245662, 0.279675, 0.309889, 0.336786, 0.360795, 0.38229,  0.401596, 0.418994,
-                                  0.790789,  0.807954, 0.820457, 0.829283, 0.835252, 0.839026, 0.841128, 0.841965, 0.841854, 0.841037, 0.839701, 0.837989,
-                                  0.546293,  0.551788, 0.556938, 0.561772, 0.566319, 0.570601, 0.574641, 0.578458, 0.582069, 0.585489, 0.588734, 0.591816,
-                                  0.808514,  0.80646,  0.804466, 0.802532, 0.800658, 0.798842, 0.797083, 0.795379, 0.79373,  0.792133, 0.790586, 0.789088})};
+        GrnParams(100.25f,
+                  PartialShape{3, 4},
+                  type,
+                  std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
+                  std::vector<T>{0.0876216,
+                                 0.175243,
+                                 0.262865,
+                                 0.350486,
+                                 0.301923,
+                                 0.362308,
+                                 0.422693,
+                                 0.483077,
+                                 0.385076,
+                                 0.427863,
+                                 0.470649,
+                                 0.513435}),
+        GrnParams(100.25f,
+                  PartialShape{2, 3, 4},
+                  type,
+                  std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
+                  std::vector<T>{0.0694629, 0.129032, 0.179525, 0.222137, 0.347314, 0.387097, 0.418891, 0.444273,
+                                 0.625166,  0.645161, 0.658258, 0.66641,  0.41125,  0.421303, 0.430287, 0.438356,
+                                 0.537789,  0.541675, 0.54503,  0.547945, 0.664327, 0.662047, 0.659774, 0.657534}),
+        GrnParams(100.25f,
+                  PartialShape{1, 2, 3, 4},
+                  type,
+                  std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24},
+                  std::vector<T>{0.0608299, 0.115422, 0.164091, 0.207321, 0.245662, 0.279675, 0.309889, 0.336786,
+                                 0.360795,  0.38229,  0.401596, 0.418994, 0.790789, 0.807954, 0.820457, 0.829283,
+                                 0.835252,  0.839026, 0.841128, 0.841965, 0.841854, 0.841037, 0.839701, 0.837989f}),
+        GrnParams(100.25f,
+                  PartialShape{2, 2, 3, 4},
+                  type,
+                  std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16,
+                                 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
+                                 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48},
+                  std::vector<T>{0.0608299, 0.115422, 0.164091, 0.207321, 0.245662, 0.279675, 0.309889, 0.336786,
+                                 0.360795,  0.38229,  0.401596, 0.418994, 0.790789, 0.807954, 0.820457, 0.829283,
+                                 0.835252,  0.839026, 0.841128, 0.841965, 0.841854, 0.841037, 0.839701, 0.837989,
+                                 0.546293,  0.551788, 0.556938, 0.561772, 0.566319, 0.570601, 0.574641, 0.578458,
+                                 0.582069,  0.585489, 0.588734, 0.591816, 0.808514, 0.80646,  0.804466, 0.802532,
+                                 0.800658,  0.798842, 0.797083, 0.795379, 0.79373,  0.792133, 0.790586, 0.789088})};
     return grnParams;
 }
 
 std::vector<GrnParams> generateGrnCombinedParams() {
-    const std::vector<std::vector<GrnParams>> grnTypeParams {generateGrnParams<element::Type_t::bf16>(element::bf16),
-                                                             generateGrnParams<element::Type_t::f16>(element::f16),
-                                                             generateGrnParams<element::Type_t::f32>(element::f32)};
+    const std::vector<std::vector<GrnParams>> grnTypeParams{generateGrnParams<element::Type_t::bf16>(element::bf16),
+                                                            generateGrnParams<element::Type_t::f16>(element::f16),
+                                                            generateGrnParams<element::Type_t::f32>(element::f32)};
     std::vector<GrnParams> combinedParams;
     std::for_each(grnTypeParams.begin(), grnTypeParams.end(), [&](std::vector<GrnParams> params) {
         combinedParams.insert(combinedParams.end(), params.begin(), params.end());
@@ -108,6 +169,8 @@ std::vector<GrnParams> generateGrnCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GRN_With_Hardcoded_Refs, ReferenceGrnLayerTest, ::testing::ValuesIn(generateGrnCombinedParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_GRN_With_Hardcoded_Refs,
+                         ReferenceGrnLayerTest,
+                         ::testing::ValuesIn(generateGrnCombinedParams()),
                          ReferenceGrnLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/group_convolution.cpp b/src/plugins/template/tests/functional/op_reference/group_convolution.cpp
index b49258f8e5a4a5..45c50624338307 100644
--- a/src/plugins/template/tests/functional/op_reference/group_convolution.cpp
+++ b/src/plugins/template/tests/functional/op_reference/group_convolution.cpp
@@ -4,8 +4,8 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/op/group_conv.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/group_conv.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -13,10 +13,17 @@ using namespace ov;
 namespace {
 struct GroupConvolutionParams {
     template <class IT>
-    GroupConvolutionParams(const PartialShape& inputShape, const PartialShape& filterShape, const PartialShape& outputShape,
-                      const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues, const std::vector<IT>& oValues,
-                      const Strides& strides, const CoordinateDiff& padBegin, const CoordinateDiff& padEnd, const Strides& dialations)
+    GroupConvolutionParams(const PartialShape& inputShape,
+                           const PartialShape& filterShape,
+                           const PartialShape& outputShape,
+                           const element::Type& iType,
+                           const std::vector<IT>& iValues,
+                           const std::vector<IT>& filterValues,
+                           const std::vector<IT>& oValues,
+                           const Strides& strides,
+                           const CoordinateDiff& padBegin,
+                           const CoordinateDiff& padEnd,
+                           const Strides& dialations)
         : inputShape(inputShape),
           filterShape(filterShape),
           outputShape(outputShape),
@@ -46,7 +53,8 @@ struct GroupConvolutionParams {
     ov::Strides dialations;
 };
 
-class ReferenceGroupConvolutionLayerTest : public testing::TestWithParam<GroupConvolutionParams>, public CommonReferenceTest {
+class ReferenceGroupConvolutionLayerTest : public testing::TestWithParam<GroupConvolutionParams>,
+                                           public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -76,13 +84,13 @@ class ReferenceGroupConvolutionLayerTest : public testing::TestWithParam<GroupCo
         const auto in = std::make_shared<op::v0::Parameter>(params.inType, params.inputShape);
         const auto filter = std::make_shared<op::v0::Parameter>(params.inType, params.filterShape);
         const auto GroupConvolution = std::make_shared<op::v1::GroupConvolution>(in,
-                                                                       filter,
-                                                                       params.strides,
-                                                                       params.padBegin,
-                                                                       params.padEnd,
-                                                                       params.dialations,
-                                                                       auto_pad);
-        return std::make_shared<ov::Model>(NodeVector {GroupConvolution}, ParameterVector {in, filter});
+                                                                                 filter,
+                                                                                 params.strides,
+                                                                                 params.padBegin,
+                                                                                 params.padEnd,
+                                                                                 params.dialations,
+                                                                                 auto_pad);
+        return std::make_shared<ov::Model>(NodeVector{GroupConvolution}, ParameterVector{in, filter});
     }
 };
 
@@ -94,74 +102,77 @@ template <element::Type_t IN_ET>
 std::vector<GroupConvolutionParams> generateGroupConvolutionParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<GroupConvolutionParams> groupConvolutionParams {
-// --------------------- 1D GroupConvolution ------------------------------------------
-        GroupConvolutionParams(PartialShape {1, 1, 6},
-                          PartialShape {1, 1, 1, 3},
-                          PartialShape {1, 1, 4},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0, 1, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{5, 6, 7, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionParams(PartialShape {1, 2, 6},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {1, 2, 4},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0, 1, 2,
-                                         1, 3, 3, 0, 1, 2},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{10, 3, 6, 6,
-                                         6, 9, 10, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionParams(PartialShape {1, 2, 6},
-                          PartialShape {2, 2, 1, 3},
-                          PartialShape {1, 4, 4},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0, 1, 2,
-                                         -1, -3, -3, 0, 1, 2},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1,
-                                         -3, 0, 1,
-                                         3, 2, -1},
-                          std::vector<T>{
-                                     10, 3, 6, 6,
-                                     6, 9, 10, 2,
-                                     0, 9, 10, 2,
-                                     -6, -15, -10, 0},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionParams(PartialShape {2, 2, 6},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {2, 2, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // -- batch 1 --
-                                    1, 3, 3, 0, 1, 2,
-                                    1, 3, 3, 0, 1, 2,
-                                    // -- batch 2 --
-                                    1, 3, 3, 0, 1, 2,
-                                    1, 3, 3, 0, 1, 2},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{
-                                     10, 3, 6, 6,
-                                     6, 9, 10, 2,
-                                     10, 3, 6, 6,
-                                     6, 9, 10, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
+    std::vector<GroupConvolutionParams> groupConvolutionParams{
+        // --------------------- 1D GroupConvolution ------------------------------------------
+        GroupConvolutionParams(PartialShape{1, 1, 6},
+                               PartialShape{1, 1, 1, 3},
+                               PartialShape{1, 1, 4},
+                               IN_ET,
+                               std::vector<T>{1, 3, 3, 0, 1, 2},
+                               std::vector<T>{2, 0, 1},
+                               std::vector<T>{5, 6, 7, 2},
+                               {1},
+                               {0},
+                               {0},
+                               {1}),
+        GroupConvolutionParams(PartialShape{1, 2, 6},
+                               PartialShape{2, 1, 1, 3},
+                               PartialShape{1, 2, 4},
+                               IN_ET,
+                               std::vector<T>{1, 3, 3, 0, 1, 2, 1, 3, 3, 0, 1, 2},
+                               std::vector<T>{1, 0, 3, 3, 0, 1},
+                               std::vector<T>{10, 3, 6, 6, 6, 9, 10, 2},
+                               {1},
+                               {0},
+                               {0},
+                               {1}),
+        GroupConvolutionParams(PartialShape{1, 2, 6},
+                               PartialShape{2, 2, 1, 3},
+                               PartialShape{1, 4, 4},
+                               IN_ET,
+                               std::vector<T>{1, 3, 3, 0, 1, 2, -1, -3, -3, 0, 1, 2},
+                               std::vector<T>{1, 0, 3, 3, 0, 1, -3, 0, 1, 3, 2, -1},
+                               std::vector<T>{10, 3, 6, 6, 6, 9, 10, 2, 0, 9, 10, 2, -6, -15, -10, 0},
+                               {1},
+                               {0},
+                               {0},
+                               {1}),
+        GroupConvolutionParams(PartialShape{2, 2, 6},
+                               PartialShape{2, 1, 1, 3},
+                               PartialShape{2, 2, 4},
+                               IN_ET,
+                               std::vector<T>{// -- batch 1 --
+                                              1,
+                                              3,
+                                              3,
+                                              0,
+                                              1,
+                                              2,
+                                              1,
+                                              3,
+                                              3,
+                                              0,
+                                              1,
+                                              2,
+                                              // -- batch 2 --
+                                              1,
+                                              3,
+                                              3,
+                                              0,
+                                              1,
+                                              2,
+                                              1,
+                                              3,
+                                              3,
+                                              0,
+                                              1,
+                                              2},
+                               std::vector<T>{1, 0, 3, 3, 0, 1},
+                               std::vector<T>{10, 3, 6, 6, 6, 9, 10, 2, 10, 3, 6, 6, 6, 9, 10, 2},
+                               {1},
+                               {0},
+                               {0},
+                               {1}),
     };
     return groupConvolutionParams;
 }
@@ -170,61 +181,72 @@ template <element::Type_t IN_ET>
 std::vector<GroupConvolutionParams> generateGroupConvolutionUintParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<GroupConvolutionParams> groupConvolutionParams {
-// --------------------- 1D GroupConvolution ------------------------------------------
-        GroupConvolutionParams(PartialShape {1, 1, 6},
-                          PartialShape {1, 1, 1, 3},
-                          PartialShape {1, 1, 4},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0, 1, 2},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{5, 6, 7, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionParams(PartialShape {1, 2, 6},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {1, 2, 4},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0, 1, 2,
-                                         1, 3, 3, 0, 1, 2},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{10, 3, 6, 6,
-                                         6, 9, 10, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionParams(PartialShape {2, 2, 6},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {2, 2, 4},
-                          IN_ET,
-                          std::vector<T>{
-                                    // -- batch 1 --
-                                    1, 3, 3, 0, 1, 2,
-                                    1, 3, 3, 0, 1, 2,
-                                    // -- batch 2 --
-                                    1, 3, 3, 0, 1, 2,
-                                    1, 3, 3, 0, 1, 2},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{
-                                     10, 3, 6, 6,
-                                     6, 9, 10, 2,
-                                     10, 3, 6, 6,
-                                     6, 9, 10, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
+    std::vector<GroupConvolutionParams> groupConvolutionParams{
+        // --------------------- 1D GroupConvolution ------------------------------------------
+        GroupConvolutionParams(PartialShape{1, 1, 6},
+                               PartialShape{1, 1, 1, 3},
+                               PartialShape{1, 1, 4},
+                               IN_ET,
+                               std::vector<T>{1, 3, 3, 0, 1, 2},
+                               std::vector<T>{2, 0, 1},
+                               std::vector<T>{5, 6, 7, 2},
+                               {1},
+                               {0},
+                               {0},
+                               {1}),
+        GroupConvolutionParams(PartialShape{1, 2, 6},
+                               PartialShape{2, 1, 1, 3},
+                               PartialShape{1, 2, 4},
+                               IN_ET,
+                               std::vector<T>{1, 3, 3, 0, 1, 2, 1, 3, 3, 0, 1, 2},
+                               std::vector<T>{1, 0, 3, 3, 0, 1},
+                               std::vector<T>{10, 3, 6, 6, 6, 9, 10, 2},
+                               {1},
+                               {0},
+                               {0},
+                               {1}),
+        GroupConvolutionParams(PartialShape{2, 2, 6},
+                               PartialShape{2, 1, 1, 3},
+                               PartialShape{2, 2, 4},
+                               IN_ET,
+                               std::vector<T>{// -- batch 1 --
+                                              1,
+                                              3,
+                                              3,
+                                              0,
+                                              1,
+                                              2,
+                                              1,
+                                              3,
+                                              3,
+                                              0,
+                                              1,
+                                              2,
+                                              // -- batch 2 --
+                                              1,
+                                              3,
+                                              3,
+                                              0,
+                                              1,
+                                              2,
+                                              1,
+                                              3,
+                                              3,
+                                              0,
+                                              1,
+                                              2},
+                               std::vector<T>{1, 0, 3, 3, 0, 1},
+                               std::vector<T>{10, 3, 6, 6, 6, 9, 10, 2, 10, 3, 6, 6, 6, 9, 10, 2},
+                               {1},
+                               {0},
+                               {0},
+                               {1}),
     };
     return groupConvolutionParams;
 }
 
 std::vector<GroupConvolutionParams> generateGroupConvolutionCombinedParams() {
-    const std::vector<std::vector<GroupConvolutionParams>> groupConvolutionTypeParams {
+    const std::vector<std::vector<GroupConvolutionParams>> groupConvolutionTypeParams{
         generateGroupConvolutionParams<element::Type_t::f64>(),
         generateGroupConvolutionParams<element::Type_t::f32>(),
         generateGroupConvolutionParams<element::Type_t::f16>(),
@@ -236,8 +258,7 @@ std::vector<GroupConvolutionParams> generateGroupConvolutionCombinedParams() {
         generateGroupConvolutionUintParams<element::Type_t::u64>(),
         generateGroupConvolutionUintParams<element::Type_t::u32>(),
         generateGroupConvolutionUintParams<element::Type_t::u16>(),
-        generateGroupConvolutionUintParams<element::Type_t::u8>()
-        };
+        generateGroupConvolutionUintParams<element::Type_t::u8>()};
     std::vector<GroupConvolutionParams> combinedParams;
 
     for (const auto& params : groupConvolutionTypeParams) {
@@ -246,7 +267,9 @@ std::vector<GroupConvolutionParams> generateGroupConvolutionCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GroupConvolution_With_Hardcoded_Refs, ReferenceGroupConvolutionLayerTest,
-    testing::ValuesIn(generateGroupConvolutionCombinedParams()), ReferenceGroupConvolutionLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_GroupConvolution_With_Hardcoded_Refs,
+                         ReferenceGroupConvolutionLayerTest,
+                         testing::ValuesIn(generateGroupConvolutionCombinedParams()),
+                         ReferenceGroupConvolutionLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/group_convolution_backprop.cpp b/src/plugins/template/tests/functional/op_reference/group_convolution_backprop.cpp
index 5570c06369030f..6cc21eb9cb4f04 100644
--- a/src/plugins/template/tests/functional/op_reference/group_convolution_backprop.cpp
+++ b/src/plugins/template/tests/functional/op_reference/group_convolution_backprop.cpp
@@ -4,8 +4,8 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/op/group_conv.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/group_conv.hpp"
 #include "openvino/opsets/opset8.hpp"
 
 using namespace reference_tests;
@@ -14,11 +14,18 @@ using namespace ov;
 namespace {
 struct GroupConvolutionBackpropDataParams {
     template <class IT>
-    GroupConvolutionBackpropDataParams(const PartialShape& inputShape, const PartialShape& filterShape, const PartialShape& outputShape,
-                      const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues, const std::vector<IT>& oValues,
-                      const Strides& strides, const CoordinateDiff& padBegin, const CoordinateDiff& padEnd, const Strides& dialations,
-                      const CoordinateDiff& outPadding = {})
+    GroupConvolutionBackpropDataParams(const PartialShape& inputShape,
+                                       const PartialShape& filterShape,
+                                       const PartialShape& outputShape,
+                                       const element::Type& iType,
+                                       const std::vector<IT>& iValues,
+                                       const std::vector<IT>& filterValues,
+                                       const std::vector<IT>& oValues,
+                                       const Strides& strides,
+                                       const CoordinateDiff& padBegin,
+                                       const CoordinateDiff& padEnd,
+                                       const Strides& dialations,
+                                       const CoordinateDiff& outPadding = {})
         : inputShape(inputShape),
           filterShape(filterShape),
           outputShape(outputShape),
@@ -52,11 +59,17 @@ struct GroupConvolutionBackpropDataParams {
 
 struct GroupConvolutionBackpropDataOutShapeParams {
     template <class IT>
-    GroupConvolutionBackpropDataOutShapeParams(const PartialShape& inputShape, const PartialShape& filterShape, const PartialShape& outputShape,
-                      const element::Type& iType,
-                      const std::vector<IT>& iValues, const std::vector<IT>& filterValues, const std::vector<IT>& oValues,
-                      const Strides& strides, const Strides& dialations,
-                      const Shape& constantOutputShape, const std::vector<int64_t>& constantOutputShapeData)
+    GroupConvolutionBackpropDataOutShapeParams(const PartialShape& inputShape,
+                                               const PartialShape& filterShape,
+                                               const PartialShape& outputShape,
+                                               const element::Type& iType,
+                                               const std::vector<IT>& iValues,
+                                               const std::vector<IT>& filterValues,
+                                               const std::vector<IT>& oValues,
+                                               const Strides& strides,
+                                               const Strides& dialations,
+                                               const Shape& constantOutputShape,
+                                               const std::vector<int64_t>& constantOutputShapeData)
         : inputShape(inputShape),
           filterShape(filterShape),
           outputShape(outputShape),
@@ -86,7 +99,9 @@ struct GroupConvolutionBackpropDataOutShapeParams {
     std::vector<int64_t> constantOutputShapeData;
 };
 
-class ReferenceGroupConvolutionBackpropDataLayerTest : public testing::TestWithParam<GroupConvolutionBackpropDataParams>, public CommonReferenceTest {
+class ReferenceGroupConvolutionBackpropDataLayerTest
+    : public testing::TestWithParam<GroupConvolutionBackpropDataParams>,
+      public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -118,30 +133,33 @@ class ReferenceGroupConvolutionBackpropDataLayerTest : public testing::TestWithP
         const auto in = std::make_shared<op::v0::Parameter>(params.inType, params.inputShape);
         const auto filter = std::make_shared<op::v0::Parameter>(params.inType, params.filterShape);
         if (params.outPadding.size() != 0) {
-            const auto GroupConvolutionBackpropData = std::make_shared<op::v1::GroupConvolutionBackpropData>(in,
-                                                                        filter,
-                                                                        params.strides,
-                                                                        params.padBegin,
-                                                                        params.padEnd,
-                                                                        params.dialations,
-                                                                        auto_pad,
-                                                                        params.outPadding);
-            return std::make_shared<ov::Model>(NodeVector {GroupConvolutionBackpropData}, ParameterVector {in, filter});
+            const auto GroupConvolutionBackpropData =
+                std::make_shared<op::v1::GroupConvolutionBackpropData>(in,
+                                                                       filter,
+                                                                       params.strides,
+                                                                       params.padBegin,
+                                                                       params.padEnd,
+                                                                       params.dialations,
+                                                                       auto_pad,
+                                                                       params.outPadding);
+            return std::make_shared<ov::Model>(NodeVector{GroupConvolutionBackpropData}, ParameterVector{in, filter});
         } else {
-            const auto GroupConvolutionBackpropData = std::make_shared<op::v1::GroupConvolutionBackpropData>(in,
-                                                                        filter,
-                                                                        params.strides,
-                                                                        params.padBegin,
-                                                                        params.padEnd,
-                                                                        params.dialations,
-                                                                        auto_pad);
-            return std::make_shared<ov::Model>(NodeVector {GroupConvolutionBackpropData}, ParameterVector {in, filter});
+            const auto GroupConvolutionBackpropData =
+                std::make_shared<op::v1::GroupConvolutionBackpropData>(in,
+                                                                       filter,
+                                                                       params.strides,
+                                                                       params.padBegin,
+                                                                       params.padEnd,
+                                                                       params.dialations,
+                                                                       auto_pad);
+            return std::make_shared<ov::Model>(NodeVector{GroupConvolutionBackpropData}, ParameterVector{in, filter});
         }
     }
 };
 
 class ReferenceGroupConvolutionBackpropDataLayerOutShapeTest
-        : public testing::TestWithParam<GroupConvolutionBackpropDataOutShapeParams>, public CommonReferenceTest {
+    : public testing::TestWithParam<GroupConvolutionBackpropDataOutShapeParams>,
+      public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -169,14 +187,17 @@ class ReferenceGroupConvolutionBackpropDataLayerOutShapeTest
 
         const auto in = std::make_shared<op::v0::Parameter>(params.inType, params.inputShape);
         const auto filter = std::make_shared<op::v0::Parameter>(params.inType, params.filterShape);
-        auto output_shape = std::make_shared<opset8::Constant>(element::i64, params.constantOutputShape, params.constantOutputShapeData);
-        const auto GroupConvolutionBackpropData = std::make_shared<op::v1::GroupConvolutionBackpropData>(in,
-                                                                    filter,
-                                                                    output_shape,
-                                                                    params.strides,
-                                                                    params.dialations,
-                                                                    auto_pad);
-        return std::make_shared<ov::Model>(NodeVector {GroupConvolutionBackpropData}, ParameterVector {in, filter});
+        auto output_shape = std::make_shared<opset8::Constant>(element::i64,
+                                                               params.constantOutputShape,
+                                                               params.constantOutputShapeData);
+        const auto GroupConvolutionBackpropData =
+            std::make_shared<op::v1::GroupConvolutionBackpropData>(in,
+                                                                   filter,
+                                                                   output_shape,
+                                                                   params.strides,
+                                                                   params.dialations,
+                                                                   auto_pad);
+        return std::make_shared<ov::Model>(NodeVector{GroupConvolutionBackpropData}, ParameterVector{in, filter});
     }
 };
 
@@ -192,104 +213,104 @@ template <element::Type_t IN_ET>
 std::vector<GroupConvolutionBackpropDataParams> generateGroupConvolutionBackpropDataFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<GroupConvolutionBackpropDataParams> groupConvolutionBackpropDataParams {
-// --------------------- 1D GroupConvolutionBackpropData ------------------------------------------
-        GroupConvolutionBackpropDataParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 1, 3},
-                          PartialShape {1, 1, 6},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{2, 6, 7, 3, 3, 0},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {1, 2, 4},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {1, 2, 6},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0,
-                                         1, 2, 1, 3},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{1, 3, 6, 9, 9, 0,
-                                         3, 6, 4, 11, 1, 3},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {1, 4, 4},
-                          PartialShape {2, 2, 1, 3},
-                          PartialShape {1, 2, 6},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0,
-                                         1, 2, -1, -3,
-                                         -3, 0, 1, 2,
-                                         0, -2, 3, -1},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1,
-                                         -3, 0, 1,
-                                         3, 2, -1},
-                          std::vector<T>{4, 9, 4, 2, 8, -3,
-                                         9, -6, -1, -1, -4, 3},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {2, 2, 4},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {2, 2, 6},
-                          IN_ET,
-                          std::vector<T>{// -- batch 1 --
-                                         1, 3, 0, 1,
-                                         1, 3, 0, 2,
-                                         // -- batch 2 --
-                                         1, 3, 0, 1,
-                                         1, 3, 0, 2},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{1, 3, 3, 10, 0, 3,
-                                         3, 9, 1,  9, 0, 2,
-                                         1, 3, 3, 10, 0, 3,
-                                         3, 9, 1,  9, 0, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {1, 1, 3, 3},
-                          PartialShape {1, 1, 1, 3, 3},
-                          PartialShape {1, 1, 6, 6},
-                          IN_ET,
-                          std::vector<T>{0.16857791f,
-                                         -0.15161794f,
-                                         0.08540368f,
-                                         0.1820628f,
-                                         -0.21746576f,
-                                         0.08245695f,
-                                         0.1431433f,
-                                         -0.43156421f,
-                                         0.30591947f},
-                          std::vector<T>{-0.06230065f,
-                                         0.37932432f,
-                                         -0.25388849f,
-                                         0.33878803f,
-                                         0.43709868f,
-                                         -0.22477469f,
-                                         0.04118127f,
-                                         -0.44696793f,
-                                         0.06373066f},
-                          std::vector<T>{0.07368518f,  -0.08925839f, -0.06627201f, 0.06301362f,  0.03732984f,  -0.01919658f,
-                                         -0.00628807f, -0.02817563f, -0.01472169f, 0.04392925f,  -0.00689478f, -0.01549204f,
-                                         0.07957941f,  -0.11459791f, -0.09505399f, 0.07681622f,  0.03604182f,  -0.01853423f,
-                                         -0.0270785f,  -0.00680824f, -0.06650258f, 0.08004665f,  0.07918708f,  -0.0724144f,
-                                         0.06256775f,  -0.17838378f, -0.18863615f, 0.20064656f,  0.133717f,    -0.06876295f,
-                                         -0.06398046f, -0.00864975f, 0.19289537f,  -0.01490572f, -0.13673618f, 0.01949645f},
-                          {2, 2},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1},
-                          {1, 1}),
+    std::vector<GroupConvolutionBackpropDataParams> groupConvolutionBackpropDataParams{
+        // --------------------- 1D GroupConvolutionBackpropData ------------------------------------------
+        GroupConvolutionBackpropDataParams(PartialShape{1, 1, 4},
+                                           PartialShape{1, 1, 1, 3},
+                                           PartialShape{1, 1, 6},
+                                           IN_ET,
+                                           std::vector<T>{1, 3, 3, 0},
+                                           std::vector<T>{2, 0, 1},
+                                           std::vector<T>{2, 6, 7, 3, 3, 0},
+                                           {1},
+                                           {0},
+                                           {0},
+                                           {1}),
+        GroupConvolutionBackpropDataParams(PartialShape{1, 2, 4},
+                                           PartialShape{2, 1, 1, 3},
+                                           PartialShape{1, 2, 6},
+                                           IN_ET,
+                                           std::vector<T>{1, 3, 3, 0, 1, 2, 1, 3},
+                                           std::vector<T>{1, 0, 3, 3, 0, 1},
+                                           std::vector<T>{1, 3, 6, 9, 9, 0, 3, 6, 4, 11, 1, 3},
+                                           {1},
+                                           {0},
+                                           {0},
+                                           {1}),
+        GroupConvolutionBackpropDataParams(PartialShape{1, 4, 4},
+                                           PartialShape{2, 2, 1, 3},
+                                           PartialShape{1, 2, 6},
+                                           IN_ET,
+                                           std::vector<T>{1, 3, 3, 0, 1, 2, -1, -3, -3, 0, 1, 2, 0, -2, 3, -1},
+                                           std::vector<T>{1, 0, 3, 3, 0, 1, -3, 0, 1, 3, 2, -1},
+                                           std::vector<T>{4, 9, 4, 2, 8, -3, 9, -6, -1, -1, -4, 3},
+                                           {1},
+                                           {0},
+                                           {0},
+                                           {1}),
+        GroupConvolutionBackpropDataParams(
+            PartialShape{2, 2, 4},
+            PartialShape{2, 1, 1, 3},
+            PartialShape{2, 2, 6},
+            IN_ET,
+            std::vector<T>{// -- batch 1 --
+                           1,
+                           3,
+                           0,
+                           1,
+                           1,
+                           3,
+                           0,
+                           2,
+                           // -- batch 2 --
+                           1,
+                           3,
+                           0,
+                           1,
+                           1,
+                           3,
+                           0,
+                           2},
+            std::vector<T>{1, 0, 3, 3, 0, 1},
+            std::vector<T>{1, 3, 3, 10, 0, 3, 3, 9, 1, 9, 0, 2, 1, 3, 3, 10, 0, 3, 3, 9, 1, 9, 0, 2},
+            {1},
+            {0},
+            {0},
+            {1}),
+        GroupConvolutionBackpropDataParams(
+            PartialShape{1, 1, 3, 3},
+            PartialShape{1, 1, 1, 3, 3},
+            PartialShape{1, 1, 6, 6},
+            IN_ET,
+            std::vector<T>{0.16857791f,
+                           -0.15161794f,
+                           0.08540368f,
+                           0.1820628f,
+                           -0.21746576f,
+                           0.08245695f,
+                           0.1431433f,
+                           -0.43156421f,
+                           0.30591947f},
+            std::vector<T>{-0.06230065f,
+                           0.37932432f,
+                           -0.25388849f,
+                           0.33878803f,
+                           0.43709868f,
+                           -0.22477469f,
+                           0.04118127f,
+                           -0.44696793f,
+                           0.06373066f},
+            std::vector<T>{0.07368518f,  -0.08925839f, -0.06627201f, 0.06301362f,  0.03732984f,  -0.01919658f,
+                           -0.00628807f, -0.02817563f, -0.01472169f, 0.04392925f,  -0.00689478f, -0.01549204f,
+                           0.07957941f,  -0.11459791f, -0.09505399f, 0.07681622f,  0.03604182f,  -0.01853423f,
+                           -0.0270785f,  -0.00680824f, -0.06650258f, 0.08004665f,  0.07918708f,  -0.0724144f,
+                           0.06256775f,  -0.17838378f, -0.18863615f, 0.20064656f,  0.133717f,    -0.06876295f,
+                           -0.06398046f, -0.00864975f, 0.19289537f,  -0.01490572f, -0.13673618f, 0.01949645f},
+            {2, 2},
+            {1, 1},
+            {1, 1},
+            {1, 1},
+            {1, 1}),
     };
     return groupConvolutionBackpropDataParams;
 }
@@ -298,71 +319,70 @@ template <element::Type_t IN_ET>
 std::vector<GroupConvolutionBackpropDataParams> generateGroupConvolutionBackpropDataIntParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<GroupConvolutionBackpropDataParams> groupConvolutionBackpropDataParams {
-// --------------------- 1D GroupConvolutionBackpropData ------------------------------------------
-        GroupConvolutionBackpropDataParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 1, 3},
-                          PartialShape {1, 1, 6},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{2, 6, 7, 3, 3, 0},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {1, 2, 4},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {1, 2, 6},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0,
-                                         1, 2, 1, 3},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{1, 3, 6, 9, 9, 0,
-                                         3, 6, 4, 11, 1, 3},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {1, 4, 4},
-                          PartialShape {2, 2, 1, 3},
-                          PartialShape {1, 2, 6},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0,
-                                         1, 2, -1, -3,
-                                         -3, 0, 1, 2,
-                                         0, -2, 3, -1},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1,
-                                         -3, 0, 1,
-                                         3, 2, -1},
-                          std::vector<T>{4, 9, 4, 2, 8, -3,
-                                         9, -6, -1, -1, -4, 3},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {2, 2, 4},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {2, 2, 6},
-                          IN_ET,
-                          std::vector<T>{// -- batch 1 --
-                                         1, 3, 0, 1,
-                                         1, 3, 0, 2,
-                                         // -- batch 2 --
-                                         1, 3, 0, 1,
-                                         1, 3, 0, 2},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{1, 3, 3, 10, 0, 3,
-                                         3, 9, 1,  9, 0, 2,
-                                         1, 3, 3, 10, 0, 3,
-                                         3, 9, 1,  9, 0, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
+    std::vector<GroupConvolutionBackpropDataParams> groupConvolutionBackpropDataParams{
+        // --------------------- 1D GroupConvolutionBackpropData ------------------------------------------
+        GroupConvolutionBackpropDataParams(PartialShape{1, 1, 4},
+                                           PartialShape{1, 1, 1, 3},
+                                           PartialShape{1, 1, 6},
+                                           IN_ET,
+                                           std::vector<T>{1, 3, 3, 0},
+                                           std::vector<T>{2, 0, 1},
+                                           std::vector<T>{2, 6, 7, 3, 3, 0},
+                                           {1},
+                                           {0},
+                                           {0},
+                                           {1}),
+        GroupConvolutionBackpropDataParams(PartialShape{1, 2, 4},
+                                           PartialShape{2, 1, 1, 3},
+                                           PartialShape{1, 2, 6},
+                                           IN_ET,
+                                           std::vector<T>{1, 3, 3, 0, 1, 2, 1, 3},
+                                           std::vector<T>{1, 0, 3, 3, 0, 1},
+                                           std::vector<T>{1, 3, 6, 9, 9, 0, 3, 6, 4, 11, 1, 3},
+                                           {1},
+                                           {0},
+                                           {0},
+                                           {1}),
+        GroupConvolutionBackpropDataParams(PartialShape{1, 4, 4},
+                                           PartialShape{2, 2, 1, 3},
+                                           PartialShape{1, 2, 6},
+                                           IN_ET,
+                                           std::vector<T>{1, 3, 3, 0, 1, 2, -1, -3, -3, 0, 1, 2, 0, -2, 3, -1},
+                                           std::vector<T>{1, 0, 3, 3, 0, 1, -3, 0, 1, 3, 2, -1},
+                                           std::vector<T>{4, 9, 4, 2, 8, -3, 9, -6, -1, -1, -4, 3},
+                                           {1},
+                                           {0},
+                                           {0},
+                                           {1}),
+        GroupConvolutionBackpropDataParams(
+            PartialShape{2, 2, 4},
+            PartialShape{2, 1, 1, 3},
+            PartialShape{2, 2, 6},
+            IN_ET,
+            std::vector<T>{// -- batch 1 --
+                           1,
+                           3,
+                           0,
+                           1,
+                           1,
+                           3,
+                           0,
+                           2,
+                           // -- batch 2 --
+                           1,
+                           3,
+                           0,
+                           1,
+                           1,
+                           3,
+                           0,
+                           2},
+            std::vector<T>{1, 0, 3, 3, 0, 1},
+            std::vector<T>{1, 3, 3, 10, 0, 3, 3, 9, 1, 9, 0, 2, 1, 3, 3, 10, 0, 3, 3, 9, 1, 9, 0, 2},
+            {1},
+            {0},
+            {0},
+            {1}),
     };
     return groupConvolutionBackpropDataParams;
 }
@@ -371,59 +391,65 @@ template <element::Type_t IN_ET>
 std::vector<GroupConvolutionBackpropDataParams> generateGroupConvolutionBackpropDataUintParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<GroupConvolutionBackpropDataParams> groupConvolutionBackpropDataParams {
-// --------------------- 1D GroupConvolutionBackpropData ------------------------------------------
-        GroupConvolutionBackpropDataParams(PartialShape {1, 1, 4},
-                          PartialShape {1, 1, 1, 3},
-                          PartialShape {1, 1, 6},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0},
-                          std::vector<T>{2, 0, 1},
-                          std::vector<T>{2, 6, 7, 3, 3, 0},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {1, 2, 4},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {1, 2, 6},
-                          IN_ET,
-                          std::vector<T>{1, 3, 3, 0,
-                                         1, 2, 1, 3},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{1, 3, 6, 9, 9, 0,
-                                         3, 6, 4, 11, 1, 3},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
-        GroupConvolutionBackpropDataParams(PartialShape {2, 2, 4},
-                          PartialShape {2, 1, 1, 3},
-                          PartialShape {2, 2, 6},
-                          IN_ET,
-                          std::vector<T>{// -- batch 1 --
-                                         1, 3, 0, 1,
-                                         1, 3, 0, 2,
-                                         // -- batch 2 --
-                                         1, 3, 0, 1,
-                                         1, 3, 0, 2},
-                          std::vector<T>{1, 0, 3,
-                                         3, 0, 1},
-                          std::vector<T>{1, 3, 3, 10, 0, 3,
-                                         3, 9, 1,  9, 0, 2,
-                                         1, 3, 3, 10, 0, 3,
-                                         3, 9, 1,  9, 0, 2},
-                          {1},
-                          {0},
-                          {0},
-                          {1}),
+    std::vector<GroupConvolutionBackpropDataParams> groupConvolutionBackpropDataParams{
+        // --------------------- 1D GroupConvolutionBackpropData ------------------------------------------
+        GroupConvolutionBackpropDataParams(PartialShape{1, 1, 4},
+                                           PartialShape{1, 1, 1, 3},
+                                           PartialShape{1, 1, 6},
+                                           IN_ET,
+                                           std::vector<T>{1, 3, 3, 0},
+                                           std::vector<T>{2, 0, 1},
+                                           std::vector<T>{2, 6, 7, 3, 3, 0},
+                                           {1},
+                                           {0},
+                                           {0},
+                                           {1}),
+        GroupConvolutionBackpropDataParams(PartialShape{1, 2, 4},
+                                           PartialShape{2, 1, 1, 3},
+                                           PartialShape{1, 2, 6},
+                                           IN_ET,
+                                           std::vector<T>{1, 3, 3, 0, 1, 2, 1, 3},
+                                           std::vector<T>{1, 0, 3, 3, 0, 1},
+                                           std::vector<T>{1, 3, 6, 9, 9, 0, 3, 6, 4, 11, 1, 3},
+                                           {1},
+                                           {0},
+                                           {0},
+                                           {1}),
+        GroupConvolutionBackpropDataParams(
+            PartialShape{2, 2, 4},
+            PartialShape{2, 1, 1, 3},
+            PartialShape{2, 2, 6},
+            IN_ET,
+            std::vector<T>{// -- batch 1 --
+                           1,
+                           3,
+                           0,
+                           1,
+                           1,
+                           3,
+                           0,
+                           2,
+                           // -- batch 2 --
+                           1,
+                           3,
+                           0,
+                           1,
+                           1,
+                           3,
+                           0,
+                           2},
+            std::vector<T>{1, 0, 3, 3, 0, 1},
+            std::vector<T>{1, 3, 3, 10, 0, 3, 3, 9, 1, 9, 0, 2, 1, 3, 3, 10, 0, 3, 3, 9, 1, 9, 0, 2},
+            {1},
+            {0},
+            {0},
+            {1}),
     };
     return groupConvolutionBackpropDataParams;
 }
 
 std::vector<GroupConvolutionBackpropDataParams> generateGroupConvolutionBackpropDataCombinedParams() {
-    const std::vector<std::vector<GroupConvolutionBackpropDataParams>> groupConvolutionBackpropDataTypeParams {
+    const std::vector<std::vector<GroupConvolutionBackpropDataParams>> groupConvolutionBackpropDataTypeParams{
         generateGroupConvolutionBackpropDataFloatParams<element::Type_t::f64>(),
         generateGroupConvolutionBackpropDataFloatParams<element::Type_t::f32>(),
         generateGroupConvolutionBackpropDataFloatParams<element::Type_t::f16>(),
@@ -435,8 +461,7 @@ std::vector<GroupConvolutionBackpropDataParams> generateGroupConvolutionBackprop
         generateGroupConvolutionBackpropDataUintParams<element::Type_t::u64>(),
         generateGroupConvolutionBackpropDataUintParams<element::Type_t::u32>(),
         generateGroupConvolutionBackpropDataUintParams<element::Type_t::u16>(),
-        generateGroupConvolutionBackpropDataUintParams<element::Type_t::u8>()
-        };
+        generateGroupConvolutionBackpropDataUintParams<element::Type_t::u8>()};
     std::vector<GroupConvolutionBackpropDataParams> combinedParams;
 
     for (const auto& params : groupConvolutionBackpropDataTypeParams) {
@@ -449,38 +474,38 @@ template <element::Type_t IN_ET>
 std::vector<GroupConvolutionBackpropDataOutShapeParams> generateGroupConvolutionBackpropDataOutShapeParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<GroupConvolutionBackpropDataOutShapeParams> groupConvolutionBackpropDataOutShapeParams {
-// --------------------- 1D GroupConvolutionBackpropData ------------------------------------------
-        GroupConvolutionBackpropDataOutShapeParams(PartialShape {1, 1, 1, 10},
-                          PartialShape {1, 1, 1, 1, 5},
-                          PartialShape {1, 1, 1, 14},
-                          IN_ET,
-                          std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9},
-                          std::vector<T>{1, 2, 3, 2, 1},
-                          std::vector<T>{0, 1, 4, 10, 18, 27, 36, 45, 54, 63, 62, 50, 26, 9},
-                          {1, 1},
-                          {1, 1},
-                          {2},
-                          {1, 14}),
+    std::vector<GroupConvolutionBackpropDataOutShapeParams> groupConvolutionBackpropDataOutShapeParams{
+        // --------------------- 1D GroupConvolutionBackpropData ------------------------------------------
+        GroupConvolutionBackpropDataOutShapeParams(PartialShape{1, 1, 1, 10},
+                                                   PartialShape{1, 1, 1, 1, 5},
+                                                   PartialShape{1, 1, 1, 14},
+                                                   IN_ET,
+                                                   std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9},
+                                                   std::vector<T>{1, 2, 3, 2, 1},
+                                                   std::vector<T>{0, 1, 4, 10, 18, 27, 36, 45, 54, 63, 62, 50, 26, 9},
+                                                   {1, 1},
+                                                   {1, 1},
+                                                   {2},
+                                                   {1, 14}),
     };
     return groupConvolutionBackpropDataOutShapeParams;
 }
 
 std::vector<GroupConvolutionBackpropDataOutShapeParams> generateGroupConvolutionBackpropDataOutShapeCombinedParams() {
-    const std::vector<std::vector<GroupConvolutionBackpropDataOutShapeParams>> groupConvolutionBackpropDataOutShapeTypeParams {
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::f64>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::f32>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::f16>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::bf16>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::i64>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::i32>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::i16>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::i8>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::u64>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::u32>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::u16>(),
-        generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::u8>()
-        };
+    const std::vector<std::vector<GroupConvolutionBackpropDataOutShapeParams>>
+        groupConvolutionBackpropDataOutShapeTypeParams{
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::f64>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::f32>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::f16>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::bf16>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::i64>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::i32>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::i16>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::i8>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::u64>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::u32>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::u16>(),
+            generateGroupConvolutionBackpropDataOutShapeParams<element::Type_t::u8>()};
     std::vector<GroupConvolutionBackpropDataOutShapeParams> combinedParams;
 
     for (const auto& params : groupConvolutionBackpropDataOutShapeTypeParams) {
@@ -489,10 +514,14 @@ std::vector<GroupConvolutionBackpropDataOutShapeParams> generateGroupConvolution
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GroupConvolutionBackpropData_With_Hardcoded_Refs, ReferenceGroupConvolutionBackpropDataLayerTest,
-    testing::ValuesIn(generateGroupConvolutionBackpropDataCombinedParams()), ReferenceGroupConvolutionBackpropDataLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_GroupConvolutionBackpropData_With_Hardcoded_Refs,
+                         ReferenceGroupConvolutionBackpropDataLayerTest,
+                         testing::ValuesIn(generateGroupConvolutionBackpropDataCombinedParams()),
+                         ReferenceGroupConvolutionBackpropDataLayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_GroupConvolutionBackpropDataOutShape_With_Hardcoded_Refs, ReferenceGroupConvolutionBackpropDataLayerOutShapeTest,
-    testing::ValuesIn(generateGroupConvolutionBackpropDataOutShapeCombinedParams()), ReferenceGroupConvolutionBackpropDataLayerOutShapeTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_GroupConvolutionBackpropDataOutShape_With_Hardcoded_Refs,
+                         ReferenceGroupConvolutionBackpropDataLayerOutShapeTest,
+                         testing::ValuesIn(generateGroupConvolutionBackpropDataOutShapeCombinedParams()),
+                         ReferenceGroupConvolutionBackpropDataLayerOutShapeTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/gru_cell.cpp b/src/plugins/template/tests/functional/op_reference/gru_cell.cpp
index bf0a8373e83cda..8811e0e29dfedf 100644
--- a/src/plugins/template/tests/functional/op_reference/gru_cell.cpp
+++ b/src/plugins/template/tests/functional/op_reference/gru_cell.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/gru_cell.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/gru_cell.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,12 +13,30 @@ using namespace ov;
 
 namespace {
 struct GRUCellParams {
-    GRUCellParams(
-        const int32_t batchSize, const int32_t inputSize, const int32_t hiddenSize, const int32_t gatesCount, const bool linearBeforeReset,
-        const reference_tests::Tensor& X, const reference_tests::Tensor& H_t, const reference_tests::Tensor& W, const reference_tests::Tensor& R, const reference_tests::Tensor& B,
-        const reference_tests::Tensor& Ho, const std::string& testcaseName = "") :
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize), gatesCount(gatesCount), linearBeforeReset(linearBeforeReset),
-        X(X), H_t(H_t), W(W), R(R), B(B), Ho(Ho), testcaseName(testcaseName) {}
+    GRUCellParams(const int32_t batchSize,
+                  const int32_t inputSize,
+                  const int32_t hiddenSize,
+                  const int32_t gatesCount,
+                  const bool linearBeforeReset,
+                  const reference_tests::Tensor& X,
+                  const reference_tests::Tensor& H_t,
+                  const reference_tests::Tensor& W,
+                  const reference_tests::Tensor& R,
+                  const reference_tests::Tensor& B,
+                  const reference_tests::Tensor& Ho,
+                  const std::string& testcaseName = "")
+        : batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          gatesCount(gatesCount),
+          linearBeforeReset(linearBeforeReset),
+          X(X),
+          H_t(H_t),
+          W(W),
+          R(R),
+          B(B),
+          Ho(Ho),
+          testcaseName(testcaseName) {}
 
     int32_t batchSize;
     int32_t inputSize;
@@ -144,78 +163,104 @@ TEST_P(ReferenceGRUCellTestHardsigmoidActivationFunction, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<GRUCellParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<GRUCellParams> params {
+    std::vector<GRUCellParams> params{
         GRUCellParams(
-            2, 3, 3, 3, false,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.52421564f, 0.78845507f, 0.9372873f, 0.59783894f, 0.18278378f, 0.2084126f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.45738035f, 0.996877f, 0.82882977f, 0.47492632f, 0.88471466f, 0.57833236f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.5815369f, 0.16559383f, 0.08464007f, 0.843122f,   0.73968244f, 0.11359601f,
-                0.8295078f, 0.9240567f,  0.10007995f, 0.20573162f, 0.09002485f, 0.2839569f,
-                0.3096991f, 0.5638341f,  0.5787327f,  0.84552664f, 0.16263747f, 0.7243242f,
-                0.8049057f, 0.43966424f, 0.46294412f, 0.9833361f,  0.31369713f, 0.1719934f,
-                0.4937093f, 0.6353004f,  0.77982515f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.16510165f, 0.52435565f, 0.2788478f, 0.99427545f, 0.1623331f,  0.01389796f,
-                0.99669236f, 0.53901845f, 0.8737506f, 0.9254788f,  0.21172932f, 0.11634306f,
-                0.40111724f, 0.37497616f, 0.2903471f, 0.6796794f,  0.65131867f, 0.78163475f,
-                0.12058706f, 0.45591718f, 0.791677f,  0.76497287f, 0.9895242f,  0.7845312f,
-                0.51267904f, 0.49030215f, 0.08498167f}),
-            reference_tests::Tensor(ET, {3 * 3}, std::vector<T>{
-                0.8286678f + 0.9175602f,
-                0.9153158f + 0.14958014f,
-                0.9581612f + 0.49230585f,
-                0.6639213f + 0.63162816f,
-                0.84239805f + 0.4161903f,
-                0.5282445f + 0.22148274f,
-                0.14153397f + 0.50496656f,
-                0.22404431f + 0.34798595f,
-                0.6549655f + 0.6699164f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.48588726f, 0.99670005f, 0.83759373f, 0.5023099f, 0.89410484f, 0.60011315f}),
+            2,
+            3,
+            3,
+            3,
+            false,
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.52421564f, 0.78845507f, 0.9372873f, 0.59783894f, 0.18278378f, 0.2084126f}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.45738035f, 0.996877f, 0.82882977f, 0.47492632f, 0.88471466f, 0.57833236f}),
+            reference_tests::Tensor(
+                ET,
+                {3 * 3, 3},
+                std::vector<T>{0.5815369f, 0.16559383f, 0.08464007f, 0.843122f,   0.73968244f, 0.11359601f, 0.8295078f,
+                               0.9240567f, 0.10007995f, 0.20573162f, 0.09002485f, 0.2839569f,  0.3096991f,  0.5638341f,
+                               0.5787327f, 0.84552664f, 0.16263747f, 0.7243242f,  0.8049057f,  0.43966424f, 0.46294412f,
+                               0.9833361f, 0.31369713f, 0.1719934f,  0.4937093f,  0.6353004f,  0.77982515f}),
+            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{0.16510165f, 0.52435565f, 0.2788478f,  0.99427545f,
+                                                                   0.1623331f,  0.01389796f, 0.99669236f, 0.53901845f,
+                                                                   0.8737506f,  0.9254788f,  0.21172932f, 0.11634306f,
+                                                                   0.40111724f, 0.37497616f, 0.2903471f,  0.6796794f,
+                                                                   0.65131867f, 0.78163475f, 0.12058706f, 0.45591718f,
+                                                                   0.791677f,   0.76497287f, 0.9895242f,  0.7845312f,
+                                                                   0.51267904f, 0.49030215f, 0.08498167f}),
+            reference_tests::Tensor(ET,
+                                    {3 * 3},
+                                    std::vector<T>{0.8286678f + 0.9175602f,
+                                                   0.9153158f + 0.14958014f,
+                                                   0.9581612f + 0.49230585f,
+                                                   0.6639213f + 0.63162816f,
+                                                   0.84239805f + 0.4161903f,
+                                                   0.5282445f + 0.22148274f,
+                                                   0.14153397f + 0.50496656f,
+                                                   0.22404431f + 0.34798595f,
+                                                   0.6549655f + 0.6699164f}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.48588726f, 0.99670005f, 0.83759373f, 0.5023099f, 0.89410484f, 0.60011315f}),
             "gru_cell_bias_clip"),
         GRUCellParams(
-            2, 3, 3, 3, true,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.12249453f, 0.6127907f, 0.5001741f, 0.5124603f, 0.04329684f, 0.023834f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.8598948f, 0.41189128f, 0.72824323f, 0.53940123f, 0.31485787f, 0.04053852f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.72259396f, 0.11561195f, 0.9457856f,  0.19037509f, 0.6964006f,  0.33459795f,
-                0.5468904f,  0.85646594f, 0.5101311f,  0.9712257f,  0.3687071f,  0.60280246f,
-                0.56943774f, 0.7475505f,  0.2490578f,  0.86977345f, 0.85542053f, 0.29660386f,
-                0.49717373f, 0.7473479f,  0.53454477f, 0.15974349f, 0.5804805f,  0.14303213f,
-                0.07514781f, 0.5865731f,  0.76409274f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.91382647f, 0.41527033f, 0.28040004f, 0.23601337f, 0.04471736f, 0.03888785f,
-                0.06308217f, 0.44844428f, 0.29384327f, 0.49037653f, 0.50421673f, 0.7366393f,
-                0.63143945f, 0.00277612f, 0.37198433f, 0.06966069f, 0.4613444f,  0.10999731f,
-                0.78273284f, 0.21453214f, 0.10751773f, 0.18332677f, 0.1326976f,  0.9998985f,
-                0.19263928f, 0.10979804f, 0.52575564f}),
-            reference_tests::Tensor(ET, {(3 + 1) * 3}, std::vector<T>{
-                0.61395123f,  // 0.09875853f + 0.5151927f,
-                1.08667738f,  // 0.37801138f + 0.708666f,
-                1.32600244f,  // 0.7729636f + 0.55303884f,
-                0.81917698f,  // 0.78493553f + 0.03424145f,
-                1.37736335f,  // 0.5662702f + 0.81109315f,
-                0.42931147f,  // 0.12406381f + 0.30524766f,
-                0.66729516f,
-                0.7752771f,
-                0.78819966f,
-                0.6606634f,
-                0.99040645f,
-                0.21112025f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.8709214f, 0.48411977f, 0.74495184f, 0.6074972f, 0.44572943f, 0.1467715f}),
+            2,
+            3,
+            3,
+            3,
+            true,
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.12249453f, 0.6127907f, 0.5001741f, 0.5124603f, 0.04329684f, 0.023834f}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8598948f, 0.41189128f, 0.72824323f, 0.53940123f, 0.31485787f, 0.04053852f}),
+            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{0.72259396f, 0.11561195f, 0.9457856f,  0.19037509f,
+                                                                   0.6964006f,  0.33459795f, 0.5468904f,  0.85646594f,
+                                                                   0.5101311f,  0.9712257f,  0.3687071f,  0.60280246f,
+                                                                   0.56943774f, 0.7475505f,  0.2490578f,  0.86977345f,
+                                                                   0.85542053f, 0.29660386f, 0.49717373f, 0.7473479f,
+                                                                   0.53454477f, 0.15974349f, 0.5804805f,  0.14303213f,
+                                                                   0.07514781f, 0.5865731f,  0.76409274f}),
+            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{0.91382647f, 0.41527033f, 0.28040004f, 0.23601337f,
+                                                                   0.04471736f, 0.03888785f, 0.06308217f, 0.44844428f,
+                                                                   0.29384327f, 0.49037653f, 0.50421673f, 0.7366393f,
+                                                                   0.63143945f, 0.00277612f, 0.37198433f, 0.06966069f,
+                                                                   0.4613444f,  0.10999731f, 0.78273284f, 0.21453214f,
+                                                                   0.10751773f, 0.18332677f, 0.1326976f,  0.9998985f,
+                                                                   0.19263928f, 0.10979804f, 0.52575564f}),
+            reference_tests::Tensor(ET,
+                                    {(3 + 1) * 3},
+                                    std::vector<T>{0.61395123f,  // 0.09875853f + 0.5151927f,
+                                                   1.08667738f,  // 0.37801138f + 0.708666f,
+                                                   1.32600244f,  // 0.7729636f + 0.55303884f,
+                                                   0.81917698f,  // 0.78493553f + 0.03424145f,
+                                                   1.37736335f,  // 0.5662702f + 0.81109315f,
+                                                   0.42931147f,  // 0.12406381f + 0.30524766f,
+                                                   0.66729516f,
+                                                   0.7752771f,
+                                                   0.78819966f,
+                                                   0.6606634f,
+                                                   0.99040645f,
+                                                   0.21112025f}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8709214f, 0.48411977f, 0.74495184f, 0.6074972f, 0.44572943f, 0.1467715f}),
             "gru_cell_linear_before_reset"),
     };
     return params;
 }
 
 std::vector<GRUCellParams> generateCombinedParams() {
-    const std::vector<std::vector<GRUCellParams>> generatedParams {
+    const std::vector<std::vector<GRUCellParams>> generatedParams{
         generateParams<element::Type_t::bf16>(),
         generateParams<element::Type_t::f16>(),
         generateParams<element::Type_t::f32>(),
@@ -232,47 +277,60 @@ std::vector<GRUCellParams> generateCombinedParams() {
 template <element::Type_t ET>
 std::vector<GRUCellParams> generateParamsHardsigmoidActivationFunction() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<GRUCellParams> params {
+    std::vector<GRUCellParams> params{
         GRUCellParams(
-            2, 3, 3, 3, true,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.12249453f, 0.6127907f, 0.5001741f, 0.5124603f, 0.04329684f, 0.023834f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.8598948f, 0.41189128f, 0.72824323f, 0.53940123f, 0.31485787f, 0.04053852f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.72259396f, 0.11561195f, 0.9457856f,  0.19037509f, 0.6964006f,  0.33459795f,
-                0.5468904f,  0.85646594f, 0.5101311f,  0.9712257f,  0.3687071f,  0.60280246f,
-                0.56943774f, 0.7475505f,  0.2490578f,  0.86977345f, 0.85542053f, 0.29660386f,
-                0.49717373f, 0.7473479f,  0.53454477f, 0.15974349f, 0.5804805f,  0.14303213f,
-                0.07514781f, 0.5865731f,  0.76409274f}),
-            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{
-                0.91382647f, 0.41527033f, 0.28040004f, 0.23601337f, 0.04471736f, 0.03888785f,
-                0.06308217f, 0.44844428f, 0.29384327f, 0.49037653f, 0.50421673f, 0.7366393f,
-                0.63143945f, 0.00277612f, 0.37198433f, 0.06966069f, 0.4613444f,  0.10999731f,
-                0.78273284f, 0.21453214f, 0.10751773f, 0.18332677f, 0.1326976f,  0.9998985f,
-                0.19263928f, 0.10979804f, 0.52575564f}),
-            reference_tests::Tensor(ET, {(3 + 1) * 3}, std::vector<T>{
-                0.09875853f + 0.5151927f,
-                0.37801138f + 0.708666f,
-                0.7729636f + 0.55303884f,
-                0.78493553f + 0.03424145f,
-                0.5662702f + 0.81109315f,
-                0.12406381f + 0.30524766f,
-                0.66729516f,
-                0.7752771f,
-                0.78819966f,
-                0.6606634f,
-                0.99040645f,
-                0.21112025f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.8598948f, 0.41189128f, 0.72824323f, 0.53940123f, 0.31485787f, 0.04053852f}),
+            2,
+            3,
+            3,
+            3,
+            true,
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.12249453f, 0.6127907f, 0.5001741f, 0.5124603f, 0.04329684f, 0.023834f}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8598948f, 0.41189128f, 0.72824323f, 0.53940123f, 0.31485787f, 0.04053852f}),
+            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{0.72259396f, 0.11561195f, 0.9457856f,  0.19037509f,
+                                                                   0.6964006f,  0.33459795f, 0.5468904f,  0.85646594f,
+                                                                   0.5101311f,  0.9712257f,  0.3687071f,  0.60280246f,
+                                                                   0.56943774f, 0.7475505f,  0.2490578f,  0.86977345f,
+                                                                   0.85542053f, 0.29660386f, 0.49717373f, 0.7473479f,
+                                                                   0.53454477f, 0.15974349f, 0.5804805f,  0.14303213f,
+                                                                   0.07514781f, 0.5865731f,  0.76409274f}),
+            reference_tests::Tensor(ET, {3 * 3, 3}, std::vector<T>{0.91382647f, 0.41527033f, 0.28040004f, 0.23601337f,
+                                                                   0.04471736f, 0.03888785f, 0.06308217f, 0.44844428f,
+                                                                   0.29384327f, 0.49037653f, 0.50421673f, 0.7366393f,
+                                                                   0.63143945f, 0.00277612f, 0.37198433f, 0.06966069f,
+                                                                   0.4613444f,  0.10999731f, 0.78273284f, 0.21453214f,
+                                                                   0.10751773f, 0.18332677f, 0.1326976f,  0.9998985f,
+                                                                   0.19263928f, 0.10979804f, 0.52575564f}),
+            reference_tests::Tensor(ET,
+                                    {(3 + 1) * 3},
+                                    std::vector<T>{0.09875853f + 0.5151927f,
+                                                   0.37801138f + 0.708666f,
+                                                   0.7729636f + 0.55303884f,
+                                                   0.78493553f + 0.03424145f,
+                                                   0.5662702f + 0.81109315f,
+                                                   0.12406381f + 0.30524766f,
+                                                   0.66729516f,
+                                                   0.7752771f,
+                                                   0.78819966f,
+                                                   0.6606634f,
+                                                   0.99040645f,
+                                                   0.21112025f}),
+            reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8598948f, 0.41189128f, 0.72824323f, 0.53940123f, 0.31485787f, 0.04053852f}),
             "gru_cell_hardsigmoid_activation_function"),
     };
     return params;
 }
 
 std::vector<GRUCellParams> generateCombinedParamsHardsigmoidActivationFunction() {
-    const std::vector<std::vector<GRUCellParams>> generatedParams {
+    const std::vector<std::vector<GRUCellParams>> generatedParams{
         generateParamsHardsigmoidActivationFunction<element::Type_t::bf16>(),
         generateParamsHardsigmoidActivationFunction<element::Type_t::f16>(),
         generateParamsHardsigmoidActivationFunction<element::Type_t::f32>(),
@@ -286,9 +344,13 @@ std::vector<GRUCellParams> generateCombinedParamsHardsigmoidActivationFunction()
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GRUCell_With_Hardcoded_Refs, ReferenceGRUCellTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceGRUCellTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_GRUCell_With_Hardcoded_Refs,
+                         ReferenceGRUCellTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceGRUCellTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_GRUCell_With_Hardcoded_Refs, ReferenceGRUCellTestHardsigmoidActivationFunction,
-    testing::ValuesIn(generateCombinedParamsHardsigmoidActivationFunction()), ReferenceGRUCellTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_GRUCell_With_Hardcoded_Refs,
+                         ReferenceGRUCellTestHardsigmoidActivationFunction,
+                         testing::ValuesIn(generateCombinedParamsHardsigmoidActivationFunction()),
+                         ReferenceGRUCellTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/gru_sequence.cpp b/src/plugins/template/tests/functional/op_reference/gru_sequence.cpp
index 246a3e3100e03a..d964cc8e4e6e32 100644
--- a/src/plugins/template/tests/functional/op_reference/gru_sequence.cpp
+++ b/src/plugins/template/tests/functional/op_reference/gru_sequence.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/gru_sequence.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/gru_sequence.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,43 +14,59 @@ using namespace ov;
 namespace {
 struct GRUSequenceParams {
     template <class T>
-    GRUSequenceParams(
-        const size_t batchSize, const size_t inputSize, const size_t hiddenSize, const size_t seqLength,
-        const float clip, const bool linear_before_reset, const op::RecurrentSequenceDirection& gru_direction,
-        const element::Type_t& iType,
-        const std::vector<T>& XValues, const std::vector<T>& H_tValues, const std::vector<int64_t>& seqLengthsValues,
-        const std::vector<T>& WValues, const std::vector<T>& RValues, const std::vector<T>& BValues,
-        const std::vector<T>& YValues, const std::vector<T>& HoValues,
-        const std::string& testcaseName = "") :
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize), seqLength(seqLength),
-        clip(clip), linear_before_reset(linear_before_reset), gru_direction(gru_direction), iType(iType), oType(iType),
-        testcaseName(testcaseName) {
-            numDirections = (gru_direction == op::RecurrentSequenceDirection::BIDIRECTIONAL) ? 2 : 1;
+    GRUSequenceParams(const size_t batchSize,
+                      const size_t inputSize,
+                      const size_t hiddenSize,
+                      const size_t seqLength,
+                      const float clip,
+                      const bool linear_before_reset,
+                      const op::RecurrentSequenceDirection& gru_direction,
+                      const element::Type_t& iType,
+                      const std::vector<T>& XValues,
+                      const std::vector<T>& H_tValues,
+                      const std::vector<int64_t>& seqLengthsValues,
+                      const std::vector<T>& WValues,
+                      const std::vector<T>& RValues,
+                      const std::vector<T>& BValues,
+                      const std::vector<T>& YValues,
+                      const std::vector<T>& HoValues,
+                      const std::string& testcaseName = "")
+        : batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          seqLength(seqLength),
+          clip(clip),
+          linear_before_reset(linear_before_reset),
+          gru_direction(gru_direction),
+          iType(iType),
+          oType(iType),
+          testcaseName(testcaseName) {
+        numDirections = (gru_direction == op::RecurrentSequenceDirection::BIDIRECTIONAL) ? 2 : 1;
 
-            Shape XShape = Shape{batchSize, seqLength, inputSize};
-            Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape seqLengthsShape = Shape{batchSize};
-            Shape WShape = Shape{numDirections, 3 * hiddenSize, inputSize};
-            Shape RShape = Shape{numDirections, 3 * hiddenSize, hiddenSize};
-            Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
-            Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape XShape = Shape{batchSize, seqLength, inputSize};
+        Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape seqLengthsShape = Shape{batchSize};
+        Shape WShape = Shape{numDirections, 3 * hiddenSize, inputSize};
+        Shape RShape = Shape{numDirections, 3 * hiddenSize, hiddenSize};
+        Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
+        Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
 
-            X = reference_tests::Tensor(XShape, iType, XValues);
-            H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
-            sequence_lengths = reference_tests::Tensor(seqLengthsShape, element::Type_t::i64, seqLengthsValues);
-            W = reference_tests::Tensor(WShape, iType, WValues);
-            R = reference_tests::Tensor(RShape, iType, RValues);
-            Y = reference_tests::Tensor(YShape, oType, YValues);
-            Ho = reference_tests::Tensor(HoShape, oType, HoValues);
+        X = reference_tests::Tensor(XShape, iType, XValues);
+        H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
+        sequence_lengths = reference_tests::Tensor(seqLengthsShape, element::Type_t::i64, seqLengthsValues);
+        W = reference_tests::Tensor(WShape, iType, WValues);
+        R = reference_tests::Tensor(RShape, iType, RValues);
+        Y = reference_tests::Tensor(YShape, oType, YValues);
+        Ho = reference_tests::Tensor(HoShape, oType, HoValues);
 
-            if (linear_before_reset == true) {
-                Shape BShape = Shape{numDirections, 4 * hiddenSize};
-                B = reference_tests::Tensor(BShape, iType, BValues);
-            } else {
-                Shape BShape = Shape{numDirections, 3 * hiddenSize};
-                B = reference_tests::Tensor(BShape, iType, BValues);
-            }
+        if (linear_before_reset == true) {
+            Shape BShape = Shape{numDirections, 4 * hiddenSize};
+            B = reference_tests::Tensor(BShape, iType, BValues);
+        } else {
+            Shape BShape = Shape{numDirections, 3 * hiddenSize};
+            B = reference_tests::Tensor(BShape, iType, BValues);
         }
+    }
 
     size_t batchSize;
     size_t inputSize;
@@ -78,7 +95,8 @@ class ReferenceGRUSequenceTest : public testing::TestWithParam<GRUSequenceParams
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.X.data, params.H_t.data, params.sequence_lengths.data, params.W.data, params.R.data, params.B.data};
+        inputData =
+            {params.X.data, params.H_t.data, params.sequence_lengths.data, params.W.data, params.R.data, params.B.data};
         refOutData = {params.Y.data, params.Ho.data};
     }
 
@@ -107,27 +125,28 @@ class ReferenceGRUSequenceTest : public testing::TestWithParam<GRUSequenceParams
     static std::shared_ptr<Model> CreateFunction(const GRUSequenceParams& params) {
         const auto X = std::make_shared<op::v0::Parameter>(params.X.type, params.X.shape);
         const auto H_t = std::make_shared<op::v0::Parameter>(params.H_t.type, params.H_t.shape);
-        const auto sequence_lengths = std::make_shared<op::v0::Parameter>(params.sequence_lengths.type, params.sequence_lengths.shape);
+        const auto sequence_lengths =
+            std::make_shared<op::v0::Parameter>(params.sequence_lengths.type, params.sequence_lengths.shape);
         const auto W = std::make_shared<op::v0::Parameter>(params.W.type, params.W.shape);
         const auto R = std::make_shared<op::v0::Parameter>(params.R.type, params.R.shape);
         const auto B = std::make_shared<op::v0::Parameter>(params.B.type, params.B.shape);
 
-        const auto gru_sequence =
-            std::make_shared<op::v5::GRUSequence>(X,
-                                                  H_t,
-                                                  sequence_lengths,
-                                                  W,
-                                                  R,
-                                                  B,
-                                                  params.hiddenSize,
-                                                  params.gru_direction,
-                                                  std::vector<std::string>{"sigmoid", "tanh"},
-                                                  std::vector<float>{},
-                                                  std::vector<float>{},
-                                                  params.clip,
-                                                  params.linear_before_reset);
+        const auto gru_sequence = std::make_shared<op::v5::GRUSequence>(X,
+                                                                        H_t,
+                                                                        sequence_lengths,
+                                                                        W,
+                                                                        R,
+                                                                        B,
+                                                                        params.hiddenSize,
+                                                                        params.gru_direction,
+                                                                        std::vector<std::string>{"sigmoid", "tanh"},
+                                                                        std::vector<float>{},
+                                                                        std::vector<float>{},
+                                                                        params.clip,
+                                                                        params.linear_before_reset);
 
-        auto function = std::make_shared<Model>(gru_sequence->outputs(), ParameterVector{X, H_t, sequence_lengths, W, R, B});
+        auto function =
+            std::make_shared<Model>(gru_sequence->outputs(), ParameterVector{X, H_t, sequence_lengths, W, R, B});
         return function;
     }
 };
@@ -140,612 +159,588 @@ template <element::Type_t ET>
 std::vector<GRUSequenceParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<GRUSequenceParams> params {
+    std::vector<GRUSequenceParams> params{
         GRUSequenceParams(
-            5, 10, 10, 10,
-            0.7f, false, op::RecurrentSequenceDirection::FORWARD,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            false,
+            op::RecurrentSequenceDirection::FORWARD,
             ET,
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
-                1.82401, 6.1306, 4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686,
-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 4.59474,
-                6.19214, 8.80766, 8.07546, 3.29232, 1.74029, 2.4198, 2.88544, 4.75644, 4.12921, 7.29896,
-                7.27759, 1.67252, 1.32823, 8.1046, 9.10476, 1.04197, 3.37783, 5.2064, 4.23835, 3.16196,
-                1.20852, 5.78501, 2.17175, 6.05313, 2.51048, 4.78967, 7.16219, 3.4651, 1.09, 2.9788,
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+                2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
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+                1.10502, 5.48298, 1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224,
+                7.95465, 2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
+                1.63073, 5.25228, 7.68488, 2.7276,  5.1788,  3.07327, 5.57423, 2.87711, 1.44374, 5.66976, 2.55051,
+                4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,  1.82401, 6.1306,
+                4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686, 4.85031, 4.85544, 4.25714,
+                2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891, 2.16793, 3.64924, 4.24733, 3.47181,
+                1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016, 7.6686,  3.68812, 2.83922, 9.83581, 9.03719,
+                7.83414, 6.86009, 1.35715, 8.32489, 7.86316, 5.09754, 5.78644, 1.98402, 2.31429, 5.5791,  2.94085,
+                9.24799, 5.15937, 2.19041, 7.87817, 2.9146,  1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937,
+                9.37912, 6.18926, 8.55681, 6.60963, 3.92066, 7.5521,  5.70463, 7.6313,  2.48866, 7.18352, 4.8413,
+                7.55702, 7.80702, 4.5785,  9.3268,  2.83159, 1.07202, 9.33716, 3.6506,  2.50256, 1.21691, 5.06801,
+                8.27505, 4.31539, 6.48286, 1.31363, 4.1912,  1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
+                5.24875, 1.94852, 5.52768, 8.97121, 5.8094,  3.53329, 4.19126, 9.06652, 3.1734,  1.21496, 9.69154,
+                4.86971, 4.1166,  6.19361, 2.13874, 9.55039, 3.8225,  9.57548, 2.96554, 3.2383,  8.77422, 3.11741,
+                8.3359,  5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474,  4.59474, 6.19214, 8.80766, 8.07546,
+                3.29232, 1.74029, 2.4198,  2.88544, 4.75644, 4.12921, 7.29896, 7.27759, 1.67252, 1.32823, 8.1046,
+                9.10476, 1.04197, 3.37783, 5.2064,  4.23835, 3.16196, 1.20852, 5.78501, 2.17175, 6.05313, 2.51048,
+                4.78967, 7.16219, 3.4651,  1.09,    2.9788,  1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892,
+                5.86648, 8.73895, 2.66603, 1.75192, 1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565,
+                7.35114, 3.1439,  10},
             std::vector<T>{
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-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 10},
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+                3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.0055,  7.44373,
+                8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 7.03475, 6.33759, 7.04489,
+                4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 6.61627, 6.94572, 3.68646, 5.01521,
+                2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937,
+                1.40811, 2.2597,  8.13163, 1.26821, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069,
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+                9.24799, 5.15937, 2.19041, 7.87817, 2.9146,  1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937,
+                9.37912, 6.18926, 8.55681, 6.60963, 3.92066, 7.5521,  5.70463, 7.6313,  2.48866, 7.18352, 4.8413,
+                7.55702, 7.80702, 4.5785,  9.3268,  2.83159, 1.07202, 9.33716, 3.6506,  2.50256, 1.21691, 5.06801,
+                8.27505, 4.31539, 6.48286, 1.31363, 4.1912,  1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
+                5.24875, 1.94852, 5.52768, 8.97121, 5.8094,  3.53329, 4.19126, 9.06652, 3.1734,  1.21496, 9.69154,
+                4.86971, 4.1166,  6.19361, 2.13874, 9.55039, 3.8225,  9.57548, 2.96554, 3.2383,  8.77422, 3.11741,
+                8.3359,  5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474,  4.59474, 6.19214, 8.80766, 8.07546,
+                3.29232, 1.74029, 2.4198,  2.88544, 4.75644, 4.12921, 7.29896, 7.27759, 1.67252, 1.32823, 8.1046,
+                9.10476, 1.04197, 3.37783, 5.2064,  4.23835, 3.16196, 1.20852, 5.78501, 2.17175, 6.05313, 2.51048,
+                4.78967, 7.16219, 3.4651,  1.09,    2.9788,  1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892,
+                5.86648, 8.73895, 2.66603, 1.75192, 1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565,
+                7.35114, 3.1439,  10},
+            std::vector<T>{1,      9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168, 3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 10},
             std::vector<T>{
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+                4.18172,  2.03983,  2.88879,  2.56292,  1.70351,  2.92843,  4.45356,  2.61818,  2.51167,  4.55468,
+                2.99471,  1.56352,  2.13079,  1.91305,  1.3388,   2.15728,  3.17635,  1.94997,  1.87881,  3.24392,
+                2.20156,  1.24526,  1.6243,   1.47881,  1.09511,  1.642,    2.32293,  1.50349,  1.45593,  2.36808,
+                1.67159,  1.03261,  1.28588,  1.18866,  0.932274, 1.2977,   1.75269,  1.20515,  1.17337,  1.78286,
+                1.31748,  0.890512, 1.05974,  0.994786, 0.823471, 1.06765,  1.37166,  1.0058,   0.984569, 1.39182,
+                1.08086,  0.795566, 0.908644, 0.86524,  0.75077,  0.913924, 1.11707,  0.872601, 0.858414, 1.13054,
+                0.922752, 0.732124, 0.807681, 0.778679, 0.702192, 0.81121,  0.946946, 0.783598, 0.774118, 0.955946,
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-                2.07971, 1.96773, 2.12343, 0.849723, 1.61283, 2.23513, 2.17077, 2.17159, 1.1731, 0.789519,
-                1.59017, 1.51535, 1.61938, 0.768311, 1.27821, 1.69402, 1.65102, 1.65157, 0.984388, 0.728083,
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+                0.746518, 0.661408, 0.695142, 0.682194, 0.648044, 0.696717, 0.75732,  0.684389, 0.680157, 0.761339,
+                5.54972,  5.17435,  5.69626,  1.4268,   3.98473,  6.07069,  5.85496,  5.8577,   2.51076,  1.22499,
+                3.90879,  3.65797,  4.00671,  1.15391,  2.86309,  4.2569,   4.11275,  4.11458,  1.8782,   1.01906,
+                2.81234,  2.64475,  2.87777,  0.971563, 2.11362,  3.04494,  2.94862,  2.94985,  1.45553,  0.881462,
+                2.07971,  1.96773,  2.12343,  0.849723, 1.61283,  2.23513,  2.17077,  2.17159,  1.1731,   0.789519,
+                1.59017,  1.51535,  1.61938,  0.768311, 1.27821,  1.69402,  1.65102,  1.65157,  0.984388, 0.728083,
+                1.26307,  1.21307,  1.28259,  0.713913, 1.05462,  1.33246,  1.30373,  1.30409,  0.858293, 0.687033,
+                1.0445,   1.0111,   1.05755,  0.677564, 0.905221, 1.09087,  1.07167,  1.07192,  0.774037, 0.659604,
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+                2.52274,  2.31475,  2.52576,  1.82803,  1.25281,  1.50004,  1.10398,  2.82557,  1.83005,  0.814145,
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+                1.17667,  1.11463,  1.17758,  0.969422, 0.797818, 0.871573, 0.753417, 1.26702,  0.970024, 0.66695,
+                0.986775, 0.945316, 0.987378, 0.848292, 0.733629, 0.782911, 0.703961, 1.04714,  0.848694, 0.646185,
+                0.859888, 0.832185, 0.86029,  0.767355, 0.690738, 0.723668, 0.670915, 0.900223, 0.767624, 0.632309,
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-                3.28853, 3.43562, 1.98044, 2.5737, 1.67356, 1.0758, 2.66654, 1.16745, 4.411, 4.79928,
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+            10,
+            10,
+            10,
+            0.7f,
+            false,
+            op::RecurrentSequenceDirection::REVERSE,
             ET,
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+                1.26307,  1.21307,  1.28259,  0.713913, 1.05462,  1.33246,  1.30373,  1.30409,  0.858293, 0.687033,
+                1.59017,  1.51535,  1.61938,  0.768311, 1.27821,  1.69402,  1.65102,  1.65157,  0.984388, 0.728083,
+                2.07971,  1.96773,  2.12343,  0.849723, 1.61283,  2.23513,  2.17077,  2.17159,  1.1731,   0.789519,
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+                5.54972,  5.17435,  5.69626,  1.4268,   3.98473,  6.07069,  5.85496,  5.8577,   2.51076,  1.22499,
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+                2.52274,  2.31475,  2.52576,  1.82803,  1.25281,  1.50004,  1.10398,  2.82557,  1.83005,  0.814145,
+                3.47537,  3.16411,  3.4799,   2.43568,  1.57482,  1.94482,  1.35209,  3.92858,  2.4387,   0.918317,
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-                2.39789, 2.49618, 1.52384, 1.92025, 1.31879, 0.919376, 1.98228, 0.980615, 3.14791, 3.40736,
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-                4.62145, 4.84158, 2.66378, 3.55164, 2.20451, 1.30991, 3.69058, 1.44707, 6.30131, 6.88241},
-            std::vector<T>{
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-                0.711027, 0.716871, 0.659048, 0.682622, 0.646854, 0.623101, 0.686311, 0.626743, 0.755629, 0.771058}),
+                0.843259, 0.85635,  0.726839, 0.779639, 0.699526, 0.646326, 0.787901, 0.654483, 0.943158, 0.977716,
+                0.961889, 0.981481, 0.787656, 0.866675, 0.746781, 0.667161, 0.879041, 0.679369, 1.1114,   1.16312,
+                1.13943,  1.16875,  0.878674, 0.996934, 0.817501, 0.698344, 1.01544,  0.716613, 1.36318,  1.44058,
+                1.40513,  1.44901,  1.01489,  1.19188,  0.92334,  0.745011, 1.21957,  0.772353, 1.74,     1.85583,
+                1.80278,  1.86845,  1.21875,  1.48362,  1.08174,  0.814853, 1.52507,  0.855772, 2.30393,  2.47729,
+                2.39789,  2.49618,  1.52384,  1.92025,  1.31879,  0.919376, 1.98228,  0.980615, 3.14791,  3.40736,
+                3.28853,  3.43562,  1.98044,  2.5737,   1.67356,  1.0758,   2.66654,  1.16745,  4.411,    4.79928,
+                4.62145,  4.84158,  2.66378,  3.55164,  2.20451,  1.30991,  3.69058,  1.44707,  6.30131,  6.88241},
+            std::vector<T>{0.611387, 0.770609, 0.76029,  0.631845, 0.770905, 0.649083, 0.674709, 0.673325, 0.718326,
+                           0.760766, 0.746518, 0.661408, 0.695142, 0.682194, 0.648044, 0.696717, 0.75732,  0.684389,
+                           0.680157, 0.761339, 0.735673, 0.725707, 0.739564, 0.626204, 0.694121, 0.749506, 0.743778,
+                           0.743851, 0.654985, 0.620846, 0.718451, 0.706082, 0.718631, 0.677138, 0.64293,  0.657632,
+                           0.634079, 0.73646,  0.677257, 0.616843, 0.711027, 0.716871, 0.659048, 0.682622, 0.646854,
+                           0.623101, 0.686311, 0.626743, 0.755629, 0.771058}),
         GRUSequenceParams(
-            5, 10, 10, 5,
-            0.f, true, op::RecurrentSequenceDirection::BIDIRECTIONAL,
+            5,
+            10,
+            10,
+            5,
+            0.f,
+            true,
+            op::RecurrentSequenceDirection::BIDIRECTIONAL,
             ET,
             std::vector<T>{
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-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
-                1.82401, 6.1306, 4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686,
-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10},
+                1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 8.6168,
+                3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.0055,  7.44373,
+                8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 7.03475, 6.33759, 7.04489,
+                4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 6.61627, 6.94572, 3.68646, 5.01521,
+                2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937,
+                1.40811, 2.2597,  8.13163, 1.26821, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069,
+                4.25135, 6.13908, 6.74053, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208,
+                1.10502, 5.48298, 1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224,
+                7.95465, 2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
+                1.63073, 5.25228, 7.68488, 2.7276,  5.1788,  3.07327, 5.57423, 2.87711, 1.44374, 5.66976, 2.55051,
+                4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,  1.82401, 6.1306,
+                4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686, 4.85031, 4.85544, 4.25714,
+                2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891, 2.16793, 3.64924, 4.24733, 3.47181,
+                1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016, 7.6686,  3.68812, 2.83922, 9.83581, 9.03719,
+                7.83414, 6.86009, 1.35715, 8.32489, 7.86316, 5.09754, 5.78644, 1.98402, 2.31429, 5.5791,  2.94085,
+                9.24799, 5.15937, 2.19041, 7.87817, 2.9146,  1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937,
+                9.37912, 6.18926, 8.55681, 6.60963, 3.92066, 7.5521,  5.70463, 7.6313,  2.48866, 7.18352, 4.8413,
+                7.55702, 7.80702, 4.5785,  9.3268,  2.83159, 1.07202, 9.33716, 3.6506,  2.50256, 1.21691, 5.06801,
+                8.27505, 4.31539, 6.48286, 1.31363, 4.1912,  1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
+                5.24875, 1.94852, 5.52768, 8.97121, 5.8094,  3.53329, 4.19126, 9.06652, 3.1734,  1.21496, 9.69154,
+                4.86971, 4.1166,  6.19361, 2.13874, 9.55039, 3.8225,  9.57548, 2.96554, 3.2383,  8.77422, 3.11741,
+                8.3359,  5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474,  10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
+                           5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595,  6.09321, 6.52544, 9.60882, 3.34881,
+                           3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937, 1.40811, 2.2597,  8.13163, 1.26821,
+                           8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
+                           2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
+                           1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10},
             std::vector<int64_t>{5, 5, 5, 5, 5},
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
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-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
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-                1.20852, 5.78501, 2.17175, 6.05313, 2.51048, 4.78967, 7.16219, 3.4651, 1.09, 2.9788,
-                1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892, 5.86648, 8.73895, 2.66603, 1.75192,
-                1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565, 7.35114, 3.1439, 1.39976,
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-                2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225, 3.99956, 1.08021, 5.54918, 7.05833,
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-                1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283, 9.88249, 4.48422,
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-                7.4718, 7.19305, 6.47932, 1.9559, 3.52616, 7.98593, 9.0115, 5.59539, 7.44137, 1.70001,
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-                7.95084, 2.11852, 9.28916, 1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549,
-                3.75218, 8.98228, 8.98158, 5.63695, 3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035,
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-                2.15026, 4.66033, 4.20769, 2.3604, 8.70826, 1.91807, 9.57809, 2.50132, 4.95464, 2.44375,
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-                3.87864, 6.44032, 9.59689, 4.74213, 2.76302, 2.49426, 6.62326, 1.50664, 3.95698, 9.82371,
-                7.94438, 2.88399, 6.26754, 4.95809, 6.52199, 3.87974, 2.0071, 3.81713, 9.94544, 2.49197,
-                5.16628, 6.71965, 1.33379, 3.27947, 8.83191, 2.25668, 1.16264, 7.20743, 8.8397, 4.19957,
-                4.57119, 8.76621, 9.39031, 5.05683, 9.77492, 7.28143, 7.78249, 6.19997, 2.21146, 8.26929,
-                1.94202, 4.0196, 6.07928, 6.6033, 5.12291, 8.3157, 3.23435, 4.80489, 8.2505, 5.93311,
-                3.22774, 1.09695, 3.22228, 3.24883, 6.54187, 3.3574, 5.71848, 4.4223, 1.32481, 8.59246,
-                5.0497, 9.78833, 1.51703, 2.4678, 2.64335, 5.87163, 3.45429, 5.43941, 7.60549, 10},
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+                3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.0055,  7.44373,
+                8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 7.03475, 6.33759, 7.04489,
+                4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 6.61627, 6.94572, 3.68646, 5.01521,
+                2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937,
+                1.40811, 2.2597,  8.13163, 1.26821, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069,
+                4.25135, 6.13908, 6.74053, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208,
+                1.10502, 5.48298, 1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224,
+                7.95465, 2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
+                1.63073, 5.25228, 7.68488, 2.7276,  5.1788,  3.07327, 5.57423, 2.87711, 1.44374, 5.66976, 2.55051,
+                4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,  1.82401, 6.1306,
+                4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686, 4.85031, 4.85544, 4.25714,
+                2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891, 2.16793, 3.64924, 4.24733, 3.47181,
+                1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016, 7.6686,  3.68812, 2.83922, 9.83581, 9.03719,
+                7.83414, 6.86009, 1.35715, 8.32489, 7.86316, 5.09754, 5.78644, 1.98402, 2.31429, 5.5791,  2.94085,
+                9.24799, 5.15937, 2.19041, 7.87817, 2.9146,  1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937,
+                9.37912, 6.18926, 8.55681, 6.60963, 3.92066, 7.5521,  5.70463, 7.6313,  2.48866, 7.18352, 4.8413,
+                7.55702, 7.80702, 4.5785,  9.3268,  2.83159, 1.07202, 9.33716, 3.6506,  2.50256, 1.21691, 5.06801,
+                8.27505, 4.31539, 6.48286, 1.31363, 4.1912,  1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
+                5.24875, 1.94852, 5.52768, 8.97121, 5.8094,  3.53329, 4.19126, 9.06652, 3.1734,  1.21496, 9.69154,
+                4.86971, 4.1166,  6.19361, 2.13874, 9.55039, 3.8225,  9.57548, 2.96554, 3.2383,  8.77422, 3.11741,
+                8.3359,  5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474,  4.59474, 6.19214, 8.80766, 8.07546,
+                3.29232, 1.74029, 2.4198,  2.88544, 4.75644, 4.12921, 7.29896, 7.27759, 1.67252, 1.32823, 8.1046,
+                9.10476, 1.04197, 3.37783, 5.2064,  4.23835, 3.16196, 1.20852, 5.78501, 2.17175, 6.05313, 2.51048,
+                4.78967, 7.16219, 3.4651,  1.09,    2.9788,  1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892,
+                5.86648, 8.73895, 2.66603, 1.75192, 1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565,
+                7.35114, 3.1439,  1.39976, 3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637,
+                8.6232,  8.54902, 2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225,  3.99956, 1.08021, 5.54918,
+                7.05833, 1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
+                5.59325, 9.89258, 2.30223, 1.4347,  9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909, 1.00912,
+                6.62167, 2.80244, 6.626,   3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902, 6.26823, 9.72608,
+                3.73491, 3.8238,  3.03815, 7.05101, 8.0103,  5.61396, 6.53738, 1.41095, 5.0149,  9.71211, 4.23604,
+                5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328,  8.2817,  5.12336, 8.98577, 5.80541, 6.19552,
+                9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817, 8.57269, 5.99975, 3.42893, 5.38068, 3.48261,
+                3.02851, 6.82079, 9.2902,  2.80427, 8.91868, 5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755,
+                2.49121, 5.52697, 8.08823, 9.13242, 2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457,
+                5.55154, 7.24966, 5.1128,  4.25147, 8.34407, 1.4123,  4.49045, 5.12671, 7.62159, 9.18673, 3.49665,
+                8.35992, 6.90684, 1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283,  9.88249,
+                4.48422, 8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155,  9.94928, 6.88321, 1.33685,
+                7.4718,  7.19305, 6.47932, 1.9559,  3.52616, 7.98593, 9.0115,  5.59539, 7.44137, 1.70001, 6.53774,
+                8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153, 5.4073,  9.00437,
+                8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473, 7.95084, 2.11852, 9.28916,
+                1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549, 3.75218, 8.98228, 8.98158, 5.63695,
+                3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035, 8.37644, 8.54954, 5.70516, 2.45744, 9.54079,
+                1.53504, 8.9785,  6.1691,  4.40962, 6.76815, 2.15026, 4.66033, 4.20769, 2.3604,  8.70826, 1.91807,
+                9.57809, 2.50132, 4.95464, 2.44375, 8.91345, 5.30605, 4.59238, 3.47923, 1.46477, 2.24843, 8.00775,
+                2.60248, 6.25095, 9.35311, 1.96897, 5.0738,  2.40393, 3.7379,  7.87712, 6.6423,  7.39986, 2.74115,
+                1.61588, 8.9169,  3.87864, 6.44032, 9.59689, 4.74213, 2.76302, 2.49426, 6.62326, 1.50664, 3.95698,
+                9.82371, 7.94438, 2.88399, 6.26754, 4.95809, 6.52199, 3.87974, 2.0071,  3.81713, 9.94544, 2.49197,
+                5.16628, 6.71965, 1.33379, 3.27947, 8.83191, 2.25668, 1.16264, 7.20743, 8.8397,  4.19957, 4.57119,
+                8.76621, 9.39031, 5.05683, 9.77492, 7.28143, 7.78249, 6.19997, 2.21146, 8.26929, 1.94202, 4.0196,
+                6.07928, 6.6033,  5.12291, 8.3157,  3.23435, 4.80489, 8.2505,  5.93311, 3.22774, 1.09695, 3.22228,
+                3.24883, 6.54187, 3.3574,  5.71848, 4.4223,  1.32481, 8.59246, 5.0497,  9.78833, 1.51703, 2.4678,
+                2.64335, 5.87163, 3.45429, 5.43941, 7.60549, 10},
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
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+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937,
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+                4.78967, 7.16219, 3.4651,  1.09,    2.9788,  1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892,
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+                3.73491, 3.8238,  3.03815, 7.05101, 8.0103,  5.61396, 6.53738, 1.41095, 5.0149,  9.71211, 4.23604,
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+                8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473, 7.95084, 2.11852, 9.28916,
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+                3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035, 8.37644, 8.54954, 5.70516, 2.45744, 9.54079,
+                1.53504, 8.9785,  6.1691,  4.40962, 6.76815, 2.15026, 4.66033, 4.20769, 2.3604,  8.70826, 1.91807,
+                9.57809, 2.50132, 4.95464, 2.44375, 8.91345, 5.30605, 4.59238, 3.47923, 1.46477, 2.24843, 8.00775,
+                2.60248, 6.25095, 9.35311, 1.96897, 5.0738,  2.40393, 3.7379,  7.87712, 6.6423,  7.39986, 2.74115,
+                1.61588, 8.9169,  3.87864, 6.44032, 9.59689, 4.74213, 2.76302, 2.49426, 6.62326, 1.50664, 3.95698,
+                9.82371, 7.94438, 2.88399, 6.26754, 4.95809, 6.52199, 3.87974, 2.0071,  3.81713, 9.94544, 2.49197,
+                5.16628, 6.71965, 1.33379, 3.27947, 8.83191, 2.25668, 1.16264, 7.20743, 8.8397,  4.19957, 4.57119,
+                8.76621, 9.39031, 5.05683, 9.77492, 7.28143, 7.78249, 6.19997, 2.21146, 8.26929, 1.94202, 4.0196,
+                6.07928, 6.6033,  5.12291, 8.3157,  3.23435, 4.80489, 8.2505,  5.93311, 3.22774, 1.09695, 3.22228,
+                3.24883, 6.54187, 3.3574,  5.71848, 4.4223,  1.32481, 8.59246, 5.0497,  9.78833, 1.51703, 2.4678,
+                2.64335, 5.87163, 3.45429, 5.43941, 7.60549, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
+                           5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595,  6.09321, 6.52544, 9.60882, 3.34881,
+                           3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937, 1.40811, 2.2597,  8.13163, 1.26821,
+                           8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 10},
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
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-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 10},
-            std::vector<T>{
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-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10}),
+                1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 1,
+                9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 1,       9.97466,
+                9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 1,       9.97466, 9.39302,
+                2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 1,       9.97466, 9.39302, 2.15312,
+                9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 8.6168,  3.81946, 5.72093, 4.99108, 3.0662,
+                5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973,
+                9.22566, 5.11484, 4.87629, 9.45215, 8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566,
+                5.11484, 4.87629, 9.45215, 8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484,
+                4.87629, 9.45215, 8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629,
+                9.45215, 8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 8.0055,
+                7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 8.0055,  7.44373,
+                8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 8.0055,  7.44373, 8.22482,
+                1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 7.03475, 6.33759, 7.04489, 4.70609,
+                2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 7.03475, 6.33759, 7.04489, 4.70609, 2.77796,
+                3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667,
+                2.27908, 8.04983, 4.71285, 1.30754, 7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908,
+                8.04983, 4.71285, 1.30754, 7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983,
+                4.71285, 1.30754, 6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033,
+                2.07541, 6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
+                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 6.61627,
+                6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 6.61627, 6.94572,
+                3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175,
+                9.19404, 3.69037, 6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 5.72319, 1.75261, 9.25175, 9.19404,
+                3.69037, 6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595,
+                6.09321, 6.52544, 9.60882, 3.34881, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595,  6.09321,
+                6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937, 1.40811, 2.2597,
+                8.13163, 1.26821, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937, 1.40811, 2.2597,  8.13163,
+                1.26821, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937, 1.40811, 2.2597,  8.13163, 1.26821,
+                3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937, 1.40811, 2.2597,  8.13163, 1.26821, 3.07914,
+                5.80104, 9.54944, 5.43754, 5.8654,  7.88937, 1.40811, 2.2597,  8.13163, 1.26821, 8.94813, 5.86709,
+                5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053, 8.94813, 5.86709, 5.03182,
+                9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053, 8.94813, 5.86709, 5.03182, 9.02922,
+                4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826,
+                5.84582, 6.87069, 4.25135, 6.13908, 6.74053, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582,
+                6.87069, 4.25135, 6.13908, 6.74053, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509,
+                8.93208, 1.10502, 5.48298, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208,
+                1.10502, 5.48298, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208, 1.10502,
+                5.48298, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
+                2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208, 1.10502, 5.48298, 1.66413,
+                8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10,      1.66413, 8.08256,
+                1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10,      1.66413, 8.08256, 1.57661,
+                4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10,      1.66413, 8.08256, 1.57661, 4.19779,
+                9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10,      1.66413, 8.08256, 1.57661, 4.19779, 9.47653,
+                4.41823, 7.86628, 7.94436, 3.71224, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
+                           5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595,  6.09321, 6.52544, 9.60882, 3.34881,
+                           3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937, 1.40811, 2.2597,  8.13163, 1.26821,
+                           8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
+                           2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
+                           1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 10}),
     };
     return params;
 }
@@ -754,618 +749,594 @@ template <element::Type_t ET>
 std::vector<GRUSequenceParams> generateParamsBF16() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<GRUSequenceParams> params {
+    std::vector<GRUSequenceParams> params{
         GRUSequenceParams(
-            5, 10, 10, 10,
-            0.7f, false, op::RecurrentSequenceDirection::FORWARD,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            false,
+            op::RecurrentSequenceDirection::FORWARD,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   10},
+            std::vector<T>{1,     4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,     2.3125,
+                           3.125, 1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,  5.84375,
+                           8.625, 4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625, 10},
             std::vector<T>{
-                0.867188, 3.375, 6.875, 5.1875, 6.4375, 0.867188, 1.64062, 2.65625, 6.875, 1.75,
-                0.777344, 2.4375, 4.75, 3.65625, 4.5, 0.777344, 1.29688, 1.96875, 4.75, 1.375,
-                0.714844, 1.82812, 3.375, 2.625, 3.1875, 0.714844, 1.0625, 1.51562, 3.375, 1.11719,
-                0.675781, 1.42188, 2.4375, 1.95312, 2.3125, 0.675781, 0.910156, 1.21875, 2.4375, 0.945312,
-                0.648438, 1.14844, 1.82812, 1.5, 1.75, 0.648438, 0.808594, 1.01562, 1.82812, 0.832031,
-                0.632812, 0.964844, 1.42188, 1.20312, 1.375, 0.632812, 0.738281, 0.878906, 1.42188, 0.753906,
-                0.621094, 0.839844, 1.14844, 1, 1.11719, 0.621094, 0.691406, 0.785156, 1.14844, 0.699219,
+                0.867188, 3.375,    6.875,    5.1875,   6.4375,   0.867188, 1.64062,  2.65625,  6.875,    1.75,
+                0.777344, 2.4375,   4.75,     3.65625,  4.5,      0.777344, 1.29688,  1.96875,  4.75,     1.375,
+                0.714844, 1.82812,  3.375,    2.625,    3.1875,   0.714844, 1.0625,   1.51562,  3.375,    1.11719,
+                0.675781, 1.42188,  2.4375,   1.95312,  2.3125,   0.675781, 0.910156, 1.21875,  2.4375,   0.945312,
+                0.648438, 1.14844,  1.82812,  1.5,      1.75,     0.648438, 0.808594, 1.01562,  1.82812,  0.832031,
+                0.632812, 0.964844, 1.42188,  1.20312,  1.375,    0.632812, 0.738281, 0.878906, 1.42188,  0.753906,
+                0.621094, 0.839844, 1.14844,  1,        1.11719,  0.621094, 0.691406, 0.785156, 1.14844,  0.699219,
                 0.613281, 0.761719, 0.964844, 0.867188, 0.945312, 0.613281, 0.660156, 0.722656, 0.964844, 0.664062,
                 0.609375, 0.707031, 0.839844, 0.777344, 0.832031, 0.609375, 0.640625, 0.679688, 0.839844, 0.640625,
-                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625, 0.652344, 0.761719, 0.625,
-                2.28125, 1.42188, 3.25, 1.98438, 3.1875, 2.9375, 4.875, 3.25, 6.4375, 4.09375,
-                1.71875, 1.14844, 2.34375, 1.53125, 2.3125, 2.15625, 3.4375, 2.34375, 4.5, 2.9375,
-                1.34375, 0.964844, 1.76562, 1.21875, 1.75, 1.64062, 2.46875, 1.76562, 3.1875, 2.15625,
-                1.09375, 0.839844, 1.375, 1.01562, 1.375, 1.29688, 1.84375, 1.375, 2.3125, 1.64062,
-                0.929688, 0.761719, 1.11719, 0.878906, 1.11719, 1.0625, 1.4375, 1.11719, 1.75, 1.29688,
-                0.816406, 0.707031, 0.945312, 0.785156, 0.945312, 0.910156, 1.15625, 0.945312, 1.375, 1.0625,
-                0.746094, 0.671875, 0.832031, 0.722656, 0.832031, 0.808594, 0.972656, 0.832031, 1.11719, 0.910156,
+                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625,    0.652344, 0.761719, 0.625,
+                2.28125,  1.42188,  3.25,     1.98438,  3.1875,   2.9375,   4.875,    3.25,     6.4375,   4.09375,
+                1.71875,  1.14844,  2.34375,  1.53125,  2.3125,   2.15625,  3.4375,   2.34375,  4.5,      2.9375,
+                1.34375,  0.964844, 1.76562,  1.21875,  1.75,     1.64062,  2.46875,  1.76562,  3.1875,   2.15625,
+                1.09375,  0.839844, 1.375,    1.01562,  1.375,    1.29688,  1.84375,  1.375,    2.3125,   1.64062,
+                0.929688, 0.761719, 1.11719,  0.878906, 1.11719,  1.0625,   1.4375,   1.11719,  1.75,     1.29688,
+                0.816406, 0.707031, 0.945312, 0.785156, 0.945312, 0.910156, 1.15625,  0.945312, 1.375,    1.0625,
+                0.746094, 0.671875, 0.832031, 0.722656, 0.832031, 0.808594, 0.972656, 0.832031, 1.11719,  0.910156,
                 0.695312, 0.648438, 0.753906, 0.679688, 0.753906, 0.738281, 0.847656, 0.753906, 0.945312, 0.808594,
                 0.664062, 0.632812, 0.699219, 0.652344, 0.699219, 0.691406, 0.761719, 0.699219, 0.832031, 0.738281,
                 0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062, 0.753906, 0.691406,
-                5.9375, 3.375, 2.71875, 4.9375, 4, 2.09375, 3.53125, 6.125, 2.21875, 1.03125,
-                4.15625, 2.4375, 2, 3.5, 2.875, 1.59375, 2.53125, 4.25, 1.6875, 0.886719,
-                2.96875, 1.82812, 1.53125, 2.53125, 2.125, 1.26562, 1.89062, 3.03125, 1.32812, 0.792969,
-                2.1875, 1.42188, 1.21875, 1.89062, 1.625, 1.04688, 1.46875, 2.21875, 1.08594, 0.730469,
-                1.65625, 1.14844, 1.01562, 1.46875, 1.28125, 0.898438, 1.17969, 1.6875, 0.925781, 0.6875,
-                1.3125, 0.964844, 0.878906, 1.17969, 1.05469, 0.800781, 0.988281, 1.32812, 0.816406, 0.65625,
-                1.07812, 0.839844, 0.785156, 0.988281, 0.902344, 0.730469, 0.855469, 1.08594, 0.746094, 0.636719,
-                0.917969, 0.761719, 0.722656, 0.855469, 0.800781, 0.6875, 0.769531, 0.925781, 0.695312, 0.625,
-                0.808594, 0.707031, 0.679688, 0.769531, 0.730469, 0.65625, 0.714844, 0.816406, 0.664062, 0.617188,
-                0.738281, 0.671875, 0.652344, 0.714844, 0.6875, 0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
-                4.0625, 4.875, 6.375, 3.375, 3.625, 4.1875, 3.4375, 1.70312, 6.5, 2.0625,
-                2.90625, 3.4375, 4.4375, 2.4375, 2.59375, 3, 2.46875, 1.34375, 4.5, 1.57812,
-                2.125, 2.46875, 3.15625, 1.82812, 1.9375, 2.1875, 1.84375, 1.09375, 3.1875, 1.25,
-                1.625, 1.84375, 2.28125, 1.42188, 1.5, 1.65625, 1.4375, 0.929688, 2.3125, 1.03125,
-                1.28125, 1.4375, 1.71875, 1.14844, 1.20312, 1.3125, 1.15625, 0.816406, 1.75, 0.886719,
-                1.05469, 1.15625, 1.34375, 0.964844, 1, 1.07812, 0.972656, 0.746094, 1.375, 0.792969,
-                0.902344, 0.972656, 1.09375, 0.839844, 0.867188, 0.917969, 0.847656, 0.695312, 1.11719, 0.730469,
+                5.9375,   3.375,    2.71875,  4.9375,   4,        2.09375,  3.53125,  6.125,    2.21875,  1.03125,
+                4.15625,  2.4375,   2,        3.5,      2.875,    1.59375,  2.53125,  4.25,     1.6875,   0.886719,
+                2.96875,  1.82812,  1.53125,  2.53125,  2.125,    1.26562,  1.89062,  3.03125,  1.32812,  0.792969,
+                2.1875,   1.42188,  1.21875,  1.89062,  1.625,    1.04688,  1.46875,  2.21875,  1.08594,  0.730469,
+                1.65625,  1.14844,  1.01562,  1.46875,  1.28125,  0.898438, 1.17969,  1.6875,   0.925781, 0.6875,
+                1.3125,   0.964844, 0.878906, 1.17969,  1.05469,  0.800781, 0.988281, 1.32812,  0.816406, 0.65625,
+                1.07812,  0.839844, 0.785156, 0.988281, 0.902344, 0.730469, 0.855469, 1.08594,  0.746094, 0.636719,
+                0.917969, 0.761719, 0.722656, 0.855469, 0.800781, 0.6875,   0.769531, 0.925781, 0.695312, 0.625,
+                0.808594, 0.707031, 0.679688, 0.769531, 0.730469, 0.65625,  0.714844, 0.816406, 0.664062, 0.617188,
+                0.738281, 0.671875, 0.652344, 0.714844, 0.6875,   0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
+                4.0625,   4.875,    6.375,    3.375,    3.625,    4.1875,   3.4375,   1.70312,  6.5,      2.0625,
+                2.90625,  3.4375,   4.4375,   2.4375,   2.59375,  3,        2.46875,  1.34375,  4.5,      1.57812,
+                2.125,    2.46875,  3.15625,  1.82812,  1.9375,   2.1875,   1.84375,  1.09375,  3.1875,   1.25,
+                1.625,    1.84375,  2.28125,  1.42188,  1.5,      1.65625,  1.4375,   0.929688, 2.3125,   1.03125,
+                1.28125,  1.4375,   1.71875,  1.14844,  1.20312,  1.3125,   1.15625,  0.816406, 1.75,     0.886719,
+                1.05469,  1.15625,  1.34375,  0.964844, 1,        1.07812,  0.972656, 0.746094, 1.375,    0.792969,
+                0.902344, 0.972656, 1.09375,  0.839844, 0.867188, 0.917969, 0.847656, 0.695312, 1.11719,  0.730469,
                 0.800781, 0.847656, 0.929688, 0.761719, 0.777344, 0.808594, 0.761719, 0.664062, 0.945312, 0.6875,
                 0.730469, 0.761719, 0.816406, 0.707031, 0.714844, 0.738281, 0.707031, 0.640625, 0.832031, 0.65625,
-                0.6875, 0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625, 0.753906, 0.636719,
-                5.53125, 5.65625, 5.125, 6.65625, 5.6875, 2.71875, 1.42188, 5, 3.96875, 6.875,
-                3.875, 3.96875, 3.625, 4.625, 4, 2, 1.14844, 3.53125, 2.84375, 4.75,
-                2.78125, 2.84375, 2.59375, 3.28125, 2.875, 1.53125, 0.964844, 2.53125, 2.09375, 3.375,
-                2.0625, 2.09375, 1.9375, 2.375, 2.125, 1.21875, 0.839844, 1.89062, 1.59375, 2.4375,
-                1.57812, 1.59375, 1.5, 1.78125, 1.625, 1.01562, 0.761719, 1.46875, 1.26562, 1.82812,
-                1.25, 1.26562, 1.20312, 1.39062, 1.28125, 0.878906, 0.707031, 1.17969, 1.04688, 1.42188,
-                1.03125, 1.04688, 1, 1.125, 1.05469, 0.785156, 0.671875, 0.988281, 0.898438, 1.14844,
+                0.6875,   0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625,    0.753906, 0.636719,
+                5.53125,  5.65625,  5.125,    6.65625,  5.6875,   2.71875,  1.42188,  5,        3.96875,  6.875,
+                3.875,    3.96875,  3.625,    4.625,    4,        2,        1.14844,  3.53125,  2.84375,  4.75,
+                2.78125,  2.84375,  2.59375,  3.28125,  2.875,    1.53125,  0.964844, 2.53125,  2.09375,  3.375,
+                2.0625,   2.09375,  1.9375,   2.375,    2.125,    1.21875,  0.839844, 1.89062,  1.59375,  2.4375,
+                1.57812,  1.59375,  1.5,      1.78125,  1.625,    1.01562,  0.761719, 1.46875,  1.26562,  1.82812,
+                1.25,     1.26562,  1.20312,  1.39062,  1.28125,  0.878906, 0.707031, 1.17969,  1.04688,  1.42188,
+                1.03125,  1.04688,  1,        1.125,    1.05469,  0.785156, 0.671875, 0.988281, 0.898438, 1.14844,
                 0.886719, 0.898438, 0.867188, 0.949219, 0.902344, 0.722656, 0.648438, 0.855469, 0.800781, 0.964844,
                 0.792969, 0.800781, 0.777344, 0.832031, 0.800781, 0.679688, 0.632812, 0.769531, 0.730469, 0.839844,
-                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875, 0.761719},
-            std::vector<T>{
-                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625, 0.652344, 0.761719, 0.625,
-                0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062, 0.753906, 0.691406,
-                0.738281, 0.671875, 0.652344, 0.714844, 0.6875, 0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
-                0.6875, 0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625, 0.753906, 0.636719,
-                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875, 0.761719}),
+                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875,   0.761719},
+            std::vector<T>{0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625,    0.652344, 0.761719,
+                           0.625,    0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062,
+                           0.753906, 0.691406, 0.738281, 0.671875, 0.652344, 0.714844, 0.6875,   0.636719, 0.675781,
+                           0.746094, 0.640625, 0.609375, 0.6875,   0.707031, 0.746094, 0.671875, 0.675781, 0.691406,
+                           0.671875, 0.625,    0.753906, 0.636719, 0.730469, 0.730469, 0.714844, 0.753906, 0.730469,
+                           0.652344, 0.621094, 0.714844, 0.6875,   0.761719}),
         GRUSequenceParams(
-            5, 10, 10, 10,
-            0.7f, false, op::RecurrentSequenceDirection::REVERSE,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            false,
+            op::RecurrentSequenceDirection::REVERSE,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   10},
+            std::vector<T>{1,     4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,     2.3125,
+                           3.125, 1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,  5.84375,
+                           8.625, 4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 10},
-            std::vector<T>{
-                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625, 0.652344, 0.761719, 0.625,
+                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625,    0.652344, 0.761719, 0.625,
                 0.609375, 0.707031, 0.839844, 0.777344, 0.832031, 0.609375, 0.640625, 0.679688, 0.839844, 0.640625,
                 0.613281, 0.761719, 0.964844, 0.867188, 0.945312, 0.613281, 0.660156, 0.722656, 0.964844, 0.664062,
-                0.621094, 0.839844, 1.14844, 1, 1.11719, 0.621094, 0.691406, 0.785156, 1.14844, 0.699219,
-                0.632812, 0.964844, 1.42188, 1.20312, 1.375, 0.632812, 0.738281, 0.878906, 1.42188, 0.753906,
-                0.648438, 1.14844, 1.82812, 1.5, 1.75, 0.648438, 0.808594, 1.01562, 1.82812, 0.832031,
-                0.675781, 1.42188, 2.4375, 1.95312, 2.3125, 0.675781, 0.910156, 1.21875, 2.4375, 0.945312,
-                0.714844, 1.82812, 3.375, 2.625, 3.1875, 0.714844, 1.0625, 1.51562, 3.375, 1.11719,
-                0.777344, 2.4375, 4.75, 3.65625, 4.5, 0.777344, 1.29688, 1.96875, 4.75, 1.375,
-                0.867188, 3.375, 6.875, 5.1875, 6.4375, 0.867188, 1.64062, 2.65625, 6.875, 1.75,
+                0.621094, 0.839844, 1.14844,  1,        1.11719,  0.621094, 0.691406, 0.785156, 1.14844,  0.699219,
+                0.632812, 0.964844, 1.42188,  1.20312,  1.375,    0.632812, 0.738281, 0.878906, 1.42188,  0.753906,
+                0.648438, 1.14844,  1.82812,  1.5,      1.75,     0.648438, 0.808594, 1.01562,  1.82812,  0.832031,
+                0.675781, 1.42188,  2.4375,   1.95312,  2.3125,   0.675781, 0.910156, 1.21875,  2.4375,   0.945312,
+                0.714844, 1.82812,  3.375,    2.625,    3.1875,   0.714844, 1.0625,   1.51562,  3.375,    1.11719,
+                0.777344, 2.4375,   4.75,     3.65625,  4.5,      0.777344, 1.29688,  1.96875,  4.75,     1.375,
+                0.867188, 3.375,    6.875,    5.1875,   6.4375,   0.867188, 1.64062,  2.65625,  6.875,    1.75,
                 0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062, 0.753906, 0.691406,
                 0.664062, 0.632812, 0.699219, 0.652344, 0.699219, 0.691406, 0.761719, 0.699219, 0.832031, 0.738281,
                 0.695312, 0.648438, 0.753906, 0.679688, 0.753906, 0.738281, 0.847656, 0.753906, 0.945312, 0.808594,
-                0.746094, 0.671875, 0.832031, 0.722656, 0.832031, 0.808594, 0.972656, 0.832031, 1.11719, 0.910156,
-                0.816406, 0.707031, 0.945312, 0.785156, 0.945312, 0.910156, 1.15625, 0.945312, 1.375, 1.0625,
-                0.929688, 0.761719, 1.11719, 0.878906, 1.11719, 1.0625, 1.4375, 1.11719, 1.75, 1.29688,
-                1.09375, 0.839844, 1.375, 1.01562, 1.375, 1.29688, 1.84375, 1.375, 2.3125, 1.64062,
-                1.34375, 0.964844, 1.76562, 1.21875, 1.75, 1.64062, 2.46875, 1.76562, 3.1875, 2.15625,
-                1.71875, 1.14844, 2.34375, 1.53125, 2.3125, 2.15625, 3.4375, 2.34375, 4.5, 2.9375,
-                2.28125, 1.42188, 3.25, 1.98438, 3.1875, 2.9375, 4.875, 3.25, 6.4375, 4.09375,
-                0.738281, 0.671875, 0.652344, 0.714844, 0.6875, 0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
-                0.808594, 0.707031, 0.679688, 0.769531, 0.730469, 0.65625, 0.714844, 0.816406, 0.664062, 0.617188,
-                0.917969, 0.761719, 0.722656, 0.855469, 0.800781, 0.6875, 0.769531, 0.925781, 0.695312, 0.625,
-                1.07812, 0.839844, 0.785156, 0.988281, 0.902344, 0.730469, 0.855469, 1.08594, 0.746094, 0.636719,
-                1.3125, 0.964844, 0.878906, 1.17969, 1.05469, 0.800781, 0.988281, 1.32812, 0.816406, 0.65625,
-                1.65625, 1.14844, 1.01562, 1.46875, 1.28125, 0.898438, 1.17969, 1.6875, 0.925781, 0.6875,
-                2.1875, 1.42188, 1.21875, 1.89062, 1.625, 1.04688, 1.46875, 2.21875, 1.08594, 0.730469,
-                2.96875, 1.82812, 1.53125, 2.53125, 2.125, 1.26562, 1.89062, 3.03125, 1.32812, 0.792969,
-                4.15625, 2.4375, 2, 3.5, 2.875, 1.59375, 2.53125, 4.25, 1.6875, 0.886719,
-                5.9375, 3.375, 2.71875, 4.9375, 4, 2.09375, 3.53125, 6.125, 2.21875, 1.03125,
-                0.6875, 0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625, 0.753906, 0.636719,
+                0.746094, 0.671875, 0.832031, 0.722656, 0.832031, 0.808594, 0.972656, 0.832031, 1.11719,  0.910156,
+                0.816406, 0.707031, 0.945312, 0.785156, 0.945312, 0.910156, 1.15625,  0.945312, 1.375,    1.0625,
+                0.929688, 0.761719, 1.11719,  0.878906, 1.11719,  1.0625,   1.4375,   1.11719,  1.75,     1.29688,
+                1.09375,  0.839844, 1.375,    1.01562,  1.375,    1.29688,  1.84375,  1.375,    2.3125,   1.64062,
+                1.34375,  0.964844, 1.76562,  1.21875,  1.75,     1.64062,  2.46875,  1.76562,  3.1875,   2.15625,
+                1.71875,  1.14844,  2.34375,  1.53125,  2.3125,   2.15625,  3.4375,   2.34375,  4.5,      2.9375,
+                2.28125,  1.42188,  3.25,     1.98438,  3.1875,   2.9375,   4.875,    3.25,     6.4375,   4.09375,
+                0.738281, 0.671875, 0.652344, 0.714844, 0.6875,   0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
+                0.808594, 0.707031, 0.679688, 0.769531, 0.730469, 0.65625,  0.714844, 0.816406, 0.664062, 0.617188,
+                0.917969, 0.761719, 0.722656, 0.855469, 0.800781, 0.6875,   0.769531, 0.925781, 0.695312, 0.625,
+                1.07812,  0.839844, 0.785156, 0.988281, 0.902344, 0.730469, 0.855469, 1.08594,  0.746094, 0.636719,
+                1.3125,   0.964844, 0.878906, 1.17969,  1.05469,  0.800781, 0.988281, 1.32812,  0.816406, 0.65625,
+                1.65625,  1.14844,  1.01562,  1.46875,  1.28125,  0.898438, 1.17969,  1.6875,   0.925781, 0.6875,
+                2.1875,   1.42188,  1.21875,  1.89062,  1.625,    1.04688,  1.46875,  2.21875,  1.08594,  0.730469,
+                2.96875,  1.82812,  1.53125,  2.53125,  2.125,    1.26562,  1.89062,  3.03125,  1.32812,  0.792969,
+                4.15625,  2.4375,   2,        3.5,      2.875,    1.59375,  2.53125,  4.25,     1.6875,   0.886719,
+                5.9375,   3.375,    2.71875,  4.9375,   4,        2.09375,  3.53125,  6.125,    2.21875,  1.03125,
+                0.6875,   0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625,    0.753906, 0.636719,
                 0.730469, 0.761719, 0.816406, 0.707031, 0.714844, 0.738281, 0.707031, 0.640625, 0.832031, 0.65625,
                 0.800781, 0.847656, 0.929688, 0.761719, 0.777344, 0.808594, 0.761719, 0.664062, 0.945312, 0.6875,
-                0.902344, 0.972656, 1.09375, 0.839844, 0.867188, 0.917969, 0.847656, 0.695312, 1.11719, 0.730469,
-                1.05469, 1.15625, 1.34375, 0.964844, 1, 1.07812, 0.972656, 0.746094, 1.375, 0.792969,
-                1.28125, 1.4375, 1.71875, 1.14844, 1.20312, 1.3125, 1.15625, 0.816406, 1.75, 0.886719,
-                1.625, 1.84375, 2.28125, 1.42188, 1.5, 1.65625, 1.4375, 0.929688, 2.3125, 1.03125,
-                2.125, 2.46875, 3.15625, 1.82812, 1.9375, 2.1875, 1.84375, 1.09375, 3.1875, 1.25,
-                2.90625, 3.4375, 4.4375, 2.4375, 2.59375, 3, 2.46875, 1.34375, 4.5, 1.57812,
-                4.0625, 4.875, 6.375, 3.375, 3.625, 4.1875, 3.4375, 1.70312, 6.5, 2.0625,
-                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875, 0.761719,
+                0.902344, 0.972656, 1.09375,  0.839844, 0.867188, 0.917969, 0.847656, 0.695312, 1.11719,  0.730469,
+                1.05469,  1.15625,  1.34375,  0.964844, 1,        1.07812,  0.972656, 0.746094, 1.375,    0.792969,
+                1.28125,  1.4375,   1.71875,  1.14844,  1.20312,  1.3125,   1.15625,  0.816406, 1.75,     0.886719,
+                1.625,    1.84375,  2.28125,  1.42188,  1.5,      1.65625,  1.4375,   0.929688, 2.3125,   1.03125,
+                2.125,    2.46875,  3.15625,  1.82812,  1.9375,   2.1875,   1.84375,  1.09375,  3.1875,   1.25,
+                2.90625,  3.4375,   4.4375,   2.4375,   2.59375,  3,        2.46875,  1.34375,  4.5,      1.57812,
+                4.0625,   4.875,    6.375,    3.375,    3.625,    4.1875,   3.4375,   1.70312,  6.5,      2.0625,
+                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875,   0.761719,
                 0.792969, 0.800781, 0.777344, 0.832031, 0.800781, 0.679688, 0.632812, 0.769531, 0.730469, 0.839844,
                 0.886719, 0.898438, 0.867188, 0.949219, 0.902344, 0.722656, 0.648438, 0.855469, 0.800781, 0.964844,
-                1.03125, 1.04688, 1, 1.125, 1.05469, 0.785156, 0.671875, 0.988281, 0.898438, 1.14844,
-                1.25, 1.26562, 1.20312, 1.39062, 1.28125, 0.878906, 0.707031, 1.17969, 1.04688, 1.42188,
-                1.57812, 1.59375, 1.5, 1.78125, 1.625, 1.01562, 0.761719, 1.46875, 1.26562, 1.82812,
-                2.0625, 2.09375, 1.9375, 2.375, 2.125, 1.21875, 0.839844, 1.89062, 1.59375, 2.4375,
-                2.78125, 2.84375, 2.59375, 3.28125, 2.875, 1.53125, 0.964844, 2.53125, 2.09375, 3.375,
-                3.875, 3.96875, 3.625, 4.625, 4, 2, 1.14844, 3.53125, 2.84375, 4.75,
-                5.53125, 5.65625, 5.125, 6.65625, 5.6875, 2.71875, 1.42188, 5, 3.96875, 6.875},
-            std::vector<T>{
-                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625, 0.652344, 0.761719, 0.625,
-                0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062, 0.753906, 0.691406,
-                0.738281, 0.671875, 0.652344, 0.714844, 0.6875, 0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
-                0.6875, 0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625, 0.753906, 0.636719,
-                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875, 0.761719}),
+                1.03125,  1.04688,  1,        1.125,    1.05469,  0.785156, 0.671875, 0.988281, 0.898438, 1.14844,
+                1.25,     1.26562,  1.20312,  1.39062,  1.28125,  0.878906, 0.707031, 1.17969,  1.04688,  1.42188,
+                1.57812,  1.59375,  1.5,      1.78125,  1.625,    1.01562,  0.761719, 1.46875,  1.26562,  1.82812,
+                2.0625,   2.09375,  1.9375,   2.375,    2.125,    1.21875,  0.839844, 1.89062,  1.59375,  2.4375,
+                2.78125,  2.84375,  2.59375,  3.28125,  2.875,    1.53125,  0.964844, 2.53125,  2.09375,  3.375,
+                3.875,    3.96875,  3.625,    4.625,    4,        2,        1.14844,  3.53125,  2.84375,  4.75,
+                5.53125,  5.65625,  5.125,    6.65625,  5.6875,   2.71875,  1.42188,  5,        3.96875,  6.875},
+            std::vector<T>{0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625,    0.652344, 0.761719,
+                           0.625,    0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062,
+                           0.753906, 0.691406, 0.738281, 0.671875, 0.652344, 0.714844, 0.6875,   0.636719, 0.675781,
+                           0.746094, 0.640625, 0.609375, 0.6875,   0.707031, 0.746094, 0.671875, 0.675781, 0.691406,
+                           0.671875, 0.625,    0.753906, 0.636719, 0.730469, 0.730469, 0.714844, 0.753906, 0.730469,
+                           0.652344, 0.621094, 0.714844, 0.6875,   0.761719}),
         GRUSequenceParams(
-            5, 10, 10, 5,
-            0.f, true, op::RecurrentSequenceDirection::BIDIRECTIONAL,
+            5,
+            10,
+            10,
+            5,
+            0.f,
+            true,
+            op::RecurrentSequenceDirection::BIDIRECTIONAL,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 10},
+            std::vector<T>{1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,   1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,   4.75,    3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125,  7.03125, 9.25,    4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,       8.1875,  7.4375,  9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,
+                           8.75,    9,       8.4375,  1.76562, 8.4375,  1.34375, 3.45312, 2.53125, 1.53125, 8.875,
+                           7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,   4.6875,  5.8125,  2.78125, 7.21875,
+                           3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,  1.16406, 1.30469, 7.75,
+                           6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,   3,       1.92188,
+                           1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,  10},
             std::vector<int64_t>{5, 5, 5, 5, 5},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 9.25,
-                6.1875, 1, 8.75, 9.75, 8.0625, 4.375, 3.28125, 9.75, 1.73438, 6.4375,
-                2.40625, 8.4375, 2.875, 6.1875, 4.75, 6.625, 4.125, 3.5625, 7.3125, 6.28125,
-                7.25, 7.75, 1.67188, 8.75, 1.32812, 7.78125, 8.125, 7.28125, 9.125, 8.75,
-                1.03906, 3.90625, 3.375, 7.03125, 5.1875, 5.0625, 4.25, 4.4375, 3.15625, 4.6875,
-                1.20312, 4.625, 5.78125, 3.84375, 2.15625, 6.59375, 6.0625, 4.875, 2.5, 9.75,
-                4.78125, 7.09375, 7.15625, 2.78125, 3.46875, 4.8125, 1.09375, 4.0625, 2.96875, 8.125,
-                1.28125, 8.875, 9.375, 9.125, 8, 6.9375, 5.65625, 3.4375, 1.14062, 3.26562,
-                3.6875, 8.6875, 5.875, 5.75, 8.75, 8.25, 2.65625, 6.125, 1.75, 7.59375,
-                1.39844, 5.65625, 5, 7.9375, 1.17188, 6.125, 1.60156, 5.1875, 8.25, 4.0625,
-                6.71875, 1.60938, 7.9375, 4.375, 7.34375, 1.71875, 3.14062, 9.875, 1.39844, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 9.25,
-                6.1875, 1, 8.75, 9.75, 8.0625, 4.375, 3.28125, 9.75, 1.73438, 6.4375,
-                2.40625, 8.4375, 2.875, 6.1875, 4.75, 6.625, 4.125, 3.5625, 7.3125, 6.28125,
-                7.25, 7.75, 1.67188, 8.75, 1.32812, 7.78125, 8.125, 7.28125, 9.125, 8.75,
-                1.03906, 3.90625, 3.375, 7.03125, 5.1875, 5.0625, 4.25, 4.4375, 3.15625, 4.6875,
-                1.20312, 4.625, 5.78125, 3.84375, 2.15625, 6.59375, 6.0625, 4.875, 2.5, 9.75,
-                4.78125, 7.09375, 7.15625, 2.78125, 3.46875, 4.8125, 1.09375, 4.0625, 2.96875, 8.125,
-                1.28125, 8.875, 9.375, 9.125, 8, 6.9375, 5.65625, 3.4375, 1.14062, 3.26562,
-                3.6875, 8.6875, 5.875, 5.75, 8.75, 8.25, 2.65625, 6.125, 1.75, 7.59375,
-                1.39844, 5.65625, 5, 7.9375, 1.17188, 6.125, 1.60156, 5.1875, 8.25, 4.0625,
-                6.71875, 1.60938, 7.9375, 4.375, 7.34375, 1.71875, 3.14062, 9.875, 1.39844, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 9.25,    6.1875,  1,       8.75,    9.75,    8.0625,  4.375,
+                3.28125, 9.75,    1.73438, 6.4375,  2.40625, 8.4375,  2.875,   6.1875,  4.75,    6.625,   4.125,
+                3.5625,  7.3125,  6.28125, 7.25,    7.75,    1.67188, 8.75,    1.32812, 7.78125, 8.125,   7.28125,
+                9.125,   8.75,    1.03906, 3.90625, 3.375,   7.03125, 5.1875,  5.0625,  4.25,    4.4375,  3.15625,
+                4.6875,  1.20312, 4.625,   5.78125, 3.84375, 2.15625, 6.59375, 6.0625,  4.875,   2.5,     9.75,
+                4.78125, 7.09375, 7.15625, 2.78125, 3.46875, 4.8125,  1.09375, 4.0625,  2.96875, 8.125,   1.28125,
+                8.875,   9.375,   9.125,   8,       6.9375,  5.65625, 3.4375,  1.14062, 3.26562, 3.6875,  8.6875,
+                5.875,   5.75,    8.75,    8.25,    2.65625, 6.125,   1.75,    7.59375, 1.39844, 5.65625, 5,
+                7.9375,  1.17188, 6.125,   1.60156, 5.1875,  8.25,    4.0625,  6.71875, 1.60938, 7.9375,  4.375,
+                7.34375, 1.71875, 3.14062, 9.875,   1.39844, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 10,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 10,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 10,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 10,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 9.25,    6.1875,  1,       8.75,    9.75,    8.0625,  4.375,
+                3.28125, 9.75,    1.73438, 6.4375,  2.40625, 8.4375,  2.875,   6.1875,  4.75,    6.625,   4.125,
+                3.5625,  7.3125,  6.28125, 7.25,    7.75,    1.67188, 8.75,    1.32812, 7.78125, 8.125,   7.28125,
+                9.125,   8.75,    1.03906, 3.90625, 3.375,   7.03125, 5.1875,  5.0625,  4.25,    4.4375,  3.15625,
+                4.6875,  1.20312, 4.625,   5.78125, 3.84375, 2.15625, 6.59375, 6.0625,  4.875,   2.5,     9.75,
+                4.78125, 7.09375, 7.15625, 2.78125, 3.46875, 4.8125,  1.09375, 4.0625,  2.96875, 8.125,   1.28125,
+                8.875,   9.375,   9.125,   8,       6.9375,  5.65625, 3.4375,  1.14062, 3.26562, 3.6875,  8.6875,
+                5.875,   5.75,    8.75,    8.25,    2.65625, 6.125,   1.75,    7.59375, 1.39844, 5.65625, 5,
+                7.9375,  1.17188, 6.125,   1.60156, 5.1875,  8.25,    4.0625,  6.71875, 1.60938, 7.9375,  4.375,
+                7.34375, 1.71875, 3.14062, 9.875,   1.39844, 10},
+            std::vector<T>{1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,   1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,   4.75,    3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125,  7.03125, 9.25,    4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,       8.1875,  7.4375,  9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,
+                           8.75,    9,       8.4375,  1.76562, 8.4375,  1.34375, 3.45312, 2.53125, 1.53125, 8.875,
+                           7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,   4.6875,  5.8125,  2.78125, 7.21875,
+                           3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,  1.16406, 1.30469, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 10}),
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  1,
+                4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  1,       4.75,
+                10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  1,       4.75,    10,
+                7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  1,       4.75,    10,      7.46875,
+                9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,   1.82812, 4.5625,  2.67188, 4.5,
+                4.125,   7,       4.5625,  9.375,   5.84375, 3.125,   1.82812, 4.5625,  2.67188, 4.5,     4.125,
+                7,       4.5625,  9.375,   5.84375, 3.125,   1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,
+                4.5625,  9.375,   5.84375, 3.125,   1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,
+                9.375,   5.84375, 3.125,   1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,
+                5.84375, 8.625,   4.75,    3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                8.625,   4.75,    3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    8.625,
+                4.75,    3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    8.625,   4.75,    3.8125,
+                7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,    4.75,
+                5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 5.8125,  7.03125, 9.25,    4.75,    5.125,
+                6,       4.875,   2.25,    9.4375,  2.78125, 5.8125,  7.03125, 9.25,    4.75,    5.125,   6,
+                4.875,   2.25,    9.4375,  2.78125, 5.8125,  7.03125, 9.25,    4.75,    5.125,   6,       4.875,
+                2.25,    9.4375,  2.78125, 5.8125,  7.03125, 9.25,    4.75,    5.125,   6,       4.875,   2.25,
+                9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625,
+                8.875,   8,       8.1875,  7.4375,  9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,
+                8,       8.1875,  7.4375,  9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8,
+                8.1875,  7.4375,  9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8,       8.1875,
+                7.4375,  9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,
+                1.76562, 8.4375,  1.34375, 3.45312, 2.53125, 1.53125, 8.875,   8.75,    9,       8.4375,  1.76562,
+                8.4375,  1.34375, 3.45312, 2.53125, 1.53125, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,  1.34375,
+                3.45312, 2.53125, 1.53125, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,  1.34375, 3.45312,
+                2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,   4.6875,  5.8125,
+                2.78125, 7.21875, 7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,   4.6875,  5.8125,  2.78125,
+                7.21875, 7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,   4.6875,  5.8125,  2.78125, 7.21875,
+                7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,   4.6875,  5.8125,  2.78125, 7.21875, 7.03125,
+                1.88281, 6.3125,  4.78125, 7.03125, 9.625,   4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375,
+                2.28125, 7.1875,  8,       8.5,     4.6875,  1.16406, 1.30469, 7.75,    3.59375, 3.84375, 2.28125,
+                7.1875,  8,       8.5,     4.6875,  1.16406, 1.30469, 7.75,    3.59375, 3.84375, 2.28125, 7.1875,
+                8,       8.5,     4.6875,  1.16406, 1.30469, 7.75,    3.59375, 3.84375, 2.28125, 7.1875,  8,
+                8.5,     4.6875,  1.16406, 1.30469, 7.75,    3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,
+                4.6875,  1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,
+                8.125,   3,       1.92188, 6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,   3,
+                1.92188, 6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,   3,       1.92188,
+                6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,   3,       1.92188, 1.65625,
+                5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,  10,      1.65625, 5,
+                5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,  10,      1.65625, 5,       5.21875,
+                9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,  10,      1.65625, 5,       5.21875, 9.125,
+                1.85938, 3.64062, 9.125,   3.59375, 2.0625,  10,      1.65625, 5,       5.21875, 9.125,   1.85938,
+                3.64062, 9.125,   3.59375, 2.0625,  10},
+            std::vector<T>{1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,   1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,   4.75,    3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125,  7.03125, 9.25,    4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,       8.1875,  7.4375,  9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,
+                           8.75,    9,       8.4375,  1.76562, 8.4375,  1.34375, 3.45312, 2.53125, 1.53125, 8.875,
+                           7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,   4.6875,  5.8125,  2.78125, 7.21875,
+                           3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,  1.16406, 1.30469, 7.75,
+                           6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,   3,       1.92188,
+                           1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,  10}),
     };
     return params;
 }
 
 std::vector<GRUSequenceParams> generateCombinedParams() {
-    const std::vector<std::vector<GRUSequenceParams>> generatedParams {
+    const std::vector<std::vector<GRUSequenceParams>> generatedParams{
         generateParams<element::Type_t::f64>(),
         generateParams<element::Type_t::f32>(),
         generateParams<element::Type_t::f16>(),
@@ -1379,7 +1350,9 @@ std::vector<GRUSequenceParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_GRUSequence_With_Hardcoded_Refs, ReferenceGRUSequenceTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceGRUSequenceTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_GRUSequence_With_Hardcoded_Refs,
+                         ReferenceGRUSequenceTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceGRUSequenceTest::getTestCaseName);
 
-} // namespace
\ No newline at end of file
+}  // namespace
\ No newline at end of file
diff --git a/src/plugins/template/tests/functional/op_reference/hard_sigmoid.cpp b/src/plugins/template/tests/functional/op_reference/hard_sigmoid.cpp
index d6142cf83d74ea..a39d927bd50875 100644
--- a/src/plugins/template/tests/functional/op_reference/hard_sigmoid.cpp
+++ b/src/plugins/template/tests/functional/op_reference/hard_sigmoid.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/hard_sigmoid.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/hard_sigmoid.hpp"
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
 
@@ -14,8 +15,12 @@ using namespace ov;
 namespace {
 struct HardSigmoidParams {
     template <class IT>
-    HardSigmoidParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
-                const float alpha, const float beta)
+    HardSigmoidParams(const ov::PartialShape& shape,
+                      const ov::element::Type& iType,
+                      const std::vector<IT>& iValues,
+                      const std::vector<IT>& oValues,
+                      const float alpha,
+                      const float beta)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -53,8 +58,11 @@ class ReferenceHardSigmoidLayerTest : public testing::TestWithParam<HardSigmoidP
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type, const float alphaData, const float betaData) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type,
+                                                 const float alphaData,
+                                                 const float betaData) {
         std::vector<float> alphaArray;
         std::vector<float> betaArray;
         alphaArray.push_back(alphaData);
@@ -63,7 +71,7 @@ class ReferenceHardSigmoidLayerTest : public testing::TestWithParam<HardSigmoidP
         const auto alpha = ov::op::v0::Constant::create(input_type, Shape{}, {alphaData});
         const auto beta = ov::op::v0::Constant::create(input_type, Shape{}, {betaData});
         const auto HardSigmoid = std::make_shared<op::v0::HardSigmoid>(in, alpha, beta);
-        return std::make_shared<ov::Model>(NodeVector {HardSigmoid}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{HardSigmoid}, ParameterVector{in});
     }
 };
 
@@ -75,28 +83,26 @@ template <element::Type_t IN_ET>
 std::vector<HardSigmoidParams> generateHardSigmoidFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<HardSigmoidParams> hardSigmoidParams {
-        HardSigmoidParams(ov::PartialShape {3},
-                    IN_ET,
-                    std::vector<T>{-1.0f, 0.0f, 1.0f},
-                    std::vector<T>{0.1f, 0.6f, 1.f},
-                    0.5,
-                    0.6),
-        HardSigmoidParams(ov::PartialShape {2, 5},
-                    IN_ET,
-                    std::vector<T>{-3.0f, -1.0f, 0.0f, 1.0f, 3.0f, 0.5f, -0.2f, 6.0f, 8.0f, 0.1f},
-                    std::vector<T>{0.0f, 0.3f, 0.5f, 0.7f, 1.0f, 0.6f, 0.46f, 1.0f, 1.0f, 0.52f},
-                    0.2,
-                    0.5)
-    };
+    std::vector<HardSigmoidParams> hardSigmoidParams{
+        HardSigmoidParams(ov::PartialShape{3},
+                          IN_ET,
+                          std::vector<T>{-1.0f, 0.0f, 1.0f},
+                          std::vector<T>{0.1f, 0.6f, 1.f},
+                          0.5,
+                          0.6),
+        HardSigmoidParams(ov::PartialShape{2, 5},
+                          IN_ET,
+                          std::vector<T>{-3.0f, -1.0f, 0.0f, 1.0f, 3.0f, 0.5f, -0.2f, 6.0f, 8.0f, 0.1f},
+                          std::vector<T>{0.0f, 0.3f, 0.5f, 0.7f, 1.0f, 0.6f, 0.46f, 1.0f, 1.0f, 0.52f},
+                          0.2,
+                          0.5)};
     return hardSigmoidParams;
 }
 
 std::vector<HardSigmoidParams> generateHardSigmoidCombinedParams() {
-    const std::vector<std::vector<HardSigmoidParams>> hardSigmoidTypeParams {
+    const std::vector<std::vector<HardSigmoidParams>> hardSigmoidTypeParams{
         generateHardSigmoidFloatParams<element::Type_t::f32>(),
-        generateHardSigmoidFloatParams<element::Type_t::f16>()
-        };
+        generateHardSigmoidFloatParams<element::Type_t::f16>()};
     std::vector<HardSigmoidParams> combinedParams;
 
     for (const auto& params : hardSigmoidTypeParams) {
@@ -105,7 +111,9 @@ std::vector<HardSigmoidParams> generateHardSigmoidCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_HardSigmoid_With_Hardcoded_Refs, ReferenceHardSigmoidLayerTest,
-    testing::ValuesIn(generateHardSigmoidCombinedParams()), ReferenceHardSigmoidLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_HardSigmoid_With_Hardcoded_Refs,
+                         ReferenceHardSigmoidLayerTest,
+                         testing::ValuesIn(generateHardSigmoidCombinedParams()),
+                         ReferenceHardSigmoidLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/hsigmoid.cpp b/src/plugins/template/tests/functional/op_reference/hsigmoid.cpp
index 3b5509578b9e5b..3382e7419f8511 100644
--- a/src/plugins/template/tests/functional/op_reference/hsigmoid.cpp
+++ b/src/plugins/template/tests/functional/op_reference/hsigmoid.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/hsigmoid.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/hsigmoid.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,7 +14,10 @@ using namespace ov;
 namespace {
 struct HSigmoidParams {
     template <class IT>
-    HSigmoidParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    HSigmoidParams(const ov::PartialShape& shape,
+                   const ov::element::Type& iType,
+                   const std::vector<IT>& iValues,
+                   const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -45,11 +49,12 @@ class ReferenceHSigmoidLayerTest : public testing::TestWithParam<HSigmoidParams>
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& HSigmoidected_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& HSigmoidected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto HSigmoid = std::make_shared<op::v5::HSigmoid>(in);
-        return std::make_shared<ov::Model>(NodeVector {HSigmoid}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{HSigmoid}, ParameterVector{in});
     }
 };
 
@@ -57,25 +62,23 @@ TEST_P(ReferenceHSigmoidLayerTest, CompareWithRefs) {
     Exec();
 }
 
-
 template <element::Type_t IN_ET>
 std::vector<HSigmoidParams> generateHSigmoidFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<HSigmoidParams> hSigmoidParams {
-        HSigmoidParams(ov::PartialShape {13},
-                    IN_ET,
-                    std::vector<T>{-10.f, -5.f, -4.f, -3.f, -2.f, -1.f, 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 10.f},
-                    std::vector<T>{0.f, 0.f, 0.f, 0.f, 0.16666667f, 0.33333333f, 0.5f, 0.66666667f, 0.83333333f, 1.f, 1.f, 1.f, 1.f})
-    };
+    std::vector<HSigmoidParams> hSigmoidParams{HSigmoidParams(
+        ov::PartialShape{13},
+        IN_ET,
+        std::vector<T>{-10.f, -5.f, -4.f, -3.f, -2.f, -1.f, 0.f, 1.f, 2.f, 3.f, 4.f, 5.f, 10.f},
+        std::vector<
+            T>{0.f, 0.f, 0.f, 0.f, 0.16666667f, 0.33333333f, 0.5f, 0.66666667f, 0.83333333f, 1.f, 1.f, 1.f, 1.f})};
     return hSigmoidParams;
 }
 
 std::vector<HSigmoidParams> generateHSigmoidCombinedParams() {
-    const std::vector<std::vector<HSigmoidParams>> hSigmoidTypeParams {
+    const std::vector<std::vector<HSigmoidParams>> hSigmoidTypeParams{
         generateHSigmoidFloatParams<element::Type_t::f32>(),
-        generateHSigmoidFloatParams<element::Type_t::f16>()
-        };
+        generateHSigmoidFloatParams<element::Type_t::f16>()};
     std::vector<HSigmoidParams> combinedParams;
 
     for (const auto& params : hSigmoidTypeParams) {
@@ -84,7 +87,9 @@ std::vector<HSigmoidParams> generateHSigmoidCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_HSigmoid_With_Hardcoded_Refs, ReferenceHSigmoidLayerTest,
-    testing::ValuesIn(generateHSigmoidCombinedParams()), ReferenceHSigmoidLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_HSigmoid_With_Hardcoded_Refs,
+                         ReferenceHSigmoidLayerTest,
+                         testing::ValuesIn(generateHSigmoidCombinedParams()),
+                         ReferenceHSigmoidLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/hswish.cpp b/src/plugins/template/tests/functional/op_reference/hswish.cpp
index fc6e6109c48d8d..0da8582df0bb3b 100644
--- a/src/plugins/template/tests/functional/op_reference/hswish.cpp
+++ b/src/plugins/template/tests/functional/op_reference/hswish.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/hswish.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/hswish.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -14,7 +15,10 @@ using namespace InferenceEngine;
 namespace {
 struct HSwishParams {
     template <class IT>
-    HSwishParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    HSwishParams(const ov::PartialShape& shape,
+                 const ov::element::Type& iType,
+                 const std::vector<IT>& iValues,
+                 const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -46,11 +50,12 @@ class ReferenceHSwishLayerTest : public testing::TestWithParam<HSwishParams>, pu
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& HSwishected_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& HSwishected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto HSwish = std::make_shared<op::v4::HSwish>(in);
-        return std::make_shared<ov::Model>(NodeVector {HSwish}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{HSwish}, ParameterVector{in});
     }
 };
 
@@ -58,29 +63,25 @@ TEST_P(ReferenceHSwishLayerTest, CompareWithRefs) {
     Exec();
 }
 
-
 template <element::Type_t IN_ET>
 std::vector<HSwishParams> generateHSwishFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<HSwishParams> hSwishParams {
-        HSwishParams(ov::PartialShape {2, 3},
-                    IN_ET,
-                    std::vector<T>{1.f, 8.f, -8.f, 17.f, -0.5f, -1.f},
-                    std::vector<T>{0.66666667f, 8.f, 0.f, 17.f, -0.20833333f, -0.33333333f}),
-        HSwishParams(ov::PartialShape {2, 2, 1, 2},
-                    IN_ET,
-                    std::vector<T>{0.1f, 0.6f, 20.f, -7.f, -5.3f, 3.5f, -9.f, 11.f},
-                    std::vector<T>{0.05166667f, 0.36f, 20.f, 0.f, 0.f, 3.5f, 0.f, 11.f})
-    };
+    std::vector<HSwishParams> hSwishParams{
+        HSwishParams(ov::PartialShape{2, 3},
+                     IN_ET,
+                     std::vector<T>{1.f, 8.f, -8.f, 17.f, -0.5f, -1.f},
+                     std::vector<T>{0.66666667f, 8.f, 0.f, 17.f, -0.20833333f, -0.33333333f}),
+        HSwishParams(ov::PartialShape{2, 2, 1, 2},
+                     IN_ET,
+                     std::vector<T>{0.1f, 0.6f, 20.f, -7.f, -5.3f, 3.5f, -9.f, 11.f},
+                     std::vector<T>{0.05166667f, 0.36f, 20.f, 0.f, 0.f, 3.5f, 0.f, 11.f})};
     return hSwishParams;
 }
 
 std::vector<HSwishParams> generateHSwishCombinedParams() {
-    const std::vector<std::vector<HSwishParams>> hSwishTypeParams {
-        generateHSwishFloatParams<element::Type_t::f32>(),
-        generateHSwishFloatParams<element::Type_t::f16>()
-        };
+    const std::vector<std::vector<HSwishParams>> hSwishTypeParams{generateHSwishFloatParams<element::Type_t::f32>(),
+                                                                  generateHSwishFloatParams<element::Type_t::f16>()};
     std::vector<HSwishParams> combinedParams;
 
     for (const auto& params : hSwishTypeParams) {
@@ -89,7 +90,9 @@ std::vector<HSwishParams> generateHSwishCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_HSwish_With_Hardcoded_Refs, ReferenceHSwishLayerTest,
-    testing::ValuesIn(generateHSwishCombinedParams()), ReferenceHSwishLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_HSwish_With_Hardcoded_Refs,
+                         ReferenceHSwishLayerTest,
+                         testing::ValuesIn(generateHSwishCombinedParams()),
+                         ReferenceHSwishLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/idft.cpp b/src/plugins/template/tests/functional/op_reference/idft.cpp
index 7969dcc0d416a4..dc3507f4edc912 100644
--- a/src/plugins/template/tests/functional/op_reference/idft.cpp
+++ b/src/plugins/template/tests/functional/op_reference/idft.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/idft.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/idft.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -16,13 +17,13 @@ namespace {
 struct IDFTParams {
     template <class T>
     IDFTParams(const Shape& input_shape,
-              const Shape& expected_shape,
-              const element::Type_t& input_type,
-              const element::Type_t& expected_type,
-              const std::vector<T>& input_value,
-              const std::vector<T>& expected_value,
-              const std::shared_ptr<op::v0::Constant>& axes,
-              const std::shared_ptr<op::v0::Constant>& signal) {
+               const Shape& expected_shape,
+               const element::Type_t& input_type,
+               const element::Type_t& expected_type,
+               const std::vector<T>& input_value,
+               const std::vector<T>& expected_value,
+               const std::shared_ptr<op::v0::Constant>& axes,
+               const std::shared_ptr<op::v0::Constant>& signal) {
         m_input_shape = input_shape;
         m_expected_shape = expected_shape;
         m_input_type = input_type;
@@ -1157,12 +1158,12 @@ std::vector<IDFTParams> generateParamsForIDFT() {
         // idft1d_eval_1
         IDFTParams(Shape{4, 6, 8, 2},
                    Shape{4, 6, 8, 2},
-                  ET,
-                  ET,
-                  idft1d_input_data_1,
-                  data_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{1}, {2}),
-                  NULL),
+                   ET,
+                   ET,
+                   idft1d_input_data_1,
+                   data_1,
+                   op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{1}, {2}),
+                   NULL),
         // idft1d_eval
         IDFTParams(Shape{2, 10, 10, 2},
                    Shape{2, 10, 10, 2},
@@ -1393,10 +1394,9 @@ std::vector<IDFTParams> generateCombinedParamsForIDFT() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_IDFT_With_Hardcoded_Refs,
-    ReferenceIDFTLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForIDFT()),
-    ReferenceIDFTLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_IDFT_With_Hardcoded_Refs,
+                         ReferenceIDFTLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForIDFT()),
+                         ReferenceIDFTLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/if.cpp b/src/plugins/template/tests/functional/op_reference/if.cpp
index 64a3b0d99a0308..81b454c01484cf 100644
--- a/src/plugins/template/tests/functional/op_reference/if.cpp
+++ b/src/plugins/template/tests/functional/op_reference/if.cpp
@@ -17,13 +17,13 @@ using namespace InferenceEngine;
 
 struct IfFunctionalBase {
     virtual std::shared_ptr<Model> create_function(const std::vector<reference_tests::Tensor>& if_inputs,
-                                                      const std::vector<reference_tests::Tensor>& results) = 0;
+                                                   const std::vector<reference_tests::Tensor>& results) = 0;
     IfFunctionalBase() {}
 };
 
 struct IfCondConst : public IfFunctionalBase {
     std::shared_ptr<Model> create_function(const std::vector<reference_tests::Tensor>& if_inputs,
-                                              const std::vector<reference_tests::Tensor>& results) override {
+                                           const std::vector<reference_tests::Tensor>& results) override {
         OPENVINO_ASSERT(if_inputs.size() == 2, "Incorrect test case! Number of inputs is not 2.");
         OPENVINO_ASSERT(results.size() == 1, "Incorrect test case! Number of outputs is not 1.");
 
@@ -55,7 +55,7 @@ struct IfCondConst : public IfFunctionalBase {
 
 struct IfCondIsNonConst : public IfFunctionalBase {
     std::shared_ptr<Model> create_function(const std::vector<reference_tests::Tensor>& if_inputs,
-                                              const std::vector<reference_tests::Tensor>& results) override {
+                                           const std::vector<reference_tests::Tensor>& results) override {
         OPENVINO_ASSERT(if_inputs.size() == 3, "Incorrect test case! Number of inputs is not 3.");
         OPENVINO_ASSERT(results.size() == 1, "Incorrect test case! Number of outputs is not 1.");
 
@@ -89,7 +89,7 @@ struct IfCondIsNonConst : public IfFunctionalBase {
 
 struct IfWithoutAdditionalInputs : IfFunctionalBase {
     std::shared_ptr<Model> create_function(const std::vector<reference_tests::Tensor>& if_inputs,
-                                              const std::vector<reference_tests::Tensor>& results) override {
+                                           const std::vector<reference_tests::Tensor>& results) override {
         OPENVINO_ASSERT(if_inputs.size() == 1, "Incorrect test case! Number of inputs is not 1.");
         OPENVINO_ASSERT(results.size() == 1, "Incorrect test case! Number of outputs is not 1.");
 
@@ -111,7 +111,7 @@ struct IfWithoutAdditionalInputs : IfFunctionalBase {
 
 struct IfDynamismCaseWithStaticInputs : public IfFunctionalBase {
     std::shared_ptr<Model> create_function(const std::vector<reference_tests::Tensor>& if_inputs,
-                                              const std::vector<reference_tests::Tensor>& results) override {
+                                           const std::vector<reference_tests::Tensor>& results) override {
         OPENVINO_ASSERT(if_inputs.size() == 4, "Incorrect test case! Number of inputs is not 4.");
         OPENVINO_ASSERT(results.size() == 2, "Incorrect test case! Number of outputs is not 2.");
 
@@ -153,7 +153,7 @@ struct IfDynamismCaseWithStaticInputs : public IfFunctionalBase {
 
 struct IfConditionIsScalar : public IfFunctionalBase {
     std::shared_ptr<Model> create_function(const std::vector<reference_tests::Tensor>& if_inputs,
-                                              const std::vector<reference_tests::Tensor>& results) override {
+                                           const std::vector<reference_tests::Tensor>& results) override {
         OPENVINO_ASSERT(if_inputs.size() == 3, "Incorrect test case! Number of inputs is not 3.");
         OPENVINO_ASSERT(results.size() == 1, "Incorrect test case! Number of outputs is not 1.");
 
@@ -189,7 +189,7 @@ struct IfConditionIsScalar : public IfFunctionalBase {
 
 struct IfConditionIsDynamic : public IfFunctionalBase {
     std::shared_ptr<Model> create_function(const std::vector<reference_tests::Tensor>& if_inputs,
-                                              const std::vector<reference_tests::Tensor>& results) override {
+                                           const std::vector<reference_tests::Tensor>& results) override {
         OPENVINO_ASSERT(if_inputs.size() == 3, "Incorrect test case! Number of inputs is not 3.");
         OPENVINO_ASSERT(results.size() == 1, "Incorrect test case! Number of outputs is not 1.");
 
@@ -318,97 +318,117 @@ INSTANTIATE_TEST_SUITE_P(
     smoke_If_With_Hardcoded_Refs,
     ReferenceIfLayerTest,
     ::testing::Values(
-        IfParams(
-            std::make_shared<IfCondConst>(true),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 1.0, 1.0, 1.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 2.0, 2.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 2.0, 2.0})},
-            "if_condition_const_is_true"),
-        IfParams(
-            std::make_shared<IfCondConst>(false),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 1.0, 1.0, 1.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 2.0, 2.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 1.0, 1.0, 1.0})},
-            "if_condition_const_is_false"),
-        IfParams(
-            std::make_shared<IfCondIsNonConst>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1}, ov::element::boolean, std::vector<unsigned char>{1}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 6.0, 12.0})},
-            "if_condition_si_non_const_true"),
-        IfParams(
-            std::make_shared<IfCondIsNonConst>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1}, ov::element::boolean, std::vector<unsigned char>{0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{3.0, 3.0, 5.0, 7.0})},
-            "if_condition_is_non_const_false"),
+        IfParams(std::make_shared<IfCondConst>(true),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 1.0, 1.0, 1.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 2.0, 2.0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 2.0, 2.0})},
+                 "if_condition_const_is_true"),
+        IfParams(std::make_shared<IfCondConst>(false),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 1.0, 1.0, 1.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 2.0, 2.0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 1.0, 1.0, 1.0})},
+                 "if_condition_const_is_false"),
+        IfParams(std::make_shared<IfCondIsNonConst>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1}, ov::element::boolean, std::vector<unsigned char>{1}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
+                 std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2},
+                                                                              ov::element::f32,
+                                                                              std::vector<float>{2.0, 2.0, 6.0, 12.0})},
+                 "if_condition_si_non_const_true"),
+        IfParams(std::make_shared<IfCondIsNonConst>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1}, ov::element::boolean, std::vector<unsigned char>{0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{3.0, 3.0, 5.0, 7.0})},
+                 "if_condition_is_non_const_false"),
         IfParams(std::make_shared<IfWithoutAdditionalInputs>(),
-                 std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1}, ov::element::boolean, std::vector<unsigned char>{1})},
-                 std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1}, ov::element::f32, std::vector<float>{8.0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1}, ov::element::boolean, std::vector<unsigned char>{1})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1}, ov::element::f32, std::vector<float>{8.0})},
                  "if_without_addition_inputs_condition_is_true"),
         IfParams(std::make_shared<IfWithoutAdditionalInputs>(),
-                 std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1}, ov::element::boolean, std::vector<unsigned char>{0})},
-                 std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1}, ov::element::f32, std::vector<float>{2.0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1}, ov::element::boolean, std::vector<unsigned char>{0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1}, ov::element::f32, std::vector<float>{2.0})},
                  "if_without_addition_inputs_condition_is_false"),
-        IfParams(
-            std::make_shared<IfConditionIsScalar>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{1}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 6.0, 12.0})},
-            "if_condition_is_scalar_cond_true"),
-        IfParams(
-            std::make_shared<IfConditionIsScalar>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{3.0, 3.0, 5.0, 7.0})},
-            "if_condition_is_scalar_cond_false"),
-        IfParams(
-            std::make_shared<IfDynamismCaseWithStaticInputs>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{1}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{4, 2, 2}, ov::element::f32, Y_gen()),
-                                reference_tests::Tensor(Shape{8, 8, 8}, ov::element::f32, Z_gen())},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 4.0, 9.0, 16.0}),
-                                reference_tests::Tensor(Shape{4, 2, 2}, ov::element::f32, Y_gen())},
-            "If_dynamism_case_with_static_inputs_condition_true"),
-        IfParams(
-            std::make_shared<IfDynamismCaseWithStaticInputs>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{4, 2, 2}, ov::element::f32, Y_gen()),
-                                reference_tests::Tensor(Shape{8, 8, 8}, ov::element::f32, Z_gen())},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 4.0, 6.0, 8.0}),
-                                reference_tests::Tensor(Shape{8, 8, 8}, ov::element::f32, Z_gen())},
-            "If_dynamism_case_with_static_inputs_condition_false"),
-        IfParams(
-            std::make_shared<IfConditionIsDynamic>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{1}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 6.0, 12.0})},
-            "if_condition_is_dynamic_cond_true"),
-        IfParams(
-            std::make_shared<IfConditionIsDynamic>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{3.0, 3.0, 5.0, 7.0})},
-            "if_condition_is_dynamic_cond_false"),
-        IfParams(
-            std::make_shared<IfDynamicInputs>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{1}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 2.0, 6.0, 12.0})},
-            "if_dynamic_inputs_cond_true"),
-        IfParams(
-            std::make_shared<IfDynamicInputs>(),
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
-                                reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
-            std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{3.0, 3.0, 5.0, 7.0})},
-            "if_dynamic_inputs_cond_false")));
+        IfParams(std::make_shared<IfConditionIsScalar>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{1}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
+                 std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2},
+                                                                              ov::element::f32,
+                                                                              std::vector<float>{2.0, 2.0, 6.0, 12.0})},
+                 "if_condition_is_scalar_cond_true"),
+        IfParams(std::make_shared<IfConditionIsScalar>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{3.0, 3.0, 5.0, 7.0})},
+                 "if_condition_is_scalar_cond_false"),
+        IfParams(std::make_shared<IfDynamismCaseWithStaticInputs>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{1}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{4, 2, 2}, ov::element::f32, Y_gen()),
+                     reference_tests::Tensor(Shape{8, 8, 8}, ov::element::f32, Z_gen())},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 4.0, 9.0, 16.0}),
+                     reference_tests::Tensor(Shape{4, 2, 2}, ov::element::f32, Y_gen())},
+                 "If_dynamism_case_with_static_inputs_condition_true"),
+        IfParams(std::make_shared<IfDynamismCaseWithStaticInputs>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{4, 2, 2}, ov::element::f32, Y_gen()),
+                     reference_tests::Tensor(Shape{8, 8, 8}, ov::element::f32, Z_gen())},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 4.0, 6.0, 8.0}),
+                     reference_tests::Tensor(Shape{8, 8, 8}, ov::element::f32, Z_gen())},
+                 "If_dynamism_case_with_static_inputs_condition_false"),
+        IfParams(std::make_shared<IfConditionIsDynamic>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{1}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
+                 std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2},
+                                                                              ov::element::f32,
+                                                                              std::vector<float>{2.0, 2.0, 6.0, 12.0})},
+                 "if_condition_is_dynamic_cond_true"),
+        IfParams(std::make_shared<IfConditionIsDynamic>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{3.0, 3.0, 5.0, 7.0})},
+                 "if_condition_is_dynamic_cond_false"),
+        IfParams(std::make_shared<IfDynamicInputs>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{1}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
+                 std::vector<reference_tests::Tensor>{reference_tests::Tensor(Shape{1, 2, 2},
+                                                                              ov::element::f32,
+                                                                              std::vector<float>{2.0, 2.0, 6.0, 12.0})},
+                 "if_dynamic_inputs_cond_true"),
+        IfParams(std::make_shared<IfDynamicInputs>(),
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{}, ov::element::boolean, std::vector<unsigned char>{0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{1.0, 2.0, 3.0, 4.0}),
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{2.0, 1.0, 2.0, 3.0})},
+                 std::vector<reference_tests::Tensor>{
+                     reference_tests::Tensor(Shape{1, 2, 2}, ov::element::f32, std::vector<float>{3.0, 3.0, 5.0, 7.0})},
+                 "if_dynamic_inputs_cond_false")));
diff --git a/src/plugins/template/tests/functional/op_reference/irdft.cpp b/src/plugins/template/tests/functional/op_reference/irdft.cpp
index 006deb031aca9b..e10224b785ec56 100644
--- a/src/plugins/template/tests/functional/op_reference/irdft.cpp
+++ b/src/plugins/template/tests/functional/op_reference/irdft.cpp
@@ -2,12 +2,14 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/irdft.hpp"
+
 #include <gtest/gtest.h>
+
 #include <iostream>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/irdft.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -91,439 +93,371 @@ TEST_P(ReferenceIRDFTLayerTest, CompareWithHardcodedRefs) {
 }
 
 static const std::vector<float> input_data_1 = {
-    4.6657147,   -1.1622906e-06, 0.21456887,    -0.14946258, -0.20476034,  -0.37063062,
-    -0.31414136, 0.5099413,      -1.1779613,    0.07057127,  -0.64047664,  -1.0058284e-07,
-    4.982774,    -1.1771917e-06, 0.6607505,     0.18829148,  -0.9772357,   1.4243596,
-    0.8640026,   0.34923682,     0.33401352,    0.25859502,  -0.7548928,   8.940697e-08,
-    5.9711604,   -1.4901161e-06, 0.5638976,     1.5429841,   -0.52065414,  0.24638398,
-    -0.27140495, 0.5040715,      0.5360231,     0.3234269,   -0.36054826,  1.7508864e-07,
-    4.7464237,   -1.2218952e-06, -0.29650804,   0.80609477,  -0.161426,    1.0022418,
-    -0.50812817, 0.7967348,      0.4394225,     -0.1588624,  -1.3835809,   -7.4505806e-08,
-    5.53836,     -1.7136335e-06, -0.38635445,   0.8284859,   -0.23278837,  -0.63777345,
-    -0.93614054, 0.3215857,      -0.14075133,   -0.67071164, -1.4772836,   2.0861626e-07,
-    5.0798974,   -1.5944242e-06, 0.056767445,   0.03468219,  -0.1497254,   -0.9672509,
-    0.2603209,   0.69644475,     -0.9208536,    0.006730467, -1.7552528,   2.682209e-07,
-    4.893558,    -1.6242266e-06, 0.6719861,     -0.13982919, 0.064845346,  -0.39896214,
-    0.21785057,  -0.5099982,     -0.65526295,   1.4383471,   -0.52023906,  2.5331974e-07,
-    6.687699,    -1.5497208e-06, -0.7423769,    0.09968524,  1.052381,     -0.21306956,
-    0.5875206,   -0.3038844,     0.3991575,     -1.1895186,  0.17579001,   3.874302e-07,
-    5.2818384,   -1.1026859e-06, 0.5087582,     0.106959194, 1.1816688,    -0.87592727,
-    0.03740315,  0.5197907,      -1.3198637,    0.6398836,   0.22712436,   2.2351742e-08,
-    5.0190897,   -1.5646219e-06, -0.087282926,  0.50819266,  -0.28002462,  0.29240948,
-    -0.32303664, 0.38377762,     -0.0051696897, -0.99301195, -2.189299,    2.0861626e-07,
-    5.0545654,   -1.5795231e-06, 0.9146397,     0.83839166,  0.870533,     0.17405808,
-    -0.56308234, -0.7806684,     0.26397777,    0.6880482,   -1.4183462,   2.682209e-07,
-    5.479953,    -1.2665987e-06, 0.49444157,    0.7534672,   -0.76784146,  -0.4507342,
-    0.88815784,  0.6985409,      -0.2727425,    -0.25027415, -0.7328796,   2.682209e-07,
-    4.1296124,   -5.662441e-07,  -0.46133032,   0.30635798,  -0.18225375,  0.42515472,
-    -0.5484285,  0.9704039,      -0.35255045,   0.17549685,  0.8870368,    -3.1292439e-07,
-    4.8632016,   -1.8924475e-06, -0.6926452,    0.025076404, -0.039108217, -1.7492937,
-    -0.8120377,  -0.85315156,    -0.0022608787, 0.45002514,  -1.1024668,   3.501773e-07,
-    5.4715447,   -1.4901161e-06, 1.1176248,     -0.2109062,  -0.27492502,  0.08983741,
-    1.1903813,   -1.007312,      -0.20150042,   -0.83919466, -0.23939973,  4.917383e-07,
-    5.1267176,   -9.983778e-07,  -0.44803134,   -0.8066604,  -0.3435102,   -0.41692197,
-    -0.22457689, -0.1076939,     -0.29129186,   -1.1880502,  0.9255183,    -1.6391277e-07,
-    3.8495903,   -5.5134296e-07, 0.09505272,    -0.12751618, -1.1264827,   0.5068884,
-    -1.055237,   -0.19516481,    -0.34035242,   -0.15379356, 1.2655814,    -2.6077032e-07,
-    4.4372616,   -9.23872e-07,   -0.72962606,   -0.23475963, -0.04278487,  1.1032158,
-    -0.558924,   -0.5300043,     1.0578637,     -0.2466627,  0.44617313,   -7.8231096e-08,
-    5.5374002,   -1.4156103e-06, 0.016273111,   -0.5989829,  -0.19913958,  0.013256833,
-    1.8512837,   0.14526272,     -0.39700353,   -0.07573915, 0.23181,      2.9429793e-07,
-    4.989425,    -1.4901161e-06, 1.0391837,     0.16554561,  -0.22647032,  -1.0689808,
-    -0.84556,    -0.82779336,    0.9430445,     0.37618563,  0.4684292,    -9.685755e-08};
+    4.6657147,      -1.1622906e-06, 0.21456887,     -0.14946258,    -0.20476034,    -0.37063062,    -0.31414136,
+    0.5099413,      -1.1779613,     0.07057127,     -0.64047664,    -1.0058284e-07, 4.982774,       -1.1771917e-06,
+    0.6607505,      0.18829148,     -0.9772357,     1.4243596,      0.8640026,      0.34923682,     0.33401352,
+    0.25859502,     -0.7548928,     8.940697e-08,   5.9711604,      -1.4901161e-06, 0.5638976,      1.5429841,
+    -0.52065414,    0.24638398,     -0.27140495,    0.5040715,      0.5360231,      0.3234269,      -0.36054826,
+    1.7508864e-07,  4.7464237,      -1.2218952e-06, -0.29650804,    0.80609477,     -0.161426,      1.0022418,
+    -0.50812817,    0.7967348,      0.4394225,      -0.1588624,     -1.3835809,     -7.4505806e-08, 5.53836,
+    -1.7136335e-06, -0.38635445,    0.8284859,      -0.23278837,    -0.63777345,    -0.93614054,    0.3215857,
+    -0.14075133,    -0.67071164,    -1.4772836,     2.0861626e-07,  5.0798974,      -1.5944242e-06, 0.056767445,
+    0.03468219,     -0.1497254,     -0.9672509,     0.2603209,      0.69644475,     -0.9208536,     0.006730467,
+    -1.7552528,     2.682209e-07,   4.893558,       -1.6242266e-06, 0.6719861,      -0.13982919,    0.064845346,
+    -0.39896214,    0.21785057,     -0.5099982,     -0.65526295,    1.4383471,      -0.52023906,    2.5331974e-07,
+    6.687699,       -1.5497208e-06, -0.7423769,     0.09968524,     1.052381,       -0.21306956,    0.5875206,
+    -0.3038844,     0.3991575,      -1.1895186,     0.17579001,     3.874302e-07,   5.2818384,      -1.1026859e-06,
+    0.5087582,      0.106959194,    1.1816688,      -0.87592727,    0.03740315,     0.5197907,      -1.3198637,
+    0.6398836,      0.22712436,     2.2351742e-08,  5.0190897,      -1.5646219e-06, -0.087282926,   0.50819266,
+    -0.28002462,    0.29240948,     -0.32303664,    0.38377762,     -0.0051696897,  -0.99301195,    -2.189299,
+    2.0861626e-07,  5.0545654,      -1.5795231e-06, 0.9146397,      0.83839166,     0.870533,       0.17405808,
+    -0.56308234,    -0.7806684,     0.26397777,     0.6880482,      -1.4183462,     2.682209e-07,   5.479953,
+    -1.2665987e-06, 0.49444157,     0.7534672,      -0.76784146,    -0.4507342,     0.88815784,     0.6985409,
+    -0.2727425,     -0.25027415,    -0.7328796,     2.682209e-07,   4.1296124,      -5.662441e-07,  -0.46133032,
+    0.30635798,     -0.18225375,    0.42515472,     -0.5484285,     0.9704039,      -0.35255045,    0.17549685,
+    0.8870368,      -3.1292439e-07, 4.8632016,      -1.8924475e-06, -0.6926452,     0.025076404,    -0.039108217,
+    -1.7492937,     -0.8120377,     -0.85315156,    -0.0022608787,  0.45002514,     -1.1024668,     3.501773e-07,
+    5.4715447,      -1.4901161e-06, 1.1176248,      -0.2109062,     -0.27492502,    0.08983741,     1.1903813,
+    -1.007312,      -0.20150042,    -0.83919466,    -0.23939973,    4.917383e-07,   5.1267176,      -9.983778e-07,
+    -0.44803134,    -0.8066604,     -0.3435102,     -0.41692197,    -0.22457689,    -0.1076939,     -0.29129186,
+    -1.1880502,     0.9255183,      -1.6391277e-07, 3.8495903,      -5.5134296e-07, 0.09505272,     -0.12751618,
+    -1.1264827,     0.5068884,      -1.055237,      -0.19516481,    -0.34035242,    -0.15379356,    1.2655814,
+    -2.6077032e-07, 4.4372616,      -9.23872e-07,   -0.72962606,    -0.23475963,    -0.04278487,    1.1032158,
+    -0.558924,      -0.5300043,     1.0578637,      -0.2466627,     0.44617313,     -7.8231096e-08, 5.5374002,
+    -1.4156103e-06, 0.016273111,    -0.5989829,     -0.19913958,    0.013256833,    1.8512837,      0.14526272,
+    -0.39700353,    -0.07573915,    0.23181,        2.9429793e-07,  4.989425,       -1.4901161e-06, 1.0391837,
+    0.16554561,     -0.22647032,    -1.0689808,     -0.84556,       -0.82779336,    0.9430445,      0.37618563,
+    0.4684292,      -9.685755e-08};
 
 static const std::vector<float> expected_irdft1d_results_1 = {
-    0.10606491,  0.7454715,   0.57231355,  0.4582412,   0.3847059,   0.27398932, 0.66796243, 0.395475,
-    0.2815729,   0.7799197,   0.59909415,  0.12294636,  0.38957402,  0.97498834, 0.46759892, 0.14017141,
-    0.04206858,  0.7279963,   0.61560553,  0.9027321,   0.6226334,   0.2601217,  0.5555177,  0.40498647,
-    0.14175586,  0.57774633,  0.52652127,  0.9385691,   0.9588788,   0.9844318,  0.23095612, 0.09707925,
-    0.24574867,  0.6907577,   0.1974319,   0.8295272,   0.34612727,  0.51401484, 0.66115797, 0.9336245,
-    0.06690067,  0.7468897,   0.39028263,  0.53575844,  0.060429193, 0.8913558,  0.77787375, 0.6701197,
-    0.7350527,   0.6636995,   0.18176624,  0.8629976,   0.45142895,  0.6497297,  0.159372,   0.40598175,
-    0.7988516,   0.7291543,   0.07090418,  0.7697132,   0.4972157,   0.7669217,  0.67975855, 0.13026066,
-    0.6587437,   0.24532892,  0.24545169,  0.83795583,  0.105490535, 0.7264323,  0.94568557, 0.7216649,
-    0.14389831,  0.7930531,   0.70895344,  0.9724701,   0.9775157,   0.49999878, 0.65569246, 0.26876843,
-    0.63248956,  0.85201293,  0.5689624,   0.023386303, 0.5546464,   0.36860028, 0.9603114,  0.39123482,
-    0.0380728,   0.89212376,  0.14387614,  0.63858676,  0.10003748,  0.8906635,  0.06681054, 0.7458642,
-    0.45452347,  0.54724604,  0.6496482,   0.7818356,   0.6608355,   0.77711326, 0.24588613, 0.013456763,
-    0.355845,    0.80388206,  0.027993264, 0.73677206,  0.52755004,  0.9052324,  0.54311025, 0.5367805,
-    0.4131242,   0.7752338,   0.109669454, 0.13664648,  0.7828739,   0.9083969,  0.5247593,  0.7493595,
-    0.19275227,  0.007190853, 0.6087981,   0.344136,    0.46909887,  0.41924855, 0.7072913,  0.19932869,
-    0.5303847,   0.651384,    0.06686331,  0.9717932,   0.65702224,  0.11786682, 0.3154073,  0.88923013,
-    0.5564087,   0.91047823,  0.28466642,  0.0934668,   0.88953066,  0.9919338,  0.18322521, 0.8185455,
-    0.566391,    0.014207997, 0.29673064,  0.6347744,   0.6801958,   0.39601147, 0.34374171, 0.7216888,
-    0.6152569,   0.76679546,  0.5860851,   0.4276813,   0.79339284,  0.13130653, 0.68764234, 0.053128112,
-    0.02611321,  0.2982243,   0.7618372,   0.3331729,   0.5468192,   0.15707079, 0.28592056, 0.15286565,
-    0.9368963,   0.350671,    0.4336494,   0.08934934,  0.41172776,  0.5850259,  0.70730376, 0.8598349,
-    0.088788144, 0.26711187,  0.8002491,   0.19422275,  0.8312039,   0.5198718,  0.40111357, 0.98375803,
-    0.77703434,  0.037818834, 0.704231,    0.689808,    0.17102319,  0.42153922, 0.7278252,  0.8030207,
-    0.9101717,   0.0199644,   0.13768466,  0.55669,     0.17991355,  0.6720098,  0.7733328,  0.20881335};
-
-static const std::vector<float> input_data_2 = {
-    2.266797,  -8.195639e-08,  -0.37842733,  -0.41015846,  -0.48980892,  -0.10356337,
-    2.5542018, -2.2351742e-08, -0.3223713,   0.671882,     0.54300576,   -0.35418037,
-    1.985015,  -2.2351742e-08, -0.030243821, -0.20105253,  0.59431964,   0.07358998,
-    1.4619737, -7.450581e-09,  -0.4356845,   0.35701087,   0.28208786,   -0.36424285,
-    1.8002605, -1.1920929e-07, -0.43280697,  -0.56735414,  -0.30007166,  -0.541847,
-    2.3052943, -1.2293458e-07, -0.39316025,  -0.5526293,   -0.30507135,  -0.6021758,
-    2.7329001, -6.7055225e-08, 0.28245124,   -0.42586988,  -0.40586215,  0.4590181,
-    3.3132548, -5.9604645e-08, 0.6297612,    0.3694744,    0.077824846,  -0.6248544,
-    2.6314974, -2.9802322e-08, 0.58795106,   -0.60349375,  -0.3224758,   0.34408605,
-    1.8399743, -9.685755e-08,  -0.43963802,  -0.079073176, -0.120658875, -1.0880115,
-    2.0531366, -4.4703484e-08, 0.80112594,   -0.53726834,  -0.17560546,  -0.026561722,
-    2.3779182, -9.685755e-08,  -0.21852754,  -0.19336401,  0.38734403,   -0.5954362,
-    1.6219761, 7.450581e-09,   -0.43100592,  0.28373614,   0.101898566,  0.52321124,
-    2.128953,  -1.4901161e-07, -0.1622684,   -0.94116735,  -0.7350497,   0.12695336,
-    3.449626,  -8.940697e-08,  0.56062996,   -0.031283244, -0.06161648,  -0.8543532,
-    3.033568,  -8.195639e-08,  -0.37023768,  -0.03989461,  -0.28719214,  -0.22382751,
-    1.9661667, -1.4901161e-08, -0.59863573,  -0.015534669, -0.31916466,  0.55380434,
-    2.227056,  -5.2154064e-08, -0.12656188,  0.6895717,    0.097157195,  0.19840825,
-    3.5129817, -2.1234155e-07, 0.11158541,   0.5870459,    0.20993343,   -0.40297145,
-    2.5986667, 0.0,            0.26602313,   -1.1560227,   0.2542065,    0.45556274};
+    0.10606491, 0.7454715,   0.57231355,  0.4582412,  0.3847059,   0.27398932,  0.66796243,  0.395475,    0.2815729,
+    0.7799197,  0.59909415,  0.12294636,  0.38957402, 0.97498834,  0.46759892,  0.14017141,  0.04206858,  0.7279963,
+    0.61560553, 0.9027321,   0.6226334,   0.2601217,  0.5555177,   0.40498647,  0.14175586,  0.57774633,  0.52652127,
+    0.9385691,  0.9588788,   0.9844318,   0.23095612, 0.09707925,  0.24574867,  0.6907577,   0.1974319,   0.8295272,
+    0.34612727, 0.51401484,  0.66115797,  0.9336245,  0.06690067,  0.7468897,   0.39028263,  0.53575844,  0.060429193,
+    0.8913558,  0.77787375,  0.6701197,   0.7350527,  0.6636995,   0.18176624,  0.8629976,   0.45142895,  0.6497297,
+    0.159372,   0.40598175,  0.7988516,   0.7291543,  0.07090418,  0.7697132,   0.4972157,   0.7669217,   0.67975855,
+    0.13026066, 0.6587437,   0.24532892,  0.24545169, 0.83795583,  0.105490535, 0.7264323,   0.94568557,  0.7216649,
+    0.14389831, 0.7930531,   0.70895344,  0.9724701,  0.9775157,   0.49999878,  0.65569246,  0.26876843,  0.63248956,
+    0.85201293, 0.5689624,   0.023386303, 0.5546464,  0.36860028,  0.9603114,   0.39123482,  0.0380728,   0.89212376,
+    0.14387614, 0.63858676,  0.10003748,  0.8906635,  0.06681054,  0.7458642,   0.45452347,  0.54724604,  0.6496482,
+    0.7818356,  0.6608355,   0.77711326,  0.24588613, 0.013456763, 0.355845,    0.80388206,  0.027993264, 0.73677206,
+    0.52755004, 0.9052324,   0.54311025,  0.5367805,  0.4131242,   0.7752338,   0.109669454, 0.13664648,  0.7828739,
+    0.9083969,  0.5247593,   0.7493595,   0.19275227, 0.007190853, 0.6087981,   0.344136,    0.46909887,  0.41924855,
+    0.7072913,  0.19932869,  0.5303847,   0.651384,   0.06686331,  0.9717932,   0.65702224,  0.11786682,  0.3154073,
+    0.88923013, 0.5564087,   0.91047823,  0.28466642, 0.0934668,   0.88953066,  0.9919338,   0.18322521,  0.8185455,
+    0.566391,   0.014207997, 0.29673064,  0.6347744,  0.6801958,   0.39601147,  0.34374171,  0.7216888,   0.6152569,
+    0.76679546, 0.5860851,   0.4276813,   0.79339284, 0.13130653,  0.68764234,  0.053128112, 0.02611321,  0.2982243,
+    0.7618372,  0.3331729,   0.5468192,   0.15707079, 0.28592056,  0.15286565,  0.9368963,   0.350671,    0.4336494,
+    0.08934934, 0.41172776,  0.5850259,   0.70730376, 0.8598349,   0.088788144, 0.26711187,  0.8002491,   0.19422275,
+    0.8312039,  0.5198718,   0.40111357,  0.98375803, 0.77703434,  0.037818834, 0.704231,    0.689808,    0.17102319,
+    0.42153922, 0.7278252,   0.8030207,   0.9101717,  0.0199644,   0.13768466,  0.55669,     0.17991355,  0.6720098,
+    0.7733328,  0.20881335};
+
+static const std::vector<float> input_data_2 = {2.266797,    -8.195639e-08,  -0.37842733,  -0.41015846,
+                                                -0.48980892, -0.10356337,    2.5542018,    -2.2351742e-08,
+                                                -0.3223713,  0.671882,       0.54300576,   -0.35418037,
+                                                1.985015,    -2.2351742e-08, -0.030243821, -0.20105253,
+                                                0.59431964,  0.07358998,     1.4619737,    -7.450581e-09,
+                                                -0.4356845,  0.35701087,     0.28208786,   -0.36424285,
+                                                1.8002605,   -1.1920929e-07, -0.43280697,  -0.56735414,
+                                                -0.30007166, -0.541847,      2.3052943,    -1.2293458e-07,
+                                                -0.39316025, -0.5526293,     -0.30507135,  -0.6021758,
+                                                2.7329001,   -6.7055225e-08, 0.28245124,   -0.42586988,
+                                                -0.40586215, 0.4590181,      3.3132548,    -5.9604645e-08,
+                                                0.6297612,   0.3694744,      0.077824846,  -0.6248544,
+                                                2.6314974,   -2.9802322e-08, 0.58795106,   -0.60349375,
+                                                -0.3224758,  0.34408605,     1.8399743,    -9.685755e-08,
+                                                -0.43963802, -0.079073176,   -0.120658875, -1.0880115,
+                                                2.0531366,   -4.4703484e-08, 0.80112594,   -0.53726834,
+                                                -0.17560546, -0.026561722,   2.3779182,    -9.685755e-08,
+                                                -0.21852754, -0.19336401,    0.38734403,   -0.5954362,
+                                                1.6219761,   7.450581e-09,   -0.43100592,  0.28373614,
+                                                0.101898566, 0.52321124,     2.128953,     -1.4901161e-07,
+                                                -0.1622684,  -0.94116735,    -0.7350497,   0.12695336,
+                                                3.449626,    -8.940697e-08,  0.56062996,   -0.031283244,
+                                                -0.06161648, -0.8543532,     3.033568,     -8.195639e-08,
+                                                -0.37023768, -0.03989461,    -0.28719214,  -0.22382751,
+                                                1.9661667,   -1.4901161e-08, -0.59863573,  -0.015534669,
+                                                -0.31916466, 0.55380434,     2.227056,     -5.2154064e-08,
+                                                -0.12656188, 0.6895717,      0.097157195,  0.19840825,
+                                                3.5129817,   -2.1234155e-07, 0.11158541,   0.5870459,
+                                                0.20993343,  -0.40297145,    2.5986667,    0.0,
+                                                0.26602313,  -1.1560227,     0.2542065,    0.45556274};
 
 static const std::vector<float> expected_irdft1d_results_2 = {
-    0.10606494, 0.7454715,   0.5723136,   0.45824113,  0.38470596,  0.59909415,  0.12294642,
-    0.38957405, 0.9749881,   0.46759906,  0.62263334,  0.26012173,  0.5555176,   0.40498644,
-    0.14175594, 0.23095612,  0.097079255, 0.24574867,  0.6907576,   0.197432,    0.066900685,
-    0.7468896,  0.39028254,  0.5357583,   0.0604293,   0.18176621,  0.8629975,   0.45142898,
-    0.64972955, 0.15937212,  0.49721566,  0.7669216,   0.6797584,   0.13026062,  0.6587438,
-    0.9456854,  0.7216646,   0.14389832,  0.7930529,   0.7089534,   0.6324895,   0.85201263,
-    0.5689623,  0.023386315, 0.55464643,  0.1438762,   0.63858664,  0.10003753,  0.8906633,
-    0.06681056, 0.66083544,  0.7771131,   0.24588616,  0.013456774, 0.35584506,  0.54311025,
-    0.53678054, 0.41312417,  0.7752337,   0.10966951,  0.19275223,  0.007190934, 0.608798,
-    0.344136,   0.46909887,  0.06686333,  0.971793,    0.65702224,  0.117866985, 0.31540743,
-    0.8895306,  0.99193364,  0.18322523,  0.81854534,  0.5663911,   0.34374166,  0.72168875,
-    0.6152569,  0.7667953,   0.58608514,  0.026113158, 0.2982243,   0.76183707,  0.3331729,
-    0.5468192,  0.43364936,  0.089349344, 0.41172776,  0.5850257,   0.7073037,   0.8312039,
-    0.5198719,  0.4011136,   0.9837578,   0.7770344,   0.72782516,  0.8030205,   0.9101716,
-    0.019964492, 0.13768478};
+    0.10606494, 0.7454715,  0.5723136,   0.45824113, 0.38470596, 0.59909415,  0.12294642, 0.38957405,  0.9749881,
+    0.46759906, 0.62263334, 0.26012173,  0.5555176,  0.40498644, 0.14175594,  0.23095612, 0.097079255, 0.24574867,
+    0.6907576,  0.197432,   0.066900685, 0.7468896,  0.39028254, 0.5357583,   0.0604293,  0.18176621,  0.8629975,
+    0.45142898, 0.64972955, 0.15937212,  0.49721566, 0.7669216,  0.6797584,   0.13026062, 0.6587438,   0.9456854,
+    0.7216646,  0.14389832, 0.7930529,   0.7089534,  0.6324895,  0.85201263,  0.5689623,  0.023386315, 0.55464643,
+    0.1438762,  0.63858664, 0.10003753,  0.8906633,  0.06681056, 0.66083544,  0.7771131,  0.24588616,  0.013456774,
+    0.35584506, 0.54311025, 0.53678054,  0.41312417, 0.7752337,  0.10966951,  0.19275223, 0.007190934, 0.608798,
+    0.344136,   0.46909887, 0.06686333,  0.971793,   0.65702224, 0.117866985, 0.31540743, 0.8895306,   0.99193364,
+    0.18322523, 0.81854534, 0.5663911,   0.34374166, 0.72168875, 0.6152569,   0.7667953,  0.58608514,  0.026113158,
+    0.2982243,  0.76183707, 0.3331729,   0.5468192,  0.43364936, 0.089349344, 0.41172776, 0.5850257,   0.7073037,
+    0.8312039,  0.5198719,  0.4011136,   0.9837578,  0.7770344,  0.72782516,  0.8030205,  0.9101716,   0.019964492,
+    0.13768478};
 
 static const std::vector<float> input_data_3 = {
-    4.665715,    -1.6093254e-06, -0.5430559,   -0.5752678,     -0.37596112,  -1.1571281,
-    -0.46793216, -0.94566363,    0.6854232,    -0.3444838,     -0.674704,    0.5946392,
-    -0.64047587, 1.3560057e-06,  4.9827743,    -1.7434359e-06, -0.43517,     -0.049020194,
-    -1.4773891,  -1.0811031,     1.2506557,    0.5371344,      1.2869358,    -0.14998645,
-    0.8555907,   0.3693859,      -0.7548918,   1.5944242e-06,  5.971161,     -1.5199184e-06,
-    -1.2643411,  0.85635287,     -0.1801207,   -1.7264944,     0.6412285,    -0.4787441,
-    0.82227707,  0.65098876,     0.9114491,    0.40323836,     -0.36054718,  1.2852252e-06,
-    4.7464237,   -1.66893e-06,   -1.5010594,   0.2253451,      -0.87915635,  -0.4252541,
-    0.4976693,   -0.6554581,     0.928985,     0.8035921,      0.6578763,    -0.15220329,
-    -1.3835799,  1.0430813e-06,  5.5383606,    -1.4901161e-06, -1.619024,    -0.10987502,
-    0.20661727,  -1.3774645,     -0.3057741,   -1.0960662,     0.2971667,    0.46700704,
-    -0.20812088, -0.602368,      -1.4772825,   9.3877316e-07,  5.0798974,    -1.758337e-06,
-    -0.7421876,  -0.61749315,    0.21938956,   -1.3415859,     -0.838238,    -0.6598083,
-    1.0601404,   -0.7129184,     -0.27083004,  0.31763482,     -1.7552516,   1.4677644e-06,
-    4.893558,    -1.4975667e-06, -0.06445231,  -0.55879503,    0.08908144,   -1.2869594,
-    0.33623943,  -0.7704663,     -0.047739983, -1.0678453,     0.48350462,   1.5768427,
-    -0.52023804, 1.1697412e-06,  6.687699,     -1.3113022e-06, -1.292419,    -1.2920969,
-    1.2041754,   -0.2943018,     1.1889167,    -0.66985166,    1.1336832,    -0.13731277,
-    0.008011267, -0.9506076,     0.1757915,    1.1026859e-06,  5.2818394,    -1.4305115e-06,
-    -0.25987166, -0.48605326,    0.90237427,   -0.8028362,     -0.3040653,   -1.6981151,
-    1.1215456,   -0.7120959,     -0.4195284,   1.3941492,      0.22712523,   8.046627e-07,
-    5.01909,     -1.7881393e-06, -1.1856917,   -0.10931289,    -0.5164983,   -0.9724103,
-    0.30577338,  -0.72837675,    0.89680094,   0.21036407,     -0.052024096, -0.9455472,
-    -2.1892984,  1.4305115e-06,  5.054565,     -1.5050173e-06, -0.3471575,   0.40542153,
-    0.36438322,  -0.9765247,     1.2703501,    -1.7359983,     -0.1160066,   -0.25323528,
-    0.9753329,   0.5339062,      -1.418345,    9.834766e-07,   5.4799523,    -1.7285347e-06,
-    -0.7905842,  0.093313254,    0.068526804,  -1.8504739,     -0.01845923,  0.26084417,
-    1.5358877,   -0.4159652,     0.089752786,  0.089908056,    -0.7328786,   1.4007092e-06,
-    4.129612,    -9.536743e-07,  -1.2393575,   -0.28046644,    -0.58673245,  -0.39608067,
-    -0.12385368, -0.53435826,    0.77853805,   0.7645384,      -0.18040559,  0.6678516,
-    0.88703763,  8.046627e-07,   4.8632016,    -1.0430813e-06, -1.1780663,   -1.0952923,
-    1.1691413,   -1.4023741,     -0.546494,    -0.92614484,    -1.1796933,   -0.31762218,
-    0.25592417,  0.0959474,      -1.1024656,   1.013279e-06,   5.471545,     -1.6987324e-06,
-    0.35812324,  -0.66833705,    0.07725692,   -1.6537004,     1.6561611,    0.051166296,
-    0.865453,    -1.1392289,     -0.23588535,  -0.5480979,     -0.2393986,   1.3411045e-06,
-    5.126718,    -9.23872e-07,   -0.6379836,   -1.6675751,     0.013057679,  -0.9891113,
-    0.20881936,  -0.30439606,    0.37222707,   0.25244698,     -0.9197892,   -0.77782196,
-    0.9255192,   1.1101365e-06,  3.8495903,    -7.4505806e-07, -0.63088936,  -0.4556699,
-    -1.1905057,  -1.2522144,     0.46207082,   -0.31992733,    -0.4309795,   0.74295896,
-    -0.6106033,  0.18823686,     1.2655822,    7.748604e-07,   4.4372616,    -7.0780516e-07,
-    -1.1016369,  -1.0079124,     -0.6083025,   -0.0011255145,  1.4406854,    -0.2912693,
-    -0.26610214, 0.87299407,     0.69553405,   -0.45576566,    0.44617438,   7.4505806e-07,
-    5.5374007,   -1.5944242e-06, -0.32642078,  -1.3683549,     0.079301864,  -0.83741367,
-    0.67391664,  0.69433576,     1.6423957,    -1.1923066,     0.0334223,    0.37603495,
-    0.23181117,  1.4156103e-06,  4.9894247,    -7.748604e-07,  0.1788401,    -0.39274544,
-    0.78422666,  -2.1340246,     0.5487572,    -0.8765497,     -0.7899384,   0.5434137,
-    0.91613716,  0.08274247,     0.46843058,   8.34465e-07};
+    4.665715,    -1.6093254e-06, -0.5430559,  -0.5752678,   -0.37596112, -1.1571281,    -0.46793216,
+    -0.94566363, 0.6854232,      -0.3444838,  -0.674704,    0.5946392,   -0.64047587,   1.3560057e-06,
+    4.9827743,   -1.7434359e-06, -0.43517,    -0.049020194, -1.4773891,  -1.0811031,    1.2506557,
+    0.5371344,   1.2869358,      -0.14998645, 0.8555907,    0.3693859,   -0.7548918,    1.5944242e-06,
+    5.971161,    -1.5199184e-06, -1.2643411,  0.85635287,   -0.1801207,  -1.7264944,    0.6412285,
+    -0.4787441,  0.82227707,     0.65098876,  0.9114491,    0.40323836,  -0.36054718,   1.2852252e-06,
+    4.7464237,   -1.66893e-06,   -1.5010594,  0.2253451,    -0.87915635, -0.4252541,    0.4976693,
+    -0.6554581,  0.928985,       0.8035921,   0.6578763,    -0.15220329, -1.3835799,    1.0430813e-06,
+    5.5383606,   -1.4901161e-06, -1.619024,   -0.10987502,  0.20661727,  -1.3774645,    -0.3057741,
+    -1.0960662,  0.2971667,      0.46700704,  -0.20812088,  -0.602368,   -1.4772825,    9.3877316e-07,
+    5.0798974,   -1.758337e-06,  -0.7421876,  -0.61749315,  0.21938956,  -1.3415859,    -0.838238,
+    -0.6598083,  1.0601404,      -0.7129184,  -0.27083004,  0.31763482,  -1.7552516,    1.4677644e-06,
+    4.893558,    -1.4975667e-06, -0.06445231, -0.55879503,  0.08908144,  -1.2869594,    0.33623943,
+    -0.7704663,  -0.047739983,   -1.0678453,  0.48350462,   1.5768427,   -0.52023804,   1.1697412e-06,
+    6.687699,    -1.3113022e-06, -1.292419,   -1.2920969,   1.2041754,   -0.2943018,    1.1889167,
+    -0.66985166, 1.1336832,      -0.13731277, 0.008011267,  -0.9506076,  0.1757915,     1.1026859e-06,
+    5.2818394,   -1.4305115e-06, -0.25987166, -0.48605326,  0.90237427,  -0.8028362,    -0.3040653,
+    -1.6981151,  1.1215456,      -0.7120959,  -0.4195284,   1.3941492,   0.22712523,    8.046627e-07,
+    5.01909,     -1.7881393e-06, -1.1856917,  -0.10931289,  -0.5164983,  -0.9724103,    0.30577338,
+    -0.72837675, 0.89680094,     0.21036407,  -0.052024096, -0.9455472,  -2.1892984,    1.4305115e-06,
+    5.054565,    -1.5050173e-06, -0.3471575,  0.40542153,   0.36438322,  -0.9765247,    1.2703501,
+    -1.7359983,  -0.1160066,     -0.25323528, 0.9753329,    0.5339062,   -1.418345,     9.834766e-07,
+    5.4799523,   -1.7285347e-06, -0.7905842,  0.093313254,  0.068526804, -1.8504739,    -0.01845923,
+    0.26084417,  1.5358877,      -0.4159652,  0.089752786,  0.089908056, -0.7328786,    1.4007092e-06,
+    4.129612,    -9.536743e-07,  -1.2393575,  -0.28046644,  -0.58673245, -0.39608067,   -0.12385368,
+    -0.53435826, 0.77853805,     0.7645384,   -0.18040559,  0.6678516,   0.88703763,    8.046627e-07,
+    4.8632016,   -1.0430813e-06, -1.1780663,  -1.0952923,   1.1691413,   -1.4023741,    -0.546494,
+    -0.92614484, -1.1796933,     -0.31762218, 0.25592417,   0.0959474,   -1.1024656,    1.013279e-06,
+    5.471545,    -1.6987324e-06, 0.35812324,  -0.66833705,  0.07725692,  -1.6537004,    1.6561611,
+    0.051166296, 0.865453,       -1.1392289,  -0.23588535,  -0.5480979,  -0.2393986,    1.3411045e-06,
+    5.126718,    -9.23872e-07,   -0.6379836,  -1.6675751,   0.013057679, -0.9891113,    0.20881936,
+    -0.30439606, 0.37222707,     0.25244698,  -0.9197892,   -0.77782196, 0.9255192,     1.1101365e-06,
+    3.8495903,   -7.4505806e-07, -0.63088936, -0.4556699,   -1.1905057,  -1.2522144,    0.46207082,
+    -0.31992733, -0.4309795,     0.74295896,  -0.6106033,   0.18823686,  1.2655822,     7.748604e-07,
+    4.4372616,   -7.0780516e-07, -1.1016369,  -1.0079124,   -0.6083025,  -0.0011255145, 1.4406854,
+    -0.2912693,  -0.26610214,    0.87299407,  0.69553405,   -0.45576566, 0.44617438,    7.4505806e-07,
+    5.5374007,   -1.5944242e-06, -0.32642078, -1.3683549,   0.079301864, -0.83741367,   0.67391664,
+    0.69433576,  1.6423957,      -1.1923066,  0.0334223,    0.37603495,  0.23181117,    1.4156103e-06,
+    4.9894247,   -7.748604e-07,  0.1788401,   -0.39274544,  0.78422666,  -2.1340246,    0.5487572,
+    -0.8765497,  -0.7899384,     0.5434137,   0.91613716,   0.08274247,  0.46843058,    8.34465e-07};
 
 static const std::vector<float> expected_irdft1d_results_3 = {
-    0.80091053, 1.548053,   1.3439665,  0.97278523, 0.65876126, 1.6395509,  1.0939313,
-    1.5905306,  0.81558955, 1.1096439,  2.0799308,  1.9659967,  0.21628714, 1.2937224,
-    1.7173465,  1.5190675,  0.62673247, 1.3878733,  2.2457566,  1.2779983,  0.9537279,
-    1.5238736,  1.6959155,  0.9063804,  1.2134336,  1.4805167,  1.277886,   0.9217217,
-    1.3267591,  2.0169291,  2.619178,   0.7248324,  1.4161175,  1.3378929,  1.6759893,
-    0.85183966, 0.53280216, 1.4385536,  1.7184939,  1.3292406,  1.1811583,  0.9698347,
-    1.5283158,  1.3752562,  0.99182767, 1.3061998,  1.7824118,  1.399513,   0.26604116,
-    1.3193192,  1.5053986,  1.0388529,  0.9190526,  1.4711612,  2.0971189,  0.37586892,
-    1.5662622,  1.6827406,  1.208139,   1.0144035,  0.96595216, 2.1122026,  1.6039357,
-    0.44462752, 0.34932646, 1.487859,   0.9802158,  1.0321891,  0.4064213,  1.7653472,
-    1.5080582,  0.75743484, 1.2409652,  2.0487022,  1.567386,   0.68034726, 1.5328329,
-    1.2476723,  1.3539927,  0.8549268};
+    0.80091053, 1.548053,   1.3439665, 0.97278523, 0.65876126, 1.6395509, 1.0939313,  1.5905306,  0.81558955,
+    1.1096439,  2.0799308,  1.9659967, 0.21628714, 1.2937224,  1.7173465, 1.5190675,  0.62673247, 1.3878733,
+    2.2457566,  1.2779983,  0.9537279, 1.5238736,  1.6959155,  0.9063804, 1.2134336,  1.4805167,  1.277886,
+    0.9217217,  1.3267591,  2.0169291, 2.619178,   0.7248324,  1.4161175, 1.3378929,  1.6759893,  0.85183966,
+    0.53280216, 1.4385536,  1.7184939, 1.3292406,  1.1811583,  0.9698347, 1.5283158,  1.3752562,  0.99182767,
+    1.3061998,  1.7824118,  1.399513,  0.26604116, 1.3193192,  1.5053986, 1.0388529,  0.9190526,  1.4711612,
+    2.0971189,  0.37586892, 1.5662622, 1.6827406,  1.208139,   1.0144035, 0.96595216, 2.1122026,  1.6039357,
+    0.44462752, 0.34932646, 1.487859,  0.9802158,  1.0321891,  0.4064213, 1.7653472,  1.5080582,  0.75743484,
+    1.2409652,  2.0487022,  1.567386,  0.68034726, 1.5328329,  1.2476723, 1.3539927,  0.8549268};
 
 static const std::vector<float> input_data_4 = {
-    52.8665,      -2.9623508e-05, 1.1642078,      3.826082,    -0.22771922,   -0.49822173,    -0.3857528,
-    3.2676966,    -2.5112464,     -0.27454787,    -8.678656,   3.7550926e-06, -0.818072,      0.8330209,
-    3.4618711,    -0.2419473,     1.7408192,      5.744002,    1.8477443,     2.039329,       0.3268112,
-    -2.7421296,   0.6809025,      1.7613728,      -2.294264,   -0.8984407,    -0.2868184,     -3.2426705,
-    -0.801461,    -0.58971727,    -1.463435,      -2.5413132,  0.116907075,   -0.5013529,     -2.8377397,
-    -2.8455539,   -0.13475686,    -1.3145845,     -2.2820292,  -0.199,        -0.056986623,   0.12560216,
-    -0.589707,    -1.7577857,     -0.5274223,     -1.0395792,  0.53813136,    -1.7159984,     0.22503978,
-    2.902198,     -1.8643543,     -1.8789856,     2.1722724,   -2.068454,     0.59446484,     0.6067899,
-    1.5525781,    1.7612485,      1.1877432,      -0.48152098, -0.16525066,   1.5497208e-06,  1.9815066,
-    0.55218977,   0.80434155,     -3.575598,      -2.1471107,  -0.57691807,   -3.004384,      3.8775828,
-    3.1358109,    -6.2584877e-07, 0.22504184,     -2.9021916,  1.0378464,     0.9877456,      0.38395065,
-    -1.6089694,   -0.5107449,     1.8621777,      -4.960479,   -1.8983803,    1.187743,       0.48151842,
-    -0.1347583,   1.3145843,      -0.9968031,     -1.3782079,  0.9922035,     1.6614089,      -0.83039653,
-    -0.043888614, 1.9431384,      -1.6448143,     0.5381324,   1.7159982,     -2.2942696,     0.8984335,
-    1.3057998,    -0.26607463,    -3.2994738,     -1.9240448,  1.4963659,     2.8365738,      -4.691832,
-    1.2995429,    -2.8377357,     2.8455553,      -0.8180722,  -0.8330165,    -1.3755352,     0.34623986,
-    -3.7555497,   -0.9723124,     -1.1528367,     -0.593254,   -0.023679793,  1.8681414,      0.6809023,
-    -1.7613728,   48.939255,      -2.4735928e-05, 1.3455832,   0.11001387,    -2.3319814,     -1.3735183,
-    -0.6780232,   -2.4875786,     0.40718403,     -1.0639579,  0.7314569,     -1.2665987e-07, 0.97006464,
-    -0.30789328,  3.3290033,      2.7749023,      -0.7520597,  -0.98800826,   1.3100916,      1.1514524,
-    1.1085359,    4.348257,       -2.839456,      2.4404035,   0.9518837,     2.1538901,      3.8438358,
-    2.410589,     3.0649068,      0.95690995,     2.2213395,   0.66509914,    -0.4409917,     -0.37408838,
-    -0.6316552,   -1.5842111,     -0.72352415,    -2.5862057,  0.2678757,     0.610149,       2.9564474,
-    0.08470708,   -2.0889034,     -8.370071,      -0.16373271, 2.0413866,     -3.3811545,     2.0487003,
-    0.0316903,    -1.078939,      -2.5515578,     -0.16135174, -0.17406325,   1.2709827,      -0.67006403,
-    -1.6342779,   0.42163712,     2.1418998,      -0.96614444, 1.9175051,     -0.8538456,     2.8014183e-06,
-    2.0189362,    0.30467552,     0.5074463,      3.7919073,   2.427857,      0.7526233,      -2.4620402,
-    0.65359443,   0.7219074,      -2.3841858e-07, 0.03169757,  1.0789458,     -2.1129081,     -1.0250417,
-    4.8181386,    -0.39162922,    -1.2349386,     1.8470186,   -0.49495277,   -1.5516026,     -0.96614635,
-    -1.9175065,   -0.7235237,     2.5862021,      0.677946,    2.0370173,     -0.29536027,    0.6505451,
-    -2.8572361,   2.3176546,      3.4459226,      1.1869265,   -3.3811545,    -2.048697,      0.95187366,
-    -2.1538982,   1.808088,       -1.1755496,     -2.7418838,  -1.6770658,    -3.5766084,     -2.8320727,
-    -0.02944839,  -1.6522555,     -0.63165283,    1.5842092,   0.9700667,     0.30789307,     0.5195943,
-    2.4985125,    3.6537378,      -0.5842519,     -0.4843334,  0.78346854,    0.84766304,     1.1503224,
-    -2.839459,    -2.440402};
+    52.8665,      -2.9623508e-05, 1.1642078,   3.826082,       -0.22771922,  -0.49822173,   -0.3857528,  3.2676966,
+    -2.5112464,   -0.27454787,    -8.678656,   3.7550926e-06,  -0.818072,    0.8330209,     3.4618711,   -0.2419473,
+    1.7408192,    5.744002,       1.8477443,   2.039329,       0.3268112,    -2.7421296,    0.6809025,   1.7613728,
+    -2.294264,    -0.8984407,     -0.2868184,  -3.2426705,     -0.801461,    -0.58971727,   -1.463435,   -2.5413132,
+    0.116907075,  -0.5013529,     -2.8377397,  -2.8455539,     -0.13475686,  -1.3145845,    -2.2820292,  -0.199,
+    -0.056986623, 0.12560216,     -0.589707,   -1.7577857,     -0.5274223,   -1.0395792,    0.53813136,  -1.7159984,
+    0.22503978,   2.902198,       -1.8643543,  -1.8789856,     2.1722724,    -2.068454,     0.59446484,  0.6067899,
+    1.5525781,    1.7612485,      1.1877432,   -0.48152098,    -0.16525066,  1.5497208e-06, 1.9815066,   0.55218977,
+    0.80434155,   -3.575598,      -2.1471107,  -0.57691807,    -3.004384,    3.8775828,     3.1358109,   -6.2584877e-07,
+    0.22504184,   -2.9021916,     1.0378464,   0.9877456,      0.38395065,   -1.6089694,    -0.5107449,  1.8621777,
+    -4.960479,    -1.8983803,     1.187743,    0.48151842,     -0.1347583,   1.3145843,     -0.9968031,  -1.3782079,
+    0.9922035,    1.6614089,      -0.83039653, -0.043888614,   1.9431384,    -1.6448143,    0.5381324,   1.7159982,
+    -2.2942696,   0.8984335,      1.3057998,   -0.26607463,    -3.2994738,   -1.9240448,    1.4963659,   2.8365738,
+    -4.691832,    1.2995429,      -2.8377357,  2.8455553,      -0.8180722,   -0.8330165,    -1.3755352,  0.34623986,
+    -3.7555497,   -0.9723124,     -1.1528367,  -0.593254,      -0.023679793, 1.8681414,     0.6809023,   -1.7613728,
+    48.939255,    -2.4735928e-05, 1.3455832,   0.11001387,     -2.3319814,   -1.3735183,    -0.6780232,  -2.4875786,
+    0.40718403,   -1.0639579,     0.7314569,   -1.2665987e-07, 0.97006464,   -0.30789328,   3.3290033,   2.7749023,
+    -0.7520597,   -0.98800826,    1.3100916,   1.1514524,      1.1085359,    4.348257,      -2.839456,   2.4404035,
+    0.9518837,    2.1538901,      3.8438358,   2.410589,       3.0649068,    0.95690995,    2.2213395,   0.66509914,
+    -0.4409917,   -0.37408838,    -0.6316552,  -1.5842111,     -0.72352415,  -2.5862057,    0.2678757,   0.610149,
+    2.9564474,    0.08470708,     -2.0889034,  -8.370071,      -0.16373271,  2.0413866,     -3.3811545,  2.0487003,
+    0.0316903,    -1.078939,      -2.5515578,  -0.16135174,    -0.17406325,  1.2709827,     -0.67006403, -1.6342779,
+    0.42163712,   2.1418998,      -0.96614444, 1.9175051,      -0.8538456,   2.8014183e-06, 2.0189362,   0.30467552,
+    0.5074463,    3.7919073,      2.427857,    0.7526233,      -2.4620402,   0.65359443,    0.7219074,   -2.3841858e-07,
+    0.03169757,   1.0789458,      -2.1129081,  -1.0250417,     4.8181386,    -0.39162922,   -1.2349386,  1.8470186,
+    -0.49495277,  -1.5516026,     -0.96614635, -1.9175065,     -0.7235237,   2.5862021,     0.677946,    2.0370173,
+    -0.29536027,  0.6505451,      -2.8572361,  2.3176546,      3.4459226,    1.1869265,     -3.3811545,  -2.048697,
+    0.95187366,   -2.1538982,     1.808088,    -1.1755496,     -2.7418838,   -1.6770658,    -3.5766084,  -2.8320727,
+    -0.02944839,  -1.6522555,     -0.63165283, 1.5842092,      0.9700667,    0.30789307,    0.5195943,   2.4985125,
+    3.6537378,    -0.5842519,     -0.4843334,  0.78346854,     0.84766304,   1.1503224,     -2.839459,   -2.440402};
 
 static const std::vector<float> input_data_5 = {
-    25.904434,   -8.46386e-06,  -5.3626504,  0.3475349,   -2.7060094,   -5.767444,
-    1.615847,    -2.6387978,    4.020789,    1.4271183,   1.5420923,    0.6126925,
-    -4.6167765,  5.5730343e-06, -0.753784,   -0.19148755, 1.4881928,    -2.7645326,
-    -0.39467168, 1.014636,      0.5598,      -1.7654291,  -0.91835654,  -2.3019042,
-    -0.49356225, -0.8411435,    0.080773115, -1.2883577,  -0.5341466,   1.4913602,
-    -0.30008763, -0.5831754,    1.7365295,   1.821624,    -0.08851206,  -1.622279,
-    -0.27249795, -0.834725,     -0.6706438,  0.4766277,   0.62642634,   0.5483514,
-    -0.5341469,  -1.4913592,    0.8286207,   0.35826343,  -1.0869694,   -1.4876881,
-    -1.6723244,  -0.06565219,   0.16255295,  0.5317876,   -0.75649667,  1.2447717,
-    0.6264261,   -0.5483517,    -0.7537827,  0.19148779,  0.6306459,    -0.23442982,
-    0.57131517,  -1.366768,     -2.7544713,  1.3638397,   0.43463084,   -0.5446956,
-    -2.9949086,  1.4802479,     0.080771565, 1.2883584,   24.998875,    -7.390976e-06,
-    -3.1970425,  -1.5453612,    1.0925753,   -6.279154,   2.237704,     -2.8844912,
-    1.8841789,   -1.3615136,    0.90471864,  0.8395144,   -2.6060505,   4.976988e-06,
-    1.1634235,   0.42319643,    2.678257,    2.4692535,   0.34259582,   0.43598562,
-    2.748452,    0.88622695,    2.2745323,   -2.8840196,  1.8120161,    -0.27884078,
-    -1.5445104,  -0.7000726,    -1.0264511,  -0.7026249,  -1.071573,    1.062395,
-    -0.64628685, -0.36214483,   -0.5110928,  -1.0534683,  -2.786768,    2.6113648,
-    0.94799054,  0.53423727,    -0.69832724, 2.1821892,   -1.0264513,   0.70262754,
-    -0.41705567, -0.17140968,   1.4991179,   2.9674625,   -0.012362838, -3.8260121,
-    -1.5786235,  -0.32526863,   1.2857957,   1.7469958,   -0.6983267,   -2.1821907,
-    1.1634252,   -0.42319855,   0.2716269,   0.21222934,  -0.46608746,  -1.6447732,
-    1.8890494,   -1.8022469,    -0.37335354, 0.69326025,  -0.07385725,  -0.1723765,
-    -1.5445105,  0.7000739};
+    25.904434,   -8.46386e-06, -5.3626504,  0.3475349,    -2.7060094,  -5.767444,     1.615847,     -2.6387978,
+    4.020789,    1.4271183,    1.5420923,   0.6126925,    -4.6167765,  5.5730343e-06, -0.753784,    -0.19148755,
+    1.4881928,   -2.7645326,   -0.39467168, 1.014636,     0.5598,      -1.7654291,    -0.91835654,  -2.3019042,
+    -0.49356225, -0.8411435,   0.080773115, -1.2883577,   -0.5341466,  1.4913602,     -0.30008763,  -0.5831754,
+    1.7365295,   1.821624,     -0.08851206, -1.622279,    -0.27249795, -0.834725,     -0.6706438,   0.4766277,
+    0.62642634,  0.5483514,    -0.5341469,  -1.4913592,   0.8286207,   0.35826343,    -1.0869694,   -1.4876881,
+    -1.6723244,  -0.06565219,  0.16255295,  0.5317876,    -0.75649667, 1.2447717,     0.6264261,    -0.5483517,
+    -0.7537827,  0.19148779,   0.6306459,   -0.23442982,  0.57131517,  -1.366768,     -2.7544713,   1.3638397,
+    0.43463084,  -0.5446956,   -2.9949086,  1.4802479,    0.080771565, 1.2883584,     24.998875,    -7.390976e-06,
+    -3.1970425,  -1.5453612,   1.0925753,   -6.279154,    2.237704,    -2.8844912,    1.8841789,    -1.3615136,
+    0.90471864,  0.8395144,    -2.6060505,  4.976988e-06, 1.1634235,   0.42319643,    2.678257,     2.4692535,
+    0.34259582,  0.43598562,   2.748452,    0.88622695,   2.2745323,   -2.8840196,    1.8120161,    -0.27884078,
+    -1.5445104,  -0.7000726,   -1.0264511,  -0.7026249,   -1.071573,   1.062395,      -0.64628685,  -0.36214483,
+    -0.5110928,  -1.0534683,   -2.786768,   2.6113648,    0.94799054,  0.53423727,    -0.69832724,  2.1821892,
+    -1.0264513,  0.70262754,   -0.41705567, -0.17140968,  1.4991179,   2.9674625,     -0.012362838, -3.8260121,
+    -1.5786235,  -0.32526863,  1.2857957,   1.7469958,    -0.6983267,  -2.1821907,    1.1634252,    -0.42319855,
+    0.2716269,   0.21222934,   -0.46608746, -1.6447732,   1.8890494,   -1.8022469,    -0.37335354,  0.69326025,
+    -0.07385725, -0.1723765,   -1.5445105,  0.7000739};
 
 static const std::vector<float> input_data_6 = {
-    101.805756,  -5.2273273e-05, 2.5097876,    3.936094,     -2.5597036,  -1.8717405,
-    -1.0637736,  0.7801182,      -2.1040666,   -1.3385094,   -7.9471993,  2.026558e-06,
-    0.15199316,  0.52512753,     6.7908745,    2.5329556,    0.98875976,  4.755993,
-    3.157838,    3.190782,       1.4353466,    1.6061276,    -2.158554,   4.201776,
-    -1.3423799,  1.2554499,      3.5570183,    -0.8320818,   2.263445,    0.36719292,
-    0.7579028,   -1.8762131,     -0.32408538,  -0.87544185,  -3.4693956,  -4.429764,
-    -0.85828185, -3.9007902,     -2.0141544,   0.4111499,    2.8994608,   0.21030927,
-    -2.6786098,  -10.127857,     -0.6911557,   1.0018079,    -2.8430226,  0.33270124,
-    0.25672907,  1.8232578,      -4.4159126,   -2.040338,    1.9982092,   -0.7974717,
-    -0.07559925, -1.0274884,     1.9742157,    3.9031482,    0.22159882,  1.4359848,
-    -1.0190966,  3.2186508e-06,  4.0004425,    0.8568655,    1.3117876,   0.2163087,
-    0.28074512,  0.17570588,     -5.466423,    4.531178,     3.857718,    -1.2516975e-06,
-    0.2567385,   -1.823246,      -1.0750613,   -0.037295938, 5.20209,     -2.0005994,
-    -1.7456844,  3.7091968,      -5.45543,     -3.4499822,   0.22159535,  -1.4359887,
-    -0.8582816,  3.9007854,      -0.31885874,  0.65880924,   0.6968423,   2.3119528,
-    -3.6876333,  2.273767,       5.38906,      -0.45788872,  -2.8430223,  -0.33269957,
-    -1.3423961,  -1.2554631,     3.1138885,    -1.4416232,   -6.0413575,  -3.6011095,
-    -2.080242,   0.0045015216,   -4.7212796,   -0.3527125,   -3.4693892,  4.429763,
-    0.15199506,  -0.52512354,    -0.85594195,  2.8447511,    -0.10181111, -1.5565643,
-    -1.6371696,  0.19021615,     0.8239815,    3.018465,     -2.158556,   -4.2017746,
-    3.9272437,   -3.9339066e-06, -0.18137527,  3.7160687,    2.1042633,   0.8752967,
-    0.29226887,  5.755277,       -2.9184306,   0.78941,      -9.410112,   3.0100346e-06,
-    -1.7881365,  1.140914,       0.13286811,   -3.01685,     2.4928799,   6.7320104,
-    0.5376528,   0.88787735,     -0.78172505,  -7.0903873,   3.5203578,   -0.6790314,
-    -3.246148,   -3.0523329,     -4.1306543,   -5.653259,    -3.866367,   -1.5466263,
-    -3.6847744,  -3.2064118,     0.5578996,    -0.12726665,  -2.2060838,  -1.2613428,
-    0.588767,    1.2716217,      -2.5499039,   -0.8091496,   -3.0134337,  0.0408957,
-    1.4991964,   6.6122847,      -0.36368948,  -3.0809648,   3.9192853,   -3.764699,
-    0.19334978,  3.9811373,      0.68720365,   -1.717634,    2.346336,    -3.3394372,
-    1.2645291,   2.241068,       1.1309403,    -0.3806507,   2.1538877,   -2.3990266,
-    0.6885946,   -1.4901161e-06, -0.037429705, 0.24751475,   0.2968948,   -7.367506,
-    -4.574969,   -1.329541,      -0.5423446,   3.2239883,    2.4139037,   2.9802322e-07,
-    0.19334424,  -3.9811373,     3.1507545,    2.0127864,    -4.4341884,  -1.2173393,
-    0.72419256,  0.015158802,    -4.4655256,   -0.34677732,  2.1538897,   2.3990245,
-    0.5887663,   -1.2716188,     -1.6747494,   -3.415226,    1.2875631,   1.0108626,
-    2.0268395,   -2.3615427,     -1.502785,    -2.8317401,   3.919288,    3.764695,
-    -3.2461433,  3.0523314,      -0.5022881,   0.9094755,    -0.55759126, -0.24697942,
-    5.0729737,   5.668646,       -4.662384,    2.9517999,    -2.2060819,  1.2613468,
-    -1.7881389,  -1.1409098,     -1.8951292,   -2.1522717,   -7.4092865,  -0.38806117,
-    -0.6685039,  -1.3767233,     -0.8713439,   0.71781945,   3.5203605,   0.6790297};
+    101.805756,  -5.2273273e-05, 2.5097876,   3.936094,      -2.5597036,  -1.8717405,     -1.0637736,   0.7801182,
+    -2.1040666,  -1.3385094,     -7.9471993,  2.026558e-06,  0.15199316,  0.52512753,     6.7908745,    2.5329556,
+    0.98875976,  4.755993,       3.157838,    3.190782,      1.4353466,   1.6061276,      -2.158554,    4.201776,
+    -1.3423799,  1.2554499,      3.5570183,   -0.8320818,    2.263445,    0.36719292,     0.7579028,    -1.8762131,
+    -0.32408538, -0.87544185,    -3.4693956,  -4.429764,     -0.85828185, -3.9007902,     -2.0141544,   0.4111499,
+    2.8994608,   0.21030927,     -2.6786098,  -10.127857,    -0.6911557,  1.0018079,      -2.8430226,   0.33270124,
+    0.25672907,  1.8232578,      -4.4159126,  -2.040338,     1.9982092,   -0.7974717,     -0.07559925,  -1.0274884,
+    1.9742157,   3.9031482,      0.22159882,  1.4359848,     -1.0190966,  3.2186508e-06,  4.0004425,    0.8568655,
+    1.3117876,   0.2163087,      0.28074512,  0.17570588,    -5.466423,   4.531178,       3.857718,     -1.2516975e-06,
+    0.2567385,   -1.823246,      -1.0750613,  -0.037295938,  5.20209,     -2.0005994,     -1.7456844,   3.7091968,
+    -5.45543,    -3.4499822,     0.22159535,  -1.4359887,    -0.8582816,  3.9007854,      -0.31885874,  0.65880924,
+    0.6968423,   2.3119528,      -3.6876333,  2.273767,      5.38906,     -0.45788872,    -2.8430223,   -0.33269957,
+    -1.3423961,  -1.2554631,     3.1138885,   -1.4416232,    -6.0413575,  -3.6011095,     -2.080242,    0.0045015216,
+    -4.7212796,  -0.3527125,     -3.4693892,  4.429763,      0.15199506,  -0.52512354,    -0.85594195,  2.8447511,
+    -0.10181111, -1.5565643,     -1.6371696,  0.19021615,    0.8239815,   3.018465,       -2.158556,    -4.2017746,
+    3.9272437,   -3.9339066e-06, -0.18137527, 3.7160687,     2.1042633,   0.8752967,      0.29226887,   5.755277,
+    -2.9184306,  0.78941,        -9.410112,   3.0100346e-06, -1.7881365,  1.140914,       0.13286811,   -3.01685,
+    2.4928799,   6.7320104,      0.5376528,   0.88787735,    -0.78172505, -7.0903873,     3.5203578,    -0.6790314,
+    -3.246148,   -3.0523329,     -4.1306543,  -5.653259,     -3.866367,   -1.5466263,     -3.6847744,   -3.2064118,
+    0.5578996,   -0.12726665,    -2.2060838,  -1.2613428,    0.588767,    1.2716217,      -2.5499039,   -0.8091496,
+    -3.0134337,  0.0408957,      1.4991964,   6.6122847,     -0.36368948, -3.0809648,     3.9192853,    -3.764699,
+    0.19334978,  3.9811373,      0.68720365,  -1.717634,     2.346336,    -3.3394372,     1.2645291,    2.241068,
+    1.1309403,   -0.3806507,     2.1538877,   -2.3990266,    0.6885946,   -1.4901161e-06, -0.037429705, 0.24751475,
+    0.2968948,   -7.367506,      -4.574969,   -1.329541,     -0.5423446,  3.2239883,      2.4139037,    2.9802322e-07,
+    0.19334424,  -3.9811373,     3.1507545,   2.0127864,     -4.4341884,  -1.2173393,     0.72419256,   0.015158802,
+    -4.4655256,  -0.34677732,    2.1538897,   2.3990245,     0.5887663,   -1.2716188,     -1.6747494,   -3.415226,
+    1.2875631,   1.0108626,      2.0268395,   -2.3615427,    -1.502785,   -2.8317401,     3.919288,     3.764695,
+    -3.2461433,  3.0523314,      -0.5022881,  0.9094755,     -0.55759126, -0.24697942,    5.0729737,    5.668646,
+    -4.662384,   2.9517999,      -2.2060819,  1.2613468,     -1.7881389,  -1.1409098,     -1.8951292,   -2.1522717,
+    -7.4092865,  -0.38806117,    -0.6685039,  -1.3767233,    -0.8713439,  0.71781945,     3.5203605,    0.6790297};
 
 static const std::vector<float> input_data_7 = {
-    0.73348462,   0.74833735,   0.40982435,   0.51988197,   0.99384421,   0.12469386,
-    0.47686314,   0.25882564,   0.67028317,   0.58466398,   0.74927361,   0.19614283,
-    0.82593526,   0.41205770,   0.74020169,   0.62222693,   0.33264240,   0.84108156,
-    0.86392366,   0.79030966,   0.79792986,   0.47647899,   0.65967837,   0.92732906,
-    0.90477190,   0.87232389,   0.55734667,   0.75560744,   0.70658521,   0.28530827,
-    0.02554864,   0.14915414,   0.29936996,   0.74239557,   0.38158196,   0.26483291,
-    0.15843351,   0.38703221,   0.79967600,   0.63790851,   0.66191234,   0.19395184,
-    0.34992850,   0.89077723,   0.40746049,   0.01455611,   0.84174579,   0.91950995,
-    0.43402124,   0.76620100,   0.96476467,   0.78331896,   0.48567269,   0.33793230,
-    0.20362115,   0.51710568,   0.55455124,   0.10148728,   0.48229121,   0.58612092,
-    0.91786709,   0.94405867,   0.54302465,   0.24146348,   0.34853454,   0.75880201,
-    0.67781768,   0.29531289,   0.35969526,   0.01040005,   0.63142510,   0.67264276,
-    0.57920180,   0.99608063,   0.91108299,   0.82647166,   0.54134147,   0.79556370,
-    0.18579404,   0.95271365,   0.61918245,   0.17552980,   0.56332554,   0.58036855,
-    0.33756331,   0.69359258,   0.03914420,   0.14962257,   0.26647894,   0.45042564,
-    0.60093050,   0.67657016,   0.12601171,   0.95279680,   0.02868298,   0.82188820,
-    0.17558198,   0.40678849,   0.90804391,   0.21813571,   0.69710526,   0.91450289,
-    0.44277349,   0.70432336,   0.88161566,   0.23739783,   0.02746046,   0.05775890,
-    0.63494471,   0.10963744,   0.68260565,   0.87579980,   0.34451002,   0.01422449,
-    0.44081511,   0.78790226,   0.42010180,   0.62148773,   0.73164358,   0.85657540,
-    0.21649672,   0.93347654,   0.65511518,   0.45192463,   0.57671214,   0.09925586,
-    0.76042901,   0.84041443,   0.91933065,   0.00541233,   0.56194300,   0.71416635,
-    0.15882159,   0.57976451,   0.37377713,   0.48352544,   0.96645849,   0.50040596,
-    0.06060478,   0.21032667,   0.33303769,   0.80884551,   0.97500277,   0.28607026,
-    0.12235457,   0.47764468,   0.09834820,   0.08864630,   0.21728048,   0.92446905,
-    0.53802798,   0.22378462,   0.66087828,   0.64754384,   0.09980577,   0.50331927,
-    0.90966904,   0.67624758,   0.22728569,   0.61184030,   0.66753081,   0.00405466,
-    0.93407600,   0.89524725,   0.34496848,   0.01595642,   0.54338693,   0.65760153,
-    0.69930304,   0.54202591,   0.66030817,   0.74371140,   0.95000083,   0.86475930,
-    0.99826786,   0.85464029,   0.89926621,   0.90551912,   0.89889036,   0.38316505,
-    0.06428984,   0.39342267,   0.40689672,   0.37076883,   0.72720439,   0.05071236,
-    0.01355718,   0.95169120,   0.03623840,   0.05569115,   0.47255274,   0.44040655};
+    0.73348462, 0.74833735, 0.40982435, 0.51988197, 0.99384421, 0.12469386, 0.47686314, 0.25882564, 0.67028317,
+    0.58466398, 0.74927361, 0.19614283, 0.82593526, 0.41205770, 0.74020169, 0.62222693, 0.33264240, 0.84108156,
+    0.86392366, 0.79030966, 0.79792986, 0.47647899, 0.65967837, 0.92732906, 0.90477190, 0.87232389, 0.55734667,
+    0.75560744, 0.70658521, 0.28530827, 0.02554864, 0.14915414, 0.29936996, 0.74239557, 0.38158196, 0.26483291,
+    0.15843351, 0.38703221, 0.79967600, 0.63790851, 0.66191234, 0.19395184, 0.34992850, 0.89077723, 0.40746049,
+    0.01455611, 0.84174579, 0.91950995, 0.43402124, 0.76620100, 0.96476467, 0.78331896, 0.48567269, 0.33793230,
+    0.20362115, 0.51710568, 0.55455124, 0.10148728, 0.48229121, 0.58612092, 0.91786709, 0.94405867, 0.54302465,
+    0.24146348, 0.34853454, 0.75880201, 0.67781768, 0.29531289, 0.35969526, 0.01040005, 0.63142510, 0.67264276,
+    0.57920180, 0.99608063, 0.91108299, 0.82647166, 0.54134147, 0.79556370, 0.18579404, 0.95271365, 0.61918245,
+    0.17552980, 0.56332554, 0.58036855, 0.33756331, 0.69359258, 0.03914420, 0.14962257, 0.26647894, 0.45042564,
+    0.60093050, 0.67657016, 0.12601171, 0.95279680, 0.02868298, 0.82188820, 0.17558198, 0.40678849, 0.90804391,
+    0.21813571, 0.69710526, 0.91450289, 0.44277349, 0.70432336, 0.88161566, 0.23739783, 0.02746046, 0.05775890,
+    0.63494471, 0.10963744, 0.68260565, 0.87579980, 0.34451002, 0.01422449, 0.44081511, 0.78790226, 0.42010180,
+    0.62148773, 0.73164358, 0.85657540, 0.21649672, 0.93347654, 0.65511518, 0.45192463, 0.57671214, 0.09925586,
+    0.76042901, 0.84041443, 0.91933065, 0.00541233, 0.56194300, 0.71416635, 0.15882159, 0.57976451, 0.37377713,
+    0.48352544, 0.96645849, 0.50040596, 0.06060478, 0.21032667, 0.33303769, 0.80884551, 0.97500277, 0.28607026,
+    0.12235457, 0.47764468, 0.09834820, 0.08864630, 0.21728048, 0.92446905, 0.53802798, 0.22378462, 0.66087828,
+    0.64754384, 0.09980577, 0.50331927, 0.90966904, 0.67624758, 0.22728569, 0.61184030, 0.66753081, 0.00405466,
+    0.93407600, 0.89524725, 0.34496848, 0.01595642, 0.54338693, 0.65760153, 0.69930304, 0.54202591, 0.66030817,
+    0.74371140, 0.95000083, 0.86475930, 0.99826786, 0.85464029, 0.89926621, 0.90551912, 0.89889036, 0.38316505,
+    0.06428984, 0.39342267, 0.40689672, 0.37076883, 0.72720439, 0.05071236, 0.01355718, 0.95169120, 0.03623840,
+    0.05569115, 0.47255274, 0.44040655};
 
 static const std::vector<float> expected_irdft2d_results_1 = {
-    0.106065355, 0.7454709,    0.5723129,   0.45824066,  0.384706,    0.27398905, 0.6679619,  0.39547434,
-    0.2815724,   0.779919,     0.59909385,  0.122946456, 0.38957337,  0.97498655, 0.46759892, 0.14017127,
-    0.04206834,  0.72799486,   0.61560476,  0.9027304,   0.6226336,   0.2601218,  0.5555171,  0.4049862,
-    0.14175594,  0.57774574,   0.52652067,  0.9385676,   0.958878,    0.9844308,  0.2309568,  0.0970796,
-    0.24574815,  0.6907565,    0.19743192,  0.8295261,   0.3461272,   0.5140136,  0.66115695, 0.93362343,
-    0.06690116,  0.74688905,   0.39028272,  0.53575796,  0.060429227, 0.89135474, 0.77787286, 0.67011875,
-    0.73505205,  0.6636992,    0.18176568,  0.8629964,   0.4514285,   0.6497283,  0.15937214, 0.40598106,
-    0.7988508,   0.72915316,   0.07090413,  0.76971227,  0.49721542,  0.7669206,  0.6797579,  0.13026048,
-    0.6587432,   0.24532847,   0.24545121,  0.83795464,  0.10549038,  0.72643167, 0.94568396, 0.72166353,
-    0.14389817,  0.79305094,   0.7089523,   0.9724684,   0.9775141,   0.49999753, 0.6556916,  0.2687679,
-    0.6324893,   0.85201234,   0.5689621,   0.023386242, 0.5546462,   0.36860004, 0.9603104,  0.3912346,
-    0.038073156, 0.8921232,    0.14387667,  0.63858616,  0.10003737,  0.8906622,  0.06681097, 0.74586314,
-    0.4545233,   0.54724485,   0.6496472,   0.7818348,   0.6608358,   0.77711284, 0.24588637, 0.0134570245,
-    0.35584468,  0.8038809,    0.027993381, 0.7367708,   0.52754945,  0.90523165, 0.54310995, 0.5367796,
-    0.41312343,  0.7752323,    0.10966998,  0.13664615,  0.7828726,   0.9083951,  0.524759,   0.7493586,
-    0.19275239,  0.0071907635, 0.60879755,  0.34413564,  0.4690983,   0.4192482,  0.70729065, 0.1993285,
-    0.5303842,   0.65138334,   0.06686333,  0.97179186,  0.657022,    0.11786719, 0.3154068,  0.8892283,
-    0.55640805,  0.9104763,    0.28466636,  0.093467236, 0.88953,     0.9919328,  0.18322526, 0.8185441,
-    0.56639117,  0.014208457,  0.29673028,  0.6347738,   0.68019533,  0.39601144, 0.34374115, 0.72168803,
-    0.61525595,  0.76679367,   0.5860848,   0.42768106,  0.7933919,   0.13130645, 0.68764144, 0.05312841,
-    0.026113434, 0.2982238,    0.7618365,   0.3331724,   0.5468184,   0.15707079, 0.28592035, 0.15286529,
-    0.9368952,   0.35067078,   0.43364897,  0.089348935, 0.41172677,  0.58502454, 0.7073026,  0.85983366,
-    0.08878795,  0.2671109,    0.8002475,   0.19422255,  0.83120316,  0.5198712,  0.40111288, 0.98375624,
-    0.77703446,  0.03781964,   0.7042304,   0.68980736,  0.17102323,  0.42153904, 0.7278248,  0.80301994,
-    0.91017085,  0.019965423,  0.13768451,  0.556689,    0.17991383,  0.6720085,  0.7733324,  0.20881362};
+    0.106065355, 0.7454709,   0.5723129,   0.45824066, 0.384706,     0.27398905, 0.6679619,  0.39547434,  0.2815724,
+    0.779919,    0.59909385,  0.122946456, 0.38957337, 0.97498655,   0.46759892, 0.14017127, 0.04206834,  0.72799486,
+    0.61560476,  0.9027304,   0.6226336,   0.2601218,  0.5555171,    0.4049862,  0.14175594, 0.57774574,  0.52652067,
+    0.9385676,   0.958878,    0.9844308,   0.2309568,  0.0970796,    0.24574815, 0.6907565,  0.19743192,  0.8295261,
+    0.3461272,   0.5140136,   0.66115695,  0.93362343, 0.06690116,   0.74688905, 0.39028272, 0.53575796,  0.060429227,
+    0.89135474,  0.77787286,  0.67011875,  0.73505205, 0.6636992,    0.18176568, 0.8629964,  0.4514285,   0.6497283,
+    0.15937214,  0.40598106,  0.7988508,   0.72915316, 0.07090413,   0.76971227, 0.49721542, 0.7669206,   0.6797579,
+    0.13026048,  0.6587432,   0.24532847,  0.24545121, 0.83795464,   0.10549038, 0.72643167, 0.94568396,  0.72166353,
+    0.14389817,  0.79305094,  0.7089523,   0.9724684,  0.9775141,    0.49999753, 0.6556916,  0.2687679,   0.6324893,
+    0.85201234,  0.5689621,   0.023386242, 0.5546462,  0.36860004,   0.9603104,  0.3912346,  0.038073156, 0.8921232,
+    0.14387667,  0.63858616,  0.10003737,  0.8906622,  0.06681097,   0.74586314, 0.4545233,  0.54724485,  0.6496472,
+    0.7818348,   0.6608358,   0.77711284,  0.24588637, 0.0134570245, 0.35584468, 0.8038809,  0.027993381, 0.7367708,
+    0.52754945,  0.90523165,  0.54310995,  0.5367796,  0.41312343,   0.7752323,  0.10966998, 0.13664615,  0.7828726,
+    0.9083951,   0.524759,    0.7493586,   0.19275239, 0.0071907635, 0.60879755, 0.34413564, 0.4690983,   0.4192482,
+    0.70729065,  0.1993285,   0.5303842,   0.65138334, 0.06686333,   0.97179186, 0.657022,   0.11786719,  0.3154068,
+    0.8892283,   0.55640805,  0.9104763,   0.28466636, 0.093467236,  0.88953,    0.9919328,  0.18322526,  0.8185441,
+    0.56639117,  0.014208457, 0.29673028,  0.6347738,  0.68019533,   0.39601144, 0.34374115, 0.72168803,  0.61525595,
+    0.76679367,  0.5860848,   0.42768106,  0.7933919,  0.13130645,   0.68764144, 0.05312841, 0.026113434, 0.2982238,
+    0.7618365,   0.3331724,   0.5468184,   0.15707079, 0.28592035,   0.15286529, 0.9368952,  0.35067078,  0.43364897,
+    0.089348935, 0.41172677,  0.58502454,  0.7073026,  0.85983366,   0.08878795, 0.2671109,  0.8002475,   0.19422255,
+    0.83120316,  0.5198712,   0.40111288,  0.98375624, 0.77703446,   0.03781964, 0.7042304,  0.68980736,  0.17102323,
+    0.42153904,  0.7278248,   0.80301994,  0.91017085, 0.019965423,  0.13768451, 0.556689,   0.17991383,  0.6720085,
+    0.7733324,   0.20881362};
 
 static const std::vector<float> expected_irdft2d_results_2 = {
-    0.10606504,   0.74547091,   0.57231341,   0.45824085,   0.38470576,   0.27398939,   0.66796227,
-    0.39547472,   0.28157284,   0.77991920,   0.00000012,   0.00000025,   0.59909402,   0.12294612,
-    0.38957398,   0.97498753,   0.46759871,   0.14017182,   0.04206866,   0.72799575,   0.61560553,
-    0.90273150,   0.00000029,   0.00000019,   0.62263335,   0.26012139,   0.55551768,   0.40498611,
-    0.14175560,   0.57774629,   0.52652119,   0.93856842,   0.95887877,   0.98443111,   0.00000026,
-    0.00000029,   0.23095626,   0.09707905,   0.24574875,   0.69075717,   0.19743158,   0.82952691,
-    0.34612741,   0.51401454,   0.66115784,   0.93362381,   0.00000013,   0.00000019,   0.06690087,
-    0.74688917,   0.39028283,   0.53575807,   0.06042910,   0.89135566,   0.77787371,   0.67011938,
-    0.73505260,   0.66369919,   0.00000020,   0.00000025,   0.66083517,   0.77711292,   0.24588620,
-    0.01345654,   0.35584463,   0.80388178,   0.02799342,   0.73677143,   0.52754998,   0.90523178,
-    0.00000020,   0.00000022,   0.54311002,   0.53678006,   0.41312413,   0.77523314,   0.10966939,
-    0.13664682,   0.78287364,   0.90839633,   0.52475940,   0.74935884,   0.00000017,   0.00000024,
-    0.19275220,   0.00719083,   0.60879792,   0.34413568,   0.46909855,   0.41924857,   0.70729118,
-    0.19932858,   0.53038468,   0.65138356,   0.00000024,   0.00000004,   0.06686326,   0.97179258,
-    0.65702215,   0.11786667,   0.31540699,   0.88922984,   0.55640881,   0.91047768,   0.28466661,
-    0.09346649,   0.00000006,   0.00000008,   0.88953045,   0.99193334,   0.18322520,   0.81854497,
-    0.56639084,   0.01420842,   0.29673067,   0.63477397,   0.68019596,   0.39601113,   0.00000014,
-    0.00000022};
+    0.10606504, 0.74547091, 0.57231341, 0.45824085, 0.38470576, 0.27398939, 0.66796227, 0.39547472, 0.28157284,
+    0.77991920, 0.00000012, 0.00000025, 0.59909402, 0.12294612, 0.38957398, 0.97498753, 0.46759871, 0.14017182,
+    0.04206866, 0.72799575, 0.61560553, 0.90273150, 0.00000029, 0.00000019, 0.62263335, 0.26012139, 0.55551768,
+    0.40498611, 0.14175560, 0.57774629, 0.52652119, 0.93856842, 0.95887877, 0.98443111, 0.00000026, 0.00000029,
+    0.23095626, 0.09707905, 0.24574875, 0.69075717, 0.19743158, 0.82952691, 0.34612741, 0.51401454, 0.66115784,
+    0.93362381, 0.00000013, 0.00000019, 0.06690087, 0.74688917, 0.39028283, 0.53575807, 0.06042910, 0.89135566,
+    0.77787371, 0.67011938, 0.73505260, 0.66369919, 0.00000020, 0.00000025, 0.66083517, 0.77711292, 0.24588620,
+    0.01345654, 0.35584463, 0.80388178, 0.02799342, 0.73677143, 0.52754998, 0.90523178, 0.00000020, 0.00000022,
+    0.54311002, 0.53678006, 0.41312413, 0.77523314, 0.10966939, 0.13664682, 0.78287364, 0.90839633, 0.52475940,
+    0.74935884, 0.00000017, 0.00000024, 0.19275220, 0.00719083, 0.60879792, 0.34413568, 0.46909855, 0.41924857,
+    0.70729118, 0.19932858, 0.53038468, 0.65138356, 0.00000024, 0.00000004, 0.06686326, 0.97179258, 0.65702215,
+    0.11786667, 0.31540699, 0.88922984, 0.55640881, 0.91047768, 0.28466661, 0.09346649, 0.00000006, 0.00000008,
+    0.88953045, 0.99193334, 0.18322520, 0.81854497, 0.56639084, 0.01420842, 0.29673067, 0.63477397, 0.68019596,
+    0.39601113, 0.00000014, 0.00000022};
 
 static const std::vector<float> expected_irdft3d_results_2 = {
-    0.29655575,   0.59799123,   0.22431113,   0.46143103,   0.53208175,   0.32705094,   0.59367000,
-    0.29963828,   0.41763943,   0.24033307,   0.42796425,   0.56577777,   0.37677909,   0.32099129,
-    0.28778578,   0.50527716,   0.39592624,   -0.01477019,  0.46390174,   0.48881302,   0.69299017,
-    0.69097986,   0.60120016,   0.82729206,   -0.09137908,  0.49852066,   0.41157645,   0.50370176,
-    0.50602146,   0.12422646,   0.66381460,   0.40124601,   0.71138931,   0.66414101,   0.50896081,
-    0.51854765,   0.21342740,   0.75042767,   0.40385838,   0.28173387,   0.29258505,   0.34233110,
-    0.44617152,   0.32590713,   0.69813927,   0.27029157,   0.49500125,   0.57849153,   0.52079012,
-    0.46437605,   0.44842544,   0.21380078,   0.57897044,   0.32123390,   0.46531573,   0.55946432,
-    0.36995799,   0.19326348,   0.26279333,   0.89411452,   0.45806675,   0.58413552,   0.47982321,
-    0.40877153,   0.23978246,   0.33369794,   0.56433968,   0.09308288,   0.20574836,   0.51936717,
-    0.46905154,   0.47775696,   0.17856948,   0.04195880,   0.24284739,   0.63731160,   0.16159543,
-    0.08925854,   0.50157161,   0.67721677,   0.75653236,   0.50840554,   0.73467008,   0.62163510,
-    0.00566245,   0.92257200,   0.42133956,   0.45249607,   0.36451271,   0.46674756,   0.65809363,
-    0.29478180,   0.79919561,   0.37987672,   0.46803394,   0.20036376,   0.30268271,   0.62990812,
-    0.29745090,   0.46503467,   0.30444576,   0.43581755,   0.38956261,   0.58891618,   0.43936615,
-    0.12833645,   0.82411153,   0.30960669,   0.24676315,   0.39269569,   0.26772071,   0.46022705,
-    0.77598541,   0.46882716,   0.40922151,   0.28451272,   0.27156988,   0.32720683,   0.48740341,
-    0.52519462,   0.47371313,   0.61046947,   0.46505542,   0.04019986,   0.27622309,   0.42926452,
-    0.49897225,   0.04617115,   0.50902017,   0.74826910,   0.28548445,   0.63409441,   0.13183664,
-    0.02507987,   0.51695660,   0.50593892,   0.17335312,   0.24157819,   0.45513622,   0.69800550,
-    0.40604969,   0.47128647,   0.59389774,   0.33534107,   0.50887902,   0.82998967,   0.22642939,
-    0.32967160,   0.50515564,   0.54070049,   0.28947697,   0.35626388,   0.58235507,   0.30633221,
-    0.50041779,   0.24975602,   0.38320678,   0.40595842,   0.50651077,   0.42963483,   0.25977121,
-    0.32014694,   0.37577291,   0.46638206,   0.05511259,   0.45463482,   0.62685054,   0.13046773,
-    0.49768469,   0.47645129,   0.56182954,   0.74548830,   0.73150766,   0.37579758,   0.14279248,
-    0.28705593,   0.45403320,   0.50334282,   0.24132925,   0.24104091,   0.31220213,   0.62432518,
-    0.20954334,   0.09285936,   0.56852238,   0.42261752,   0.52830257,   0.25272655,   0.72091123,
-    0.46923499,   0.24439716,   0.72211522,   0.33004626,   0.30411236,   0.56189500,   0.37390448,
-    0.40768394,   0.13754946,   0.41746636,   0.50960175,   0.34250750,   0.65386079,   0.46042782,
-    0.54099804,   0.41183749,   0.40593833,   0.21666628,   0.38087729,   0.64666439,   0.19817938,
-    0.29519793,   0.46272810,   0.49454878,   0.59059650,   0.54134465,   0.56793991,   0.29395146,
-    0.52647797,   0.61291826,   0.24633402,   0.24791051,   0.22666050,   0.43238182,   0.20337301,
-    0.31388571,   0.59658993,   0.29774026,   0.39935257,   0.77171166,   0.54813165,   0.74253426,
-    0.49906203,   0.53449270,   0.22820431,   0.19888670,   0.56200754,   0.55242130,   0.36939947,
-    0.01671917,   0.60996081};
-
-static const std::vector<float> expected_irdft3d_results_3 ={
-    0.51795123,   0.01846075,   0.03363710,   -0.02286412,   -0.00527071,   -0.05116411,
-    -0.01142488,   -0.01784910,   -0.01088149,   0.01049122,   -0.00829387,   0.00942086,
-    -0.02915924,   0.05941228,   0.05868882,   -0.02329090,   0.06043447,   0.01260666,
-    0.04213929,   -0.03578551,   -0.00354573,   -0.02047438,   -0.03469945,   -0.02365786,
-    0.00807303,   0.02364844,   -0.00346402,   -0.00134415,   0.04106979,   0.04961361,
-    -0.01212564,   -0.04288128,   -0.26157875,   -0.01917418,   -0.04232584,   0.02477720,
-    0.02514449,   0.04955597,   -0.00301304,   0.00663580,   0.01947190,   -0.01163269,
-    -0.07920224,   -0.01201069,   0.00564843,   0.00283007,   -0.05916596,   0.03569793,
-    -0.02454099,   -0.01977048,   -0.00360401,   0.00924050,   -0.01237082,   -0.04213287,
-    -0.03306797,   -0.01442351,   -0.02601594,   0.07406829,   -0.02896844,   0.00503278,
-    0.00700455,   0.02915976,   0.01761130,   -0.04474307,   0.03632101,   0.00957998,
-    -0.02003984,   -0.04022581,   0.03104216,   0.00388626,   0.05861915,   0.01034101,
-    -0.00741989,   0.01010181,   0.01496502,   -0.00544559,   0.04015258,   -0.00600315,
-    -0.06137903,   0.07850411,   -0.00074931,   0.02540785,   -0.00166176,   0.02205904,
-    -0.02429718,   0.04010517,   0.02375359,   0.02229406,   0.01806382,   -0.06089136,
-    0.00447113,   -0.03169147,   0.02836490,   -0.05821620,   0.03905417,   0.03987032,
-    0.29899586,   -0.02616866,   -0.00927641,   -0.02134532,   -0.02480746,   -0.02636082,
-    -0.05009444,   -0.02208490,   0.02632000,   0.00493334,   -0.00402312,   -0.00935831,
-    0.04154630,   0.00849218,   0.00232782,   -0.01192997,   -0.03309486,   0.01678531,
-    0.03526979,   0.09272132,   0.01420703,   -0.01919909,   0.01321082,   -0.01661140,
-    0.07861365,   -0.02784724,   0.03900426,   -0.00096805,   -0.02880604,   0.02753764,
-    -0.02092520,   -0.01412453};
+    0.29655575, 0.59799123, 0.22431113, 0.46143103, 0.53208175, 0.32705094, 0.59367000,  0.29963828, 0.41763943,
+    0.24033307, 0.42796425, 0.56577777, 0.37677909, 0.32099129, 0.28778578, 0.50527716,  0.39592624, -0.01477019,
+    0.46390174, 0.48881302, 0.69299017, 0.69097986, 0.60120016, 0.82729206, -0.09137908, 0.49852066, 0.41157645,
+    0.50370176, 0.50602146, 0.12422646, 0.66381460, 0.40124601, 0.71138931, 0.66414101,  0.50896081, 0.51854765,
+    0.21342740, 0.75042767, 0.40385838, 0.28173387, 0.29258505, 0.34233110, 0.44617152,  0.32590713, 0.69813927,
+    0.27029157, 0.49500125, 0.57849153, 0.52079012, 0.46437605, 0.44842544, 0.21380078,  0.57897044, 0.32123390,
+    0.46531573, 0.55946432, 0.36995799, 0.19326348, 0.26279333, 0.89411452, 0.45806675,  0.58413552, 0.47982321,
+    0.40877153, 0.23978246, 0.33369794, 0.56433968, 0.09308288, 0.20574836, 0.51936717,  0.46905154, 0.47775696,
+    0.17856948, 0.04195880, 0.24284739, 0.63731160, 0.16159543, 0.08925854, 0.50157161,  0.67721677, 0.75653236,
+    0.50840554, 0.73467008, 0.62163510, 0.00566245, 0.92257200, 0.42133956, 0.45249607,  0.36451271, 0.46674756,
+    0.65809363, 0.29478180, 0.79919561, 0.37987672, 0.46803394, 0.20036376, 0.30268271,  0.62990812, 0.29745090,
+    0.46503467, 0.30444576, 0.43581755, 0.38956261, 0.58891618, 0.43936615, 0.12833645,  0.82411153, 0.30960669,
+    0.24676315, 0.39269569, 0.26772071, 0.46022705, 0.77598541, 0.46882716, 0.40922151,  0.28451272, 0.27156988,
+    0.32720683, 0.48740341, 0.52519462, 0.47371313, 0.61046947, 0.46505542, 0.04019986,  0.27622309, 0.42926452,
+    0.49897225, 0.04617115, 0.50902017, 0.74826910, 0.28548445, 0.63409441, 0.13183664,  0.02507987, 0.51695660,
+    0.50593892, 0.17335312, 0.24157819, 0.45513622, 0.69800550, 0.40604969, 0.47128647,  0.59389774, 0.33534107,
+    0.50887902, 0.82998967, 0.22642939, 0.32967160, 0.50515564, 0.54070049, 0.28947697,  0.35626388, 0.58235507,
+    0.30633221, 0.50041779, 0.24975602, 0.38320678, 0.40595842, 0.50651077, 0.42963483,  0.25977121, 0.32014694,
+    0.37577291, 0.46638206, 0.05511259, 0.45463482, 0.62685054, 0.13046773, 0.49768469,  0.47645129, 0.56182954,
+    0.74548830, 0.73150766, 0.37579758, 0.14279248, 0.28705593, 0.45403320, 0.50334282,  0.24132925, 0.24104091,
+    0.31220213, 0.62432518, 0.20954334, 0.09285936, 0.56852238, 0.42261752, 0.52830257,  0.25272655, 0.72091123,
+    0.46923499, 0.24439716, 0.72211522, 0.33004626, 0.30411236, 0.56189500, 0.37390448,  0.40768394, 0.13754946,
+    0.41746636, 0.50960175, 0.34250750, 0.65386079, 0.46042782, 0.54099804, 0.41183749,  0.40593833, 0.21666628,
+    0.38087729, 0.64666439, 0.19817938, 0.29519793, 0.46272810, 0.49454878, 0.59059650,  0.54134465, 0.56793991,
+    0.29395146, 0.52647797, 0.61291826, 0.24633402, 0.24791051, 0.22666050, 0.43238182,  0.20337301, 0.31388571,
+    0.59658993, 0.29774026, 0.39935257, 0.77171166, 0.54813165, 0.74253426, 0.49906203,  0.53449270, 0.22820431,
+    0.19888670, 0.56200754, 0.55242130, 0.36939947, 0.01671917, 0.60996081};
+
+static const std::vector<float> expected_irdft3d_results_3 = {
+    0.51795123,  0.01846075,  0.03363710,  -0.02286412, -0.00527071, -0.05116411, -0.01142488, -0.01784910, -0.01088149,
+    0.01049122,  -0.00829387, 0.00942086,  -0.02915924, 0.05941228,  0.05868882,  -0.02329090, 0.06043447,  0.01260666,
+    0.04213929,  -0.03578551, -0.00354573, -0.02047438, -0.03469945, -0.02365786, 0.00807303,  0.02364844,  -0.00346402,
+    -0.00134415, 0.04106979,  0.04961361,  -0.01212564, -0.04288128, -0.26157875, -0.01917418, -0.04232584, 0.02477720,
+    0.02514449,  0.04955597,  -0.00301304, 0.00663580,  0.01947190,  -0.01163269, -0.07920224, -0.01201069, 0.00564843,
+    0.00283007,  -0.05916596, 0.03569793,  -0.02454099, -0.01977048, -0.00360401, 0.00924050,  -0.01237082, -0.04213287,
+    -0.03306797, -0.01442351, -0.02601594, 0.07406829,  -0.02896844, 0.00503278,  0.00700455,  0.02915976,  0.01761130,
+    -0.04474307, 0.03632101,  0.00957998,  -0.02003984, -0.04022581, 0.03104216,  0.00388626,  0.05861915,  0.01034101,
+    -0.00741989, 0.01010181,  0.01496502,  -0.00544559, 0.04015258,  -0.00600315, -0.06137903, 0.07850411,  -0.00074931,
+    0.02540785,  -0.00166176, 0.02205904,  -0.02429718, 0.04010517,  0.02375359,  0.02229406,  0.01806382,  -0.06089136,
+    0.00447113,  -0.03169147, 0.02836490,  -0.05821620, 0.03905417,  0.03987032,  0.29899586,  -0.02616866, -0.00927641,
+    -0.02134532, -0.02480746, -0.02636082, -0.05009444, -0.02208490, 0.02632000,  0.00493334,  -0.00402312, -0.00935831,
+    0.04154630,  0.00849218,  0.00232782,  -0.01192997, -0.03309486, 0.01678531,  0.03526979,  0.09272132,  0.01420703,
+    -0.01919909, 0.01321082,  -0.01661140, 0.07861365,  -0.02784724, 0.03900426,  -0.00096805, -0.02880604, 0.02753764,
+    -0.02092520, -0.01412453};
 
 static const std::vector<float> expected_irdft3d_results_4 = {
-    0.24882269,   -0.00554157,   -0.00759689,   -0.00413212,   0.01099624,   0.02191469,
-    0.02829072,   -0.01410181,   0.04826954,   0.03587530,   -0.01151859,   0.03459743,
-    0.03157633,   -0.03446264,   0.03595825,   -0.01176664,   0.00625817,   0.00981066,
-    -0.11900401,   -0.02756717,   0.01933546,   0.03042892,   -0.04917013,   0.00048474,
-    -0.01849990,   -0.01050222,   -0.02433642,   -0.08657554,   -0.03473007,   -0.01486101,
-    0.00137630,   -0.01972852,   -0.06159696,   0.02284726,   -0.03851998,   -0.00885092,
-    0.02397606,   -0.02071742,   -0.00586151,   -0.01287085,   0.01713095,   -0.07724825,
-    0.05983482,   -0.02824272,   0.02959802,   0.04051825,   0.00219584,   0.04053028,
-    0.00415529,   0.02379833,   -0.01936524,   0.04350142,   0.02095385,   0.03121966,
-    -0.02675550,   0.01142533,   0.05606331,   0.02115209,   0.00866956,   0.05367358,
-    -0.00479556,   0.05423974,   -0.01172735,   -0.01203834,   0.00181946,   0.00594081,
-    0.00527473,   0.00781714,   0.07042868,   -0.02243115,   0.03207793,   -0.04213578,
-    0.14912935,   -0.01012542,   -0.05799989,   -0.02889979,   0.02934662,   0.03385938,
-    0.00951527,   -0.01760542,   -0.01611288,   0.29838892,   -0.01029289,   -0.06226702,
-    -0.03670440,   0.03954893,   0.00725941,   0.04219448,   -0.03698240,   0.03564729};
+    0.24882269,  -0.00554157, -0.00759689, -0.00413212, 0.01099624,  0.02191469,  0.02829072,  -0.01410181, 0.04826954,
+    0.03587530,  -0.01151859, 0.03459743,  0.03157633,  -0.03446264, 0.03595825,  -0.01176664, 0.00625817,  0.00981066,
+    -0.11900401, -0.02756717, 0.01933546,  0.03042892,  -0.04917013, 0.00048474,  -0.01849990, -0.01050222, -0.02433642,
+    -0.08657554, -0.03473007, -0.01486101, 0.00137630,  -0.01972852, -0.06159696, 0.02284726,  -0.03851998, -0.00885092,
+    0.02397606,  -0.02071742, -0.00586151, -0.01287085, 0.01713095,  -0.07724825, 0.05983482,  -0.02824272, 0.02959802,
+    0.04051825,  0.00219584,  0.04053028,  0.00415529,  0.02379833,  -0.01936524, 0.04350142,  0.02095385,  0.03121966,
+    -0.02675550, 0.01142533,  0.05606331,  0.02115209,  0.00866956,  0.05367358,  -0.00479556, 0.05423974,  -0.01172735,
+    -0.01203834, 0.00181946,  0.00594081,  0.00527473,  0.00781714,  0.07042868,  -0.02243115, 0.03207793,  -0.04213578,
+    0.14912935,  -0.01012542, -0.05799989, -0.02889979, 0.02934662,  0.03385938,  0.00951527,  -0.01760542, -0.01611288,
+    0.29838892,  -0.01029289, -0.06226702, -0.03670440, 0.03954893,  0.00725941,  0.04219448,  -0.03698240, 0.03564729};
 
 template <element::Type_t ET>
 std::vector<IRDFTParams> generateParamsForIRDFT() {
@@ -609,186 +543,186 @@ std::vector<IRDFTParams> generateParamsForIRDFT() {
                     expected_irdft2d_results_1,
                     op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
                     NULL),
-       // irdft2d_eval_1_positive_negative_axes
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, -1}),
-                  NULL),
-       // irdft2d_eval_1_negative_positive_axes
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, 2}),
-                  NULL),
-       // irdft2d_eval_1_negative_negative_axes
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, -1}),
-                  NULL),
-       // irdft2d_eval_1_signal_size_0_s10_10
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, 10})),
-       // irdft2d_eval_1_signal_size_0_s10_10_positive_negative_axes
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, -1}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, 10})),
-       // irdft2d_eval_1_signal_size_0_s10_10_negative_positive_axes
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, 10})),
-       // irdft2d_eval_1_signal_size_0_s10_10_negative_negative_axes
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, -1}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, 10})),
-       // irdft2d_eval_1_signal_size_0_s10_m1
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, -1})),
-       // irdft2d_eval_1_signal_size_0_sm1_10
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-1, 10})),
-       // irdft2d_eval_1_signal_size_0_sm1_m1
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_4,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-1, -1})),
-       // irdft2d_eval_2_signal_size
-       IRDFTParams(Shape{2, 5, 7, 2},
-                  Shape{2, 5, 12},
-                  ET,
-                  ET,
-                  input_data_5,
-                  expected_irdft2d_results_2,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {5, 12})),
-       // irdft2d_eval_2_signal_size_positive_negative_axes
-       IRDFTParams(Shape{2, 5, 7, 2},
-                  Shape{2, 5, 12},
-                  ET,
-                  ET,
-                  input_data_5,
-                  expected_irdft2d_results_2,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, -1}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {5, 12})),
-       // irdft2d_eval_2_signal_size_negative_positive_axes
-       IRDFTParams(Shape{2, 5, 7, 2},
-                  Shape{2, 5, 12},
-                  ET,
-                  ET,
-                  input_data_5,
-                  expected_irdft2d_results_2,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {5, 12})),
-       // irdft2d_eval_2_signal_size_negative_negative_axes
-       IRDFTParams(Shape{2, 5, 7, 2},
-                  Shape{2, 5, 12},
-                  ET,
-                  ET,
-                  input_data_5,
-                  expected_irdft2d_results_2,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, -1}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {5, 12})),
-       // irdft3d_eval_1
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_6,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {0, 1, 2}),
-                  NULL),
-       // irdft3d_eval_1_negative_axes_and_signal_size
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{2, 10, 10},
-                  ET,
-                  ET,
-                  input_data_6,
-                  expected_irdft1d_results_1,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {-3, 1, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {-1, 10, -1})),
-       // irdft3d_eval_2
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{4, 5, 12},
-                  ET,
-                  ET,
-                  input_data_6,
-                  expected_irdft3d_results_2,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {0, 1, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {4, 5, 12})),
-       // irdft3d_eval_2_negative_axes
-       IRDFTParams(Shape{2, 10, 6, 2},
-                  Shape{4, 5, 12},
-                  ET,
-                  ET,
-                  input_data_6,
-                  expected_irdft3d_results_2,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {-3, -2, 2}),
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {4, 5, 12})),
-       // irdft3d_reversed_axes
-       IRDFTParams(Shape{3, 4, 8, 2},
-                  Shape{4, 4, 8},
-                  ET,
-                  ET,
-                  input_data_7,
-                  expected_irdft3d_results_3,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {2, 1, 0}),
-                  NULL),
-       // irdft3d_reversed_negative_axes
-       IRDFTParams(Shape{3, 4, 8, 2},
-                  Shape{4, 4, 8},
-                  ET,
-                  ET,
-                  input_data_7,
-                  expected_irdft3d_results_3,
-                  op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {-1, -2, -3}),
-                  NULL),
+        // irdft2d_eval_1_positive_negative_axes
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, -1}),
+                    NULL),
+        // irdft2d_eval_1_negative_positive_axes
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, 2}),
+                    NULL),
+        // irdft2d_eval_1_negative_negative_axes
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, -1}),
+                    NULL),
+        // irdft2d_eval_1_signal_size_0_s10_10
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, 10})),
+        // irdft2d_eval_1_signal_size_0_s10_10_positive_negative_axes
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, -1}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, 10})),
+        // irdft2d_eval_1_signal_size_0_s10_10_negative_positive_axes
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, 10})),
+        // irdft2d_eval_1_signal_size_0_s10_10_negative_negative_axes
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, -1}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, 10})),
+        // irdft2d_eval_1_signal_size_0_s10_m1
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {10, -1})),
+        // irdft2d_eval_1_signal_size_0_sm1_10
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-1, 10})),
+        // irdft2d_eval_1_signal_size_0_sm1_m1
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_4,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-1, -1})),
+        // irdft2d_eval_2_signal_size
+        IRDFTParams(Shape{2, 5, 7, 2},
+                    Shape{2, 5, 12},
+                    ET,
+                    ET,
+                    input_data_5,
+                    expected_irdft2d_results_2,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {5, 12})),
+        // irdft2d_eval_2_signal_size_positive_negative_axes
+        IRDFTParams(Shape{2, 5, 7, 2},
+                    Shape{2, 5, 12},
+                    ET,
+                    ET,
+                    input_data_5,
+                    expected_irdft2d_results_2,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {1, -1}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {5, 12})),
+        // irdft2d_eval_2_signal_size_negative_positive_axes
+        IRDFTParams(Shape{2, 5, 7, 2},
+                    Shape{2, 5, 12},
+                    ET,
+                    ET,
+                    input_data_5,
+                    expected_irdft2d_results_2,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {5, 12})),
+        // irdft2d_eval_2_signal_size_negative_negative_axes
+        IRDFTParams(Shape{2, 5, 7, 2},
+                    Shape{2, 5, 12},
+                    ET,
+                    ET,
+                    input_data_5,
+                    expected_irdft2d_results_2,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {-2, -1}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{2}, {5, 12})),
+        // irdft3d_eval_1
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_6,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {0, 1, 2}),
+                    NULL),
+        // irdft3d_eval_1_negative_axes_and_signal_size
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{2, 10, 10},
+                    ET,
+                    ET,
+                    input_data_6,
+                    expected_irdft1d_results_1,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {-3, 1, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {-1, 10, -1})),
+        // irdft3d_eval_2
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{4, 5, 12},
+                    ET,
+                    ET,
+                    input_data_6,
+                    expected_irdft3d_results_2,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {0, 1, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {4, 5, 12})),
+        // irdft3d_eval_2_negative_axes
+        IRDFTParams(Shape{2, 10, 6, 2},
+                    Shape{4, 5, 12},
+                    ET,
+                    ET,
+                    input_data_6,
+                    expected_irdft3d_results_2,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {-3, -2, 2}),
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {4, 5, 12})),
+        // irdft3d_reversed_axes
+        IRDFTParams(Shape{3, 4, 8, 2},
+                    Shape{4, 4, 8},
+                    ET,
+                    ET,
+                    input_data_7,
+                    expected_irdft3d_results_3,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {2, 1, 0}),
+                    NULL),
+        // irdft3d_reversed_negative_axes
+        IRDFTParams(Shape{3, 4, 8, 2},
+                    Shape{4, 4, 8},
+                    ET,
+                    ET,
+                    input_data_7,
+                    expected_irdft3d_results_3,
+                    op::v0::Constant::create<int64_t>(element::Type_t::i64, Shape{3}, {-1, -2, -3}),
+                    NULL),
         // irdft3d_reversed_axes_with_signals
         IRDFTParams(Shape{3, 4, 8, 2},
                     Shape{10, 3, 3},
@@ -813,9 +747,7 @@ std::vector<IRDFTParams> generateParamsForIRDFT() {
 }
 
 std::vector<IRDFTParams> generateCombinedParamsForIRDFT() {
-    const std::vector<std::vector<IRDFTParams>> allTypeParams{
-        generateParamsForIRDFT<element::Type_t::f32>()
-    };
+    const std::vector<std::vector<IRDFTParams>> allTypeParams{generateParamsForIRDFT<element::Type_t::f32>()};
 
     std::vector<IRDFTParams> combinedParams;
 
@@ -826,9 +758,8 @@ std::vector<IRDFTParams> generateCombinedParamsForIRDFT() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_IRDFT_With_Hardcoded_Refs,
-    ReferenceIRDFTLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForIRDFT()),
-    ReferenceIRDFTLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_IRDFT_With_Hardcoded_Refs,
+                         ReferenceIRDFTLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForIRDFT()),
+                         ReferenceIRDFTLayerTest::getTestCaseName);
 }  // namespace
\ No newline at end of file
diff --git a/src/plugins/template/tests/functional/op_reference/is_finite.cpp b/src/plugins/template/tests/functional/op_reference/is_finite.cpp
index dcd937786e9d26..479cd157038ec8 100644
--- a/src/plugins/template/tests/functional/op_reference/is_finite.cpp
+++ b/src/plugins/template/tests/functional/op_reference/is_finite.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/is_finite.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/is_finite.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,10 +16,10 @@ namespace {
 struct IsFiniteParams {
     template <class IT, class OT>
     IsFiniteParams(const PartialShape& shape,
-                  const element::Type& iType,
-                  const element::Type& oType,
-                  const std::vector<IT>& iValues,
-                  const std::vector<OT>& oValues)
+                   const element::Type& iType,
+                   const element::Type& oType,
+                   const std::vector<IT>& iValues,
+                   const std::vector<OT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(oType),
@@ -51,8 +53,8 @@ class ReferenceIsFiniteLayerTest : public testing::TestWithParam<IsFiniteParams>
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto is_finite = std::make_shared<op::v10::IsFinite>(in);
         return std::make_shared<Model>(NodeVector{is_finite}, ParameterVector{in});
@@ -70,16 +72,17 @@ std::vector<IsFiniteParams> generateParamsForIsFiniteFloat() {
 
     std::vector<IsFiniteParams> params{
         IsFiniteParams(ov::PartialShape{8},
-                       IN_ET, element::Type_t::boolean,
-                       std::vector<T>{std::numeric_limits<T>::infinity(), 0.0000f,
-                            std::numeric_limits<T>::max(), -0.5000f,
-                            -std::numeric_limits<T>::infinity(), 1.0000f,
-                            std::numeric_limits<T>::min(), std::nanf("")},
-                       std::vector<U>{false, true,
-                                      true, true,
-                                      false, true,
-                                      true, false})
-    };
+                       IN_ET,
+                       element::Type_t::boolean,
+                       std::vector<T>{std::numeric_limits<T>::infinity(),
+                                      0.0000f,
+                                      std::numeric_limits<T>::max(),
+                                      -0.5000f,
+                                      -std::numeric_limits<T>::infinity(),
+                                      1.0000f,
+                                      std::numeric_limits<T>::min(),
+                                      std::nanf("")},
+                       std::vector<U>{false, true, true, true, false, true, true, false})};
     return params;
 }
 
@@ -100,9 +103,8 @@ std::vector<IsFiniteParams> generateCombinedParamsForIsFinite() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_IsFinite_With_Hardcoded_Refs,
-    ReferenceIsFiniteLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForIsFinite()),
-    ReferenceIsFiniteLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_IsFinite_With_Hardcoded_Refs,
+                         ReferenceIsFiniteLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForIsFinite()),
+                         ReferenceIsFiniteLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/is_inf.cpp b/src/plugins/template/tests/functional/op_reference/is_inf.cpp
index 00437481be4803..83f4660c659255 100644
--- a/src/plugins/template/tests/functional/op_reference/is_inf.cpp
+++ b/src/plugins/template/tests/functional/op_reference/is_inf.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/is_inf.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/is_inf.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -60,9 +62,9 @@ class ReferenceIsInfLayerTest : public testing::TestWithParam<IsInfParams>, publ
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type,
-                                                    op::v10::IsInf::Attributes attrs) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type,
+                                                 op::v10::IsInf::Attributes attrs) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto is_inf = std::make_shared<op::v10::IsInf>(in, attrs);
         return std::make_shared<Model>(NodeVector{is_inf}, ParameterVector{in});
@@ -78,20 +80,20 @@ std::vector<IsInfParams> generateParamsForIsInfDefault() {
     using T = typename element_type_traits<IN_ET>::value_type;
     using U = typename element_type_traits<element::Type_t::boolean>::value_type;
     op::v10::IsInf::Attributes attrs{};
-    std::vector<IsInfParams> params{
-        IsInfParams("IsInfDefault", ov::PartialShape{8},
-                    IN_ET, element::Type_t::boolean,
-                    std::vector<T>{std::numeric_limits<T>::infinity(), 0.0000f,
-                                    std::numeric_limits<T>::max(), -0.5000f,
-                                    -std::numeric_limits<T>::infinity(), 1.0000f,
-                                    std::numeric_limits<T>::min(), std::nanf("")},
-                    std::vector<U>{true, false,
-                                    false, false,
-                                    true, false,
-                                    false, false},
-                    attrs
-        )
-    };
+    std::vector<IsInfParams> params{IsInfParams("IsInfDefault",
+                                                ov::PartialShape{8},
+                                                IN_ET,
+                                                element::Type_t::boolean,
+                                                std::vector<T>{std::numeric_limits<T>::infinity(),
+                                                               0.0000f,
+                                                               std::numeric_limits<T>::max(),
+                                                               -0.5000f,
+                                                               -std::numeric_limits<T>::infinity(),
+                                                               1.0000f,
+                                                               std::numeric_limits<T>::min(),
+                                                               std::nanf("")},
+                                                std::vector<U>{true, false, false, false, true, false, false, false},
+                                                attrs)};
     return params;
 }
 
@@ -101,20 +103,20 @@ std::vector<IsInfParams> generateParamsForIsInfPositive() {
     using U = typename element_type_traits<element::Type_t::boolean>::value_type;
     op::v10::IsInf::Attributes attrs{};
     attrs.detect_negative = false;
-    std::vector<IsInfParams> params{
-        IsInfParams("IsInfPositiveOnly", ov::PartialShape{8},
-                    IN_ET, element::Type_t::boolean,
-                    std::vector<T>{std::numeric_limits<T>::infinity(), 0.0000f,
-                                    std::numeric_limits<T>::max(), -0.5000f,
-                                    -std::numeric_limits<T>::infinity(), 1.0000f,
-                                    std::numeric_limits<T>::min(), std::nanf("")},
-                    std::vector<U>{true, false,
-                                    false, false,
-                                    false, false,
-                                    false, false},
-                    attrs
-        )
-    };
+    std::vector<IsInfParams> params{IsInfParams("IsInfPositiveOnly",
+                                                ov::PartialShape{8},
+                                                IN_ET,
+                                                element::Type_t::boolean,
+                                                std::vector<T>{std::numeric_limits<T>::infinity(),
+                                                               0.0000f,
+                                                               std::numeric_limits<T>::max(),
+                                                               -0.5000f,
+                                                               -std::numeric_limits<T>::infinity(),
+                                                               1.0000f,
+                                                               std::numeric_limits<T>::min(),
+                                                               std::nanf("")},
+                                                std::vector<U>{true, false, false, false, false, false, false, false},
+                                                attrs)};
     return params;
 }
 
@@ -124,20 +126,20 @@ std::vector<IsInfParams> generateParamsForIsInfNegative() {
     using U = typename element_type_traits<element::Type_t::boolean>::value_type;
     op::v10::IsInf::Attributes attrs{};
     attrs.detect_positive = false;
-    std::vector<IsInfParams> params{
-        IsInfParams("IsInfNegativeOnly", ov::PartialShape{8},
-                    IN_ET, element::Type_t::boolean,
-                    std::vector<T>{std::numeric_limits<T>::infinity(), 0.0000f,
-                                    std::numeric_limits<T>::max(), -0.5000f,
-                                    -std::numeric_limits<T>::infinity(), 1.0000f,
-                                    std::numeric_limits<T>::min(), std::nanf("")},
-                    std::vector<U>{false, false,
-                                    false, false,
-                                    true, false,
-                                    false, false},
-                    attrs
-        )
-    };
+    std::vector<IsInfParams> params{IsInfParams("IsInfNegativeOnly",
+                                                ov::PartialShape{8},
+                                                IN_ET,
+                                                element::Type_t::boolean,
+                                                std::vector<T>{std::numeric_limits<T>::infinity(),
+                                                               0.0000f,
+                                                               std::numeric_limits<T>::max(),
+                                                               -0.5000f,
+                                                               -std::numeric_limits<T>::infinity(),
+                                                               1.0000f,
+                                                               std::numeric_limits<T>::min(),
+                                                               std::nanf("")},
+                                                std::vector<U>{false, false, false, false, true, false, false, false},
+                                                attrs)};
     return params;
 }
 
@@ -148,20 +150,20 @@ std::vector<IsInfParams> generateParamsForIsInfNone() {
     op::v10::IsInf::Attributes attrs{};
     attrs.detect_negative = false;
     attrs.detect_positive = false;
-    std::vector<IsInfParams> params{
-        IsInfParams("IsInfDetectNone", ov::PartialShape{8},
-                    IN_ET, element::Type_t::boolean,
-                    std::vector<T>{std::numeric_limits<T>::infinity(), 0.0000f,
-                                    std::numeric_limits<T>::max(), -0.5000f,
-                                    -std::numeric_limits<T>::infinity(), 1.0000f,
-                                    std::numeric_limits<T>::min(), std::nanf("")},
-                    std::vector<U>{false, false,
-                                    false, false,
-                                    false, false,
-                                    false, false},
-                    attrs
-        )
-    };
+    std::vector<IsInfParams> params{IsInfParams("IsInfDetectNone",
+                                                ov::PartialShape{8},
+                                                IN_ET,
+                                                element::Type_t::boolean,
+                                                std::vector<T>{std::numeric_limits<T>::infinity(),
+                                                               0.0000f,
+                                                               std::numeric_limits<T>::max(),
+                                                               -0.5000f,
+                                                               -std::numeric_limits<T>::infinity(),
+                                                               1.0000f,
+                                                               std::numeric_limits<T>::min(),
+                                                               std::nanf("")},
+                                                std::vector<U>{false, false, false, false, false, false, false, false},
+                                                attrs)};
     return params;
 }
 
@@ -194,9 +196,8 @@ std::vector<IsInfParams> generateCombinedParamsForIsInf() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_IsInf_With_Hardcoded_Refs,
-    ReferenceIsInfLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForIsInf()),
-    ReferenceIsInfLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_IsInf_With_Hardcoded_Refs,
+                         ReferenceIsInfLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForIsInf()),
+                         ReferenceIsInfLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/is_nan.cpp b/src/plugins/template/tests/functional/op_reference/is_nan.cpp
index edc00e26c11f9c..d8163b0587703c 100644
--- a/src/plugins/template/tests/functional/op_reference/is_nan.cpp
+++ b/src/plugins/template/tests/functional/op_reference/is_nan.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/is_nan.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/is_nan.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,10 +16,10 @@ namespace {
 struct IsNaNParams {
     template <class IT, class OT>
     IsNaNParams(const PartialShape& shape,
-                  const element::Type& iType,
-                  const element::Type& oType,
-                  const std::vector<IT>& iValues,
-                  const std::vector<OT>& oValues)
+                const element::Type& iType,
+                const element::Type& oType,
+                const std::vector<IT>& iValues,
+                const std::vector<OT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(oType),
@@ -51,8 +53,8 @@ class ReferenceIsNaNLayerTest : public testing::TestWithParam<IsNaNParams>, publ
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto is_nan = std::make_shared<op::v10::IsNaN>(in);
         return std::make_shared<Model>(NodeVector{is_nan}, ParameterVector{in});
@@ -68,18 +70,18 @@ std::vector<IsNaNParams> generateParamsForIsNaNFloat() {
     using T = typename element_type_traits<IN_ET>::value_type;
     using U = typename element_type_traits<element::Type_t::boolean>::value_type;
 
-    std::vector<IsNaNParams> params{
-        IsNaNParams(ov::PartialShape{8},
-                       IN_ET, element::Type_t::boolean,
-                       std::vector<T>{std::numeric_limits<T>::infinity(), 0.0000f,
-                            std::numeric_limits<T>::max(), -0.5000f,
-                            -std::numeric_limits<T>::infinity(), 1.0000f,
-                            std::numeric_limits<T>::min(), std::nanf("")},
-                       std::vector<U>{false, false,
-                          false, false,
-                          false, false,
-                          false, true})
-    };
+    std::vector<IsNaNParams> params{IsNaNParams(ov::PartialShape{8},
+                                                IN_ET,
+                                                element::Type_t::boolean,
+                                                std::vector<T>{std::numeric_limits<T>::infinity(),
+                                                               0.0000f,
+                                                               std::numeric_limits<T>::max(),
+                                                               -0.5000f,
+                                                               -std::numeric_limits<T>::infinity(),
+                                                               1.0000f,
+                                                               std::numeric_limits<T>::min(),
+                                                               std::nanf("")},
+                                                std::vector<U>{false, false, false, false, false, false, false, true})};
     return params;
 }
 
@@ -100,9 +102,8 @@ std::vector<IsNaNParams> generateCombinedParamsForIsNaN() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_IsNaN_With_Hardcoded_Refs,
-    ReferenceIsNaNLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForIsNaN()),
-    ReferenceIsNaNLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_IsNaN_With_Hardcoded_Refs,
+                         ReferenceIsNaNLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForIsNaN()),
+                         ReferenceIsNaNLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/less.cpp b/src/plugins/template/tests/functional/op_reference/less.cpp
index 0c540020de8700..0ec6fbe0dd2e94 100644
--- a/src/plugins/template/tests/functional/op_reference/less.cpp
+++ b/src/plugins/template/tests/functional/op_reference/less.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/less.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/less.hpp"
 #include "comparison.hpp"
 
 using namespace ov;
@@ -16,43 +17,43 @@ namespace {
 template <element::Type_t IN_ET>
 std::vector<RefComparisonParams> generateComparisonParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RefComparisonParams> compParams {
+    std::vector<RefComparisonParams> compParams{
         // 1D // 2D // 3D // 4D
-        Builder {}
+        Builder{}
             .compType(ComparisonTypes::LESS)
-            .input1({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .input2({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {0, 0, 0, 0}}),
-        Builder {}
+            .input1({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .input2({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{0, 0, 0, 0}}),
+        Builder{}
             .compType(ComparisonTypes::LESS)
-            .input1({{2, 3}, type, std::vector<T> {0, 6, 45, 1, 21, 21}})
-            .input2({{2, 3}, type, std::vector<T> {1, 18, 23, 1, 19, 21}})
-            .expected({{2, 3}, element::boolean, std::vector<char> {1, 1, 0, 0, 0, 0}}),
-        Builder {}
+            .input1({{2, 3}, type, std::vector<T>{0, 6, 45, 1, 21, 21}})
+            .input2({{2, 3}, type, std::vector<T>{1, 18, 23, 1, 19, 21}})
+            .expected({{2, 3}, element::boolean, std::vector<char>{1, 1, 0, 0, 0, 0}}),
+        Builder{}
             .compType(ComparisonTypes::LESS)
-            .input1({{1}, type, std::vector<T> {53}})
-            .input2({{1}, type, std::vector<T> {53}})
-            .expected({{1}, element::boolean, std::vector<char> {0}}),
-        Builder {}
+            .input1({{1}, type, std::vector<T>{53}})
+            .input2({{1}, type, std::vector<T>{53}})
+            .expected({{1}, element::boolean, std::vector<char>{0}}),
+        Builder{}
             .compType(ComparisonTypes::LESS)
-            .input1({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 1, 5, 11, 8}})
-            .input2({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 10, 5, 11, 8}})
-            .expected({{2, 4}, element::boolean, std::vector<char> {0, 0, 0, 0, 1, 0, 0, 0}}),
-        Builder {}
+            .input1({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 1, 5, 11, 8}})
+            .input2({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 10, 5, 11, 8}})
+            .expected({{2, 4}, element::boolean, std::vector<char>{0, 0, 0, 0, 1, 0, 0, 0}}),
+        Builder{}
             .compType(ComparisonTypes::LESS)
-            .input1({{3, 1, 2}, type, std::vector<T> {2, 1, 4, 1, 3, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{3, 2, 2}, element::boolean, std::vector<char> {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}),
-        Builder {}
+            .input1({{3, 1, 2}, type, std::vector<T>{2, 1, 4, 1, 3, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{3, 2, 2}, element::boolean, std::vector<char>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}),
+        Builder{}
             .compType(ComparisonTypes::LESS)
-            .input1({{2, 1, 2, 1}, type, std::vector<T> {2, 1, 4, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {0, 0, 0, 0}})};
+            .input1({{2, 1, 2, 1}, type, std::vector<T>{2, 1, 4, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{0, 0, 0, 0}})};
     return compParams;
 }
 
 std::vector<RefComparisonParams> generateComparisonCombinedParams() {
-    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams{
         generateComparisonParams<element::Type_t::f32>(element::f32),
         generateComparisonParams<element::Type_t::f16>(element::f16),
         generateComparisonParams<element::Type_t::i32>(element::i32),
@@ -66,8 +67,10 @@ std::vector<RefComparisonParams> generateComparisonCombinedParams() {
     return combinedParams;
 }
 
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateComparisonCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs,
+                         ReferenceComparisonLayerTest,
+                         ::testing::ValuesIn(generateComparisonCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
-} // namespace ComparisonOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ComparisonOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/less_eq.cpp b/src/plugins/template/tests/functional/op_reference/less_eq.cpp
index 4e6122dd8bbc4c..183068ac519e93 100644
--- a/src/plugins/template/tests/functional/op_reference/less_eq.cpp
+++ b/src/plugins/template/tests/functional/op_reference/less_eq.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/less_eq.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/less_eq.hpp"
 #include "comparison.hpp"
 
 using namespace ov;
@@ -16,43 +17,43 @@ namespace {
 template <element::Type_t IN_ET>
 std::vector<RefComparisonParams> generateComparisonParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RefComparisonParams> compParams {
+    std::vector<RefComparisonParams> compParams{
         // 1D // 2D // 3D // 4D
-        Builder {}
+        Builder{}
             .compType(ComparisonTypes::LESS_EQUAL)
-            .input1({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .input2({{2, 2}, type, std::vector<T> {0, 12, 23, 0}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {1, 1, 1, 1}}),
-        Builder {}
+            .input1({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .input2({{2, 2}, type, std::vector<T>{0, 12, 23, 0}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{1, 1, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::LESS_EQUAL)
-            .input1({{2, 3}, type, std::vector<T> {0, 6, 45, 1, 21, 21}})
-            .input2({{2, 3}, type, std::vector<T> {1, 18, 23, 1, 19, 21}})
-            .expected({{2, 3}, element::boolean, std::vector<char> {1, 1, 0, 1, 0, 1}}),
-        Builder {}
+            .input1({{2, 3}, type, std::vector<T>{0, 6, 45, 1, 21, 21}})
+            .input2({{2, 3}, type, std::vector<T>{1, 18, 23, 1, 19, 21}})
+            .expected({{2, 3}, element::boolean, std::vector<char>{1, 1, 0, 1, 0, 1}}),
+        Builder{}
             .compType(ComparisonTypes::LESS_EQUAL)
-            .input1({{1}, type, std::vector<T> {53}})
-            .input2({{1}, type, std::vector<T> {53}})
-            .expected({{1}, element::boolean, std::vector<char> {1}}),
-        Builder {}
+            .input1({{1}, type, std::vector<T>{53}})
+            .input2({{1}, type, std::vector<T>{53}})
+            .expected({{1}, element::boolean, std::vector<char>{1}}),
+        Builder{}
             .compType(ComparisonTypes::LESS_EQUAL)
-            .input1({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 1, 5, 11, 8}})
-            .input2({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 10, 5, 11, 8}})
-            .expected({{2, 4}, element::boolean, std::vector<char> {1, 1, 1, 1, 1, 1, 1, 1}}),
-        Builder {}
+            .input1({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 1, 5, 11, 8}})
+            .input2({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 10, 5, 11, 8}})
+            .expected({{2, 4}, element::boolean, std::vector<char>{1, 1, 1, 1, 1, 1, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::LESS_EQUAL)
-            .input1({{3, 1, 2}, type, std::vector<T> {2, 1, 4, 1, 3, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{3, 2, 2}, element::boolean, std::vector<char> {0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1}}),
-        Builder {}
+            .input1({{3, 1, 2}, type, std::vector<T>{2, 1, 4, 1, 3, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{3, 2, 2}, element::boolean, std::vector<char>{0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1}}),
+        Builder{}
             .compType(ComparisonTypes::LESS_EQUAL)
-            .input1({{2, 1, 2, 1}, type, std::vector<T> {2, 1, 4, 1}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {0, 1, 0, 1}})};
+            .input1({{2, 1, 2, 1}, type, std::vector<T>{2, 1, 4, 1}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{0, 1, 0, 1}})};
     return compParams;
 }
 
 std::vector<RefComparisonParams> generateComparisonCombinedParams() {
-    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams{
         generateComparisonParams<element::Type_t::f32>(element::f32),
         generateComparisonParams<element::Type_t::f16>(element::f16),
         generateComparisonParams<element::Type_t::i32>(element::i32),
@@ -66,8 +67,10 @@ std::vector<RefComparisonParams> generateComparisonCombinedParams() {
     return combinedParams;
 }
 
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateComparisonCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs,
+                         ReferenceComparisonLayerTest,
+                         ::testing::ValuesIn(generateComparisonCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
-} // namespace ComparisonOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ComparisonOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/log.cpp b/src/plugins/template/tests/functional/op_reference/log.cpp
index 1c4d8b09892585..792db8892982cc 100644
--- a/src/plugins/template/tests/functional/op_reference/log.cpp
+++ b/src/plugins/template/tests/functional/op_reference/log.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/log.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/log.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,9 +16,9 @@ namespace {
 struct LogParams {
     template <class IT>
     LogParams(const PartialShape& shape,
-                const element::Type& iType,
-                const std::vector<IT>& iValues,
-                const std::vector<IT>& oValues)
+              const element::Type& iType,
+              const std::vector<IT>& iValues,
+              const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -50,8 +52,8 @@ class ReferenceLogLayerTest : public testing::TestWithParam<LogParams>, public C
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto log = std::make_shared<op::v0::Log>(in);
         return std::make_shared<Model>(NodeVector{log}, ParameterVector{in});
@@ -66,38 +68,36 @@ template <element::Type_t IN_ET>
 std::vector<LogParams> generateParamsForLog() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<LogParams> logParams{
-        LogParams(ov::PartialShape{8},
-                  IN_ET,
-                  std::vector<T>{0.125f, 0.25f, 0.5f, 1.f, 2.f, 4.f, 8.f, 16.f},
-                  std::vector<T>{-2.07944154f, -1.38629436f, -0.69314718f, 0.00000000f, 0.69314718f, 1.38629436f, 2.07944154f, 2.77258872f})
-    };
+    std::vector<LogParams> logParams{LogParams(ov::PartialShape{8},
+                                               IN_ET,
+                                               std::vector<T>{0.125f, 0.25f, 0.5f, 1.f, 2.f, 4.f, 8.f, 16.f},
+                                               std::vector<T>{-2.07944154f,
+                                                              -1.38629436f,
+                                                              -0.69314718f,
+                                                              0.00000000f,
+                                                              0.69314718f,
+                                                              1.38629436f,
+                                                              2.07944154f,
+                                                              2.77258872f})};
     return logParams;
 }
 
-
 template <element::Type_t IN_ET>
 std::vector<LogParams> generateParamsForLogInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     std::vector<LogParams> logParams{
-        LogParams(ov::PartialShape{4},
-                  IN_ET,
-                  std::vector<T>{10, 100, 1000, 10000},
-                  std::vector<T>{2, 4, 6, 9})
-    };
+        LogParams(ov::PartialShape{4}, IN_ET, std::vector<T>{10, 100, 1000, 10000}, std::vector<T>{2, 4, 6, 9})};
     return logParams;
 }
 
 std::vector<LogParams> generateCombinedParamsForLog() {
-    const std::vector<std::vector<LogParams>> allTypeParams{
-        generateParamsForLog<element::Type_t::f32>(),
-        generateParamsForLog<element::Type_t::f16>(),
-        generateParamsForLogInt<element::Type_t::i64>(),
-        generateParamsForLogInt<element::Type_t::i32>(),
-        generateParamsForLogInt<element::Type_t::u64>(),
-        generateParamsForLogInt<element::Type_t::u32>()
-    };
+    const std::vector<std::vector<LogParams>> allTypeParams{generateParamsForLog<element::Type_t::f32>(),
+                                                            generateParamsForLog<element::Type_t::f16>(),
+                                                            generateParamsForLogInt<element::Type_t::i64>(),
+                                                            generateParamsForLogInt<element::Type_t::i32>(),
+                                                            generateParamsForLogInt<element::Type_t::u64>(),
+                                                            generateParamsForLogInt<element::Type_t::u32>()};
 
     std::vector<LogParams> combinedParams;
 
@@ -108,10 +108,9 @@ std::vector<LogParams> generateCombinedParamsForLog() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Log_With_Hardcoded_Refs,
-    ReferenceLogLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForLog()),
-    ReferenceLogLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Log_With_Hardcoded_Refs,
+                         ReferenceLogLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForLog()),
+                         ReferenceLogLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/log_softmax.cpp b/src/plugins/template/tests/functional/op_reference/log_softmax.cpp
index d449e0bcfaf439..1d834f6ff71cfb 100644
--- a/src/plugins/template/tests/functional/op_reference/log_softmax.cpp
+++ b/src/plugins/template/tests/functional/op_reference/log_softmax.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/log_softmax.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/log_softmax.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -14,8 +15,11 @@ using namespace InferenceEngine;
 namespace {
 struct LogSoftmaxParams {
     template <class IT>
-    LogSoftmaxParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
-                const int64_t axis)
+    LogSoftmaxParams(const ov::PartialShape& shape,
+                     const ov::element::Type& iType,
+                     const std::vector<IT>& iValues,
+                     const std::vector<IT>& oValues,
+                     const int64_t axis)
         : axis(axis),
           pshape(shape),
           inType(iType),
@@ -51,11 +55,13 @@ class ReferenceLogSoftmaxLayerTest : public testing::TestWithParam<LogSoftmaxPar
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type, const int64_t axis) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type,
+                                                 const int64_t axis) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto LogSoftmax = std::make_shared<op::v5::LogSoftmax>(in, axis);
-        return std::make_shared<ov::Model>(NodeVector {LogSoftmax}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{LogSoftmax}, ParameterVector{in});
     }
 };
 
@@ -67,173 +73,171 @@ template <element::Type_t IN_ET>
 std::vector<LogSoftmaxParams> generateLogSoftmaxFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<LogSoftmaxParams> logSoftmaxParams {
-        LogSoftmaxParams(ov::PartialShape {1},
-                    IN_ET,
-                    std::vector<T>{1},
-                    std::vector<T>{0},
-                    0),
-        LogSoftmaxParams(ov::PartialShape {2, 4},
-                    IN_ET,
-                    std::vector<T>{0, 1, 2, 3, 10000, 10001, 10002, 10003},
-                    std::vector<T>{-10000., -10000., -10000., -10000., 0., 0., 0., 0.},
-                    0),
-        LogSoftmaxParams(ov::PartialShape {2, 4},
-                    IN_ET,
-                    std::vector<T>{0, 1, 2, 3, 10000, 10001, 10002, 10003},
-                    std::vector<T>{-3.4401896, -2.4401896, -1.4401897, -0.4401897, -3.4401896, -2.4401896, -1.4401897, -0.4401897},
-                    1),
-        LogSoftmaxParams(ov::PartialShape {2, 4},
-                    IN_ET,
-                    std::vector<T>{0, 1, 2, 3, 10000, 10001, 10002, 10003},
-                    std::vector<T>{-3.4401896, -2.4401896, -1.4401897, -0.4401897, -3.4401896, -2.4401896, -1.4401897, -0.4401897},
-                    -1),
-        LogSoftmaxParams(ov::PartialShape {2, 4},
-                    IN_ET,
-                    std::vector<T>{0, 1, 2, 3, 10000, 10001, 10002, 10003},
-                    std::vector<T>{-10000., -10000., -10000., -10000., 0., 0., 0., 0.},
-                    -2),
-        LogSoftmaxParams(ov::PartialShape {3, 2, 3},
-                    IN_ET,
-                    std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
-                    std::vector<T>{-12.0024818,
-                                   -12.0024818,
-                                   -12.0024818,
-                                   -12.0024818,
-                                   -12.0024818,
-                                   -12.0024818,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03},
-                    0),
-        LogSoftmaxParams(ov::PartialShape {3, 2, 3},
-                    IN_ET,
-                    std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
-                    std::vector<T>{-3.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -0.04858735},
-                    1),
-        LogSoftmaxParams(ov::PartialShape {3, 2, 3},
-                    IN_ET,
-                    std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
-                    std::vector<T>{-2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596},
-                    2),
-        LogSoftmaxParams(ov::PartialShape {3, 2, 3},
-                    IN_ET,
-                    std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
-                    std::vector<T>{-2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596,
-                                   -2.40760596,
-                                   -1.40760596,
-                                   -0.40760596},
-                    -1),
-        LogSoftmaxParams(ov::PartialShape {3, 2, 3},
-                    IN_ET,
-                    std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
-                    std::vector<T>{-3.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -3.04858735,
-                                   -0.04858735,
-                                   -0.04858735,
-                                   -0.04858735},
-                    -2),
-        LogSoftmaxParams(ov::PartialShape {3, 2, 3},
-                    IN_ET,
-                    std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
-                    std::vector<T>{-12.0024818,
-                                   -12.0024818,
-                                   -12.0024818,
-                                   -12.0024818,
-                                   -12.0024818,
-                                   -12.0024818,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -6.00248181,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03,
-                                   -2.48181414e-03},
-                    -3)
-    };
+    std::vector<LogSoftmaxParams> logSoftmaxParams{
+        LogSoftmaxParams(ov::PartialShape{1}, IN_ET, std::vector<T>{1}, std::vector<T>{0}, 0),
+        LogSoftmaxParams(ov::PartialShape{2, 4},
+                         IN_ET,
+                         std::vector<T>{0, 1, 2, 3, 10000, 10001, 10002, 10003},
+                         std::vector<T>{-10000., -10000., -10000., -10000., 0., 0., 0., 0.},
+                         0),
+        LogSoftmaxParams(
+            ov::PartialShape{2, 4},
+            IN_ET,
+            std::vector<T>{0, 1, 2, 3, 10000, 10001, 10002, 10003},
+            std::vector<
+                T>{-3.4401896, -2.4401896, -1.4401897, -0.4401897, -3.4401896, -2.4401896, -1.4401897, -0.4401897},
+            1),
+        LogSoftmaxParams(
+            ov::PartialShape{2, 4},
+            IN_ET,
+            std::vector<T>{0, 1, 2, 3, 10000, 10001, 10002, 10003},
+            std::vector<
+                T>{-3.4401896, -2.4401896, -1.4401897, -0.4401897, -3.4401896, -2.4401896, -1.4401897, -0.4401897},
+            -1),
+        LogSoftmaxParams(ov::PartialShape{2, 4},
+                         IN_ET,
+                         std::vector<T>{0, 1, 2, 3, 10000, 10001, 10002, 10003},
+                         std::vector<T>{-10000., -10000., -10000., -10000., 0., 0., 0., 0.},
+                         -2),
+        LogSoftmaxParams(ov::PartialShape{3, 2, 3},
+                         IN_ET,
+                         std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
+                         std::vector<T>{-12.0024818,
+                                        -12.0024818,
+                                        -12.0024818,
+                                        -12.0024818,
+                                        -12.0024818,
+                                        -12.0024818,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03},
+                         0),
+        LogSoftmaxParams(ov::PartialShape{3, 2, 3},
+                         IN_ET,
+                         std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
+                         std::vector<T>{-3.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -0.04858735},
+                         1),
+        LogSoftmaxParams(ov::PartialShape{3, 2, 3},
+                         IN_ET,
+                         std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
+                         std::vector<T>{-2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596},
+                         2),
+        LogSoftmaxParams(ov::PartialShape{3, 2, 3},
+                         IN_ET,
+                         std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
+                         std::vector<T>{-2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596,
+                                        -2.40760596,
+                                        -1.40760596,
+                                        -0.40760596},
+                         -1),
+        LogSoftmaxParams(ov::PartialShape{3, 2, 3},
+                         IN_ET,
+                         std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
+                         std::vector<T>{-3.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -3.04858735,
+                                        -0.04858735,
+                                        -0.04858735,
+                                        -0.04858735},
+                         -2),
+        LogSoftmaxParams(ov::PartialShape{3, 2, 3},
+                         IN_ET,
+                         std::vector<T>{-9, -8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, 8},
+                         std::vector<T>{-12.0024818,
+                                        -12.0024818,
+                                        -12.0024818,
+                                        -12.0024818,
+                                        -12.0024818,
+                                        -12.0024818,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -6.00248181,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03,
+                                        -2.48181414e-03},
+                         -3)};
     return logSoftmaxParams;
 }
 
 std::vector<LogSoftmaxParams> generateLogSoftmaxCombinedParams() {
-    const std::vector<std::vector<LogSoftmaxParams>> logSoftmaxTypeParams {
+    const std::vector<std::vector<LogSoftmaxParams>> logSoftmaxTypeParams{
         generateLogSoftmaxFloatParams<element::Type_t::f32>(),
-        generateLogSoftmaxFloatParams<element::Type_t::f16>()
-        };
+        generateLogSoftmaxFloatParams<element::Type_t::f16>()};
     std::vector<LogSoftmaxParams> combinedParams;
 
     for (const auto& params : logSoftmaxTypeParams) {
@@ -242,7 +246,9 @@ std::vector<LogSoftmaxParams> generateLogSoftmaxCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_LogSoftmax_With_Hardcoded_Refs, ReferenceLogSoftmaxLayerTest,
-    testing::ValuesIn(generateLogSoftmaxCombinedParams()), ReferenceLogSoftmaxLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_LogSoftmax_With_Hardcoded_Refs,
+                         ReferenceLogSoftmaxLayerTest,
+                         testing::ValuesIn(generateLogSoftmaxCombinedParams()),
+                         ReferenceLogSoftmaxLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/logical.hpp b/src/plugins/template/tests/functional/op_reference/logical.hpp
index f5bd6c0e9a3413..894b262bcb6115 100644
--- a/src/plugins/template/tests/functional/op_reference/logical.hpp
+++ b/src/plugins/template/tests/functional/op_reference/logical.hpp
@@ -5,7 +5,6 @@
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
-
 #include "openvino/op/logical_and.hpp"
 #include "openvino/op/logical_not.hpp"
 #include "openvino/op/logical_or.hpp"
@@ -16,12 +15,7 @@ using namespace ov;
 namespace reference_tests {
 namespace LogicalOpsRefTestDefinitions {
 
-enum LogicalTypes {
-    LOGICAL_AND,
-    LOGICAL_OR,
-    LOGICAL_XOR,
-    LOGICAL_NOT
-};
+enum LogicalTypes { LOGICAL_AND, LOGICAL_OR, LOGICAL_XOR, LOGICAL_NOT };
 
 struct RefLogicalParams {
     LogicalTypes opType;
@@ -49,7 +43,7 @@ class ReferenceLogicalLayerTest : public testing::TestWithParam<RefLogicalParams
         const auto& param = obj.param;
         std::ostringstream result;
         result << "LogicalType=" << param.opType << "_";
-        for (size_t i =0; i< param.inputs.size(); i++) {
+        for (size_t i = 0; i < param.inputs.size(); i++) {
             const auto input = param.inputs[i];
             result << "inpt_shape" << i << "=" << input.shape << "_";
             result << "inpt_type" << i << "=" << input.type << "_";
@@ -59,7 +53,8 @@ class ReferenceLogicalLayerTest : public testing::TestWithParam<RefLogicalParams
     }
 
 private:
-    static std::shared_ptr<ov::Model> CreateFunction(LogicalTypes op_type, const std::vector<reference_tests::Tensor>& inputs) {
+    static std::shared_ptr<ov::Model> CreateFunction(LogicalTypes op_type,
+                                                     const std::vector<reference_tests::Tensor>& inputs) {
         ov::ParameterVector params_vec;
         for (auto& input : inputs) {
             params_vec.push_back(std::make_shared<op::v0::Parameter>(input.type, input.shape));
@@ -86,8 +81,8 @@ class ReferenceLogicalLayerTest : public testing::TestWithParam<RefLogicalParams
         default: {
             throw std::runtime_error("Incorrect type of Logical operation");
         }
-    }
-        return std::make_shared<ov::Model>(ov::NodeVector {logical_op}, ov::ParameterVector {params_vec});
+        }
+        return std::make_shared<ov::Model>(ov::NodeVector{logical_op}, ov::ParameterVector{params_vec});
     }
 };
 }  // namespace LogicalOpsRefTestDefinitions
diff --git a/src/plugins/template/tests/functional/op_reference/logical_and.cpp b/src/plugins/template/tests/functional/op_reference/logical_and.cpp
index 254b3e0c8d86ef..a4ec39b1249d0e 100644
--- a/src/plugins/template/tests/functional/op_reference/logical_and.cpp
+++ b/src/plugins/template/tests/functional/op_reference/logical_and.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/logical_and.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/logical_and.hpp"
 #include "logical.hpp"
 
 using namespace ov;
@@ -14,26 +15,34 @@ namespace LogicalOpsRefTestDefinitions {
 namespace {
 
 std::vector<RefLogicalParams> generateLogicalParams() {
-    std::vector<RefLogicalParams> logicalParams {
-        Builder {}
+    std::vector<RefLogicalParams> logicalParams{
+        Builder{}
             .opType(LogicalTypes::LOGICAL_AND)
-            .inputs({{{2, 2}, element::boolean, std::vector<char> {true, false, true, false}},
-                     {{2, 2}, element::boolean, std::vector<char> {false, true, true, false}}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {false, false, true, false}}),
-        Builder {}
+            .inputs({{{2, 2}, element::boolean, std::vector<char>{true, false, true, false}},
+                     {{2, 2}, element::boolean, std::vector<char>{false, true, true, false}}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{false, false, true, false}}),
+        Builder{}
             .opType(LogicalTypes::LOGICAL_AND)
-            .inputs({{{2, 1, 2, 1}, element::boolean, std::vector<char> {true, false, true, false}},
-                     {{1, 1, 2, 1}, element::boolean, std::vector<char> {true, false}}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {true, false, true, false}}),
-        Builder {}
+            .inputs({{{2, 1, 2, 1}, element::boolean, std::vector<char>{true, false, true, false}},
+                     {{1, 1, 2, 1}, element::boolean, std::vector<char>{true, false}}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{true, false, true, false}}),
+        Builder{}
             .opType(LogicalTypes::LOGICAL_AND)
-            .inputs({{{3, 4}, element::boolean, std::vector<char> {true, true, true, true, true, false, true, false, false, true, true, true}},
-                     {{3, 4}, element::boolean, std::vector<char> {true, true, true, true, true, false, true, false, false, true, true, false}}})
-            .expected({{3, 4}, element::boolean, std::vector<char> {true, true, true, true, true, false, true, false, false, true, true, false}})};
+            .inputs({{{3, 4},
+                      element::boolean,
+                      std::vector<char>{true, true, true, true, true, false, true, false, false, true, true, true}},
+                     {{3, 4},
+                      element::boolean,
+                      std::vector<char>{true, true, true, true, true, false, true, false, false, true, true, false}}})
+            .expected({{3, 4},
+                       element::boolean,
+                       std::vector<char>{true, true, true, true, true, false, true, false, false, true, true, false}})};
     return logicalParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_LogicalAnd_With_Hardcoded_Refs, ReferenceLogicalLayerTest, ::testing::ValuesIn(generateLogicalParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_LogicalAnd_With_Hardcoded_Refs,
+                         ReferenceLogicalLayerTest,
+                         ::testing::ValuesIn(generateLogicalParams()),
                          ReferenceLogicalLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/logical_not.cpp b/src/plugins/template/tests/functional/op_reference/logical_not.cpp
index fb63207d99a6b1..4a596416d856a1 100644
--- a/src/plugins/template/tests/functional/op_reference/logical_not.cpp
+++ b/src/plugins/template/tests/functional/op_reference/logical_not.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/logical_not.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/logical_not.hpp"
 #include "logical.hpp"
 
 using namespace ov;
@@ -14,15 +15,17 @@ namespace LogicalOpsRefTestDefinitions {
 namespace {
 
 std::vector<RefLogicalParams> generateLogicalParams() {
-    std::vector<RefLogicalParams> logicalParams {
-        Builder {}
+    std::vector<RefLogicalParams> logicalParams{
+        Builder{}
             .opType(LogicalTypes::LOGICAL_NOT)
-            .inputs({{{2, 2}, element::boolean, std::vector<char> {true, false, true, false}}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {false, true, false, true}})};
+            .inputs({{{2, 2}, element::boolean, std::vector<char>{true, false, true, false}}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{false, true, false, true}})};
     return logicalParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_LogicalNot_With_Hardcoded_Refs, ReferenceLogicalLayerTest, ::testing::ValuesIn(generateLogicalParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_LogicalNot_With_Hardcoded_Refs,
+                         ReferenceLogicalLayerTest,
+                         ::testing::ValuesIn(generateLogicalParams()),
                          ReferenceLogicalLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/logical_or.cpp b/src/plugins/template/tests/functional/op_reference/logical_or.cpp
index 34249cfea693e9..db0021acc1f09e 100644
--- a/src/plugins/template/tests/functional/op_reference/logical_or.cpp
+++ b/src/plugins/template/tests/functional/op_reference/logical_or.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/logical_or.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/logical_or.hpp"
 #include "logical.hpp"
 
 using namespace ov;
@@ -14,26 +15,34 @@ namespace LogicalOpsRefTestDefinitions {
 namespace {
 
 std::vector<RefLogicalParams> generateLogicalParams() {
-    std::vector<RefLogicalParams> logicalParams {
-        Builder {}
+    std::vector<RefLogicalParams> logicalParams{
+        Builder{}
             .opType(LogicalTypes::LOGICAL_OR)
-            .inputs({{{2, 2}, element::boolean, std::vector<char> {true, false, true, false}},
-                     {{2, 2}, element::boolean, std::vector<char> {false, true, true, false}}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {true, true, true, false}}),
-        Builder {}
+            .inputs({{{2, 2}, element::boolean, std::vector<char>{true, false, true, false}},
+                     {{2, 2}, element::boolean, std::vector<char>{false, true, true, false}}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{true, true, true, false}}),
+        Builder{}
             .opType(LogicalTypes::LOGICAL_OR)
-            .inputs({{{2, 1, 2, 1}, element::boolean, std::vector<char> {true, false, true, false}},
-                     {{1, 1, 2, 1}, element::boolean, std::vector<char> {true, false}}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {true, false, true, false}}),
-        Builder {}
+            .inputs({{{2, 1, 2, 1}, element::boolean, std::vector<char>{true, false, true, false}},
+                     {{1, 1, 2, 1}, element::boolean, std::vector<char>{true, false}}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{true, false, true, false}}),
+        Builder{}
             .opType(LogicalTypes::LOGICAL_OR)
-            .inputs({{{3, 4}, element::boolean, std::vector<char> {true, true, true, true, true, false, true, false, false, true, true, true}},
-                     {{3, 4}, element::boolean, std::vector<char> {true, true, true, true, true, true, true, false, false, true, true, false}}})
-            .expected({{3, 4}, element::boolean, std::vector<char> {true, true, true, true, true, true, true, false, false, true, true, true}})};
+            .inputs({{{3, 4},
+                      element::boolean,
+                      std::vector<char>{true, true, true, true, true, false, true, false, false, true, true, true}},
+                     {{3, 4},
+                      element::boolean,
+                      std::vector<char>{true, true, true, true, true, true, true, false, false, true, true, false}}})
+            .expected({{3, 4},
+                       element::boolean,
+                       std::vector<char>{true, true, true, true, true, true, true, false, false, true, true, true}})};
     return logicalParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_LogicalOr_With_Hardcoded_Refs, ReferenceLogicalLayerTest, ::testing::ValuesIn(generateLogicalParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_LogicalOr_With_Hardcoded_Refs,
+                         ReferenceLogicalLayerTest,
+                         ::testing::ValuesIn(generateLogicalParams()),
                          ReferenceLogicalLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/logical_xor.cpp b/src/plugins/template/tests/functional/op_reference/logical_xor.cpp
index 30be39f2e77359..20d07a28a482d1 100644
--- a/src/plugins/template/tests/functional/op_reference/logical_xor.cpp
+++ b/src/plugins/template/tests/functional/op_reference/logical_xor.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/logical_xor.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/logical_xor.hpp"
 #include "logical.hpp"
 
 using namespace ov;
@@ -14,26 +15,35 @@ namespace LogicalOpsRefTestDefinitions {
 namespace {
 
 std::vector<RefLogicalParams> generateLogicalParams() {
-    std::vector<RefLogicalParams> logicalParams {
-        Builder {}
+    std::vector<RefLogicalParams> logicalParams{
+        Builder{}
             .opType(LogicalTypes::LOGICAL_XOR)
-            .inputs({{{2, 2}, element::boolean, std::vector<char> {true, false, true, false}},
-                     {{2, 2}, element::boolean, std::vector<char> {false, true, true, false}}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {true, true, false, false}}),
-        Builder {}
+            .inputs({{{2, 2}, element::boolean, std::vector<char>{true, false, true, false}},
+                     {{2, 2}, element::boolean, std::vector<char>{false, true, true, false}}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{true, true, false, false}}),
+        Builder{}
             .opType(LogicalTypes::LOGICAL_XOR)
-            .inputs({{{2, 1, 2, 1}, element::boolean, std::vector<char> {true, false, true, false}},
-                     {{1, 1, 2, 1}, element::boolean, std::vector<char> {true, false}}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {false, false, false, false}}),
-        Builder {}
+            .inputs({{{2, 1, 2, 1}, element::boolean, std::vector<char>{true, false, true, false}},
+                     {{1, 1, 2, 1}, element::boolean, std::vector<char>{true, false}}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{false, false, false, false}}),
+        Builder{}
             .opType(LogicalTypes::LOGICAL_XOR)
-            .inputs({{{3, 4}, element::boolean, std::vector<char> {true, true, true, true, true, false, true, false, false, true, true, true}},
-                     {{3, 4}, element::boolean, std::vector<char> {true, true, true, true, true, true, true, false, false, true, true, false}}})
-            .expected({{3, 4}, element::boolean, std::vector<char> {false, false, false, false, false, true, false, false, false, false, false, true}})};
+            .inputs({{{3, 4},
+                      element::boolean,
+                      std::vector<char>{true, true, true, true, true, false, true, false, false, true, true, true}},
+                     {{3, 4},
+                      element::boolean,
+                      std::vector<char>{true, true, true, true, true, true, true, false, false, true, true, false}}})
+            .expected(
+                {{3, 4},
+                 element::boolean,
+                 std::vector<char>{false, false, false, false, false, true, false, false, false, false, false, true}})};
     return logicalParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_LogicalOr_With_Hardcoded_Refs, ReferenceLogicalLayerTest, ::testing::ValuesIn(generateLogicalParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_LogicalOr_With_Hardcoded_Refs,
+                         ReferenceLogicalLayerTest,
+                         ::testing::ValuesIn(generateLogicalParams()),
                          ReferenceLogicalLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/loop.cpp b/src/plugins/template/tests/functional/op_reference/loop.cpp
index 3e7f9ad63b51bf..7ff49b7173f9ab 100644
--- a/src/plugins/template/tests/functional/op_reference/loop.cpp
+++ b/src/plugins/template/tests/functional/op_reference/loop.cpp
@@ -8,14 +8,11 @@
 #include <openvino/opsets/opset8.hpp>
 
 #include "base_reference_test.hpp"
-#include "functional_test_utils/skip_tests_config.hpp"
 #include "common_test_utils/common_utils.hpp"
+#include "functional_test_utils/skip_tests_config.hpp"
 
 namespace {
-enum LOOP_IN_TYPE {
-    INVARIANT,
-    MERGED
-};
+enum LOOP_IN_TYPE { INVARIANT, MERGED };
 
 struct LoopFunctionalBase {
     virtual std::shared_ptr<ov::Model> create_function(const std::vector<reference_tests::Tensor>& loop_inputs,
@@ -49,8 +46,8 @@ struct LoopDynamicInputs : public LoopFunctionalBase {
         // Body
         auto sum = std::make_shared<ov::opset8::Add>(Xi, Yi);
         auto Zo = std::make_shared<ov::opset8::Multiply>(sum, M_body);
-        auto body = std::make_shared<ov::Model>(ov::OutputVector{body_condition, Zo},
-                                                ov::ParameterVector{Xi, Yi, M_body});
+        auto body =
+            std::make_shared<ov::Model>(ov::OutputVector{body_condition, Zo}, ov::ParameterVector{Xi, Yi, M_body});
 
         auto loop = std::make_shared<ov::opset8::Loop>(trip_count, exec_condition);
         loop->set_function(body);
@@ -72,10 +69,10 @@ struct LoopParams {
                const std::vector<reference_tests::Tensor>& loop_inputs,
                const std::vector<reference_tests::Tensor>& expected_results,
                const std::string& test_case_name)
-            : function(functional),
-              inputs(loop_inputs),
-              expected_results(expected_results),
-              test_case_name(test_case_name) {}
+        : function(functional),
+          inputs(loop_inputs),
+          expected_results(expected_results),
+          test_case_name(test_case_name) {}
 
     std::shared_ptr<LoopFunctionalBase> function;
     std::vector<reference_tests::Tensor> inputs;
@@ -109,23 +106,22 @@ TEST_P(ReferenceLoopLayerTest, TensorIteratorWithHardcodedRefs) {
 }
 
 INSTANTIATE_TEST_SUITE_P(
-        smoke_TensorIterator_With_Hardcoded_Refs,
-        ReferenceLoopLayerTest,
-        ::testing::Values(
-                LoopParams(
-                        std::make_shared<LoopDynamicInputs>(),
-                        std::vector<reference_tests::Tensor>{
-                                reference_tests::Tensor(ov::element::f32, ov::Shape{2, 2}, std::vector<float>{0, 1, 2, 3}),
-                                reference_tests::Tensor(ov::element::f32, ov::Shape{2, 2}, std::vector<float>{1, 2, 3, 4}),
-                                reference_tests::Tensor(ov::element::f32, ov::Shape{2, 2}, std::vector<float>{5, 4, 3, 2})},
-                        // 5*(0+1)*(0+1)*(0+1) = 5
-                        // 4*(1+2)*(1+2)*(1+2) = 108
-                        // 3*(2+3)*(2+3)*(2+3) = 375
-                        // 2*(3+4)*(3+4)*(3+4) = 686
-                        std::vector<reference_tests::Tensor>{
-                                reference_tests::Tensor(ov::element::f32, ov::Shape{2, 2}, std::vector<float>{5, 108, 375, 686})},
-                        "loop_dynamic_inputs")),
-        ReferenceLoopLayerTest::getTestCaseName);
+    smoke_TensorIterator_With_Hardcoded_Refs,
+    ReferenceLoopLayerTest,
+    ::testing::Values(LoopParams(
+        std::make_shared<LoopDynamicInputs>(),
+        std::vector<reference_tests::Tensor>{
+            reference_tests::Tensor(ov::element::f32, ov::Shape{2, 2}, std::vector<float>{0, 1, 2, 3}),
+            reference_tests::Tensor(ov::element::f32, ov::Shape{2, 2}, std::vector<float>{1, 2, 3, 4}),
+            reference_tests::Tensor(ov::element::f32, ov::Shape{2, 2}, std::vector<float>{5, 4, 3, 2})},
+        // 5*(0+1)*(0+1)*(0+1) = 5
+        // 4*(1+2)*(1+2)*(1+2) = 108
+        // 3*(2+3)*(2+3)*(2+3) = 375
+        // 2*(3+4)*(3+4)*(3+4) = 686
+        std::vector<reference_tests::Tensor>{
+            reference_tests::Tensor(ov::element::f32, ov::Shape{2, 2}, std::vector<float>{5, 108, 375, 686})},
+        "loop_dynamic_inputs")),
+    ReferenceLoopLayerTest::getTestCaseName);
 
 struct LoopStaticInputs : public LoopFunctionalBase {
     std::shared_ptr<ov::Model> create_function(const std::vector<reference_tests::Tensor>& loop_inputs,
@@ -146,7 +142,8 @@ struct LoopStaticInputs : public LoopFunctionalBase {
             body_params.emplace_back(std::make_shared<ov::opset8::Parameter>(net_type, pshape));
         }
 
-        const auto body_condition_const = std::make_shared<ov::opset8::Constant>(ov::element::boolean, ov::Shape{1}, true);
+        const auto body_condition_const =
+            std::make_shared<ov::opset8::Constant>(ov::element::boolean, ov::Shape{1}, true);
         const auto exec_condition = std::make_shared<ov::opset8::Constant>(ov::element::boolean, ov::Shape{1}, true);
         std::shared_ptr<ov::Node> trip_count_input;
         trip_count_input = std::make_shared<ov::opset8::Constant>(ov::element::i64, ov::Shape{1}, trip_count);
@@ -157,8 +154,7 @@ struct LoopStaticInputs : public LoopFunctionalBase {
             Zo = std::make_shared<ov::opset8::Add>(body_params[i], Zo);
         }
 
-        const auto body = std::make_shared<ov::Model>(ov::OutputVector{body_condition_const, Zo},
-                                                       body_params);
+        const auto body = std::make_shared<ov::Model>(ov::OutputVector{body_condition_const, Zo}, body_params);
 
         const auto loop = std::make_shared<ov::opset8::Loop>(trip_count_input, exec_condition);
         loop->set_function(body);
@@ -184,27 +180,27 @@ struct LoopStaticInputs : public LoopFunctionalBase {
         const auto result0 = std::make_shared<ov::opset8::Result>(out0);
         const auto result1 = std::make_shared<ov::opset8::Result>(out1);
         const auto result2 = std::make_shared<ov::opset8::Result>(out2);
-        const auto function = std::make_shared<ov::Model>(ov::ResultVector{result0, result1, result2}, loop_params, "loop");
+        const auto function =
+            std::make_shared<ov::Model>(ov::ResultVector{result0, result1, result2}, loop_params, "loop");
         return function;
     }
 };
 
 struct LoopStaticParams {
-    LoopStaticParams(
-            const std::shared_ptr<LoopFunctionalBase>& functional,
-            const std::vector<reference_tests::Tensor>& loop_inputs,
-            const std::vector<reference_tests::Tensor>& expected_results,
-            const int64_t& trip_count,
-            const std::vector<LOOP_IN_TYPE>& loop_in_type,
-            const ov::element::Type& net_type,
-            const std::string& test_case_name)
-          : function(functional),
-            inputs(loop_inputs),
-            expected_results(expected_results),
-            trip_count(trip_count),
-            loop_in_type(loop_in_type),
-            net_type(net_type),
-            test_case_name(test_case_name) {}
+    LoopStaticParams(const std::shared_ptr<LoopFunctionalBase>& functional,
+                     const std::vector<reference_tests::Tensor>& loop_inputs,
+                     const std::vector<reference_tests::Tensor>& expected_results,
+                     const int64_t& trip_count,
+                     const std::vector<LOOP_IN_TYPE>& loop_in_type,
+                     const ov::element::Type& net_type,
+                     const std::string& test_case_name)
+        : function(functional),
+          inputs(loop_inputs),
+          expected_results(expected_results),
+          trip_count(trip_count),
+          loop_in_type(loop_in_type),
+          net_type(net_type),
+          test_case_name(test_case_name) {}
 
     std::shared_ptr<LoopFunctionalBase> function;
     std::vector<reference_tests::Tensor> inputs;
@@ -215,7 +211,8 @@ struct LoopStaticParams {
     std::string test_case_name;
 };
 
-class ReferenceLoopLayerStaticTest : public testing::TestWithParam<LoopStaticParams>, public reference_tests::CommonReferenceTest {
+class ReferenceLoopLayerStaticTest : public testing::TestWithParam<LoopStaticParams>,
+                                     public reference_tests::CommonReferenceTest {
 public:
     void SetUp() override {
         SKIP_IF_CURRENT_TEST_IS_DISABLED()
@@ -262,138 +259,110 @@ TEST_P(ReferenceLoopLayerStaticTest, CompareWithRefs) {
 template <ov::element::Type_t ET>
 std::vector<LoopStaticParams> generateParams() {
     using T = typename ov::element_type_traits<ET>::value_type;
-    std::vector<LoopStaticParams> params {
+    std::vector<LoopStaticParams> params{
         LoopStaticParams(
-                std::make_shared<LoopStaticInputs>(),
-                {reference_tests::Tensor(
-                        ET,
-                        {10, 1, 10},
-                        std::vector<T>{
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
-                            3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6,
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
-                            3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6,
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2}),
-                 reference_tests::Tensor(
-                        ET,
-                        {1, 1, 1},
-                        std::vector<T>{7}),
-                 reference_tests::Tensor(
-                        ET,
-                        {10, 1, 10},
-                        std::vector<T>{
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
-                            3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6,
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
-                            3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6,
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2})},
-                {reference_tests::Tensor(
-                        ov::element::Type_t::boolean,
-                        {1},
-                        std::vector<char>{1}),
-                 reference_tests::Tensor(
-                        ET,
-                        {10, 1, 10},
-                        std::vector<T>{
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
-                            13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
-                            13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11}),
-                 reference_tests::Tensor(
-                        ET,
-                        {10, 1, 10},
-                        std::vector<T>{
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
-                            13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
-                            13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11})},
-                1,
-                {LOOP_IN_TYPE::INVARIANT, LOOP_IN_TYPE::INVARIANT, LOOP_IN_TYPE::MERGED},
-                ET,
-                "loop_for_common"),
+            std::make_shared<LoopStaticInputs>(),
+            {reference_tests::Tensor(ET, {10, 1, 10}, std::vector<T>{7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7,
+                                                                     4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4,
+                                                                     5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5,
+                                                                     2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
+                                                                     3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3,
+                                                                     0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2}),
+             reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{7}),
+             reference_tests::Tensor(ET, {10, 1, 10}, std::vector<T>{7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7,
+                                                                     4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4,
+                                                                     5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5,
+                                                                     2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
+                                                                     3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3,
+                                                                     0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2})},
+            {reference_tests::Tensor(ov::element::Type_t::boolean, {1}, std::vector<char>{1}),
+             reference_tests::Tensor(
+                 ET,
+                 {10, 1, 10},
+                 std::vector<T>{21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
+                                13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
+                                21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
+                                13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
+                                21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11}),
+             reference_tests::Tensor(
+                 ET,
+                 {10, 1, 10},
+                 std::vector<T>{21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
+                                13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
+                                21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
+                                13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
+                                21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11})},
+            1,
+            {LOOP_IN_TYPE::INVARIANT, LOOP_IN_TYPE::INVARIANT, LOOP_IN_TYPE::MERGED},
+            ET,
+            "loop_for_common"),
 
         LoopStaticParams(
-                std::make_shared<LoopStaticInputs>(),
-                {reference_tests::Tensor(
-                        ET,
-                        {10, 1, 10},
-                        std::vector<T>{
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
-                            3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6,
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
-                            3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6,
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2}),
-                 reference_tests::Tensor(
-                        ET,
-                        {1, 1, 1},
-                        std::vector<T>{7}),
-                 reference_tests::Tensor(
-                        ET,
-                        {10, 1, 10},
-                        std::vector<T>{
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
-                            3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6,
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
-                            3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6,
-                            7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2})},
-                {reference_tests::Tensor(
-                        ov::element::Type_t::boolean,
-                        {1},
-                        std::vector<char>{1}),
-                 reference_tests::Tensor(
-                        ET,
-                        {10, 1, 10},
-                        std::vector<T>{
-                            77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47,
-                            53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71,
-                            77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47,
-                            53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71,
-                            77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47}),
-                 reference_tests::Tensor(
-                        ET,
-                        {10, 5, 10},
-                        std::vector<T>{
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 35, 26, 29, 20, 23, 14, 17, 32, 35, 26,
-                            49, 37, 41, 29, 33, 21, 25, 45, 49, 37, 63, 48, 53, 38, 43, 28, 33, 58, 63, 48,
-                            77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
-                            29, 20, 23, 14, 17, 32, 35, 26, 29, 20, 41, 29, 33, 21, 25, 45, 49, 37, 41, 29,
-                            53, 38, 43, 28, 33, 58, 63, 48, 53, 38, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47,
-
-                            13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  23, 14, 17, 32, 35, 26, 29, 20, 23, 14,
-                            33, 21, 25, 45, 49, 37, 41, 29, 33, 21, 43, 28, 33, 58, 63, 48, 53, 38, 43, 28,
-                            53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
-                            17, 32, 35, 26, 29, 20, 23, 14, 17, 32, 25, 45, 49, 37, 41, 29, 33, 21, 25, 45,
-                            33, 58, 63, 48, 53, 38, 43, 28, 33, 58, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71,
-
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 35, 26, 29, 20, 23, 14, 17, 32, 35, 26,
-                            49, 37, 41, 29, 33, 21, 25, 45, 49, 37, 63, 48, 53, 38, 43, 28, 33, 58, 63, 48,
-                            77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
-                            29, 20, 23, 14, 17, 32, 35, 26, 29, 20, 41, 29, 33, 21, 25, 45, 49, 37, 41, 29,
-                            53, 38, 43, 28, 33, 58, 63, 48, 53, 38, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47,
-
-                            13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  23, 14, 17, 32, 35, 26, 29, 20, 23, 14,
-                            33, 21, 25, 45, 49, 37, 41, 29, 33, 21, 43, 28, 33, 58, 63, 48, 53, 38, 43, 28,
-                            53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
-                            17, 32, 35, 26, 29, 20, 23, 14, 17, 32, 25, 45, 49, 37, 41, 29, 33, 21, 25, 45,
-                            33, 58, 63, 48, 53, 38, 43, 28, 33, 58, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71,
-
-                            21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 35, 26, 29, 20, 23, 14, 17, 32, 35, 26,
-                            49, 37, 41, 29, 33, 21, 25, 45, 49, 37, 63, 48, 53, 38, 43, 28, 33, 58, 63, 48,
-                            77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
-                            29, 20, 23, 14, 17, 32, 35, 26, 29, 20, 41, 29, 33, 21, 25, 45, 49, 37, 41, 29,
-                            53, 38, 43, 28, 33, 58, 63, 48, 53, 38, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47})},
-                5,
-                {LOOP_IN_TYPE::INVARIANT, LOOP_IN_TYPE::INVARIANT, LOOP_IN_TYPE::MERGED},
-                ET,
-               "loop_for_common"),
+            std::make_shared<LoopStaticInputs>(),
+            {reference_tests::Tensor(ET, {10, 1, 10}, std::vector<T>{7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7,
+                                                                     4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4,
+                                                                     5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5,
+                                                                     2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
+                                                                     3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3,
+                                                                     0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2}),
+             reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{7}),
+             reference_tests::Tensor(ET, {10, 1, 10}, std::vector<T>{7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7,
+                                                                     4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4,
+                                                                     5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5,
+                                                                     2, 3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2,
+                                                                     3, 0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2, 3,
+                                                                     0, 1, 6, 7, 4, 5, 2, 3, 0, 1, 6, 7, 4, 5, 2})},
+            {reference_tests::Tensor(ov::element::Type_t::boolean, {1}, std::vector<char>{1}),
+             reference_tests::Tensor(
+                 ET,
+                 {10, 1, 10},
+                 std::vector<T>{77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47,
+                                53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71,
+                                77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47,
+                                53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71,
+                                77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47}),
+             reference_tests::Tensor(
+                 ET,
+                 {10, 5, 10},
+                 std::vector<T>{21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 35, 26, 29, 20, 23, 14, 17, 32, 35, 26,
+                                49, 37, 41, 29, 33, 21, 25, 45, 49, 37, 63, 48, 53, 38, 43, 28, 33, 58, 63, 48,
+                                77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
+                                29, 20, 23, 14, 17, 32, 35, 26, 29, 20, 41, 29, 33, 21, 25, 45, 49, 37, 41, 29,
+                                53, 38, 43, 28, 33, 58, 63, 48, 53, 38, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47,
+
+                                13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  23, 14, 17, 32, 35, 26, 29, 20, 23, 14,
+                                33, 21, 25, 45, 49, 37, 41, 29, 33, 21, 43, 28, 33, 58, 63, 48, 53, 38, 43, 28,
+                                53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
+                                17, 32, 35, 26, 29, 20, 23, 14, 17, 32, 25, 45, 49, 37, 41, 29, 33, 21, 25, 45,
+                                33, 58, 63, 48, 53, 38, 43, 28, 33, 58, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71,
+
+                                21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 35, 26, 29, 20, 23, 14, 17, 32, 35, 26,
+                                49, 37, 41, 29, 33, 21, 25, 45, 49, 37, 63, 48, 53, 38, 43, 28, 33, 58, 63, 48,
+                                77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
+                                29, 20, 23, 14, 17, 32, 35, 26, 29, 20, 41, 29, 33, 21, 25, 45, 49, 37, 41, 29,
+                                53, 38, 43, 28, 33, 58, 63, 48, 53, 38, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47,
+
+                                13, 7,  9,  19, 21, 15, 17, 11, 13, 7,  23, 14, 17, 32, 35, 26, 29, 20, 23, 14,
+                                33, 21, 25, 45, 49, 37, 41, 29, 33, 21, 43, 28, 33, 58, 63, 48, 53, 38, 43, 28,
+                                53, 35, 41, 71, 77, 59, 65, 47, 53, 35, 9,  19, 21, 15, 17, 11, 13, 7,  9,  19,
+                                17, 32, 35, 26, 29, 20, 23, 14, 17, 32, 25, 45, 49, 37, 41, 29, 33, 21, 25, 45,
+                                33, 58, 63, 48, 53, 38, 43, 28, 33, 58, 41, 71, 77, 59, 65, 47, 53, 35, 41, 71,
+
+                                21, 15, 17, 11, 13, 7,  9,  19, 21, 15, 35, 26, 29, 20, 23, 14, 17, 32, 35, 26,
+                                49, 37, 41, 29, 33, 21, 25, 45, 49, 37, 63, 48, 53, 38, 43, 28, 33, 58, 63, 48,
+                                77, 59, 65, 47, 53, 35, 41, 71, 77, 59, 17, 11, 13, 7,  9,  19, 21, 15, 17, 11,
+                                29, 20, 23, 14, 17, 32, 35, 26, 29, 20, 41, 29, 33, 21, 25, 45, 49, 37, 41, 29,
+                                53, 38, 43, 28, 33, 58, 63, 48, 53, 38, 65, 47, 53, 35, 41, 71, 77, 59, 65, 47})},
+            5,
+            {LOOP_IN_TYPE::INVARIANT, LOOP_IN_TYPE::INVARIANT, LOOP_IN_TYPE::MERGED},
+            ET,
+            "loop_for_common"),
     };
     return params;
 }
 
 std::vector<LoopStaticParams> generateCombinedParams() {
-    const std::vector<std::vector<LoopStaticParams>> generatedParams {
+    const std::vector<std::vector<LoopStaticParams>> generatedParams{
         generateParams<ov::element::Type_t::i8>(),
         generateParams<ov::element::Type_t::i16>(),
         generateParams<ov::element::Type_t::i32>(),
@@ -414,6 +383,8 @@ std::vector<LoopStaticParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Loop_With_Hardcoded_Refs, ReferenceLoopLayerStaticTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceLoopLayerStaticTest::getTestCaseName);
-}
+INSTANTIATE_TEST_SUITE_P(smoke_Loop_With_Hardcoded_Refs,
+                         ReferenceLoopLayerStaticTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceLoopLayerStaticTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/lrn.cpp b/src/plugins/template/tests/functional/op_reference/lrn.cpp
index 273ec0d31c361e..4e18d69e1fa119 100644
--- a/src/plugins/template/tests/functional/op_reference/lrn.cpp
+++ b/src/plugins/template/tests/functional/op_reference/lrn.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/lrn.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/lrn.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -115,12 +116,12 @@ class ReferenceLRNLayerTest : public testing::TestWithParam<LRNParams>, public C
 
 private:
     static std::shared_ptr<Model> CreateFunction(const Shape& input_shape,
-                                                    const element::Type_t& input_type,
-                                                    const float& alpah,
-                                                    const float& beta,
-                                                    const float& bias,
-                                                    const size_t& size,
-                                                    const std::shared_ptr<op::v0::Constant>& axes) {
+                                                 const element::Type_t& input_type,
+                                                 const float& alpah,
+                                                 const float& beta,
+                                                 const float& bias,
+                                                 const size_t& size,
+                                                 const std::shared_ptr<op::v0::Constant>& axes) {
         auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
 
         std::shared_ptr<op::v0::LRN> lrn;
@@ -161,7 +162,10 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  0.5669467f,
                                  0.7784989f,
                                  0.7720487f},
-                  3, 0.5, 1, 3,
+                  3,
+                  0.5,
+                  1,
+                  3,
                   NULL),
         // lrn_across_h
         LRNParams(Shape{2, 3, 2, 1},
@@ -181,7 +185,10 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  0.7448453f,
                                  0.6711560f,
                                  0.7382717f},
-                  3, 0.5, 1, 3,
+                  3,
+                  0.5,
+                  1,
+                  3,
                   std::make_shared<op::v0::Constant>(element::Type_t::i64, Shape{1}, std::vector<int64_t>{2})),
         // lrn_across_hw
         LRNParams(Shape{2, 3, 2, 1},
@@ -201,7 +208,10 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  1.2813632f,
                                  1.1572751f,
                                  1.2730026f},
-                  3, 0.5, 1, 3,
+                  3,
+                  0.5,
+                  1,
+                  3,
                   std::make_shared<op::v0::Constant>(element::Type_t::i64, Shape{2}, std::vector<int64_t>{2, 3})),
         // lrn_across_all_dims
         LRNParams(Shape{2, 3, 2, 1},
@@ -221,7 +231,10 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  2.0256331f,
                                  2.4576957f,
                                  2.7034652f},
-                  3, 0.5, 1, 3,
+                  3,
+                  0.5,
+                  1,
+                  3,
                   std::make_shared<op::v0::Constant>(element::Type_t::i64, Shape{4}, std::vector<int64_t>{0, 1, 2, 3})),
         // lrn_across_nw
         LRNParams(Shape{2, 3, 2, 1},
@@ -241,7 +254,10 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  1.6164477f,
                                  1.5877683f,
                                  1.5608464f},
-                  3, 0.5, 1, 3,
+                  3,
+                  0.5,
+                  1,
+                  3,
                   std::make_shared<op::v0::Constant>(element::Type_t::i64, Shape{2}, std::vector<int64_t>{0, 3})),
         // lrn_across_empty
         LRNParams(Shape{2, 3, 2, 1},
@@ -261,7 +277,10 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  0.5761660f,
                                  0.5763904f,
                                  0.5765567f},
-                  3, 0.5, 1, 3,
+                  3,
+                  0.5,
+                  1,
+                  3,
                   std::make_shared<op::v0::Constant>(element::Type_t::i64, Shape{0}, std::vector<int64_t>{})),
         // lrn_6D_across_2_axes
         LRNParams(Shape{2, 3, 2, 2, 1, 1},
@@ -273,7 +292,10 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  0.9149914f, 1.0674900f, 0.7213357f, 0.8115027f, 0.9016696f, 0.9918366f,
                                  0.7656109f, 0.8294119f, 0.8932127f, 0.9570137f, 0.7892218f, 0.8385482f,
                                  0.8878745f, 0.9372009f, 0.8038679f, 0.8440613f, 0.8842546f, 0.9244481f},
-                  3, 0.5, 1, 3,
+                  3,
+                  0.5,
+                  1,
+                  3,
                   std::make_shared<op::v0::Constant>(element::Type_t::i64, Shape{2}, std::vector<int64_t>{2, 3})),
         // lrn_2d_across_empty
         LRNParams(Shape{12},
@@ -293,9 +315,12 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  0.5761660f,
                                  0.5763904f,
                                  0.5765566f},
-                  3, 0.5, 1, 3,
+                  3,
+                  0.5,
+                  1,
+                  3,
                   std::make_shared<op::v0::Constant>(element::Type_t::i64, Shape{0}, std::vector<int64_t>{})),
-                                     // lrn_2d_across_empty
+        // lrn_2d_across_empty
         LRNParams(Shape{6, 2},
                   Shape{6, 2},
                   ET,
@@ -324,7 +349,10 @@ std::vector<LRNParams> generateParamsForLRN() {
                                  -0.3425926f,
                                  0.3559732f,
                                  -0.7039225f},
-                  0.0002, 0.5, 2.0, 3,
+                  0.0002,
+                  0.5,
+                  2.0,
+                  3,
                   std::make_shared<op::v0::Constant>(element::Type_t::i64, Shape{1}, std::vector<int64_t>{0})),
     };
 
@@ -332,10 +360,8 @@ std::vector<LRNParams> generateParamsForLRN() {
 }
 
 std::vector<LRNParams> generateCombinedParamsForLRN() {
-    const std::vector<std::vector<LRNParams>> allTypeParams{
-        generateParamsForLRN<element::Type_t::f64>(),
-        generateParamsForLRN<element::Type_t::f32>()
-    };
+    const std::vector<std::vector<LRNParams>> allTypeParams{generateParamsForLRN<element::Type_t::f64>(),
+                                                            generateParamsForLRN<element::Type_t::f32>()};
 
     std::vector<LRNParams> combinedParams;
 
@@ -346,10 +372,9 @@ std::vector<LRNParams> generateCombinedParamsForLRN() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_LRN_With_Hardcoded_Refs,
-    ReferenceLRNLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForLRN()),
-    ReferenceLRNLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_LRN_With_Hardcoded_Refs,
+                         ReferenceLRNLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForLRN()),
+                         ReferenceLRNLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/lstm_cell.cpp b/src/plugins/template/tests/functional/op_reference/lstm_cell.cpp
index 22c7cf71fb6697..8df731e9f6f459 100644
--- a/src/plugins/template/tests/functional/op_reference/lstm_cell.cpp
+++ b/src/plugins/template/tests/functional/op_reference/lstm_cell.cpp
@@ -4,9 +4,9 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset4.hpp"
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
+#include "openvino/opsets/opset4.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -159,18 +159,17 @@ class ReferenceLSTMCellTestBiasClip : public ReferenceLSTMCellTest {
         const auto C_t = std::make_shared<opset1::Parameter>(params.C_t.type, params.C_t.shape);
         const auto B = std::make_shared<opset1::Parameter>(params.B.type, params.B.shape);
 
-        const auto lstm_cell =
-            std::make_shared<opset4::LSTMCell>(X,
-                                               H_t,
-                                               C_t,
-                                               W,
-                                               R,
-                                               B,
-                                               params.hiddenSize,
-                                               std::vector<std::string>{"sigmoid", "tanh", "tanh"},
-                                               std::vector<float>{},
-                                               std::vector<float>{},
-                                               clip_threshold);
+        const auto lstm_cell = std::make_shared<opset4::LSTMCell>(X,
+                                                                  H_t,
+                                                                  C_t,
+                                                                  W,
+                                                                  R,
+                                                                  B,
+                                                                  params.hiddenSize,
+                                                                  std::vector<std::string>{"sigmoid", "tanh", "tanh"},
+                                                                  std::vector<float>{},
+                                                                  std::vector<float>{},
+                                                                  clip_threshold);
 
         auto function = std::make_shared<Model>(lstm_cell->outputs(), ParameterVector{X, H_t, C_t, W, R, B});
         return function;
@@ -243,7 +242,13 @@ class ReferenceLSTMCellV1TestBiasClip : public ReferenceLSTMCellTestBiasClip {
         threshold = 1e-1f;
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.X.data, params.H_t.data, params.C_t.data, params.W.data, params.R.data, params.B.data, params.P.data};
+        inputData = {params.X.data,
+                     params.H_t.data,
+                     params.C_t.data,
+                     params.W.data,
+                     params.R.data,
+                     params.B.data,
+                     params.P.data};
         refOutData = {params.Ho.data, params.Co.data};
     }
 
@@ -259,21 +264,20 @@ class ReferenceLSTMCellV1TestBiasClip : public ReferenceLSTMCellTestBiasClip {
         const auto B = std::make_shared<opset1::Parameter>(params.B.type, params.B.shape);
         const auto P = std::make_shared<opset1::Parameter>(params.P.type, params.P.shape);
 
-        const auto lstm_cell =
-            std::make_shared<opset1::LSTMCell>(X,
-                                               H_t,
-                                               C_t,
-                                               W,
-                                               R,
-                                               B,
-                                               P,
-                                               params.hiddenSize,
-                                               op::LSTMWeightsFormat::FICO,
-                                               std::vector<std::string>{"sigmoid", "tanh", "tanh"},
-                                               std::vector<float>{},
-                                               std::vector<float>{},
-                                               clip_threshold,
-                                               false);
+        const auto lstm_cell = std::make_shared<opset1::LSTMCell>(X,
+                                                                  H_t,
+                                                                  C_t,
+                                                                  W,
+                                                                  R,
+                                                                  B,
+                                                                  P,
+                                                                  params.hiddenSize,
+                                                                  op::LSTMWeightsFormat::FICO,
+                                                                  std::vector<std::string>{"sigmoid", "tanh", "tanh"},
+                                                                  std::vector<float>{},
+                                                                  std::vector<float>{},
+                                                                  clip_threshold,
+                                                                  false);
 
         auto function = std::make_shared<Model>(lstm_cell->outputs(), ParameterVector{X, H_t, C_t, W, R, B, P});
         return function;
@@ -295,43 +299,59 @@ TEST_P(ReferenceLSTMCellV1TestBiasClip, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<LSTMCellParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<LSTMCellParams> params {
-        Builder {}
-        .batchSize(2)
-        .inputSize(3)
-        .hiddenSize(3)
-        .gatesCount(4)
-        .X(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
-        .W(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
-            9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
-            6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
-            8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
-            5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
-            3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
-        .R(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            0.0987983f, 0.52032113f, 0.5848073f, 0.5356095f, 0.74497133f, 0.73260087f,
-            0.1700787f, 0.45684233f, 0.1495722f, 0.42734373f, 0.4433832f, 0.25906256f,
-            0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
-            0.6881257f, 0.8170279f, 0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
-            0.86843914f, 0.45967972f, 0.6237719f, 0.11074839f, 0.6029616f, 0.3149305f,
-            0.46504205f, 0.5843412f, 0.8733427f, 0.7687243f, 0.07074859f, 0.39188156f}))
-        .H_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
-        .C_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
-        .B(reference_tests::Tensor(ET, {4 * 3}, std::vector<T>(4 * 3, 0.f)))
-        .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
-        .Ho(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.81457126f, 0.61109227f, 0.769522f, 0.52239674f, 0.4324641f, 0.63183f}))
-        .Co(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1.4444952f, 0.9635685f, 1.2875274f, 0.8053419f, 0.7184521f, 0.95803297f}))
-        .testcaseName("lstm_cell_zero_bias_default_attrs")
-    };
+    std::vector<LSTMCellParams> params{
+        Builder{}
+            .batchSize(2)
+            .inputSize(3)
+            .hiddenSize(3)
+            .gatesCount(4)
+            .X(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
+            .W(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{
+                    3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
+                    9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
+                    6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
+                    8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
+                    5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
+                    3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
+            .R(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
+                               0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
+                               0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
+                               0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
+                               0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
+                               0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
+            .H_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
+            .C_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
+            .B(reference_tests::Tensor(ET, {4 * 3}, std::vector<T>(4 * 3, 0.f)))
+            .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
+            .Ho(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.81457126f, 0.61109227f, 0.769522f, 0.52239674f, 0.4324641f, 0.63183f}))
+            .Co(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{1.4444952f, 0.9635685f, 1.2875274f, 0.8053419f, 0.7184521f, 0.95803297f}))
+            .testcaseName("lstm_cell_zero_bias_default_attrs")};
     return params;
 }
 
 std::vector<LSTMCellParams> generateCombinedParams() {
-    const std::vector<std::vector<LSTMCellParams>> generatedParams {
+    const std::vector<std::vector<LSTMCellParams>> generatedParams{
         generateParams<element::Type_t::bf16>(),
         generateParams<element::Type_t::f16>(),
         generateParams<element::Type_t::f32>(),
@@ -348,64 +368,81 @@ std::vector<LSTMCellParams> generateCombinedParams() {
 template <element::Type_t ET>
 std::vector<LSTMCellParams> generateParamsBiasDefaultAttrs() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<LSTMCellParams> params {
-        Builder {}
-        .batchSize(2)
-        .inputSize(3)
-        .hiddenSize(3)
-        .gatesCount(4)
-        .X(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
-        .W(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
-            9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
-            6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
-            8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
-            5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
-            3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
-        .R(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
-            0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
-            0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
-            0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
-            0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
-            0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
-        .H_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
-        .C_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
-        .B(reference_tests::Tensor(ET, {4 * 3}, std::vector<T>{1.07393714f,
-                                              1.15248052f,
-                                              1.16671345f,
-                                              0.21450312f,
-                                              1.2380678f,
-                                              1.51688835f,
-                                              0.46718366f,
-                                              0.91810346f,
-                                              1.1274234f,
-                                              0.51022074f,
-                                              1.11389844f,
-                                              0.74174305f}))
-        .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
-        .Ho(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.81014400720596313,
-                                              0.76665538549423218,
-                                              0.82509011030197144,
-                                              0.6479143500328064,
-                                              0.66586339473724365,
-                                              0.74838578701019287}))
-        .Co(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1.6800162792205811,
-                                              1.1150213479995728,
-                                              1.4578367471694946,
-                                              1.0649888515472412,
-                                              0.93761754035949707,
-                                              1.3659683465957642}))
-        .testcaseName("lstm_cell_bias_default_attrs"),
+    std::vector<LSTMCellParams> params{
+        Builder{}
+            .batchSize(2)
+            .inputSize(3)
+            .hiddenSize(3)
+            .gatesCount(4)
+            .X(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
+            .W(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{
+                    3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
+                    9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
+                    6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
+                    8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
+                    5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
+                    3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
+            .R(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
+                               0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
+                               0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
+                               0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
+                               0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
+                               0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
+            .H_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
+            .C_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
+            .B(reference_tests::Tensor(ET,
+                                       {4 * 3},
+                                       std::vector<T>{1.07393714f,
+                                                      1.15248052f,
+                                                      1.16671345f,
+                                                      0.21450312f,
+                                                      1.2380678f,
+                                                      1.51688835f,
+                                                      0.46718366f,
+                                                      0.91810346f,
+                                                      1.1274234f,
+                                                      0.51022074f,
+                                                      1.11389844f,
+                                                      0.74174305f}))
+            .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
+            .Ho(reference_tests::Tensor(ET,
+                                        {2, 3},
+                                        std::vector<T>{0.81014400720596313,
+                                                       0.76665538549423218,
+                                                       0.82509011030197144,
+                                                       0.6479143500328064,
+                                                       0.66586339473724365,
+                                                       0.74838578701019287}))
+            .Co(reference_tests::Tensor(ET,
+                                        {2, 3},
+                                        std::vector<T>{1.6800162792205811,
+                                                       1.1150213479995728,
+                                                       1.4578367471694946,
+                                                       1.0649888515472412,
+                                                       0.93761754035949707,
+                                                       1.3659683465957642}))
+            .testcaseName("lstm_cell_bias_default_attrs"),
     };
     return params;
 }
 
 std::vector<LSTMCellParams> generateCombinedParamsBiasDefaultAttrs() {
-    const std::vector<std::vector<LSTMCellParams>> generatedParams {
+    const std::vector<std::vector<LSTMCellParams>> generatedParams{
         generateParamsBiasDefaultAttrs<element::Type_t::bf16>(),
         generateParamsBiasDefaultAttrs<element::Type_t::f16>(),
         generateParamsBiasDefaultAttrs<element::Type_t::f32>(),
@@ -422,64 +459,81 @@ std::vector<LSTMCellParams> generateCombinedParamsBiasDefaultAttrs() {
 template <element::Type_t ET>
 std::vector<LSTMCellParams> generateParamsBiasClip() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<LSTMCellParams> params {
-        Builder {}
-        .batchSize(2)
-        .inputSize(3)
-        .hiddenSize(3)
-        .gatesCount(4)
-        .X(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
-        .W(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
-            9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
-            6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
-            8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
-            5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
-            3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
-        .R(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
-            0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
-            0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
-            0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
-            0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
-            0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
-        .H_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
-        .C_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
-        .B(reference_tests::Tensor(ET, {4 * 3}, std::vector<T>{1.07393714f,
-                                              1.15248052f,
-                                              1.16671345f,
-                                              0.21450312f,
-                                              1.2380678f,
-                                              1.51688835f,
-                                              0.46718366f,
-                                              0.91810346f,
-                                              1.1274234f,
-                                              0.51022074f,
-                                              1.11389844f,
-                                              0.74174305f}))
-        .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
-        .Ho(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.81014400720596313,
-                                              0.76665538549423218,
-                                              0.82387429475784302,
-                                              0.6479143500328064,
-                                              0.66586339473724365,
-                                              0.74838578701019287}))
-        .Co(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1.6800162792205811,
-                                              1.1150213479995728,
-                                              1.4510968923568726,
-                                              1.0649888515472412,
-                                              0.93761754035949707,
-                                              1.3659683465957642}))
-        .testcaseName("lstm_cell_bias_clip"),
+    std::vector<LSTMCellParams> params{
+        Builder{}
+            .batchSize(2)
+            .inputSize(3)
+            .hiddenSize(3)
+            .gatesCount(4)
+            .X(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
+            .W(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{
+                    3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
+                    9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
+                    6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
+                    8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
+                    5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
+                    3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
+            .R(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
+                               0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
+                               0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
+                               0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
+                               0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
+                               0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
+            .H_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
+            .C_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
+            .B(reference_tests::Tensor(ET,
+                                       {4 * 3},
+                                       std::vector<T>{1.07393714f,
+                                                      1.15248052f,
+                                                      1.16671345f,
+                                                      0.21450312f,
+                                                      1.2380678f,
+                                                      1.51688835f,
+                                                      0.46718366f,
+                                                      0.91810346f,
+                                                      1.1274234f,
+                                                      0.51022074f,
+                                                      1.11389844f,
+                                                      0.74174305f}))
+            .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
+            .Ho(reference_tests::Tensor(ET,
+                                        {2, 3},
+                                        std::vector<T>{0.81014400720596313,
+                                                       0.76665538549423218,
+                                                       0.82387429475784302,
+                                                       0.6479143500328064,
+                                                       0.66586339473724365,
+                                                       0.74838578701019287}))
+            .Co(reference_tests::Tensor(ET,
+                                        {2, 3},
+                                        std::vector<T>{1.6800162792205811,
+                                                       1.1150213479995728,
+                                                       1.4510968923568726,
+                                                       1.0649888515472412,
+                                                       0.93761754035949707,
+                                                       1.3659683465957642}))
+            .testcaseName("lstm_cell_bias_clip"),
     };
     return params;
 }
 
 std::vector<LSTMCellParams> generateCombinedParamsBiasClip() {
-    const std::vector<std::vector<LSTMCellParams>> generatedParams {
+    const std::vector<std::vector<LSTMCellParams>> generatedParams{
         generateParamsBiasClip<element::Type_t::bf16>(),
         generateParamsBiasClip<element::Type_t::f16>(),
         generateParamsBiasClip<element::Type_t::f32>(),
@@ -493,55 +547,77 @@ std::vector<LSTMCellParams> generateCombinedParamsBiasClip() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_LSTMCell_With_Hardcoded_Refs, ReferenceLSTMCellTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceLSTMCellTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_LSTMCell_With_Hardcoded_Refs,
+                         ReferenceLSTMCellTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceLSTMCellTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_LSTMCell_With_Hardcoded_Refs, ReferenceLSTMCellTestBiasDefaultAttrs,
-    testing::ValuesIn(generateCombinedParamsBiasDefaultAttrs()), ReferenceLSTMCellTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_LSTMCell_With_Hardcoded_Refs,
+                         ReferenceLSTMCellTestBiasDefaultAttrs,
+                         testing::ValuesIn(generateCombinedParamsBiasDefaultAttrs()),
+                         ReferenceLSTMCellTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_LSTMCell_With_Hardcoded_Refs, ReferenceLSTMCellTestBiasClip,
-    testing::ValuesIn(generateCombinedParamsBiasClip()), ReferenceLSTMCellTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_LSTMCell_With_Hardcoded_Refs,
+                         ReferenceLSTMCellTestBiasClip,
+                         testing::ValuesIn(generateCombinedParamsBiasClip()),
+                         ReferenceLSTMCellTest::getTestCaseName);
 
 template <element::Type_t ET>
 std::vector<LSTMCellParams> generateParamsV1() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<LSTMCellParams> params {
-        Builder {}
-        .batchSize(2)
-        .inputSize(3)
-        .hiddenSize(3)
-        .gatesCount(4)
-        .X(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
-        .W(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
-            9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
-            6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
-            8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
-            5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
-            3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
-        .R(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            0.0987983f, 0.52032113f, 0.5848073f, 0.5356095f, 0.74497133f, 0.73260087f,
-            0.1700787f, 0.45684233f, 0.1495722f, 0.42734373f, 0.4433832f, 0.25906256f,
-            0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
-            0.6881257f, 0.8170279f, 0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
-            0.86843914f, 0.45967972f, 0.6237719f, 0.11074839f, 0.6029616f, 0.3149305f,
-            0.46504205f, 0.5843412f, 0.8733427f, 0.7687243f, 0.07074859f, 0.39188156f}))
-        .H_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
-        .C_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
-        .B(reference_tests::Tensor(ET, {4 * 3}, std::vector<T>(4 * 3, 0.f)))
-        .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
-        .Ho(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.81457126f, 0.61109227f, 0.769522f, 0.52239674f, 0.4324641f, 0.63183f}))
-        .Co(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1.4444952f, 0.9635685f, 1.2875274f, 0.8053419f, 0.7184521f, 0.95803297f}))
-        .testcaseName("lstm_cell_v1_zero_bias_default_attrs")
-    };
+    std::vector<LSTMCellParams> params{
+        Builder{}
+            .batchSize(2)
+            .inputSize(3)
+            .hiddenSize(3)
+            .gatesCount(4)
+            .X(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
+            .W(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{
+                    3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
+                    9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
+                    6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
+                    8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
+                    5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
+                    3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
+            .R(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
+                               0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
+                               0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
+                               0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
+                               0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
+                               0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
+            .H_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
+            .C_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
+            .B(reference_tests::Tensor(ET, {4 * 3}, std::vector<T>(4 * 3, 0.f)))
+            .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
+            .Ho(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.81457126f, 0.61109227f, 0.769522f, 0.52239674f, 0.4324641f, 0.63183f}))
+            .Co(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{1.4444952f, 0.9635685f, 1.2875274f, 0.8053419f, 0.7184521f, 0.95803297f}))
+            .testcaseName("lstm_cell_v1_zero_bias_default_attrs")};
     return params;
 }
 
 std::vector<LSTMCellParams> generateCombinedParamsV1() {
-    const std::vector<std::vector<LSTMCellParams>> generatedParams {
+    const std::vector<std::vector<LSTMCellParams>> generatedParams{
         generateParamsV1<element::Type_t::bf16>(),
         generateParamsV1<element::Type_t::f16>(),
         generateParamsV1<element::Type_t::f32>(),
@@ -558,64 +634,81 @@ std::vector<LSTMCellParams> generateCombinedParamsV1() {
 template <element::Type_t ET>
 std::vector<LSTMCellParams> generateParamsBiasDefaultAttrsV1() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<LSTMCellParams> params {
-        Builder {}
-        .batchSize(2)
-        .inputSize(3)
-        .hiddenSize(3)
-        .gatesCount(4)
-        .X(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
-        .W(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
-            9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
-            6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
-            8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
-            5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
-            3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
-        .R(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
-            0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
-            0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
-            0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
-            0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
-            0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
-        .H_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
-        .C_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
-        .B(reference_tests::Tensor(ET, {4 * 3}, std::vector<T>{1.07393714f,
-                                              1.15248052f,
-                                              1.16671345f,
-                                              0.21450312f,
-                                              1.2380678f,
-                                              1.51688835f,
-                                              0.46718366f,
-                                              0.91810346f,
-                                              1.1274234f,
-                                              0.51022074f,
-                                              1.11389844f,
-                                              0.74174305f}))
-        .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
-        .Ho(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.81014400720596313,
-                                              0.76665538549423218,
-                                              0.82509011030197144,
-                                              0.6479143500328064,
-                                              0.66586339473724365,
-                                              0.74838578701019287}))
-        .Co(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1.6800162792205811,
-                                              1.1150213479995728,
-                                              1.4578367471694946,
-                                              1.0649888515472412,
-                                              0.93761754035949707,
-                                              1.3659683465957642}))
-        .testcaseName("lstm_cell_v1_bias_default_attrs"),
+    std::vector<LSTMCellParams> params{
+        Builder{}
+            .batchSize(2)
+            .inputSize(3)
+            .hiddenSize(3)
+            .gatesCount(4)
+            .X(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
+            .W(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{
+                    3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
+                    9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
+                    6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
+                    8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
+                    5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
+                    3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
+            .R(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
+                               0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
+                               0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
+                               0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
+                               0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
+                               0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
+            .H_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
+            .C_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
+            .B(reference_tests::Tensor(ET,
+                                       {4 * 3},
+                                       std::vector<T>{1.07393714f,
+                                                      1.15248052f,
+                                                      1.16671345f,
+                                                      0.21450312f,
+                                                      1.2380678f,
+                                                      1.51688835f,
+                                                      0.46718366f,
+                                                      0.91810346f,
+                                                      1.1274234f,
+                                                      0.51022074f,
+                                                      1.11389844f,
+                                                      0.74174305f}))
+            .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
+            .Ho(reference_tests::Tensor(ET,
+                                        {2, 3},
+                                        std::vector<T>{0.81014400720596313,
+                                                       0.76665538549423218,
+                                                       0.82509011030197144,
+                                                       0.6479143500328064,
+                                                       0.66586339473724365,
+                                                       0.74838578701019287}))
+            .Co(reference_tests::Tensor(ET,
+                                        {2, 3},
+                                        std::vector<T>{1.6800162792205811,
+                                                       1.1150213479995728,
+                                                       1.4578367471694946,
+                                                       1.0649888515472412,
+                                                       0.93761754035949707,
+                                                       1.3659683465957642}))
+            .testcaseName("lstm_cell_v1_bias_default_attrs"),
     };
     return params;
 }
 
 std::vector<LSTMCellParams> generateCombinedParamsBiasDefaultAttrsV1() {
-    const std::vector<std::vector<LSTMCellParams>> generatedParams {
+    const std::vector<std::vector<LSTMCellParams>> generatedParams{
         generateParamsBiasDefaultAttrsV1<element::Type_t::bf16>(),
         generateParamsBiasDefaultAttrsV1<element::Type_t::f16>(),
         generateParamsBiasDefaultAttrsV1<element::Type_t::f32>(),
@@ -632,64 +725,81 @@ std::vector<LSTMCellParams> generateCombinedParamsBiasDefaultAttrsV1() {
 template <element::Type_t ET>
 std::vector<LSTMCellParams> generateParamsBiasClipV1() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<LSTMCellParams> params {
-        Builder {}
-        .batchSize(2)
-        .inputSize(3)
-        .hiddenSize(3)
-        .gatesCount(4)
-        .X(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
-        .W(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
-            9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
-            6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
-            8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
-            5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
-            3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
-        .R(reference_tests::Tensor(ET, {4 * 3, 3}, std::vector<T>{
-            0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
-            0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
-            0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
-            0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
-            0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
-            0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
-        .H_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
-        .C_t(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-            0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
-        .B(reference_tests::Tensor(ET, {4 * 3}, std::vector<T>{1.07393714f,
-                                              1.15248052f,
-                                              1.16671345f,
-                                              0.21450312f,
-                                              1.2380678f,
-                                              1.51688835f,
-                                              0.46718366f,
-                                              0.91810346f,
-                                              1.1274234f,
-                                              0.51022074f,
-                                              1.11389844f,
-                                              0.74174305f}))
-        .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
-        .Ho(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.81014400720596313,
-                                              0.76665538549423218,
-                                              0.82387429475784302,
-                                              0.6479143500328064,
-                                              0.66586339473724365,
-                                              0.74838578701019287}))
-        .Co(reference_tests::Tensor(ET, {2, 3}, std::vector<T>{1.6800162792205811,
-                                              1.1150213479995728,
-                                              1.4510968923568726,
-                                              1.0649888515472412,
-                                              0.93761754035949707,
-                                              1.3659683465957642}))
-        .testcaseName("lstm_cell_v1_bias_clip"),
+    std::vector<LSTMCellParams> params{
+        Builder{}
+            .batchSize(2)
+            .inputSize(3)
+            .hiddenSize(3)
+            .gatesCount(4)
+            .X(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.81342685f, 0.84108883f, 0.8152282f, 0.46893653f, 0.0901856f, 0.37088776f}))
+            .W(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{
+                    3.3330739e-01f, 3.6229487e-04f, 4.6773660e-01f, 4.3046016e-01f, 7.3950343e-02f, 3.8063636e-01f,
+                    9.6921772e-01f, 9.6897459e-01f, 6.2964785e-01f, 3.1134409e-01f, 8.4709978e-01f, 9.4928098e-01f,
+                    6.1676943e-01f, 6.6020679e-01f, 1.9072217e-01f, 8.8032126e-02f, 4.0472135e-01f, 6.8342745e-01f,
+                    8.3432144e-01f, 4.4928190e-01f, 7.9524308e-01f, 5.3966165e-01f, 8.5936421e-01f, 8.3136767e-01f,
+                    5.5125546e-02f, 4.7791195e-01f, 3.5788772e-01f, 6.7507404e-01f, 2.1716513e-01f, 2.7473119e-01f,
+                    3.3999152e-02f, 9.6835363e-01f, 3.7581277e-01f, 2.4026000e-01f, 6.7418844e-01f, 3.4199652e-01f}))
+            .R(reference_tests::Tensor(
+                ET,
+                {4 * 3, 3},
+                std::vector<T>{0.0987983f,  0.52032113f, 0.5848073f,  0.5356095f,  0.74497133f, 0.73260087f,
+                               0.1700787f,  0.45684233f, 0.1495722f,  0.42734373f, 0.4433832f,  0.25906256f,
+                               0.03854987f, 0.47480518f, 0.37215272f, 0.99890584f, 0.74019486f, 0.3518967f,
+                               0.6881257f,  0.8170279f,  0.54088944f, 0.81225616f, 0.14619833f, 0.42941234f,
+                               0.86843914f, 0.45967972f, 0.6237719f,  0.11074839f, 0.6029616f,  0.3149305f,
+                               0.46504205f, 0.5843412f,  0.8733427f,  0.7687243f,  0.07074859f, 0.39188156f}))
+            .H_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.77956f, 0.5331557f, 0.04297554f, 0.7962175f, 0.7635707f, 0.11989366f}))
+            .C_t(reference_tests::Tensor(
+                ET,
+                {2, 3},
+                std::vector<T>{0.8488452f, 0.18851636f, 0.5020695f, 0.29716516f, 0.06740791f, 0.45384037f}))
+            .B(reference_tests::Tensor(ET,
+                                       {4 * 3},
+                                       std::vector<T>{1.07393714f,
+                                                      1.15248052f,
+                                                      1.16671345f,
+                                                      0.21450312f,
+                                                      1.2380678f,
+                                                      1.51688835f,
+                                                      0.46718366f,
+                                                      0.91810346f,
+                                                      1.1274234f,
+                                                      0.51022074f,
+                                                      1.11389844f,
+                                                      0.74174305f}))
+            .P(reference_tests::Tensor(ET, {3 * 3}, std::vector<T>(3 * 3, 0.f)))
+            .Ho(reference_tests::Tensor(ET,
+                                        {2, 3},
+                                        std::vector<T>{0.81014400720596313,
+                                                       0.76665538549423218,
+                                                       0.82387429475784302,
+                                                       0.6479143500328064,
+                                                       0.66586339473724365,
+                                                       0.74838578701019287}))
+            .Co(reference_tests::Tensor(ET,
+                                        {2, 3},
+                                        std::vector<T>{1.6800162792205811,
+                                                       1.1150213479995728,
+                                                       1.4510968923568726,
+                                                       1.0649888515472412,
+                                                       0.93761754035949707,
+                                                       1.3659683465957642}))
+            .testcaseName("lstm_cell_v1_bias_clip"),
     };
     return params;
 }
 
 std::vector<LSTMCellParams> generateCombinedParamsBiasClipV1() {
-    const std::vector<std::vector<LSTMCellParams>> generatedParams {
+    const std::vector<std::vector<LSTMCellParams>> generatedParams{
         generateParamsBiasClipV1<element::Type_t::bf16>(),
         generateParamsBiasClipV1<element::Type_t::f16>(),
         generateParamsBiasClipV1<element::Type_t::f32>(),
@@ -703,12 +813,18 @@ std::vector<LSTMCellParams> generateCombinedParamsBiasClipV1() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_LSTMCellV1_With_Hardcoded_Refs, ReferenceLSTMCellV1Test,
-    testing::ValuesIn(generateCombinedParamsV1()), ReferenceLSTMCellV1Test::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_LSTMCellV1_With_Hardcoded_Refs, ReferenceLSTMCellV1TestBiasDefaultAttrs,
-    testing::ValuesIn(generateCombinedParamsBiasDefaultAttrsV1()), ReferenceLSTMCellV1Test::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_LSTMCellV1_With_Hardcoded_Refs, ReferenceLSTMCellV1TestBiasClip,
-    testing::ValuesIn(generateCombinedParamsBiasClipV1()), ReferenceLSTMCellV1Test::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_LSTMCellV1_With_Hardcoded_Refs,
+                         ReferenceLSTMCellV1Test,
+                         testing::ValuesIn(generateCombinedParamsV1()),
+                         ReferenceLSTMCellV1Test::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_LSTMCellV1_With_Hardcoded_Refs,
+                         ReferenceLSTMCellV1TestBiasDefaultAttrs,
+                         testing::ValuesIn(generateCombinedParamsBiasDefaultAttrsV1()),
+                         ReferenceLSTMCellV1Test::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_LSTMCellV1_With_Hardcoded_Refs,
+                         ReferenceLSTMCellV1TestBiasClip,
+                         testing::ValuesIn(generateCombinedParamsBiasClipV1()),
+                         ReferenceLSTMCellV1Test::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/lstm_sequence.cpp b/src/plugins/template/tests/functional/op_reference/lstm_sequence.cpp
index 027dddf4572d32..9e13293e9ab6d0 100644
--- a/src/plugins/template/tests/functional/op_reference/lstm_sequence.cpp
+++ b/src/plugins/template/tests/functional/op_reference/lstm_sequence.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/lstm_sequence.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/lstm_sequence.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,42 +14,57 @@ using namespace ov;
 namespace {
 struct LSTMSequenceParams {
     template <class T>
-    LSTMSequenceParams(
-        const size_t batchSize, const size_t inputSize, const size_t hiddenSize, const size_t seqLength,
-        const float clip, const op::RecurrentSequenceDirection& lstm_direction,
-        const element::Type_t& iType,
-        const std::vector<T>& XValues, const std::vector<T>& H_tValues, const std::vector<T>& C_tValues,
-        const std::vector<int64_t>& S_tValues,
-        const std::vector<T>& WValues, const std::vector<T>& RValues, const std::vector<T>& BValues,
-        const std::vector<T>& YValues, const std::vector<T>& HoValues, const std::vector<T>& CoValues,
-        const std::string& testcaseName = "") :
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize), seqLength(seqLength),
-        clip(clip), lstm_direction(lstm_direction), iType(iType), oType(iType),
-        testcaseName(testcaseName) {
-            numDirections = (lstm_direction == op::RecurrentSequenceDirection::BIDIRECTIONAL) ? 2 : 1;
+    LSTMSequenceParams(const size_t batchSize,
+                       const size_t inputSize,
+                       const size_t hiddenSize,
+                       const size_t seqLength,
+                       const float clip,
+                       const op::RecurrentSequenceDirection& lstm_direction,
+                       const element::Type_t& iType,
+                       const std::vector<T>& XValues,
+                       const std::vector<T>& H_tValues,
+                       const std::vector<T>& C_tValues,
+                       const std::vector<int64_t>& S_tValues,
+                       const std::vector<T>& WValues,
+                       const std::vector<T>& RValues,
+                       const std::vector<T>& BValues,
+                       const std::vector<T>& YValues,
+                       const std::vector<T>& HoValues,
+                       const std::vector<T>& CoValues,
+                       const std::string& testcaseName = "")
+        : batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          seqLength(seqLength),
+          clip(clip),
+          lstm_direction(lstm_direction),
+          iType(iType),
+          oType(iType),
+          testcaseName(testcaseName) {
+        numDirections = (lstm_direction == op::RecurrentSequenceDirection::BIDIRECTIONAL) ? 2 : 1;
 
-            Shape XShape = Shape{batchSize, seqLength, inputSize};
-            Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape C_tShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape S_tShape = Shape{batchSize};
-            Shape WShape = Shape{numDirections, 4 * hiddenSize, inputSize};
-            Shape RShape = Shape{numDirections, 4 * hiddenSize, hiddenSize};
-            Shape BShape = Shape{numDirections, 4 * hiddenSize};
-            Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
-            Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape CoShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape XShape = Shape{batchSize, seqLength, inputSize};
+        Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape C_tShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape S_tShape = Shape{batchSize};
+        Shape WShape = Shape{numDirections, 4 * hiddenSize, inputSize};
+        Shape RShape = Shape{numDirections, 4 * hiddenSize, hiddenSize};
+        Shape BShape = Shape{numDirections, 4 * hiddenSize};
+        Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
+        Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape CoShape = Shape{batchSize, numDirections, hiddenSize};
 
-            X = reference_tests::Tensor(XShape, iType, XValues);
-            H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
-            C_t = reference_tests::Tensor(C_tShape, iType, C_tValues);
-            S_t = reference_tests::Tensor(S_tShape, element::Type_t::i64, S_tValues);
-            W = reference_tests::Tensor(WShape, iType, WValues);
-            R = reference_tests::Tensor(RShape, iType, RValues);
-            B = reference_tests::Tensor(BShape, iType, BValues);
-            Y = reference_tests::Tensor(YShape, oType, YValues);
-            Ho = reference_tests::Tensor(HoShape, oType, HoValues);
-            Co = reference_tests::Tensor(CoShape, oType, CoValues);
-        }
+        X = reference_tests::Tensor(XShape, iType, XValues);
+        H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
+        C_t = reference_tests::Tensor(C_tShape, iType, C_tValues);
+        S_t = reference_tests::Tensor(S_tShape, element::Type_t::i64, S_tValues);
+        W = reference_tests::Tensor(WShape, iType, WValues);
+        R = reference_tests::Tensor(RShape, iType, RValues);
+        B = reference_tests::Tensor(BShape, iType, BValues);
+        Y = reference_tests::Tensor(YShape, oType, YValues);
+        Ho = reference_tests::Tensor(HoShape, oType, HoValues);
+        Co = reference_tests::Tensor(CoShape, oType, CoValues);
+    }
 
     size_t batchSize;
     size_t inputSize;
@@ -75,44 +91,62 @@ struct LSTMSequenceParams {
 
 struct LSTMSequenceV1Params {
     template <class T>
-    LSTMSequenceV1Params(
-        const size_t batchSize, const size_t inputSize, const size_t hiddenSize, const size_t seqLength,
-        const float clip, const bool input_forget, const op::RecurrentSequenceDirection& lstm_direction,
-        const element::Type_t& iType,
-        const std::vector<T>& XValues, const std::vector<T>& H_tValues, const std::vector<T>& C_tValues,
-        const std::vector<int64_t>& S_tValues,
-        const std::vector<T>& WValues, const std::vector<T>& RValues, const std::vector<T>& BValues, const std::vector<T>& PValues,
-        const std::vector<T>& YValues, const std::vector<T>& HoValues, const std::vector<T>& CoValues,
-        const std::string& testcaseName = "") :
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize), seqLength(seqLength),
-        clip(clip), input_forget(input_forget), lstm_direction(lstm_direction), iType(iType), oType(iType),
-        testcaseName(testcaseName) {
-            numDirections = (lstm_direction == op::RecurrentSequenceDirection::BIDIRECTIONAL) ? 2 : 1;
+    LSTMSequenceV1Params(const size_t batchSize,
+                         const size_t inputSize,
+                         const size_t hiddenSize,
+                         const size_t seqLength,
+                         const float clip,
+                         const bool input_forget,
+                         const op::RecurrentSequenceDirection& lstm_direction,
+                         const element::Type_t& iType,
+                         const std::vector<T>& XValues,
+                         const std::vector<T>& H_tValues,
+                         const std::vector<T>& C_tValues,
+                         const std::vector<int64_t>& S_tValues,
+                         const std::vector<T>& WValues,
+                         const std::vector<T>& RValues,
+                         const std::vector<T>& BValues,
+                         const std::vector<T>& PValues,
+                         const std::vector<T>& YValues,
+                         const std::vector<T>& HoValues,
+                         const std::vector<T>& CoValues,
+                         const std::string& testcaseName = "")
+        : batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          seqLength(seqLength),
+          clip(clip),
+          input_forget(input_forget),
+          lstm_direction(lstm_direction),
+          iType(iType),
+          oType(iType),
+          testcaseName(testcaseName) {
+        numDirections = (lstm_direction == op::RecurrentSequenceDirection::BIDIRECTIONAL) ? 2 : 1;
 
-            Shape XShape = Shape{batchSize, seqLength, inputSize};
-            Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape C_tShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape S_tShape = Shape{batchSize};
-            Shape WShape = Shape{numDirections, 4 * hiddenSize, inputSize};
-            Shape RShape = Shape{numDirections, 4 * hiddenSize, hiddenSize};
-            Shape BShape = Shape{numDirections, 4 * hiddenSize};
-            Shape PShape = Shape{numDirections, 3 * hiddenSize};
-            Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
-            Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape CoShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape XShape = Shape{batchSize, seqLength, inputSize};
+        Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape C_tShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape S_tShape = Shape{batchSize};
+        Shape WShape = Shape{numDirections, 4 * hiddenSize, inputSize};
+        Shape RShape = Shape{numDirections, 4 * hiddenSize, hiddenSize};
+        Shape BShape = Shape{numDirections, 4 * hiddenSize};
+        Shape PShape = Shape{numDirections, 3 * hiddenSize};
+        Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
+        Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape CoShape = Shape{batchSize, numDirections, hiddenSize};
 
-            X = reference_tests::Tensor(XShape, iType, XValues);
-            H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
-            C_t = reference_tests::Tensor(C_tShape, iType, C_tValues);
-            S_t = reference_tests::Tensor(S_tShape, element::Type_t::i64, S_tValues);
-            W = reference_tests::Tensor(WShape, iType, WValues);
-            R = reference_tests::Tensor(RShape, iType, RValues);
-            B = reference_tests::Tensor(BShape, iType, BValues);
-            P = reference_tests::Tensor(PShape, iType, PValues);
-            Y = reference_tests::Tensor(YShape, oType, YValues);
-            Ho = reference_tests::Tensor(HoShape, oType, HoValues);
-            Co = reference_tests::Tensor(CoShape, oType, CoValues);
-        }
+        X = reference_tests::Tensor(XShape, iType, XValues);
+        H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
+        C_t = reference_tests::Tensor(C_tShape, iType, C_tValues);
+        S_t = reference_tests::Tensor(S_tShape, element::Type_t::i64, S_tValues);
+        W = reference_tests::Tensor(WShape, iType, WValues);
+        R = reference_tests::Tensor(RShape, iType, RValues);
+        B = reference_tests::Tensor(BShape, iType, BValues);
+        P = reference_tests::Tensor(PShape, iType, PValues);
+        Y = reference_tests::Tensor(YShape, oType, YValues);
+        Ho = reference_tests::Tensor(HoShape, oType, HoValues);
+        Co = reference_tests::Tensor(CoShape, oType, CoValues);
+    }
 
     size_t batchSize;
     size_t inputSize;
@@ -144,7 +178,13 @@ class ReferenceLSTMSequenceTest : public testing::TestWithParam<LSTMSequencePara
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.X.data, params.H_t.data, params.C_t.data, params.S_t.data, params.W.data, params.R.data, params.B.data};
+        inputData = {params.X.data,
+                     params.H_t.data,
+                     params.C_t.data,
+                     params.S_t.data,
+                     params.W.data,
+                     params.R.data,
+                     params.B.data};
         refOutData = {params.Y.data, params.Ho.data, params.Co.data};
     }
 
@@ -205,7 +245,14 @@ class ReferenceLSTMSequenceV1Test : public testing::TestWithParam<LSTMSequenceV1
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.X.data, params.H_t.data, params.C_t.data, params.S_t.data, params.W.data, params.R.data, params.B.data, params.P.data};
+        inputData = {params.X.data,
+                     params.H_t.data,
+                     params.C_t.data,
+                     params.S_t.data,
+                     params.W.data,
+                     params.R.data,
+                     params.B.data,
+                     params.P.data};
         refOutData = {params.Y.data, params.Ho.data, params.Co.data};
     }
 
@@ -262,7 +309,8 @@ class ReferenceLSTMSequenceV1Test : public testing::TestWithParam<LSTMSequenceV1
                                                    params.clip,
                                                    params.input_forget);
 
-        auto function = std::make_shared<Model>(lstm_sequence->outputs(), ParameterVector{X, H_t, C_t, S_t, W, R, B, P});
+        auto function =
+            std::make_shared<Model>(lstm_sequence->outputs(), ParameterVector{X, H_t, C_t, S_t, W, R, B, P});
         return function;
     }
 };
@@ -279,815 +327,970 @@ template <element::Type_t ET>
 std::vector<LSTMSequenceParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<LSTMSequenceParams> params {
+    std::vector<LSTMSequenceParams> params{
         LSTMSequenceParams(
-            5, 10, 10, 10,
-            0.7f, op::RecurrentSequenceDirection::FORWARD,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            op::RecurrentSequenceDirection::FORWARD,
             ET,
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
-                1.82401, 6.1306, 4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686,
-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 4.59474,
-                6.19214, 8.80766, 8.07546, 3.29232, 1.74029, 2.4198, 2.88544, 4.75644, 4.12921, 7.29896,
-                7.27759, 1.67252, 1.32823, 8.1046, 9.10476, 1.04197, 3.37783, 5.2064, 4.23835, 3.16196,
-                1.20852, 5.78501, 2.17175, 6.05313, 2.51048, 4.78967, 7.16219, 3.4651, 1.09, 2.9788,
-                1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892, 5.86648, 8.73895, 2.66603, 1.75192,
-                1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565, 7.35114, 3.1439, 1.39976,
-                3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637, 8.6232, 8.54902,
-                2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225, 3.99956, 1.08021, 5.54918, 7.05833,
-                1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
-                5.59325, 9.89258, 2.30223, 1.4347, 9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909,
-                1.00912, 6.62167, 2.80244, 6.626, 3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902,
-                6.26823, 9.72608, 3.73491, 3.8238, 3.03815, 7.05101, 8.0103, 5.61396, 6.53738, 1.41095,
-                5.0149, 9.71211, 4.23604, 5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328, 8.2817,
-                5.12336, 8.98577, 5.80541, 6.19552, 9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817,
-                8.57269, 5.99975, 3.42893, 5.38068, 3.48261, 3.02851, 6.82079, 9.2902, 2.80427, 8.91868,
-                5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755, 2.49121, 5.52697, 8.08823, 9.13242,
-                2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457, 5.55154, 7.24966, 5.1128,
-                4.25147, 8.34407, 1.4123, 4.49045, 5.12671, 7.62159, 9.18673, 3.49665, 8.35992, 6.90684,
-                1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283, 9.88249, 4.48422,
-                8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155, 9.94928, 6.88321, 1.33685,
-                7.4718, 7.19305, 6.47932, 1.9559, 3.52616, 7.98593, 9.0115, 5.59539, 7.44137, 1.70001,
-                6.53774, 8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153,
-                5.4073, 9.00437, 8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473,
-                7.95084, 2.11852, 9.28916, 1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549,
-                3.75218, 8.98228, 8.98158, 5.63695, 3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035,
-                8.37644, 8.54954, 5.70516, 2.45744, 9.54079, 1.53504, 8.9785, 6.1691, 4.40962, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
+                1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 8.6168,
+                3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.0055,  7.44373,
+                8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 7.03475, 6.33759, 7.04489,
+                4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 6.61627, 6.94572, 3.68646, 5.01521,
+                2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937,
+                1.40811, 2.2597,  8.13163, 1.26821, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069,
+                4.25135, 6.13908, 6.74053, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208,
+                1.10502, 5.48298, 1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224,
+                7.95465, 2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
+                1.63073, 5.25228, 7.68488, 2.7276,  5.1788,  3.07327, 5.57423, 2.87711, 1.44374, 5.66976, 2.55051,
+                4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,  1.82401, 6.1306,
+                4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686, 4.85031, 4.85544, 4.25714,
+                2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891, 2.16793, 3.64924, 4.24733, 3.47181,
+                1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016, 7.6686,  3.68812, 2.83922, 9.83581, 9.03719,
+                7.83414, 6.86009, 1.35715, 8.32489, 7.86316, 5.09754, 5.78644, 1.98402, 2.31429, 5.5791,  2.94085,
+                9.24799, 5.15937, 2.19041, 7.87817, 2.9146,  1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937,
+                9.37912, 6.18926, 8.55681, 6.60963, 3.92066, 7.5521,  5.70463, 7.6313,  2.48866, 7.18352, 4.8413,
+                7.55702, 7.80702, 4.5785,  9.3268,  2.83159, 1.07202, 9.33716, 3.6506,  2.50256, 1.21691, 5.06801,
+                8.27505, 4.31539, 6.48286, 1.31363, 4.1912,  1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
+                5.24875, 1.94852, 5.52768, 8.97121, 5.8094,  3.53329, 4.19126, 9.06652, 3.1734,  1.21496, 9.69154,
+                4.86971, 4.1166,  6.19361, 2.13874, 9.55039, 3.8225,  9.57548, 2.96554, 3.2383,  8.77422, 3.11741,
+                8.3359,  5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474,  4.59474, 6.19214, 8.80766, 8.07546,
+                3.29232, 1.74029, 2.4198,  2.88544, 4.75644, 4.12921, 7.29896, 7.27759, 1.67252, 1.32823, 8.1046,
+                9.10476, 1.04197, 3.37783, 5.2064,  4.23835, 3.16196, 1.20852, 5.78501, 2.17175, 6.05313, 2.51048,
+                4.78967, 7.16219, 3.4651,  1.09,    2.9788,  1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892,
+                5.86648, 8.73895, 2.66603, 1.75192, 1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565,
+                7.35114, 3.1439,  1.39976, 3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637,
+                8.6232,  8.54902, 2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225,  3.99956, 1.08021, 5.54918,
+                7.05833, 1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
+                5.59325, 9.89258, 2.30223, 1.4347,  9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909, 1.00912,
+                6.62167, 2.80244, 6.626,   3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902, 6.26823, 9.72608,
+                3.73491, 3.8238,  3.03815, 7.05101, 8.0103,  5.61396, 6.53738, 1.41095, 5.0149,  9.71211, 4.23604,
+                5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328,  8.2817,  5.12336, 8.98577, 5.80541, 6.19552,
+                9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817, 8.57269, 5.99975, 3.42893, 5.38068, 3.48261,
+                3.02851, 6.82079, 9.2902,  2.80427, 8.91868, 5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755,
+                2.49121, 5.52697, 8.08823, 9.13242, 2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457,
+                5.55154, 7.24966, 5.1128,  4.25147, 8.34407, 1.4123,  4.49045, 5.12671, 7.62159, 9.18673, 3.49665,
+                8.35992, 6.90684, 1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283,  9.88249,
+                4.48422, 8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155,  9.94928, 6.88321, 1.33685,
+                7.4718,  7.19305, 6.47932, 1.9559,  3.52616, 7.98593, 9.0115,  5.59539, 7.44137, 1.70001, 6.53774,
+                8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153, 5.4073,  9.00437,
+                8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473, 7.95084, 2.11852, 9.28916,
+                1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549, 3.75218, 8.98228, 8.98158, 5.63695,
+                3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035, 8.37644, 8.54954, 5.70516, 2.45744, 9.54079,
+                1.53504, 8.9785,  6.1691,  4.40962, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
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+            std::vector<T>{0.559698, 0.587499, 0.58592,  0.563707, 0.587544, 0.56698,  0.571671, 0.571423, 0.579197,
+                           0.585993, 0.583768, 0.569262, 0.575267, 0.573003, 0.566785, 0.575539, 0.58546,  0.57339,
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+                           0.562011, 0.573728, 0.56272,  0.585197, 0.587567},
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+                           1.34833, 1.26322, 1.29695, 1.284,   1.24985, 1.29853, 1.35913, 1.2862,  1.28197, 1.36315,
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         LSTMSequenceParams(
-            5, 10, 10, 10,
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+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            op::RecurrentSequenceDirection::REVERSE,
             ET,
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+                           0.562011, 0.573728, 0.56272,  0.585197, 0.587567},
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         LSTMSequenceParams(
-            5, 10, 10, 10,
-            0.f, op::RecurrentSequenceDirection::BIDIRECTIONAL,
+            5,
+            10,
+            10,
+            10,
+            0.f,
+            op::RecurrentSequenceDirection::BIDIRECTIONAL,
             ET,
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-                -2.42598, -3.80421, -0.981378, -1.63223, -4.18565, 1.30126, 0.627183, -4.24035, -4.25213, 5},
-            std::vector<T>{
-                -5, 0.0972095, -3.16646, 3.08769, 4.37785, -4.70394, 2.84984, -3.36123, -0.661491, 0.742674,
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-                -3.61267, -2.40318, 0.749356, 4.85626, -3.93755, -0.299189, -4.53363, -2.2065, 0.998577, -4.88086,
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-                4.71373, -1.11216, -0.158811, 3.29267, -4.30107, -0.782312, -3.3017, 2.70345, 4.31324, 5},
+            std::vector<T>{-5,         3.90155,    -3.69293,  -4.60241,   3.26436,     0.320779,  4.5631,    -0.380737,
+                           4.23738,    -1.26079,   -3.45027,  3.92344,    -4.7321,     -2.08498,  -1.01256,  3.07289,
+                           1.27094,    4.07925,    0.563973,  3.39919,    -4.49512,    3.06235,   4.30816,   -1.3597,
+                           1.90948,    -3.70685,   3.32686,   -1.81646,   2.37202,     0.967696,  -1.36293,  2.94971,
+                           1.98481,    3.21879,    3.99466,   3.31899,    4.09958,     4.74914,   1.5612,    3.1199,
+                           -3.97256,   -2.62472,   -1.20655,  1.99236,    -0.150548,   -0.847778, 1.38662,   2.5929,
+                           0.575229,   1.93455,    4.13259,   -4.75387,   3.37378,     -1.16795,  -2.01229,  -4.93703,
+                           -0.624426,  2.37937,    -1.2424,   -0.0675053, -4.8596,     -2.50563,  -1.52865,  2.96687,
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+                           -4.38315,   0.542347,   0.706112,  -0.378897,  4.48829,     -1.55226,  3.84449,   -0.689599,
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+                           0.627183,   -4.24035,   -4.25213,  5},
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+                           -0.661491, 0.742674,  -2.82977,  3.30679,   -2.0046,   -1.39169,   3.69357,    -4.87822,
+                           1.75331,   -0.187543, 4.77267,   -2.89035,  -2.86541,  4.43989,    -1.73837,   4.86129,
+                           -0.626666, 4.65384,   -2.42069,  2.59966,   -3.07773,  -2.17051,   2.69538,    -4.91818,
+                           -1.47175,  -2.66442,  -1.14894,  -3.90875,  -0.92652,  -0.946207,  2.70024,    3.4187,
+                           -1.06892,  -0.336707, -3.95977,  -3.09231,  1.72681,   -0.253682,  3.01543,    -2.52343,
+                           2.41461,   1.73951,   1.55908,   -2.88157,  0.895772,  2.83656,    -0.0438242, -3.9921,
+                           3.78771,   1.16734,   1.89495,   4.71639,   -0.788449, -4.285,     -3.09649,   -2.73812,
+                           -4.50129,  -3.22373,  0.570888,  4.57888,   4.49166,   -0.0809164, -3.61267,   -2.40318,
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+                           -4.95235,  -4.83644,  -0.938169, -3.2432,   -3.98636,  -0.724817,  1.77318,    0.215689,
+                           -1.7268,   0.475434,  2.16854,   -0.953869, 0.724856,  3.98419,    -2.91751,   3.49012,
+                           -2.84873,  -3.42912,  -1.53297,  5},
+            std::vector<T>{-5,       -2.4224,   0.545224,   2.07068,  -0.174741, 4.84283,  0.469625,  -1.36484,
+                           -2.49666, 1.16077,   -2.47798,   1.30443,  4.90657,   -4.86712, 2.60958,   -3.6434,
+                           4.98959,  2.83648,   3.12445,    1.24863,  -3.56188,  1.18263,  4.00651,   -4.49285,
+                           -3.35389, 3.84102,   -0.692219,  4.58475,  -2.85036,  -2.88143, 3.93052,   2.39646,
+                           -2.43019, -1.74484,  1.43614,    4.831,    1.03788,   0.298718, -0.686032, -0.304259,
+                           -2.28994, -3.89952,  -1.95116,   -4.86558, 1.41202,   -4.93245, -2.05543,  2.04177,
+                           -4.60741, -1.50938,  3.88719,    1.83697,  -4.37124,  1.66286,  1.39415,   3.97862,
+                           -3.03259, -0.518552, 0.380681,   4.66685,  4.75549,   -1.81382, -4.49654,  -2.51648,
+                           4.04178,  -4.34012,  -0.0679991, -2.20335, 2.7089,    3.73041,  4.24063,   0.901985,
+                           3.52631,  4.06229,   -1.28391,   -4.74323, -3.84049,  3.54115,  -3.26689,  -2.21037,
+                           -2.83436, -3.75905,  -3.71528,   3.58726,  4.65168,   -2.66566, -1.87998,  1.95093,
+                           3.66591,  -3.2642,   4.71373,    -1.11216, -0.158811, 3.29267,  -4.30107,  -0.782312,
+                           -3.3017,  2.70345,   4.31324,    5},
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             std::vector<T>{
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-                0.761594, -5.61929e-05, -4.03471e-09, -9.05792e-10, -2.44896e-14, -0.761593, -1.53072e-14, 4.80451e-06, 4.97845e-05, 2.61901e-17},
-            std::vector<T>{
-                -1.23107e-30, 0.00725055, 0.76182, 1.27929e-05, 1.58846e-07, -0.680477, -5.73051e-15, 6.33457e-20, 0.000288991, 0.00312473,
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-                0.00463415, -0.218827, -3.33063e-20, 2.62387e-15, 0.000655749, -0.761594, -9.3791e-19, 3.55914e-07, 1.21115e-10, 8.51853e-05,
-                0.746421, -0.203347, 0.964016, -0.675211, -0.757478, 4.1336e-13, 1.31125e-14, -0.752869, -3.40686e-11, -9.04177e-20,
-                -6.2253e-22, 8.88893e-22, 0.000599919, -6.13229e-19, 9.45362e-05, 1.03827e-16, -0.00543732, -9.86013e-09, -0.761408, 0.214137,
-                -8.00209e-24, 0.679937, 0.917833, -1.34199e-10, 1.89431e-07, -0.761594, -0.0442637, -0.000217974, 0.00476938, 0.0246565,
-                -0.761481, 3.44292e-08, -0.644774, 5.99614e-06, -2.4661e-12, 0.939834, -0.732183, 0.758408, -0.406918, 0.761563,
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-                -2.38573e-16, -3.53137e-05, -0.438905, 0.0134316, 4.40739e-11, -3.01366e-05, -1.38874e-32, -3.77945e-21, 0.0780586, 1.6805e-13,
-                0.751234, -0.803057, 0.811984, 7.895e-05, 0.761593, -0.00119532, -5.48256e-06, 0.757714, 0.761594, -0.761511},
-            std::vector<T>{
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-                -0.999991, 0.976968, 1, -3.63016e-07, 0.0208492, 3.42118e-07, -0.00543741, -9.86013e-09, -0.999558, 0.219696,
-                -1.00056, 0.828996, 1.99999, -2.98023e-07, 1.61781e-05, -1, -0.044346, -1.00563, 0.099386, 0.0246731,
-                -0.999731, 3.44351e-08, -0.766302, 5.99614e-06, -0.087751, 1.73662, -0.999998, 1, -0.431925, 0.999926,
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-                0.975781, -1.10725, 1.13283, 7.895e-05, 1, -0.00119563, -0.99991, 0.990824, 1, -1}),
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+                -0.93456,    -2.73502,    3.51855,   4.47696,    2.91625,    -0.68445,  4.43112,   -4.38335,  3.58399,
+                -3.5086,     0.863423,    -0.279341, 2.84091,    3.83352,    -2.69488,  2.11292,   -4.86518,  1.38034,
+                1.30028,     -1.84802,    4.05115,   1.67509,    4.59603,    2.46173,   1.70552,   -2.21902,  4.04495,
+                1.18181,     -2.28113,    -4.71689,  -3.04267,   0.500298,   -2.41982,  3.09957,   -2.96136,  3.4832,
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+                2.24535,     -1.10242,    -3.97405,  3.67443,    2.69645,    3.40125,   -3.05413,  2.16447,   3.45673,
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+                -0.395894,   4.39348,     0.466077,  0.766771,   2.01238,    2.06508,   0.772249,  1.9867,    -0.996579,
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+                -0.913088,   -4.2081,     3.61542,   -3.64835,   1.87344,    0.211608,  3.65209,   -4.61966,  3.15605,
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+                -3.80798,    -4.92614,    1.72164,   4.90619,    0.68811,    -2.84043,  0.228619,  3.06368,   1.88669,
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+                -2.0607,     -4.7294,     -1.1922,   -4.25132,   2.51276,    -2.46105,  3.63289,   -2.9029,   -3.89352,
+                -4.56467,    4.42607,     4.82693,   -2.69463,   4.51783,    -0.907243, -2.78669,  4.18723,   2.34626,
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+                -3.71999,    4.20983,     0.778437,  4.03383,    1.31396,    3.58678,   4.77689,   0.578005,  -2.15946,
+                -4.90681,    1.4671,      2.04727,   -4.43527,   -1.89183,   3.54344,   3.0036,    3.81351,   -0.304046,
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+                1.45256,     -1.15546,    1.60745,   -3.76519,   3.94909,    1.43606,   -3.87999,  1.78168,   0.370893,
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+                -0.77331,    -0.164568,   -3.97808,  -1.30991,   3.64372,    4.19263,   3.90947,   -1.78475,  3.94366,
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+                1.04336,     -1.78493,    4.46535,   2.2445,     3.79802,    -1.44113,  2.9843,    -3.40275,  4.31126,
+                1.63422,     -4.32046,    4.21314,   4.49346,    2.26706,    -4.63838,  -2.81771,  -3.23518,  -0.494282,
+                1.80663,     -0.345847,   -4.71775,  -4.64164,   -1.17283,   1.11853,   -1.94206,  3.73188,   3.61315,
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+                -2.42048,    2.69591,     4.02649,   -1.87481,   4.63578,    0.771746,  4.82279,   -1.68132,  2.46822,
+                4.48127,     -2.72111,    -0.355886, 0.266078,   -4.89841,   -0.850352, 2.77856,   0.429384,  3.58205,
+                3.09831,     4.72246,     -2.40146,  -2.7575,    4.35845,    -1.53977,  -2.47573,  1.727,     1.54918,
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+                -3.26495,    -2.32184,    0.154838,  -4.15034,   -3.54186,   2.08248,   3.73156,   -1.08542,  3.89507,
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+                -1.16367,    2.6852,      0.136113,  3.24949,    1.48249,    -1.75121,  2.93909,   -3.09163,  0.826285,
+                2.60739,     -1.63573,    3.22668,   0.00300903, 0.575604,   -0.267615, -4.62369,  -3.98882,  3.31384,
+                -3.84641,    -0.164339,   -1.9838,   3.45511,    -1.04323,   3.56878,   3.3694,    -4.81446,  1.85392,
+                1.59741,     4.2085,      1.54342,   -1.25854,   -0.0477599, 4.83944,   3.41224,   -4.87642,  3.34542,
+                4.34374,     1.68048,     -4.17476,  -3.99847,   -1.0523,    -4.77302,  -3.79443,  -1.23287,  -2.90961,
+                -3.20999,    1.85511,     2.06811,   -2.20368,   -1.81411,   -2.62059,  1.88005,   -3.17691,  -2.90064,
+                -3.11477,    1.7461,      -3.02032,  -4.01402,   -4.87155,   -2.7408,   2.13552,   3.60602,   -3.68662,
+                3.94441,     1.75357,     3.18497,   -2.67031,   3.28189,    0.764719,  1.62342,   -1.16762,  -4.59845,
+                0.336623,    2.26649,     3.89547,   2.07511,    2.93817,    -1.03081,  3.30557,   0.72491,   3.1453,
+                0.769547,    -2.92608,    0.13144,   -0.0691925, -4.07191,   4.01141,   -3.50862,  -0.749251, -3.21837,
+                1.06989,     3.97227,     1.54475,   4.78368,    -3.18741,   4.10281,   3.61094,   -2.81927,  4.0446,
+                -0.688241,   -0.195357,   -1.89505,  1.3421,     3.13891,    -0.625937, -3.07901,  0.676794,  -4.31063,
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+                -4.84057,    4.20739,     -0.915956, 2.33027,    2.63642,    1.31649,   -3.45589,  3.61696,   1.39562,
+                1.50066,     0.953228,    2.33703,   -1.74775,   1.90994,    0.158689,  2.00179,   1.97409,   -0.447395,
+                3.93314,     0.379663,    -3.20044,  -4.63811,   3.33694,    -2.92811,  -0.334244, -1.82335,  -1.99341,
+                -2.38105,    -3.42019,    4.49144,   4.50581,    0.146444,   -4.01907,  2.76861,   2.54542,   -4.88271,
+                4.25518,     3.71932,     -2.67843,  -4.61096,   2.49717,    3.22838,   2.91755,   2.81098,   -0.212338,
+                -4.09407,    3.46949,     -0.264652, 0.653515,   0.510898,   1.74902,   -0.615688, 0.225622,  3.35548,
+                2.3847,      0.542832,    -1.47433,  2.86275,    -3.14377,   -3.10022,  4.98831,   1.61969,   0.994205,
+                3.34565,     -2.12893,    -2.35919,  0.905238,   -0.847957,  -3.33345,  -0.448516, 1.31451,   3.56578,
+                -4.07352,    -0.694577,   -3.23525,  1.98038,    4.05222,    0.15182,   2.11475,   -4.91253,  -2.83372,
+                -0.800172,   -0.797281,   4.91775,   0.71457,    2.64354,    -4.37525,  3.93947,   4.29284,   0.376963,
+                0.483439,    -1.20476,    1.54934,   -1.60458,   -2.03934,   3.17352,   1.84459,   -0.57479,  2.83865,
+                4.82469,     -0.00921004, -3.30157,  -3.63386,   -3.94658,   1.96984,   4.15967,   3.75591,   -0.538282,
+                -1.32521,    0.128334,    -0.57577,  0.96914,    1.10537,    2.45218,   2.8899,    1.61422,   1.46003,
+                2.45143,     1.49513,     0.761625,  -3.07383,   0.554756,   4.26704,   0.702351,  5},
+            std::vector<T>{
+                -5,        -2.76745,    -3.36272,  0.786832,  -0.536305, -2.6808,   2.75696,    -2.38186,  -2.97924,
+                -1.8377,   -1.8783,     -2.34573,  1.51361,   -0.429618, -0.165277, -4.11843,   2.8142,    2.19643,
+                4.21874,   1.96632,     -1.04831,  -3.02755,  3.21475,   -0.624601, 2.22647,    0.583331,  -3.05985,
+                -2.92969,  4.40203,     4.96686,   -2.67395,  0.58967,   1.75651,   3.90978,    -2.32869,  -0.251364,
+                -0.076078, -2.76866,    3.98696,   -3.89213,  -0.84402,  -0.84834,  -3.69578,   -2.08657,  -3.91955,
+                4.22513,   -3.88648,    -1.39718,  -0.026567, 1.30207,   2.68671,   1.60689,    3.78493,   -1.1378,
+                -1.50906,  4.42047,     1.11537,   3.98267,   -0.826257, 0.65135,   -3.50771,   3.93109,   1.36732,
+                -2.45974,  -1.47327,    0.772411,  2.65195,   3.03698,   -0.592716, -0.558972,  3.40876,   3.26508,
+                -3.91006,  0.147352,    4.54504,   0.695234,  4.9661,    -0.64909,  1.45945,    3.82606,   -4.26746,
+                2.80674,   3.86749,     -0.115914, -2.02211,  -3.06485,  2.15541,   -0.715792,  0.966579,  -1.59997,
+                -4.06261,  0.592467,    -0.94068,  -2.1352,   2.87121,   4.68889,   -4.91329,   0.299997,  -1.02383,
+                1.62808,   3.77503,     -3.10425,  -3.31658,  2.88163,   -4.02717,  2.43578,    2.97519,   -2.72692,
+                -2.94946,  -4.62235,    0.938072,  -3.56148,  4.96502,   -4.73707,  3.46557,    -0.84019,  4.05851,
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+                0.505384,  2.92792,     4.47033,   0.221046,  0.757135,  2.87319,   -2.95227,   -3.87443,  3.22101,
+                -3.01482,  -3.17032,    1.28237,   -4.21317,  -0.735796, -3.95619,  2.21906,    1.35044,   2.38934,
+                3.73366,   -2.37152,    -1.21153,  2.32514,   -2.52731,  -1.27155,  -3.50355,   -3.01653,  -2.55113,
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+                4.96817,   1.81584,     -2.77298,  -3.77737,  0.511126,  -3.95519,  0.312086,   2.07223,   0.682299,
+                -1.93266,  -2.17914,    -0.747721, -1.33989,  -4.1225,   2.73361,   1.20164,    2.0721,    0.616006,
+                -2.14654,  -1.09562,    2.69654,   -1.29804,  -3.06921,  0.918753,  -0.960092,  -2.76928,  -4.81197,
+                -0.228397, 2.9628,      -3.62481,  -0.877274, -0.636959, -2.77519,  1.92274,    -2.71535,  0.823748,
+                0.0571949, -2.80894,    -2.93044,  2.44277,   3.72529,   -1.39665,  0.419583,   -0.735395, 0.141612,
+                4.91315,   -1.85428,    3.59253,   4.63525,   -4.308,    -4.04851,  -4.52805,   3.46887,   -3.40928,
+                1.49532,   -4.29342,    0.864934,  -4.68825,  -4.24461,  4.62154,   0.258795,   -1.59565,  -4.96134,
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+                1.14779,   -4.36729,    3.8481,    -1.66048,  -0.950351, 3.57762,   -2.33159,   1.01822,   1.35339,
+                4.7311,    -4.59032,    3.43969,   -0.238646, -1.39467,  -0.329268, 3.23937,    -0.284994, -3.59913,
+                -2.26108,  -0.378409,   -3.475,    -0.160139, -0.838942, 0.527827,  -1.51829,   -2.46392,  1.89068,
+                -4.46563,  -2.60946,    3.53656,   -2.20977,  -0.851908, -2.42698,  -2.03249,   -0.938796, 2.09651,
+                -0.967279, -2.06681,    -4.58985,  3.24781,   -2.63077,  4.56093,   3.17359,    -2.34826,  1.58482,
+                -4.12192,  -2.55048,    -3.4803,   0.631562,  -4.64767,  4.07145,   -4.89086,   -3.90578,  0.794496,
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+                -4.91899,  2.37826,     -1.77523,  -3.23982,  -1.69375,  -0.837184, 1.1934,     -1.10572,  -1.22483,
+                4.71149,   2.96609,     -0.676543, -3.31718,  -3.692,    -2.9575,   -3.52942,   0.411185,  -2.41244,
+                -0.401702, -1.8739,     -0.132347, 1.13978,   -4.45176,  0.169302,  3.5423,     3.94282,   1.60127,
+                -4.07808,  2.34236,     -0.781839, -2.74102,  4.48042,   -4.34059,  -1.30121,   -0.93276,  1.11985,
+                -3.90853,  -0.286499,   -1.01405,  -2.77668,  0.288616,  -4.16595,  -2.3096,    -2.44363,  1.24341,
+                3.73431,   -0.00587227, -4.89328,  4.75827,   -4.9217,   3.8995,    2.46474,    3.20115,   1.39757,
+                3.46744,   3.32388,     -1.17844,  2.83398,   -1.88155,  -3.75103,  -2.30867,   -1.46387,  2.3986,
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+                -4.46146,  3.65466,     2.02678,   4.93931,   -4.48006,  -4.70468,  -0.0110495, -4.34515,  2.66921,
+                -2.4087,   3.08708,     4.72305,   3.14726,   -2.3531,   0.719721,  -2.08273,   -4.30752,  -3.36451,
+                0.7731,    0.323962,    -2.62083,  0.261967,  -3.56867,  2.00299,   0.649599,   1.86126,   1.56565,
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+                -3.62565,  -0.934082,   -1.81757,  -1.77204,  -3.26355,  4.35017,   3.13568,    0.702371,  -3.24041,
+                0.0219689, 2.41334,     -1.23636,  3.9868,    4.02405,   -1.44978,  0.281016,   4.02714,   -3.745,
+                -0.925299, 0.628337,    4.63236,   -3.27555,  4.35052,   3.93893,   -1.18177,   3.12756,   2.48858,
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+                2.45058,   1.58468,     3.9512,    4.54651,   -0.556351, 2.948,     1.81753,    -3.51936,  -0.504748,
+                -3.25792,  3.13386,     -0.620701, 4.71377,   3.99684,   -3.2282,   3.46386,    -2.72125,  -1.49549,
+                -3.83636,  -4.7897,     0.78226,   2.3058,    -4.82898,  -2.61577,  -4.87581,   2.31266,   1.67058,
+                -0.312257, -0.545391,   -3.86117,  -4.92605,  -0.722609, -0.144248, -4.35181,   0.483898,  -3.27626,
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+                -0.816687, -3.66164,    0.3431,    -2.17813,  -4.99742,  -4.13003,  -4.34429,   3.15146,   0.477193,
+                -3.18597,  4.0696,      -3.04081,  -0.751688, -2.3623,   2.81943,   1.98781,    1.14407,   2.95467,
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+                2.019,     1.88438,     -1.20996,  -2.34781,  0.800072,  4.22213,   3.82745,    0.660494,  -0.233822,
+                -3.85401,  -1.10944,    1.61249,   -2.75312,  -0.620572, -2.36705,  -4.35225,   -4.28065,  -0.369473,
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+                -3.72608,  3.21041,     -0.309079, -1.20312,  -1.04395,  -3.59398,  0.6059,     2.61891,   4.45666,
+                -4.75106,  3.21227,     1.7304,    -2.32413,  3.76143,   3.02153,   -3.54336,   -0.34727,  4.84026,
+                -0.198416, -3.46508,    -0.201522, 3.50927,   -1.84184,  -2.48124,  -0.669658,  -4.94919,  -3.52275,
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+                -1.05859,  -0.206402,   0.79939,   4.87222,   0.225406,  4.48362,   -2.90358,   1.55703,   1.98258,
+                2.35008,   3.94249,     2.61202,   -3.53563,  1.82492,   -2.68085,  -0.527339,  3.24015,   3.29355,
+                1.34272,   -1.10936,    -2.71789,  3.91075,   -2.14601,  -0.396423, -3.01396,   0.340825,  -4.43331,
+                -4.90419,  3.48833,     -3.20166,  2.02417,   -1.30311,  1.58947,   -3.03143,   3.37555,   -1.96399,
+                1.02333,   -3.52225,    -1.53211,  0.12215,   -1.34119,  -0.846173, -0.635141,  4.67665,   -0.405799,
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+                0.677431,  -4.85236,    3.18685,   -2.53947,  1.13715,   4.96326,   -0.793396,  1.19392,   2.5294,
+                2.75801,   -4.3221,     3.15646,   -1.48667,  -4.94554,  -3.23913,  4.02479,    -2.08067,  0.183081,
+                -4.38464,  -2.46221,    -4.73904,  -0.697342, -4.85434,  4.90753,   2.70221,    -1.31093,  -4.60081,
+                -3.58929,  3.71782,     -1.75827,  0.163215,  -3.75722,  1.62284,   -1.24612,   1.14538,   2.96385,
+                -4.10806,  -0.186223,   2.97828,   -3.48557,  0.912886,  -2.47933,  -0.141892,  1.38328,   -1.35453,
+                0.0855794, -0.420718,   2.81809,   -1.58504,  -3.24831,  -3.06183,  -1.00012,   -3.06554,  1.15852,
+                -4.66011,  -1.68974,    2.15275,   -4.81303,  -1.0497,   4.24721,   0.752416,   -2.9178,   2.80425,
+                -4.72424,  -4.04212,    1.70999,   4.54444,   2.7805,    -0.316397, -2.46779,   3.17646,   0.187879,
+                1.74938,   3.01256,     -3.66057,  2.37244,   2.91338,   2.67634,   -2.33103,   -1.07969,  1.37713,
+                -3.45046,  1.41599,     -2.58735,  1.66767,   0.978738,  -1.99731,  -1.185,     4.02593,   -3.86151,
+                3.34423,   3.45627,     -3.98229,  4.22739,   -3.05438,  -4.33193,  3.05151,    4.80124,   4.1618,
+                -3.6186,   -4.59032,    4.59652,   -1.2784,   -1.30989,  -3.37153,  2.88972,    -4.98978,  0.866851,
+                2.13723,   -1.54307,    -2.96314,  -0.727502, 1.31068,   0.444759,  1.69446,    2.77479,   -1.25197,
+                -0.59404,  -3.28619,    -2.14284,  4.55701,   -1.99698,  -4.1932,   1.98522,    0.330638,  4.14927,
+                -1.58213,  -1.19538,    -2.64269,  -4.77377,  -4.50282,  2.11742,   1.85531,    -1.0953,   -4.23724,
+                0.736428,  -3.5851,     1.48482,   0.141458,  -1.86905,  3.5453,    -2.82172,   -3.05134,  -3.75254,
+                4.95023,   -1.05753,    1.91518,   -3.26179,  4.54684,   -4.10982,  -1.89519,   1.14695,   1.47464,
+                1.4862,    -4.79501,    -4.77577,  -2.36627,  0.19994,   3.35062,   1.23547,    5},
+            std::vector<T>{-5,        -4.90212, 2.04852,  -4.06222, -2.05556, 1.71858,  4.89697,   -3.57399, 3.22732,
+                           -1.36818,  -3.74683, -4.60178, 0.196569, 1.58981,  -3.29433, -2.98955,  2.02674,  1.8465,
+                           -1.85874,  -2.1893,  4.83577,  1.90244,  2.07352,  0.598257, 3.49708,   1.4686,   0.754768,
+                           1.94554,   3.96111,  0.133566, -3.82646, 4.88763,  0.229708, -2.03485,  3.4875,   1.79253,
+                           -0.38706,  -2.65237, 0.100763, -2.15537, 1.71114,  4.87242,  -0.449133, 3.7298,   -4.50384,
+                           0.0434988, -4.31846, -4.79365, -2.04677, -4.72319, 1.47757,  1.06105,   3.82314,  3.14707,
+                           4.1567,    1.89765,  4.28057,  3.15959,  1.97148,  3.77296,  2.90827,   3.08369,  4.84089,
+                           -1.83596,  2.32062,  -4.18992, 1.58745,  0.212731, -3.36909, -1.486,    2.07869,  -1.65644,
+                           1.39901,   1.31554,  1.7938,   4.02885,  -1.31798, 0.48152,  -0.964317, 5},
+            std::vector<T>{
+                -0.999909,    -5.07626e-11, 4.13326e-13,  5.835e-05,    -1.30828e-35, 0.761594,     -3.42026e-22,
+                -1.13159e-30, -4.18379e-13, 0.821244,     -0.999909,    -5.07626e-11, 0.49691,      0.000728936,
+                6.90693e-27,  0.963522,     -9.60537e-09, -0.997578,    -0.0213497,   5.66025e-14,  -0.999928,
+                2.69134e-08,  4.40231e-06,  -6.96162e-19, 0.511536,     0.287868,     -0.762594,    -0.997594,
+                -0.9476,      0.76483,      -0.999465,    1.57167e-10,  0.49691,      -3.00368e-17, -1.50091e-08,
+                0.785706,     -0.368554,    -0.997594,    -0.981176,    -0.761575,    -7.99627e-07, 9.21166e-05,
+                0.332835,     4.10511e-31,  -9.42096e-13, 0.378887,     -0.00455473,  2.21606e-11,  -0.997432,
+                1.16333e-05,  -8.98809e-32, 3.03724e-15,  0.25859,      -0.000176827, -0.954949,    2.55493e-17,
+                -0.983461,    9.09049e-13,  -0.980796,    0.784393,     -0.000793236, 2.55449e-20,  5.38752e-09,
+                -9.86419e-35, -1.94761e-19, 1.83397e-12,  -0.988398,    3.78249e-10,  -0.997432,    0.771463,
+                -3.52882e-15, 1.21005e-16,  0.000182383,  -4.34274e-08, -0.594177,    1.33054e-06,  -0.920454,
+                0.76128,      -0.999382,    0.000389586,  -9.19733e-06, 4.3138e-07,   1.41793e-21,  -0.761594,
+                0.305402,     0.000580937,  -0.531783,    -1.00171e-05, 5.83801e-30,  0.0243704,    -1.23107e-30,
+                0.00725055,   0.76182,      1.27929e-05,  1.58846e-07,  -0.680477,    -5.73051e-15, 6.33457e-20,
+                0.000288991,  0.00312473,   0.761596,     -0.000445729, 2.03617e-09,  5.11049e-30,  0.964028,
+                -1.18563e-22, 3.80413e-32,  -1.97169e-18, -0.759971,    -1.27976e-07, 0.74886,      -0.000445729,
+                0.805263,     -1.49589e-10, 0.641535,     -1.41323e-07, 1.47308e-24,  -4.77803e-13, -5.96046e-08,
+                -1.95598e-10, -0.581045,    -0.00103914,  0.805263,     1.64052e-14,  0.00323384,   1.15601e-13,
+                6.4162e-14,   2.77607e-22,  0.0497418,    5.30151e-18,  -0.329421,    -2.57703e-06, 0.963854,
+                -1.01966e-13, -1.18368e-08, 6.02313e-09,  0.114898,     9.46065e-13,  0.761594,     2.13439e-08,
+                0.523866,     0.761529,     0.760565,     -0.00461076,  0.00150048,   -0.00174691,  -0.436961,
+                5.48788e-11,  2.41781e-14,  2.19602e-08,  -6.14432e-17, 8.04105e-14,  -3.89646e-18, -0.00379894,
+                3.63214e-16,  -0.616305,    0.964023,     5.81763e-07,  1.09818e-06,  2.19604e-08,  -0.87856,
+                -0.354106,    -0.715297,    -1.65026e-20, 6.05625e-17,  2.48927e-05,  1.96127e-05,  1.41168e-23,
+                5.4023e-07,   0.761544,     -3.06545e-19, -7.18136e-08, -1.8746e-07,  -1.47835e-07, 1.34948e-07,
+                0.761594,     0.999987,     3.23361e-26,  1.28856e-06,  0.761618,     -0.892197,    1.36596e-19,
+                6.65404e-09,  -2.64782e-09, 0.766419,     -0.998266,    0.000204802,  1.00874e-08,  -4.23892e-11,
+                2.38972e-09,  -0.901095,    0.00314948,   0.156432,     -3.46747e-21, 0.766474,     -4.19696e-07,
+                0.00359662,   0.985378,     1.26476e-26,  1.36917e-06,  -8.30729e-05, 1.09966e-09,  3.39125e-24,
+                -2.54402e-09, -0.0224086,   0.999078,     -8.56764e-17, 2.17593e-09,  -5.3338e-18,  -2.09897e-25,
+                -0.731555,    1.0058e-09,   1.80811e-06,  -7.35442e-08, 5.03322e-18,  0.99907,      5.06163e-08,
+                0.998803,     -3.31849e-14, -0.314541,    6.56072e-06,  2.3231e-05,   -0.734035,    -0.801636,
+                0.761566,     1.44226e-12,  -0.521044,    0.998576,     2.04797e-08,  -0.999782,    8.46822e-16,
+                0.236769,     -1.06652e-14, -0.000473771, 0.964,        1.61872e-15,  -0.918253,    -6.50992e-10,
+                1.19996e-09,  -0.976642,    -1.74187e-06, 2.59573e-19,  -2.2928e-13,  -8.87904e-17, 0.148158,
+                4.75517e-15,  -0.98799,     -6.50965e-10, -0.761594,    0.760215,     0.000518275,  0.434619,
+                -0.0692393,   -0.761594,    0.274058,     6.53858e-08,  -0.998366,    -3.22841e-06, 1.72996e-06,
+                0.963795,     -0.735883,    -1.68637e-22, 0.00299617,   -2.95948e-14, -0.754872,    0.964028,
+                -0.832263,    2.96769e-05,  -1.3113e-06,  0.761594,     1.00882e-20,  -0.700681,    0.251888,
+                -1.44631e-16, -5.78152e-16, 0.964028,     -3.13362e-09, 2.38789e-16,  -1.29541e-06, -4.12287e-11,
+                3.57653e-37,  -0.953416,    -0.00116461,  4.51481e-11,  0.000654999,  -9.88477e-13, -8.25559e-09,
+                3.24498e-11,  0.631349,     -2.22783e-15, 0.00463415,   -0.218827,    -3.33063e-20, 2.62387e-15,
+                0.000655749,  -0.761594,    -9.3791e-19,  3.55914e-07,  1.21115e-10,  8.51853e-05,  0.746421,
+                -0.203347,    0.964016,     -0.675211,    -0.757478,    4.1336e-13,   1.31125e-14,  -0.752869,
+                -3.40686e-11, -9.04177e-20, 0.761593,     -0.203337,    0.761593,     4.32757e-13,  0.761594,
+                1.12104e-12,  1.10405e-22,  2.21747e-11,  -0.761594,    -0.000232199, -7.34674e-20, -0.761592,
+                1.12101e-05,  0.96248,      1.05897e-15,  -0.961035,    0.995049,     0.714666,     -0.11871,
+                0.252246,     -3.96402e-21, -0.116561,    -2.34864e-11, 1.73253e-05,  6.71033e-11,  -0.761585,
+                0.964016,     5.67781e-08,  -0.00572334,  0.76158,      -0.520498,    5.11946e-09,  -1.68016e-05,
+                7.55615e-09,  0.959448,     -2.85015e-19, 0.753059,     4.49821e-06,  1.60358e-10,  3.66218e-21,
+                -2.05996e-14, 9.10536e-05,  0.443528,     0.000286103,  1.1389e-16,   -0.332143,    0.000106997,
+                1.66753e-09,  -0.761594,    7.13778e-13,  -0.71679,     -0.761576,    0.754419,     0.000282388,
+                -0.762039,    9.84022e-09,  -0.0872869,   7.7548e-11,   6.80808e-09,  2.60995e-08,  4.78222e-09,
+                -0.501957,    0.762282,     -0.753946,    -1.47174e-09, -0.964027,    -0.7082,      -0.963465,
+                -9.54667e-13, 3.02122e-08,  7.1591e-12,   6.3354e-14,   2.94622e-22,  -0.940787,    -6.09716e-15,
+                -2.65188e-14, -0.0115473,   -0.758209,    6.95914e-17,  0.760974,     0.140932,     4.35034e-05,
+                0.760892,     -0.632027,    -0.76149,     2.15703e-11,  0.777049,     -0.00238567,  5.3589e-28,
+                0.760506,     -8.19313e-13, -0.99918,     -1.76353e-09, -3.25938e-08, 3.69808e-14,  5.13777e-15,
+                -0.992067,    3.2008e-13,   -4.27895e-35, -0.00033198,  -2.22583e-14, 2.33933e-18,  -1.83076e-06,
+                -2.05328e-23, 0.335589,     6.74499e-20,  -0.993734,    3.25956e-15,  -0.76157,     0.761592,
+                -1.39733e-26, 3.51873e-08,  -0.000449794, 0.753596,     6.14397e-06,  -0.0399566,   6.81031e-16,
+                -1.4436e-16,  6.54251e-37,  6.25711e-16,  -0.751923,    1.76327e-06,  -0.759611,    -5.82387e-22,
+                -3.55939e-10, 2.0026e-05,   1.42291e-08,  0.00127849,   -0.761586,    0.920489,     -0.0123201,
+                1.49775e-11,  -0.759593,    0.760956,     -1.59088e-19, 1.89399e-06,  1.41353e-17,  -3.71678e-07,
+                -7.58637e-09, 4.56301e-13,  -0.76173,     6.38001e-12,  -3.26879e-12, 2.54147e-19,  0.00349909,
+                1.94641e-15,  0.000533218,  -0.680174,    -0.798763,    -0.749397,    -1.51134e-16, 0.76157,
+                -0.758462,    0.212695,     2.33021e-17,  1.62019e-15,  -5.34576e-05, -2.0166e-15,  -0.0958154,
+                -3.4894e-05,  1.54693e-09,  0.761228,     -0.045171,    -0.654946,    0.658682,     0.000900979,
+                -0.0121633,   -9.55765e-07, -5.83339e-07, -0.697058,    3.12132e-18,  0.599694,     -2.41771e-11,
+                0.128772,     0.0345568,    0.0222523,    -3.01504e-23, -1.42109e-23, 1.32333e-13,  5.34001e-15,
+                -6.2253e-22,  8.88893e-22,  0.000599919,  -6.13229e-19, 9.45362e-05,  1.03827e-16,  -0.00543732,
+                -9.86013e-09, -0.761408,    0.214137,     -8.00209e-24, 0.679937,     0.917833,     -1.34199e-10,
+                1.89431e-07,  -0.761594,    -0.0442637,   -0.000217974, 0.00476938,   0.0246565,    -5.376e-08,
+                0.784315,     0.00101343,   0.0946926,    0.980865,     -0.761594,    -0.707944,    -4.73592e-12,
+                4.01193e-13,  1.73187e-07,  0.000424088,  2.85811e-08,  3.59465e-08,  -0.472002,    0.867616,
+                -0.757693,    -2.0641e-10,  -0.994265,    -9.17776e-06, 5.91256e-15,  0.963968,     0.31226,
+                0.0461947,    1.10725e-08,  2.92814e-07,  -5.24128e-08, -0.00704819,  -7.04583e-10, -0.000118595,
+                -0.760989,    0.761239,     0.312348,     0.0461707,    -4.89262e-06, 0.762134,     0.0216284,
+                4.89744e-20,  -0.705499,    -0.0105222,   -2.47122e-06, -0.0353277,   -0.529026,    0.0371158,
+                0.0910813,    0.964028,     0.761582,     0.0233926,    -2.56495e-19, 2.55893e-06,  -4.6058e-09,
+                0.0361859,    0.947518,     0.645797,     -1.36319e-07, 1.11416e-06,  -0.000967128, 1.71085e-06,
+                -3.83432e-05, -4.46048e-12, 1.68634e-09,  3.07729e-10,  0.0198492,    0.055882,     -1.79771e-09,
+                -2.43386e-18, -0.228931,    0.760035,     -0.761594,    -0.393895,    0.761594,     0.761594,
+                0.0695398,    -2.10839e-05, -0.761593,    -0.761593,    -7.67992e-12, -0.000156758, -0.761546,
+                -7.03448e-14, -1.32276e-19, -9.58347e-39, 4.26105e-18,  -5.41441e-05, 4.03958e-17,  4.40911e-16,
+                -0.747015,    -0.879764,    2.22597e-08,  -0.0910139,   0.999823,     0.999852,     -0.946979,
+                4.04764e-10,  1.04581e-21,  1.30145e-14,  9.21577e-17,  -0.000708233, 0.761594,     3.99524e-13,
+                9.18395e-17,  8.95967e-25,  6.11501e-20,  0.00901172,   -2.49613e-41, -1.17426e-18, 3.85668e-09,
+                -0.0678945,   7.0955e-16,   -0.761593,    0.792416,     0.999844,     0.441572,     0.00697713,
+                5.52616e-05,  2.76337e-24,  0.0128815,    -8.97325e-09, 0.0575689,    -9.19902e-17, 0.79131,
+                0.90745,      0.442877,     1.65895e-09,  -9.49956e-12, -0.761592,    0.759226,     -0.788664,
+                0.428198,     4.22296e-08,  0.960446,     -3.30814e-05, -7.32391e-11, -0.761195,    0.761591,
+                -0.11482,     0.00328929,   -0.751446,    -0.0329113,   -2.38419e-07, -0.742049,    -0.761814,
+                2.28806e-08,  9.20868e-10,  7.83398e-05,  0.163255,     0.693679,     0.0233387,    -0.0002779,
+                -0.00744079,  0.761594,     -1.92574e-35, -6.19079e-15, 0.841117,     3.61402e-15,  7.29652e-05,
+                -3.43512e-15, 2.44003e-10,  5.02575e-21,  -0.575338,    0.760067,     -7.58183e-07, -0.411779,
+                0.937771,     -5.07946e-26, -0.0015457,   0.625772,     -0.128913,    7.19112e-12,  -0.483728,
+                5.19518e-07,  2.4981e-17,   -2.77282e-10, -6.1325e-23,  4.02951e-22,  -0.55648,     0.627102,
+                -6.88607e-19, 9.6838e-17,   -0.0142015,   1.0327e-05,   -0.761481,    3.44292e-08,  -0.644774,
+                5.99614e-06,  -2.4661e-12,  0.939834,     -0.732183,    0.758408,     -0.406918,    0.761563,
+                0.624331,     0.959323,     -0.757392,    0.00112301,   0.0215218,    -7.76243e-10, -6.42156e-20,
+                -3.81184e-11, 2.64018e-18,  -0.00122851,  -9.04986e-17, 0.959198,     -0.180509,    8.1107e-09,
+                4.4799e-16,   -0.761594,    0.761594,     -3.2702e-11,  6.12426e-16,  -7.52802e-11, 0.727842,
+                0.736519,     0.00697721,   0.00189766,   0.65557,      -8.23888e-06, 1.19768e-19,  -0.628732,
+                4.50315e-07,  -0.596042,    -0.130076,    -0.0570775,   -0.758032,    -0.720559,    0.329393,
+                -0.000139915, -7.64476e-11, -1.93167e-30, 8.91504e-10,  -5.52299e-08, -0.00538237,  -1.59122e-08,
+                -4.0649e-14,  -0.747447,    0.871613,     4.90251e-14,  0.760524,     0.623387,     0.761594,
+                -0.963604,    -0.761594,    -0.760084,    0.76159,      -0.726583,    0.783823,     2.00219e-05,
+                1.12777e-06,  1.49013e-16,  0.761591,     -0.625537,    2.84003e-10,  4.32528e-16,  2.39073e-07,
+                -6.75822e-06, 2.44769e-23,  -1.39062e-07, 0.768824,     -0.000734329, -1.18028e-08, -9.31533e-16,
+                1.32778e-09,  -5.24861e-07, 0.7686,       1.34084e-06,  -0.0222266,   -0.775352,    0.000264648,
+                -2.44784e-27, -8.62503e-05, -0.523765,    8.05469e-07,  -8.00327e-17, 1.0076e-08,   0.655086,
+                1.12223e-07,  -2.45992e-13, 0.761594,     -0.000735076, -3.16667e-21, -1.0616e-12,  0.999911,
+                6.67684e-10,  -0.386663,    9.55342e-24,  0.000750192,  -3.04876e-14, 1.69092e-13,  2.57222e-30,
+                -0.886215,    -8.85092e-18, -0.999066,    -0.992009,    -9.64733e-07, 0.999793,     0.999959,
+                -4.526e-09,   -0.993717,    6.25306e-09,  1.5415e-21,   0.761594,     -5.23755e-08, -0.827688,
+                -0,           5.99811e-22,  0.999958,     -0.580146,    -6.79704e-17, 1.83394e-07,  1.31284e-13,
+                3.62265e-10,  0.35334,      -0.00903121,  -0.991192,    7.53642e-07,  -0.00913154,  -1.29673e-06,
+                -1.76794e-11, 1.83017e-07,  -0.000150782, 0.761551,     -0.739773,    -0.268164,    -0.991253,
+                0.761593,     -8.46913e-07, 4.02483e-07,  -0.0547462,   -0.0433184,   -0.0128592,   -0.000826936,
+                3.57959e-13,  -0.073303,    2.14562e-10,  7.38332e-11,  0.00409962,   0.724394,     -1.16275e-22,
+                1.63268e-25,  -1.47741e-05, 3.33773e-08,  -7.77931e-12, 2.71497e-08,  3.42017e-05,  0.761594,
+                -2.43217e-13, -6.87127e-23, -0.761548,    7.04828e-08,  -0.761307,    1.3015e-07,   -0.00537324,
+                1.27446e-16,  0.763627,     4.22074e-15,  -8.45132e-18, 0.00159667,   0.756707,     0.129373,
+                -0.964029,    0.761554,     3.34318e-14,  3.74157e-15,  0.763626,     4.1317e-22,   -0.734039,
+                4.81716e-07,  0.753698,     0.758801,     -0.995055,    -0.76151,     1.11652e-10,  1.10396e-07,
+                0.761582,     0.761191,     -0.949494,    4.12621e-08,  -0.0185743,   -5.64389e-13, 1.35275e-28,
+                -0.761587,    -2.38573e-16, -3.53137e-05, -0.438905,    0.0134316,    4.40739e-11,  -3.01366e-05,
+                -1.38874e-32, -3.77945e-21, 0.0780586,    1.6805e-13,   0.751234,     -0.803057,    0.811984,
+                7.895e-05,    0.761593,     -0.00119532,  -5.48256e-06, 0.757714,     0.761594,     -0.761511,
+                -1.92404e-24, -1.41394e-08, 0.983753,     4.33593e-18,  6.11314e-09,  -0.000849993, -0.96402,
+                -3.8176e-18,  -1.24685e-14, 8.03048e-05,  0.994964,     0.130676,     0.922726,     1.28861e-07,
+                0.761594,     -6.48442e-30, -0.761584,    0.761594,     -3.41314e-14, -1.08584e-06, 0.963591,
+                0.130676,     0.542119,     -0.725731,    0.761583,     -1.63707e-11, 2.25863e-17,  0.766755,
+                -0.761594,    -9.47899e-06, 0.760034,     0.0996578,    0.757886,     -0.761808,    -0.000816665,
+                -0.000733465, 0.761594,     0.670761,     -4.79781e-25, -3.77769e-09, -0.071795,    -2.09178e-29,
+                -2.96662e-22, -5.45929e-22, 4.72562e-14,  2.23143e-12,  2.66405e-05,  0.948048,     -5.47349e-07,
+                0.761064,     -0.071795,    -1.62295e-13, -2.48377e-11, 0.000322916,  1.0934e-18,   0.745943,
+                0.000203257,  2.9748e-09,   2.94779e-09,  0.000904395,  -1.33357e-12, -0.761594,    4.154e-08,
+                0.761365,     -1.23576e-05, -0.118402,    0.758765,     8.3947e-11,   0.757683,     0.00091744,
+                6.04679e-13,  -8.36692e-05, -7.73738e-13, -0.964028,    -2.87151e-05, -0.964027,    -0.761415,
+                2.8511e-12,   0.982895,     0.000913338,  0.761594,     -5.61929e-05, -4.03471e-09, -9.05792e-10,
+                -2.44896e-14, -0.761593,    -1.53072e-14, 4.80451e-06,  4.97845e-05,  2.61901e-17},
+            std::vector<T>{
+                -1.23107e-30, 0.00725055,   0.76182,      1.27929e-05,  1.58846e-07,  -0.680477,    -5.73051e-15,
+                6.33457e-20,  0.000288991,  0.00312473,   0.761596,     -0.000445729, 2.03617e-09,  5.11049e-30,
+                0.964028,     -1.18563e-22, 3.80413e-32,  -1.97169e-18, -0.759971,    -1.27976e-07, 0.00463415,
+                -0.218827,    -3.33063e-20, 2.62387e-15,  0.000655749,  -0.761594,    -9.3791e-19,  3.55914e-07,
+                1.21115e-10,  8.51853e-05,  0.746421,     -0.203347,    0.964016,     -0.675211,    -0.757478,
+                4.1336e-13,   1.31125e-14,  -0.752869,    -3.40686e-11, -9.04177e-20, -6.2253e-22,  8.88893e-22,
+                0.000599919,  -6.13229e-19, 9.45362e-05,  1.03827e-16,  -0.00543732,  -9.86013e-09, -0.761408,
+                0.214137,     -8.00209e-24, 0.679937,     0.917833,     -1.34199e-10, 1.89431e-07,  -0.761594,
+                -0.0442637,   -0.000217974, 0.00476938,   0.0246565,    -0.761481,    3.44292e-08,  -0.644774,
+                5.99614e-06,  -2.4661e-12,  0.939834,     -0.732183,    0.758408,     -0.406918,    0.761563,
+                0.624331,     0.959323,     -0.757392,    0.00112301,   0.0215218,    -7.76243e-10, -6.42156e-20,
+                -3.81184e-11, 2.64018e-18,  -0.00122851,  -2.38573e-16, -3.53137e-05, -0.438905,    0.0134316,
+                4.40739e-11,  -3.01366e-05, -1.38874e-32, -3.77945e-21, 0.0780586,    1.6805e-13,   0.751234,
+                -0.803057,    0.811984,     7.895e-05,    0.761593,     -0.00119532,  -5.48256e-06, 0.757714,
+                0.761594,     -0.761511},
+            std::vector<T>{-1.14805e-14,
+                           0.00725081,
+                           1.00065,
+                           1.27929e-05,
+                           1.29939,
+                           -0.999801,
+                           -5.73051e-15,
+                           3.93105e-11,
+                           1.9999,
+                           0.0243762,
+                           1,
+                           -0.000445729,
+                           2.03617e-09,
+                           5.11049e-30,
+                           2,
+                           -1.67708e-22,
+                           1,
+                           -0.0034493,
+                           -1,
+                           -0.591546,
+                           0.00463418,
+                           -2.86822,
+                           -0.230709,
+                           0.0172415,
+                           0.000655749,
+                           -1,
+                           -3.072e-06,
+                           0.746059,
+                           7.45091e-09,
+                           8.51853e-05,
+                           0.965889,
+                           -0.206222,
+                           1.99984,
+                           -0.999999,
+                           -0.990272,
+                           1.11695e-12,
+                           0.0222863,
+                           -0.979547,
+                           -2,
+                           -1.01401,
+                           -0.999991,
+                           0.976968,
+                           1,
+                           -3.63016e-07,
+                           0.0208492,
+                           3.42118e-07,
+                           -0.00543741,
+                           -9.86013e-09,
+                           -0.999558,
+                           0.219696,
+                           -1.00056,
+                           0.828996,
+                           1.99999,
+                           -2.98023e-07,
+                           1.61781e-05,
+                           -1,
+                           -0.044346,
+                           -1.00563,
+                           0.099386,
+                           0.0246731,
+                           -0.999731,
+                           3.44351e-08,
+                           -0.766302,
+                           5.99614e-06,
+                           -0.087751,
+                           1.73662,
+                           -0.999998,
+                           1,
+                           -0.431925,
+                           0.999926,
+                           0.732687,
+                           1.93734,
+                           -0.99007,
+                           1.41437,
+                           0.0215275,
+                           -7.76243e-10,
+                           -1.4114e-06,
+                           -1.2676,
+                           9.7866e-11,
+                           -0.999843,
+                           -0.0294529,
+                           -3.65437e-05,
+                           -0.470874,
+                           0.998836,
+                           1.19728e-05,
+                           -3.01366e-05,
+                           -1.90968e-25,
+                           -2.75275e-07,
+                           0.0782207,
+                           0.000366083,
+                           0.975781,
+                           -1.10725,
+                           1.13283,
+                           7.895e-05,
+                           1,
+                           -0.00119563,
+                           -0.99991,
+                           0.990824,
+                           1,
+                           -1}),
     };
     return params;
 }
@@ -1096,740 +1299,704 @@ template <element::Type_t ET>
 std::vector<LSTMSequenceParams> generateParamsBF16() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<LSTMSequenceParams> params {
+    std::vector<LSTMSequenceParams> params{
         LSTMSequenceParams(
-            5, 10, 10, 10,
-            0.7f, op::RecurrentSequenceDirection::FORWARD,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            op::RecurrentSequenceDirection::FORWARD,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  10},
+            std::vector<T>{
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,     2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,  5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625, 1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375, 10},
             std::vector<T>{
                 0.523438, 0.667969, 0.667969, 0.667969, 0.667969, 0.523438, 0.632812, 0.664062, 0.667969, 0.640625,
-                0.539062, 0.664062, 0.667969, 0.667969, 0.667969, 0.539062, 0.617188, 0.65625, 0.667969, 0.625,
+                0.539062, 0.664062, 0.667969, 0.667969, 0.667969, 0.539062, 0.617188, 0.65625,  0.667969, 0.625,
                 0.546875, 0.648438, 0.667969, 0.664062, 0.667969, 0.546875, 0.601562, 0.640625, 0.667969, 0.609375,
-                0.546875, 0.632812, 0.664062, 0.65625, 0.664062, 0.546875, 0.585938, 0.625, 0.664062, 0.59375,
-                0.554688, 0.617188, 0.65625, 0.640625, 0.648438, 0.554688, 0.578125, 0.609375, 0.65625, 0.585938,
-                0.554688, 0.601562, 0.640625, 0.625, 0.640625, 0.554688, 0.570312, 0.59375, 0.640625, 0.578125,
-                0.554688, 0.59375, 0.625, 0.609375, 0.625, 0.554688, 0.570312, 0.585938, 0.625, 0.570312,
-                0.554688, 0.585938, 0.609375, 0.59375, 0.609375, 0.554688, 0.5625, 0.578125, 0.609375, 0.570312,
-                0.554688, 0.570312, 0.59375, 0.585938, 0.59375, 0.554688, 0.5625, 0.570312, 0.59375, 0.5625,
-                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625, 0.570312, 0.585938, 0.5625,
-                0.65625, 0.617188, 0.664062, 0.648438, 0.664062, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969,
-                0.648438, 0.601562, 0.664062, 0.632812, 0.664062, 0.65625, 0.667969, 0.664062, 0.667969, 0.664062,
+                0.546875, 0.632812, 0.664062, 0.65625,  0.664062, 0.546875, 0.585938, 0.625,    0.664062, 0.59375,
+                0.554688, 0.617188, 0.65625,  0.640625, 0.648438, 0.554688, 0.578125, 0.609375, 0.65625,  0.585938,
+                0.554688, 0.601562, 0.640625, 0.625,    0.640625, 0.554688, 0.570312, 0.59375,  0.640625, 0.578125,
+                0.554688, 0.59375,  0.625,    0.609375, 0.625,    0.554688, 0.570312, 0.585938, 0.625,    0.570312,
+                0.554688, 0.585938, 0.609375, 0.59375,  0.609375, 0.554688, 0.5625,   0.578125, 0.609375, 0.570312,
+                0.554688, 0.570312, 0.59375,  0.585938, 0.59375,  0.554688, 0.5625,   0.570312, 0.59375,  0.5625,
+                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625,   0.570312, 0.585938, 0.5625,
+                0.65625,  0.617188, 0.664062, 0.648438, 0.664062, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969,
+                0.648438, 0.601562, 0.664062, 0.632812, 0.664062, 0.65625,  0.667969, 0.664062, 0.667969, 0.664062,
                 0.632812, 0.585938, 0.648438, 0.617188, 0.648438, 0.648438, 0.664062, 0.648438, 0.667969, 0.65625,
-                0.617188, 0.578125, 0.632812, 0.601562, 0.632812, 0.632812, 0.65625, 0.632812, 0.664062, 0.648438,
+                0.617188, 0.578125, 0.632812, 0.601562, 0.632812, 0.632812, 0.65625,  0.632812, 0.664062, 0.648438,
                 0.601562, 0.570312, 0.617188, 0.585938, 0.617188, 0.617188, 0.640625, 0.617188, 0.648438, 0.632812,
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-                0.570312, 0.5625, 0.578125, 0.570312, 0.578125, 0.578125, 0.59375, 0.578125, 0.609375, 0.585938,
-                0.570312, 0.5625, 0.570312, 0.5625, 0.570312, 0.570312, 0.585938, 0.570312, 0.59375, 0.578125,
-                0.5625, 0.554688, 0.570312, 0.5625, 0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
-                0.667969, 0.667969, 0.664062, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969, 0.65625, 0.5625,
-                0.667969, 0.664062, 0.65625, 0.667969, 0.664062, 0.640625, 0.664062, 0.667969, 0.640625, 0.5625,
-                0.664062, 0.648438, 0.640625, 0.664062, 0.65625, 0.625, 0.65625, 0.664062, 0.625, 0.554688,
-                0.65625, 0.632812, 0.625, 0.65625, 0.648438, 0.609375, 0.640625, 0.664062, 0.609375, 0.554688,
-                0.648438, 0.617188, 0.609375, 0.640625, 0.632812, 0.59375, 0.625, 0.648438, 0.59375, 0.554688,
-                0.632812, 0.601562, 0.59375, 0.625, 0.617188, 0.585938, 0.609375, 0.632812, 0.585938, 0.554688,
-                0.617188, 0.59375, 0.585938, 0.609375, 0.601562, 0.578125, 0.59375, 0.617188, 0.578125, 0.554688,
-                0.601562, 0.585938, 0.578125, 0.59375, 0.585938, 0.570312, 0.585938, 0.601562, 0.570312, 0.554688,
+                0.585938, 0.570312, 0.601562, 0.578125, 0.601562, 0.601562, 0.625,    0.601562, 0.640625, 0.617188,
+                0.578125, 0.5625,   0.585938, 0.570312, 0.585938, 0.585938, 0.609375, 0.585938, 0.625,    0.601562,
+                0.570312, 0.5625,   0.578125, 0.570312, 0.578125, 0.578125, 0.59375,  0.578125, 0.609375, 0.585938,
+                0.570312, 0.5625,   0.570312, 0.5625,   0.570312, 0.570312, 0.585938, 0.570312, 0.59375,  0.578125,
+                0.5625,   0.554688, 0.570312, 0.5625,   0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
+                0.667969, 0.667969, 0.664062, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969, 0.65625,  0.5625,
+                0.667969, 0.664062, 0.65625,  0.667969, 0.664062, 0.640625, 0.664062, 0.667969, 0.640625, 0.5625,
+                0.664062, 0.648438, 0.640625, 0.664062, 0.65625,  0.625,    0.65625,  0.664062, 0.625,    0.554688,
+                0.65625,  0.632812, 0.625,    0.65625,  0.648438, 0.609375, 0.640625, 0.664062, 0.609375, 0.554688,
+                0.648438, 0.617188, 0.609375, 0.640625, 0.632812, 0.59375,  0.625,    0.648438, 0.59375,  0.554688,
+                0.632812, 0.601562, 0.59375,  0.625,    0.617188, 0.585938, 0.609375, 0.632812, 0.585938, 0.554688,
+                0.617188, 0.59375,  0.585938, 0.609375, 0.601562, 0.578125, 0.59375,  0.617188, 0.578125, 0.554688,
+                0.601562, 0.585938, 0.578125, 0.59375,  0.585938, 0.570312, 0.585938, 0.601562, 0.570312, 0.554688,
                 0.585938, 0.570312, 0.570312, 0.585938, 0.578125, 0.570312, 0.578125, 0.585938, 0.570312, 0.554688,
-                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625, 0.570312, 0.578125, 0.5625, 0.554688,
+                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625,   0.570312, 0.578125, 0.5625,   0.554688,
                 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.632812, 0.667969, 0.648438,
                 0.664062, 0.667969, 0.667969, 0.664062, 0.664062, 0.664062, 0.664062, 0.617188, 0.667969, 0.632812,
-                0.65625, 0.664062, 0.667969, 0.648438, 0.65625, 0.65625, 0.648438, 0.601562, 0.667969, 0.617188,
-                0.648438, 0.65625, 0.664062, 0.632812, 0.640625, 0.648438, 0.640625, 0.59375, 0.664062, 0.601562,
-                0.632812, 0.640625, 0.648438, 0.617188, 0.625, 0.632812, 0.625, 0.585938, 0.648438, 0.59375,
-                0.617188, 0.625, 0.632812, 0.601562, 0.609375, 0.617188, 0.609375, 0.570312, 0.640625, 0.585938,
-                0.601562, 0.609375, 0.617188, 0.59375, 0.59375, 0.601562, 0.59375, 0.570312, 0.625, 0.570312,
-                0.585938, 0.59375, 0.601562, 0.585938, 0.585938, 0.585938, 0.585938, 0.5625, 0.609375, 0.570312,
-                0.578125, 0.585938, 0.59375, 0.570312, 0.578125, 0.578125, 0.578125, 0.5625, 0.59375, 0.5625,
-                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625, 0.585938, 0.5625,
+                0.65625,  0.664062, 0.667969, 0.648438, 0.65625,  0.65625,  0.648438, 0.601562, 0.667969, 0.617188,
+                0.648438, 0.65625,  0.664062, 0.632812, 0.640625, 0.648438, 0.640625, 0.59375,  0.664062, 0.601562,
+                0.632812, 0.640625, 0.648438, 0.617188, 0.625,    0.632812, 0.625,    0.585938, 0.648438, 0.59375,
+                0.617188, 0.625,    0.632812, 0.601562, 0.609375, 0.617188, 0.609375, 0.570312, 0.640625, 0.585938,
+                0.601562, 0.609375, 0.617188, 0.59375,  0.59375,  0.601562, 0.59375,  0.570312, 0.625,    0.570312,
+                0.585938, 0.59375,  0.601562, 0.585938, 0.585938, 0.585938, 0.585938, 0.5625,   0.609375, 0.570312,
+                0.578125, 0.585938, 0.59375,  0.570312, 0.578125, 0.578125, 0.578125, 0.5625,   0.59375,  0.5625,
+                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625,   0.585938, 0.5625,
                 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.664062, 0.617188, 0.667969, 0.667969, 0.667969,
-                0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625, 0.601562, 0.667969, 0.664062, 0.667969,
-                0.664062, 0.664062, 0.664062, 0.667969, 0.664062, 0.640625, 0.585938, 0.664062, 0.65625, 0.667969,
-                0.65625, 0.65625, 0.65625, 0.664062, 0.65625, 0.625, 0.578125, 0.65625, 0.648438, 0.664062,
-                0.648438, 0.648438, 0.640625, 0.65625, 0.648438, 0.609375, 0.570312, 0.640625, 0.632812, 0.65625,
-                0.632812, 0.632812, 0.625, 0.640625, 0.632812, 0.59375, 0.570312, 0.625, 0.617188, 0.640625,
-                0.617188, 0.617188, 0.609375, 0.625, 0.617188, 0.585938, 0.5625, 0.609375, 0.601562, 0.625,
-                0.601562, 0.601562, 0.59375, 0.609375, 0.601562, 0.578125, 0.5625, 0.59375, 0.585938, 0.609375,
-                0.585938, 0.585938, 0.585938, 0.59375, 0.585938, 0.570312, 0.5625, 0.585938, 0.578125, 0.59375,
-                0.578125, 0.578125, 0.578125, 0.585938, 0.578125, 0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
-            std::vector<T>{
-                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625, 0.570312, 0.585938, 0.5625,
-                0.5625, 0.554688, 0.570312, 0.5625, 0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
-                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625, 0.570312, 0.578125, 0.5625, 0.554688,
-                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625, 0.585938, 0.5625,
+                0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625,  0.601562, 0.667969, 0.664062, 0.667969,
+                0.664062, 0.664062, 0.664062, 0.667969, 0.664062, 0.640625, 0.585938, 0.664062, 0.65625,  0.667969,
+                0.65625,  0.65625,  0.65625,  0.664062, 0.65625,  0.625,    0.578125, 0.65625,  0.648438, 0.664062,
+                0.648438, 0.648438, 0.640625, 0.65625,  0.648438, 0.609375, 0.570312, 0.640625, 0.632812, 0.65625,
+                0.632812, 0.632812, 0.625,    0.640625, 0.632812, 0.59375,  0.570312, 0.625,    0.617188, 0.640625,
+                0.617188, 0.617188, 0.609375, 0.625,    0.617188, 0.585938, 0.5625,   0.609375, 0.601562, 0.625,
+                0.601562, 0.601562, 0.59375,  0.609375, 0.601562, 0.578125, 0.5625,   0.59375,  0.585938, 0.609375,
+                0.585938, 0.585938, 0.585938, 0.59375,  0.585938, 0.570312, 0.5625,   0.585938, 0.578125, 0.59375,
                 0.578125, 0.578125, 0.578125, 0.585938, 0.578125, 0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
-            std::vector<T>{
-                1.20312, 1.27344, 1.375, 1.32031, 1.35156, 1.20312, 1.22656, 1.25781, 1.375, 1.23438,
-                1.25, 1.21875, 1.26562, 1.23438, 1.26562, 1.26562, 1.32031, 1.26562, 1.35156, 1.28906,
-                1.34375, 1.27344, 1.25781, 1.32031, 1.28906, 1.24219, 1.28125, 1.34375, 1.24219, 1.21875,
-                1.28906, 1.32031, 1.35156, 1.27344, 1.28125, 1.29688, 1.28125, 1.22656, 1.35156, 1.23438,
-                1.32812, 1.32812, 1.32031, 1.35938, 1.32812, 1.25781, 1.21875, 1.32031, 1.28906, 1.375}),
+            std::vector<T>{0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625,   0.570312, 0.585938,
+                           0.5625,   0.5625,   0.554688, 0.570312, 0.5625,   0.570312, 0.570312, 0.578125, 0.570312,
+                           0.585938, 0.570312, 0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625,   0.570312,
+                           0.578125, 0.5625,   0.554688, 0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312,
+                           0.570312, 0.5625,   0.585938, 0.5625,   0.578125, 0.578125, 0.578125, 0.585938, 0.578125,
+                           0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
+            std::vector<T>{1.20312, 1.27344, 1.375,   1.32031, 1.35156, 1.20312, 1.22656, 1.25781, 1.375,   1.23438,
+                           1.25,    1.21875, 1.26562, 1.23438, 1.26562, 1.26562, 1.32031, 1.26562, 1.35156, 1.28906,
+                           1.34375, 1.27344, 1.25781, 1.32031, 1.28906, 1.24219, 1.28125, 1.34375, 1.24219, 1.21875,
+                           1.28906, 1.32031, 1.35156, 1.27344, 1.28125, 1.29688, 1.28125, 1.22656, 1.35156, 1.23438,
+                           1.32812, 1.32812, 1.32031, 1.35938, 1.32812, 1.25781, 1.21875, 1.32031, 1.28906, 1.375}),
         LSTMSequenceParams(
-            5, 10, 10, 10,
-            0.7f, op::RecurrentSequenceDirection::REVERSE,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            op::RecurrentSequenceDirection::REVERSE,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 10},
-            std::vector<T>{
-                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625, 0.570312, 0.585938, 0.5625,
-                0.554688, 0.570312, 0.59375, 0.585938, 0.59375, 0.554688, 0.5625, 0.570312, 0.59375, 0.5625,
-                0.554688, 0.585938, 0.609375, 0.59375, 0.609375, 0.554688, 0.5625, 0.578125, 0.609375, 0.570312,
-                0.554688, 0.59375, 0.625, 0.609375, 0.625, 0.554688, 0.570312, 0.585938, 0.625, 0.570312,
-                0.554688, 0.601562, 0.640625, 0.625, 0.640625, 0.554688, 0.570312, 0.59375, 0.640625, 0.578125,
-                0.554688, 0.617188, 0.65625, 0.640625, 0.648438, 0.554688, 0.578125, 0.609375, 0.65625, 0.585938,
-                0.546875, 0.632812, 0.664062, 0.65625, 0.664062, 0.546875, 0.585938, 0.625, 0.664062, 0.59375,
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  10},
+            std::vector<T>{
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,     2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,  5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625, 1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375, 10},
+            std::vector<T>{
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+                0.554688, 0.570312, 0.59375,  0.585938, 0.59375,  0.554688, 0.5625,   0.570312, 0.59375,  0.5625,
+                0.554688, 0.585938, 0.609375, 0.59375,  0.609375, 0.554688, 0.5625,   0.578125, 0.609375, 0.570312,
+                0.554688, 0.59375,  0.625,    0.609375, 0.625,    0.554688, 0.570312, 0.585938, 0.625,    0.570312,
+                0.554688, 0.601562, 0.640625, 0.625,    0.640625, 0.554688, 0.570312, 0.59375,  0.640625, 0.578125,
+                0.554688, 0.617188, 0.65625,  0.640625, 0.648438, 0.554688, 0.578125, 0.609375, 0.65625,  0.585938,
+                0.546875, 0.632812, 0.664062, 0.65625,  0.664062, 0.546875, 0.585938, 0.625,    0.664062, 0.59375,
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+                0.539062, 0.664062, 0.667969, 0.667969, 0.667969, 0.539062, 0.617188, 0.65625,  0.667969, 0.625,
                 0.523438, 0.667969, 0.667969, 0.667969, 0.667969, 0.523438, 0.632812, 0.664062, 0.667969, 0.640625,
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-                0.570312, 0.5625, 0.570312, 0.5625, 0.570312, 0.570312, 0.585938, 0.570312, 0.59375, 0.578125,
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-                0.585938, 0.570312, 0.601562, 0.578125, 0.601562, 0.601562, 0.625, 0.601562, 0.640625, 0.617188,
+                0.5625,   0.554688, 0.570312, 0.5625,   0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
+                0.570312, 0.5625,   0.570312, 0.5625,   0.570312, 0.570312, 0.585938, 0.570312, 0.59375,  0.578125,
+                0.570312, 0.5625,   0.578125, 0.570312, 0.578125, 0.578125, 0.59375,  0.578125, 0.609375, 0.585938,
+                0.578125, 0.5625,   0.585938, 0.570312, 0.585938, 0.585938, 0.609375, 0.585938, 0.625,    0.601562,
+                0.585938, 0.570312, 0.601562, 0.578125, 0.601562, 0.601562, 0.625,    0.601562, 0.640625, 0.617188,
                 0.601562, 0.570312, 0.617188, 0.585938, 0.617188, 0.617188, 0.640625, 0.617188, 0.648438, 0.632812,
-                0.617188, 0.578125, 0.632812, 0.601562, 0.632812, 0.632812, 0.65625, 0.632812, 0.664062, 0.648438,
+                0.617188, 0.578125, 0.632812, 0.601562, 0.632812, 0.632812, 0.65625,  0.632812, 0.664062, 0.648438,
                 0.632812, 0.585938, 0.648438, 0.617188, 0.648438, 0.648438, 0.664062, 0.648438, 0.667969, 0.65625,
-                0.648438, 0.601562, 0.664062, 0.632812, 0.664062, 0.65625, 0.667969, 0.664062, 0.667969, 0.664062,
-                0.65625, 0.617188, 0.664062, 0.648438, 0.664062, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969,
-                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625, 0.570312, 0.578125, 0.5625, 0.554688,
+                0.648438, 0.601562, 0.664062, 0.632812, 0.664062, 0.65625,  0.667969, 0.664062, 0.667969, 0.664062,
+                0.65625,  0.617188, 0.664062, 0.648438, 0.664062, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969,
+                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625,   0.570312, 0.578125, 0.5625,   0.554688,
                 0.585938, 0.570312, 0.570312, 0.585938, 0.578125, 0.570312, 0.578125, 0.585938, 0.570312, 0.554688,
-                0.601562, 0.585938, 0.578125, 0.59375, 0.585938, 0.570312, 0.585938, 0.601562, 0.570312, 0.554688,
-                0.617188, 0.59375, 0.585938, 0.609375, 0.601562, 0.578125, 0.59375, 0.617188, 0.578125, 0.554688,
-                0.632812, 0.601562, 0.59375, 0.625, 0.617188, 0.585938, 0.609375, 0.632812, 0.585938, 0.554688,
-                0.648438, 0.617188, 0.609375, 0.640625, 0.632812, 0.59375, 0.625, 0.648438, 0.59375, 0.554688,
-                0.65625, 0.632812, 0.625, 0.65625, 0.648438, 0.609375, 0.640625, 0.664062, 0.609375, 0.554688,
-                0.664062, 0.648438, 0.640625, 0.664062, 0.65625, 0.625, 0.65625, 0.664062, 0.625, 0.554688,
-                0.667969, 0.664062, 0.65625, 0.667969, 0.664062, 0.640625, 0.664062, 0.667969, 0.640625, 0.5625,
-                0.667969, 0.667969, 0.664062, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969, 0.65625, 0.5625,
-                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625, 0.585938, 0.5625,
-                0.578125, 0.585938, 0.59375, 0.570312, 0.578125, 0.578125, 0.578125, 0.5625, 0.59375, 0.5625,
-                0.585938, 0.59375, 0.601562, 0.585938, 0.585938, 0.585938, 0.585938, 0.5625, 0.609375, 0.570312,
-                0.601562, 0.609375, 0.617188, 0.59375, 0.59375, 0.601562, 0.59375, 0.570312, 0.625, 0.570312,
-                0.617188, 0.625, 0.632812, 0.601562, 0.609375, 0.617188, 0.609375, 0.570312, 0.640625, 0.585938,
-                0.632812, 0.640625, 0.648438, 0.617188, 0.625, 0.632812, 0.625, 0.585938, 0.648438, 0.59375,
-                0.648438, 0.65625, 0.664062, 0.632812, 0.640625, 0.648438, 0.640625, 0.59375, 0.664062, 0.601562,
-                0.65625, 0.664062, 0.667969, 0.648438, 0.65625, 0.65625, 0.648438, 0.601562, 0.667969, 0.617188,
+                0.601562, 0.585938, 0.578125, 0.59375,  0.585938, 0.570312, 0.585938, 0.601562, 0.570312, 0.554688,
+                0.617188, 0.59375,  0.585938, 0.609375, 0.601562, 0.578125, 0.59375,  0.617188, 0.578125, 0.554688,
+                0.632812, 0.601562, 0.59375,  0.625,    0.617188, 0.585938, 0.609375, 0.632812, 0.585938, 0.554688,
+                0.648438, 0.617188, 0.609375, 0.640625, 0.632812, 0.59375,  0.625,    0.648438, 0.59375,  0.554688,
+                0.65625,  0.632812, 0.625,    0.65625,  0.648438, 0.609375, 0.640625, 0.664062, 0.609375, 0.554688,
+                0.664062, 0.648438, 0.640625, 0.664062, 0.65625,  0.625,    0.65625,  0.664062, 0.625,    0.554688,
+                0.667969, 0.664062, 0.65625,  0.667969, 0.664062, 0.640625, 0.664062, 0.667969, 0.640625, 0.5625,
+                0.667969, 0.667969, 0.664062, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969, 0.65625,  0.5625,
+                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625,   0.585938, 0.5625,
+                0.578125, 0.585938, 0.59375,  0.570312, 0.578125, 0.578125, 0.578125, 0.5625,   0.59375,  0.5625,
+                0.585938, 0.59375,  0.601562, 0.585938, 0.585938, 0.585938, 0.585938, 0.5625,   0.609375, 0.570312,
+                0.601562, 0.609375, 0.617188, 0.59375,  0.59375,  0.601562, 0.59375,  0.570312, 0.625,    0.570312,
+                0.617188, 0.625,    0.632812, 0.601562, 0.609375, 0.617188, 0.609375, 0.570312, 0.640625, 0.585938,
+                0.632812, 0.640625, 0.648438, 0.617188, 0.625,    0.632812, 0.625,    0.585938, 0.648438, 0.59375,
+                0.648438, 0.65625,  0.664062, 0.632812, 0.640625, 0.648438, 0.640625, 0.59375,  0.664062, 0.601562,
+                0.65625,  0.664062, 0.667969, 0.648438, 0.65625,  0.65625,  0.648438, 0.601562, 0.667969, 0.617188,
                 0.664062, 0.667969, 0.667969, 0.664062, 0.664062, 0.664062, 0.664062, 0.617188, 0.667969, 0.632812,
                 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.632812, 0.667969, 0.648438,
                 0.578125, 0.578125, 0.578125, 0.585938, 0.578125, 0.570312, 0.554688, 0.578125, 0.570312, 0.585938,
-                0.585938, 0.585938, 0.585938, 0.59375, 0.585938, 0.570312, 0.5625, 0.585938, 0.578125, 0.59375,
-                0.601562, 0.601562, 0.59375, 0.609375, 0.601562, 0.578125, 0.5625, 0.59375, 0.585938, 0.609375,
-                0.617188, 0.617188, 0.609375, 0.625, 0.617188, 0.585938, 0.5625, 0.609375, 0.601562, 0.625,
-                0.632812, 0.632812, 0.625, 0.640625, 0.632812, 0.59375, 0.570312, 0.625, 0.617188, 0.640625,
-                0.648438, 0.648438, 0.640625, 0.65625, 0.648438, 0.609375, 0.570312, 0.640625, 0.632812, 0.65625,
-                0.65625, 0.65625, 0.65625, 0.664062, 0.65625, 0.625, 0.578125, 0.65625, 0.648438, 0.664062,
-                0.664062, 0.664062, 0.664062, 0.667969, 0.664062, 0.640625, 0.585938, 0.664062, 0.65625, 0.667969,
-                0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625, 0.601562, 0.667969, 0.664062, 0.667969,
+                0.585938, 0.585938, 0.585938, 0.59375,  0.585938, 0.570312, 0.5625,   0.585938, 0.578125, 0.59375,
+                0.601562, 0.601562, 0.59375,  0.609375, 0.601562, 0.578125, 0.5625,   0.59375,  0.585938, 0.609375,
+                0.617188, 0.617188, 0.609375, 0.625,    0.617188, 0.585938, 0.5625,   0.609375, 0.601562, 0.625,
+                0.632812, 0.632812, 0.625,    0.640625, 0.632812, 0.59375,  0.570312, 0.625,    0.617188, 0.640625,
+                0.648438, 0.648438, 0.640625, 0.65625,  0.648438, 0.609375, 0.570312, 0.640625, 0.632812, 0.65625,
+                0.65625,  0.65625,  0.65625,  0.664062, 0.65625,  0.625,    0.578125, 0.65625,  0.648438, 0.664062,
+                0.664062, 0.664062, 0.664062, 0.667969, 0.664062, 0.640625, 0.585938, 0.664062, 0.65625,  0.667969,
+                0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625,  0.601562, 0.667969, 0.664062, 0.667969,
                 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.664062, 0.617188, 0.667969, 0.667969, 0.667969},
-            std::vector<T>{
-                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625, 0.570312, 0.585938, 0.5625,
-                0.5625, 0.554688, 0.570312, 0.5625, 0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
-                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625, 0.570312, 0.578125, 0.5625, 0.554688,
-                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625, 0.585938, 0.5625,
-                0.578125, 0.578125, 0.578125, 0.585938, 0.578125, 0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
-            std::vector<T>{
-                1.20312, 1.27344, 1.375, 1.32031, 1.35156, 1.20312, 1.22656, 1.25781, 1.375, 1.23438,
-                1.25, 1.21875, 1.26562, 1.23438, 1.26562, 1.26562, 1.32031, 1.26562, 1.35156, 1.28906,
-                1.34375, 1.27344, 1.25781, 1.32031, 1.28906, 1.24219, 1.28125, 1.34375, 1.24219, 1.21875,
-                1.28906, 1.32031, 1.35156, 1.27344, 1.28125, 1.29688, 1.28125, 1.22656, 1.35156, 1.23438,
-                1.32812, 1.32812, 1.32031, 1.35938, 1.32812, 1.25781, 1.21875, 1.32031, 1.28906, 1.375}),
+            std::vector<T>{0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625,   0.570312, 0.585938,
+                           0.5625,   0.5625,   0.554688, 0.570312, 0.5625,   0.570312, 0.570312, 0.578125, 0.570312,
+                           0.585938, 0.570312, 0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625,   0.570312,
+                           0.578125, 0.5625,   0.554688, 0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312,
+                           0.570312, 0.5625,   0.585938, 0.5625,   0.578125, 0.578125, 0.578125, 0.585938, 0.578125,
+                           0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
+            std::vector<T>{1.20312, 1.27344, 1.375,   1.32031, 1.35156, 1.20312, 1.22656, 1.25781, 1.375,   1.23438,
+                           1.25,    1.21875, 1.26562, 1.23438, 1.26562, 1.26562, 1.32031, 1.26562, 1.35156, 1.28906,
+                           1.34375, 1.27344, 1.25781, 1.32031, 1.28906, 1.24219, 1.28125, 1.34375, 1.24219, 1.21875,
+                           1.28906, 1.32031, 1.35156, 1.27344, 1.28125, 1.29688, 1.28125, 1.22656, 1.35156, 1.23438,
+                           1.32812, 1.32812, 1.32031, 1.35938, 1.32812, 1.25781, 1.21875, 1.32031, 1.28906, 1.375}),
         LSTMSequenceParams(
-            5, 10, 10, 5,
-            0.7f, op::RecurrentSequenceDirection::BIDIRECTIONAL,
+            5,
+            10,
+            10,
+            5,
+            0.7f,
+            op::RecurrentSequenceDirection::BIDIRECTIONAL,
             ET,
             std::vector<T>{
-                1, 9.375, 9, 3.84375, 2.17188, 2.65625, 1.35938, 2.84375, 8.4375, 6.125,
-                5.78125, 6.375, 9.625, 9.625, 5.15625, 6.875, 9.3125, 7.75, 4.375, 6.875,
-                2.39062, 7.71875, 9, 9.625, 1.23438, 1.07812, 3.625, 1.95312, 4.5625, 3.6875,
-                8.25, 6.90625, 6.625, 8.25, 9.125, 8.875, 6, 9.625, 8.5, 7.5,
-                1.45312, 6.78125, 8.25, 7.4375, 9.375, 5.1875, 4.25, 3.9375, 7.1875, 4.9375,
-                2.15625, 7.5625, 8.5, 9.9375, 3.85938, 7.0625, 7.625, 8.125, 6.375, 2.53125,
-                4.25, 1.23438, 8.125, 8.1875, 7.28125, 9.125, 8.375, 1.21875, 9.125, 5.4375,
-                8.5, 5.75, 9.1875, 6.375, 9.75, 1.46875, 6.875, 9, 8.25, 7.5625,
-                1.92188, 8.375, 3.125, 5.5, 4.40625, 8.25, 7.28125, 1.85938, 5.375, 2.96875,
-                4.75, 3.32812, 6.75, 5.1875, 7.8125, 5.125, 6, 7.375, 7.25, 2.59375,
-                9.25, 5.78125, 1.21875, 2.5, 8.5, 7.90625, 4.4375, 9.375, 3.6875, 6.5,
-                1.05469, 2.34375, 4.9375, 5.40625, 7.625, 4.375, 4.375, 8.625, 5.4375, 9.1875,
-                1.125, 4.4375, 3.25, 3.84375, 4.125, 6.125, 8.125, 2.6875, 9.4375, 2.125,
-                1.90625, 7.1875, 7.625, 8.1875, 9.75, 6.15625, 7.34375, 9.75, 9.5625, 6.6875,
-                9.375, 9, 4.6875, 5.4375, 4.03125, 4.15625, 7.9375, 7.4375, 4, 5.53125,
-                1.74219, 3.03125, 9.0625, 3.20312, 8.0625, 8.125, 7.4375, 5.4375, 5, 9.25,
-                7.75, 9.5, 6.90625, 5.8125, 4.25, 3.26562, 4.375, 7.5, 6.84375, 4.3125,
-                1.5, 5.5, 1.70312, 3.03125, 1.82812, 4.1875, 8.25, 6.84375, 1.58594, 3.8125,
-                3.01562, 7.90625, 2.375, 8, 7.125, 8.625, 2.125, 9.5, 3.3125, 1.96875,
-                4.9375, 9.1875, 1.98438, 4, 3.82812, 8.375, 4.15625, 9.0625, 7.84375, 1.38281,
-                1.89062, 2.75, 9.375, 3.65625, 3.9375, 6.625, 4.8125, 1.77344, 3.4375, 2.28125,
-                8.0625, 5.625, 5.0625, 7.1875, 1.75, 8.6875, 1.63281, 6.8125, 3.96875, 6.25,
-                2.71875, 7.375, 8.5, 3.26562, 1.55469, 9.125, 6, 4.96875, 6.125, 1.1875,
-                5.15625, 9.625, 9.5, 6.875, 4.09375, 5.625, 8.9375, 7.125, 4.875, 5.375,
-                9.9375, 9.3125, 8.1875, 5.625, 9.5, 1.64844, 4.40625, 6.09375, 4.625, 10},
-            std::vector<T>{
-                -1, 9.1875, 5.5625, 6.625, 2.65625, 8.125, 8.25, 4.875, 9.4375, 5.875,
-                1.26562, 4.71875, 8.0625, 1.76562, 2.46875, 8, 4.875, 5.375, 6.15625, 1.45312,
-                2.95312, 5.84375, 8.5, 1.375, 3.6875, 8.25, 4.25, 9.9375, 8.8125, 6.75,
-                1.10938, 9.5, 7.0625, 7.625, 5.3125, 8.375, 9.75, 2.03125, 2.90625, 7.625,
-                2.90625, 8.375, 9.5, 1.66406, 3.9375, 2.875, 9.875, 8.25, 4.9375, 9.25,
-                9.6875, 2.34375, 3.3125, 9.625, 7.8125, 4.34375, 2.71875, 7.4375, 3.53125, 1.9375,
-                7.9375, 8.875, 1.07031, 6.25, 4.1875, 7.125, 3.09375, 9, 4.4375, 2.60938,
-                1.98438, 2.76562, 4.65625, 5.125, 4.625, 8.375, 7.9375, 6.6875, 8.5625, 6.8125,
-                4.53125, 5.09375, 5.1875, 6.0625, 1.9375, 7, 2.71875, 6.8125, 7.0625, 1.42188,
-                5.25, 3.34375, 8.1875, 1.07812, 3.21875, 8.6875, 7.6875, 1.27344, 7.0625, 10},
-            std::vector<T>{
-                1, 9.6875, 3.3125, 3.09375, 6, 9.5, 7.375, 2.5625, 5.3125, 7.625,
-                9.875, 1.01562, 5.9375, 4, 4.25, 2.4375, 3.25, 6.5625, 6.53125, 5.71875,
-                3.26562, 7.875, 6.6875, 1.10938, 9.875, 9.875, 1.11719, 7.75, 7.84375, 6.75,
-                2.21875, 6, 10, 9.125, 8, 1.92188, 8.25, 9.1875, 6.625, 5.96875,
-                2.28125, 8.0625, 6.5625, 3.84375, 9.125, 7.0625, 1.45312, 1.34375, 2.46875, 4.59375,
-                8.9375, 8.5, 4.875, 2.4375, 9.625, 4.15625, 2.9375, 9.875, 2.90625, 1.25,
-                9, 5.53125, 7.65625, 4.03125, 3.3125, 3.46875, 3.92188, 8.125, 6.78125, 9.5,
-                9.875, 5.6875, 6.4375, 5.0625, 5.75, 6.8125, 4.875, 2.65625, 5.21875, 3.9375,
-                3.4375, 4.5, 1.98438, 5.71875, 3.75, 7.5625, 1.11719, 2.29688, 6.75, 6.8125,
-                1.0625, 6.78125, 3.65625, 6.4375, 7.3125, 5.625, 1.35156, 8.4375, 4.125, 10},
+                1,       9.375,   9,       3.84375, 2.17188, 2.65625, 1.35938, 2.84375, 8.4375,  6.125,   5.78125,
+                6.375,   9.625,   9.625,   5.15625, 6.875,   9.3125,  7.75,    4.375,   6.875,   2.39062, 7.71875,
+                9,       9.625,   1.23438, 1.07812, 3.625,   1.95312, 4.5625,  3.6875,  8.25,    6.90625, 6.625,
+                8.25,    9.125,   8.875,   6,       9.625,   8.5,     7.5,     1.45312, 6.78125, 8.25,    7.4375,
+                9.375,   5.1875,  4.25,    3.9375,  7.1875,  4.9375,  2.15625, 7.5625,  8.5,     9.9375,  3.85938,
+                7.0625,  7.625,   8.125,   6.375,   2.53125, 4.25,    1.23438, 8.125,   8.1875,  7.28125, 9.125,
+                8.375,   1.21875, 9.125,   5.4375,  8.5,     5.75,    9.1875,  6.375,   9.75,    1.46875, 6.875,
+                9,       8.25,    7.5625,  1.92188, 8.375,   3.125,   5.5,     4.40625, 8.25,    7.28125, 1.85938,
+                5.375,   2.96875, 4.75,    3.32812, 6.75,    5.1875,  7.8125,  5.125,   6,       7.375,   7.25,
+                2.59375, 9.25,    5.78125, 1.21875, 2.5,     8.5,     7.90625, 4.4375,  9.375,   3.6875,  6.5,
+                1.05469, 2.34375, 4.9375,  5.40625, 7.625,   4.375,   4.375,   8.625,   5.4375,  9.1875,  1.125,
+                4.4375,  3.25,    3.84375, 4.125,   6.125,   8.125,   2.6875,  9.4375,  2.125,   1.90625, 7.1875,
+                7.625,   8.1875,  9.75,    6.15625, 7.34375, 9.75,    9.5625,  6.6875,  9.375,   9,       4.6875,
+                5.4375,  4.03125, 4.15625, 7.9375,  7.4375,  4,       5.53125, 1.74219, 3.03125, 9.0625,  3.20312,
+                8.0625,  8.125,   7.4375,  5.4375,  5,       9.25,    7.75,    9.5,     6.90625, 5.8125,  4.25,
+                3.26562, 4.375,   7.5,     6.84375, 4.3125,  1.5,     5.5,     1.70312, 3.03125, 1.82812, 4.1875,
+                8.25,    6.84375, 1.58594, 3.8125,  3.01562, 7.90625, 2.375,   8,       7.125,   8.625,   2.125,
+                9.5,     3.3125,  1.96875, 4.9375,  9.1875,  1.98438, 4,       3.82812, 8.375,   4.15625, 9.0625,
+                7.84375, 1.38281, 1.89062, 2.75,    9.375,   3.65625, 3.9375,  6.625,   4.8125,  1.77344, 3.4375,
+                2.28125, 8.0625,  5.625,   5.0625,  7.1875,  1.75,    8.6875,  1.63281, 6.8125,  3.96875, 6.25,
+                2.71875, 7.375,   8.5,     3.26562, 1.55469, 9.125,   6,       4.96875, 6.125,   1.1875,  5.15625,
+                9.625,   9.5,     6.875,   4.09375, 5.625,   8.9375,  7.125,   4.875,   5.375,   9.9375,  9.3125,
+                8.1875,  5.625,   9.5,     1.64844, 4.40625, 6.09375, 4.625,   10},
+            std::vector<T>{-1,      9.1875,  5.5625,  6.625,   2.65625, 8.125,   8.25,    4.875,   9.4375,  5.875,
+                           1.26562, 4.71875, 8.0625,  1.76562, 2.46875, 8,       4.875,   5.375,   6.15625, 1.45312,
+                           2.95312, 5.84375, 8.5,     1.375,   3.6875,  8.25,    4.25,    9.9375,  8.8125,  6.75,
+                           1.10938, 9.5,     7.0625,  7.625,   5.3125,  8.375,   9.75,    2.03125, 2.90625, 7.625,
+                           2.90625, 8.375,   9.5,     1.66406, 3.9375,  2.875,   9.875,   8.25,    4.9375,  9.25,
+                           9.6875,  2.34375, 3.3125,  9.625,   7.8125,  4.34375, 2.71875, 7.4375,  3.53125, 1.9375,
+                           7.9375,  8.875,   1.07031, 6.25,    4.1875,  7.125,   3.09375, 9,       4.4375,  2.60938,
+                           1.98438, 2.76562, 4.65625, 5.125,   4.625,   8.375,   7.9375,  6.6875,  8.5625,  6.8125,
+                           4.53125, 5.09375, 5.1875,  6.0625,  1.9375,  7,       2.71875, 6.8125,  7.0625,  1.42188,
+                           5.25,    3.34375, 8.1875,  1.07812, 3.21875, 8.6875,  7.6875,  1.27344, 7.0625,  10},
+            std::vector<T>{1,       9.6875,  3.3125,  3.09375, 6,      9.5,     7.375,   2.5625,  5.3125,  7.625,
+                           9.875,   1.01562, 5.9375,  4,       4.25,   2.4375,  3.25,    6.5625,  6.53125, 5.71875,
+                           3.26562, 7.875,   6.6875,  1.10938, 9.875,  9.875,   1.11719, 7.75,    7.84375, 6.75,
+                           2.21875, 6,       10,      9.125,   8,      1.92188, 8.25,    9.1875,  6.625,   5.96875,
+                           2.28125, 8.0625,  6.5625,  3.84375, 9.125,  7.0625,  1.45312, 1.34375, 2.46875, 4.59375,
+                           8.9375,  8.5,     4.875,   2.4375,  9.625,  4.15625, 2.9375,  9.875,   2.90625, 1.25,
+                           9,       5.53125, 7.65625, 4.03125, 3.3125, 3.46875, 3.92188, 8.125,   6.78125, 9.5,
+                           9.875,   5.6875,  6.4375,  5.0625,  5.75,   6.8125,  4.875,   2.65625, 5.21875, 3.9375,
+                           3.4375,  4.5,     1.98438, 5.71875, 3.75,   7.5625,  1.11719, 2.29688, 6.75,    6.8125,
+                           1.0625,  6.78125, 3.65625, 6.4375,  7.3125, 5.625,   1.35156, 8.4375,  4.125,   10},
             std::vector<int64_t>{5, 5, 5, 5, 5},
             std::vector<T>{
-                1, 6.9375, 6.75, 6.1875, 2.4375, 3.67188, 6.9375, 3.57812, 4.25, 1.53906,
-                4.8125, 9, 6.1875, 7.3125, 9.5, 5.53125, 9.6875, 4.84375, 4.65625, 7.84375,
-                3.03125, 6.1875, 8.625, 9.875, 9.5, 9.0625, 8.125, 9.875, 4.875, 2.79688,
-                9.5, 4.4375, 1.55469, 2.78125, 8.75, 8.5, 2.34375, 2.90625, 6.25, 2.71875,
-                5.25, 6.875, 8, 7.375, 8.9375, 1.875, 3.0625, 5.75, 7.375, 7.75,
-                1.125, 6.75, 6.75, 3, 6.65625, 5.125, 3.84375, 6.625, 9.125, 3.92188,
-                7, 4.3125, 9.625, 5.53125, 7.6875, 1.85156, 7.03125, 7.375, 3.5, 5.9375,
-                9.125, 2.0625, 6.5625, 7.375, 3.4375, 3.17188, 1.25, 9, 2.75, 3.40625,
-                5.9375, 5.53125, 3.3125, 6.625, 8.25, 6.84375, 2.82812, 1.27344, 8.625, 5.1875,
-                1.79688, 1.97656, 2.125, 9.875, 2.73438, 2.40625, 6.625, 2.76562, 3.76562, 5.59375,
-                7.1875, 6.40625, 8.5625, 6.21875, 6.46875, 8.0625, 7.6875, 2.1875, 9.0625, 6.3125,
-                9.0625, 2.90625, 2.17188, 7.4375, 3.125, 1.40625, 8.25, 7.0625, 8.375, 4.6875,
-                5.125, 1.875, 8.375, 3.4375, 9.6875, 9.3125, 7.5, 8.3125, 4.5, 7.5625,
-                1.92188, 1.46094, 8.75, 3.34375, 7.9375, 6, 8.5, 1.23438, 2.75, 7.25,
-                7.4375, 4.09375, 8.625, 6.34375, 5.5, 6.3125, 1.23438, 7.875, 8.25, 7.25,
-                7.65625, 8.25, 9.25, 9.625, 4.3125, 9.125, 3.64062, 6.4375, 5.9375, 9.125,
-                6.1875, 6.625, 3, 1.65625, 5.75, 6.1875, 4.71875, 8.125, 6.25, 2.5,
-                3.40625, 3.20312, 9.1875, 9.8125, 8.125, 4.125, 1.08594, 4.78125, 9.5625, 5.0625,
-                5.625, 3.5, 8.25, 1.73438, 3.5625, 8.0625, 2.23438, 3.0625, 3.34375, 3.40625,
-                3.625, 9.75, 1.14062, 4.84375, 9.125, 5.5, 8, 9.5, 5.125, 7.25,
-                9.4375, 2.0625, 5.90625, 9.75, 6.1875, 6, 7.3125, 7.3125, 7.34375, 7.5625,
-                6.1875, 9.125, 7.28125, 7.75, 4.59375, 7.5, 7.71875, 9.75, 9.5, 9.9375,
-                5.90625, 1.20312, 1.75, 7.75, 8.8125, 3.5625, 8.5, 9.25, 8.375, 7.84375,
-                4.9375, 7.4375, 6.75, 1.46875, 3.53125, 7.15625, 6.0625, 3.8125, 5.34375, 1.60938,
-                9.6875, 8.4375, 4.65625, 5.46875, 3.65625, 5.125, 9.125, 1.23438, 6.875, 1.79688,
-                4.1875, 2.26562, 2.78125, 9.25, 3.28125, 6.5625, 7.3125, 8.1875, 8.9375, 4,
-                8.625, 5.3125, 9.875, 4.375, 4.09375, 1.125, 2.84375, 8.375, 7.90625, 4.75,
-                4.625, 4.75, 3.17188, 7.59375, 4.5, 2.46875, 4.03125, 3.26562, 2.5, 7.28125,
-                6.3125, 7.6875, 1.00781, 1.3125, 7.625, 4.375, 2.0625, 4.1875, 7.625, 4.40625,
-                3.6875, 8.75, 4.09375, 2.84375, 5.21875, 3.65625, 9.5625, 1.71875, 5.9375, 1.79688,
-                5.8125, 5.625, 1.46875, 1.32812, 1.95312, 4.3125, 1.41406, 3.125, 9.1875, 6.3125,
-                5.3125, 4.1875, 1.17969, 1.32031, 9.5, 9.875, 6.78125, 2.32812, 7.1875, 4.3125,
-                7.90625, 4.6875, 7.875, 3.59375, 4.6875, 1.3125, 1.71094, 3.98438, 8.75, 8.625,
-                2.21875, 9.5, 7.1875, 3.92188, 5.6875, 5.75, 8.75, 6.625, 1.34375, 1.99219,
-                8.3125, 1.73438, 5.5625, 7.84375, 1.15625, 2.125, 4.5, 5.75, 7, 3.5,
-                7.375, 4.1875, 5.3125, 7.0625, 3.8125, 1.85156, 9, 6.75, 4.3125, 9.9375,
-                8.125, 8.75, 1.09375, 9.875, 6.46875, 2.32812, 3.84375, 8.75, 6.6875, 3.17188,
-                4.75, 5.25, 5.875, 4.625, 5.59375, 7.25, 8.625, 2.84375, 7, 4.0625,
-                6.5, 3.15625, 6.5, 4.65625, 7.8125, 2.6875, 5.6875, 4, 5.9375, 5.53125,
-                6.96875, 5.78125, 9.125, 6.53125, 8.125, 2.90625, 5.625, 5.125, 7.4375, 3.78125,
-                5.5, 8, 9.4375, 8.75, 6.75, 5.59375, 8.375, 2.4375, 1.27344, 4.90625,
-                8.875, 9.5, 5.21875, 6.9375, 9, 3.0625, 3.25, 2.39062, 1.92188, 2.54688,
-                3.73438, 7.28125, 4.5, 5.09375, 7.5, 2.14062, 1.10938, 2.32812, 3.875, 4.8125,
-                1.95312, 1.98438, 6.34375, 4.8125, 6.84375, 5.3125, 9.1875, 8.3125, 6.5, 7.125,
-                2.59375, 4.0625, 1.27344, 5.09375, 5.75, 1.48438, 6.1875, 5.1875, 9.9375, 8.3125,
-                2.14062, 5.21875, 5.0625, 1.94531, 6.6875, 7.75, 8.625, 6.3125, 5.8125, 8.75,
-                6.375, 8.875, 1.16406, 6.125, 1, 3.71875, 3.1875, 6.96875, 1.14062, 6.09375,
-                8.75, 1.5, 5.25, 5.1875, 1.48438, 2.96875, 2.03125, 4.40625, 9.625, 4.125,
-                5, 2.45312, 9.25, 5.875, 5.9375, 4.6875, 8.25, 5.3125, 1.73438, 7.4375,
-                4.625, 7.6875, 3.4375, 6.53125, 2.64062, 8.75, 2.57812, 7.8125, 4.4375, 6.0625,
-                4.5, 9.125, 7.96875, 2.65625, 8.125, 8.8125, 5.25, 5.65625, 4.84375, 7.96875,
-                3.09375, 2.3125, 7.34375, 8.5, 6.25, 2.79688, 7.8125, 5.8125, 7.0625, 5.84375,
-                6.4375, 9.1875, 5.03125, 2.01562, 1.8125, 6.5625, 9.5625, 4.96875, 5.8125, 4.75,
-                6.6875, 9.625, 4.625, 7.71875, 4.6875, 6.4375, 3.59375, 2.25, 3.0625, 6.375,
-                2.0625, 6.9375, 1.0625, 9.25, 7.0625, 3.90625, 9.875, 3.09375, 6.125, 9.1875,
-                2.9375, 4.0625, 5.6875, 6.4375, 8.25, 8.5, 7.1875, 6.46875, 9.125, 3.71875,
-                5.1875, 9.25, 9.375, 6.25, 8.5, 1.67188, 2.09375, 5.78125, 1.78125, 5.8125,
-                4.84375, 8.125, 1.64062, 9, 7.8125, 4.5, 3.64062, 1.9375, 1.24219, 9.25,
-                4.4375, 1.48438, 1.67188, 8.25, 7.75, 2.875, 3.28125, 3.9375, 8.75, 5.4375,
-                2.875, 5.6875, 1.99219, 9.625, 1.39062, 4.46875, 9.5, 7.375, 9.875, 2.98438,
-                3.0625, 9.875, 9.5625, 1.14062, 4.6875, 5.53125, 2.98438, 4.5, 9.25, 4.5625,
-                7.625, 3.1875, 8.4375, 1.65625, 3, 6, 9.75, 5.3125, 4.375, 6.75,
-                3.8125, 2.65625, 8.75, 1.23438, 2.40625, 2.875, 2.20312, 8.8125, 3.42188, 5.25,
-                8, 8.375, 2.8125, 4.5625, 6.40625, 4.875, 4.25, 9, 2.25, 5.75,
-                7, 8.5, 6.4375, 7.1875, 5.59375, 2.48438, 1.53125, 8.1875, 2.15625, 2.01562,
-                9.25, 8.375, 6.1875, 8, 9.125, 3.8125, 6.6875, 8, 8.75, 7.625,
-                9.75, 4.8125, 6, 2.78125, 3.5625, 8.5625, 1.07812, 9.9375, 6.8125, 7.125,
-                7.3125, 4.5625, 1.50781, 1.15625, 3.79688, 2.8125, 8.6875, 6.28125, 8.1875, 7.75,
-                8.875, 7.8125, 5.21875, 5.53125, 9.125, 5.125, 4.125, 1.35938, 6.25, 3.1875,
-                8.375, 1, 8, 8.625, 5.25, 8.875, 3.75, 7.5, 1.32812, 1.80469,
-                4.5, 2.15625, 6.8125, 2.375, 4.4375, 9.5625, 6.9375, 6.4375, 2.10938, 2.5625,
-                9, 1.71875, 6.78125, 6, 2, 7, 7.09375, 4.5, 5.8125, 8.625,
-                7.59375, 6.6875, 4.625, 3.35938, 9, 8.625, 1.51562, 9.5625, 6.25, 3.03125,
-                3.59375, 1.85156, 5.5625, 8.3125, 7.375, 2.21875, 8.5625, 3.0625, 7.1875, 7,
-                2.59375, 3.92188, 8.125, 3.09375, 7.4375, 6.375, 7.375, 8.125, 6.75, 7.78125,
-                2.5, 5, 7.5625, 1.42188, 9.0625, 1.875, 4.8125, 3.09375, 5.34375, 3.34375,
-                1.92188, 10, 4.3125, 5.03125, 8.75, 6.40625, 9.25, 9.125, 9, 7.4375,
-                3.89062, 4.4375, 9, 6.34375, 9.25, 9.875, 1.79688, 5.0625, 9, 3.04688,
-                6.6875, 2.98438, 5.40625, 8.125, 9.75, 3.125, 4.125, 3.48438, 8.4375, 8.75,
-                4.375, 8.375, 6.4375, 3.5, 3.89062, 5.4375, 9.5, 4.03125, 7.5, 10},
-            std::vector<T>{
-                1, 5.96875, 3, 8.75, 2.46875, 8.6875, 6.1875, 3.09375, 5, 5.3125,
-                3.09375, 3.25, 7.96875, 8.625, 3.34375, 6.8125, 2.8125, 9.5, 3.84375, 1.14062,
-                3.8125, 1.09375, 3.375, 7.0625, 6.875, 9.5, 5.125, 2.25, 5.34375, 6.3125,
-                1.79688, 5.4375, 8, 6.0625, 7.46875, 7, 9.25, 1.74219, 7.25, 3.5625,
-                4.5625, 3.01562, 2.78125, 8.125, 8.375, 2.53125, 4.9375, 6.375, 7.5, 3.78125,
-                6, 2.89062, 2.75, 8.4375, 2.85938, 2, 9.4375, 1.32812, 10, 4.3125,
-                3.09375, 9.75, 6, 9.125, 7.0625, 5.46875, 9, 4.625, 3.40625, 9.75,
-                5.25, 6.75, 5.4375, 3.96875, 3, 6.15625, 9.0625, 5.59375, 2, 2.51562,
-                4.75, 7.5625, 4.75, 5.28125, 2.17188, 1.00781, 3.625, 6.1875, 1.96875, 8.625,
-                9.25, 9.1875, 2, 2.75, 4.25, 1, 5.46875, 4.5, 6.65625, 3.5,
-                7.90625, 7.4375, 6.9375, 5.1875, 8.875, 2.375, 4.46875, 7.1875, 4.125, 6.9375,
-                9.5, 1.92969, 6.5, 6.5625, 9.0625, 8.5, 4.75, 4.6875, 6.0625, 9.8125,
-                2.34375, 4.65625, 9, 9.5, 6.71875, 5.40625, 3.28125, 6.5625, 4.1875, 1.1875,
-                6.1875, 2.8125, 7.875, 8.625, 8.25, 5, 4.9375, 4.625, 5, 7.4375,
-                8.5625, 5.3125, 8.4375, 6.5, 1.98438, 2.0625, 5.625, 7.625, 9.5625, 9.5,
-                6.125, 8, 10, 2.625, 4.90625, 2.95312, 6.8125, 8.75, 8.9375, 6.5,
-                1.65625, 7.84375, 8, 4.125, 9, 8.0625, 5.375, 6.0625, 3.6875, 7.0625,
-                2.73438, 7.28125, 7.4375, 5.375, 4.84375, 2.03125, 6.375, 6.5625, 4.0625, 2.125,
-                1.84375, 3.0625, 6.03125, 9.375, 4.625, 9.375, 3.57812, 2.84375, 8.0625, 6.65625,
-                9.75, 5.125, 1.07812, 8.4375, 5.75, 7.25, 4.5625, 3.54688, 6.9375, 6.625,
-                8.875, 6.40625, 2.70312, 6.0625, 2.5, 5.6875, 8.0625, 4.4375, 1.875, 8.1875,
-                7.6875, 3.25, 8.125, 7.6875, 3.03125, 9.75, 2.84375, 9.6875, 1.34375, 6.375,
-                6.34375, 8.6875, 2.28125, 6.375, 9.9375, 8.375, 1.23438, 6.3125, 8.625, 7.625,
-                4.75, 9.6875, 9.125, 4.75, 6.375, 2.6875, 8.75, 2.60938, 5.75, 4.4375,
-                8.25, 6.4375, 2.64062, 6.5625, 6.125, 9.625, 3.84375, 2.5, 3.09375, 7.75,
-                7.25, 3.96875, 5.9375, 1.09375, 8.125, 5.625, 9.5, 9.25, 5.6875, 3.03125,
-                6.1875, 2.85938, 8.0625, 4.75, 2.84375, 7.375, 2, 4.0625, 8.375, 4.1875,
-                2.78125, 3.04688, 2.64062, 9.5, 6.625, 9.875, 1.70312, 6.6875, 4.8125, 7,
-                1.9375, 1.32031, 7.5, 2.21875, 6.6875, 3.34375, 7.625, 1.53125, 8.875, 1.75781,
-                3.35938, 4.8125, 4.40625, 5.46875, 7.5625, 3.29688, 3.21875, 6.25, 4.34375, 5,
-                2.34375, 4.875, 2.78125, 7.46875, 3.20312, 5.4375, 6.875, 2, 5.375, 6.71875,
-                5.5625, 3.34375, 3.78125, 9.625, 1.8125, 5.125, 2.90625, 1.80469, 3.625, 5.34375,
-                1.76562, 5.6875, 9.5625, 9.4375, 10, 1.17188, 7.125, 9.5, 3, 7.1875,
-                2.09375, 2.98438, 5.9375, 9.375, 1.9375, 1.89062, 5.75, 3.21875, 7.375, 2.46875,
-                6.125, 4.96875, 3.75, 1.0625, 3.53125, 7.875, 4.8125, 9.125, 4.28125, 9.125,
-                1.78906, 8.0625, 7.9375, 1.32812, 6.5625, 4.25, 7.375, 6.875, 6.0625, 6.53125,
-                3.5625, 4.4375, 4.5, 6.875, 7.9375, 9.625, 4.3125, 1.09375, 2.73438, 7.75,
-                6.3125, 9.75, 4.625, 4.71875, 3, 2.40625, 1.17188, 7.625, 5.28125, 6.6875,
-                8.125, 9.625, 2.23438, 4.84375, 4.6875, 7.96875, 4.9375, 3.46875, 3, 9.5,
-                7.21875, 6.25, 3.0625, 1.34375, 6.25, 1.39844, 5.5625, 5.34375, 2.96875, 9.375,
-                2.85938, 7, 7.6875, 4.6875, 8.875, 4.40625, 4.25, 8.625, 5.875, 8,
-                4.8125, 1.46875, 5.625, 3, 9.875, 2.03125, 3.82812, 6.375, 8.75, 4.5625,
-                9.625, 8.625, 1.625, 6.1875, 1.85938, 9.125, 1.42188, 5.0625, 8.625, 4.5625,
-                2.4375, 8.875, 6.84375, 7.3125, 1.63281, 3.28125, 6.25, 3.70312, 1.28125, 6.96875,
-                1.67969, 5.875, 9.625, 7.3125, 5.71875, 9.9375, 4.0625, 6.5625, 1.03125, 3.84375,
-                4.1875, 9.5, 4.21875, 5.25, 1.64062, 4.78125, 4.28125, 7.8125, 6.1875, 8,
-                1.85938, 5.375, 1.9375, 8.125, 6, 4.90625, 1.53125, 2.53125, 6.53125, 1.67188,
-                1.5625, 2.48438, 8.9375, 2.75, 4, 3.65625, 4.625, 5.5625, 8.75, 4.9375,
-                3.40625, 8.1875, 6.40625, 7.0625, 6.6875, 6.0625, 9.75, 8.375, 1.36719, 9.625,
-                8.625, 8.375, 5.28125, 7.90625, 4.25, 9.6875, 5.1875, 6.6875, 8.375, 3.71875,
-                5.25, 9.5, 2.25, 7.1875, 3.46875, 7.53125, 5.15625, 7.84375, 2.375, 4,
-                5.34375, 8.6875, 4.75, 7, 5.96875, 9, 4.125, 6.34375, 3.28125, 5,
-                7.1875, 7.8125, 1.48438, 2.40625, 3.15625, 1.03125, 8.625, 5.78125, 3.5, 8.0625,
-                4.71875, 9.75, 3.3125, 5.09375, 3.65625, 4.5, 4.625, 7.6875, 7.375, 9.5,
-                4.625, 2.46875, 3.625, 6.125, 1.36719, 8.375, 8.375, 6.53125, 3.125, 5.75,
-                9.625, 3.3125, 8.375, 2.65625, 3.375, 3.60938, 6.9375, 4.9375, 1.78906, 9.25,
-                3.20312, 6.4375, 2.375, 2.40625, 6.0625, 3.75, 1.3125, 4.3125, 9.125, 9.3125,
-                1.09375, 8.3125, 1.98438, 8.1875, 6.1875, 1.21094, 8.25, 6.75, 5.75, 9.25,
-                4.75, 7.0625, 4.84375, 4.0625, 7.78125, 2.1875, 2.90625, 3.01562, 9.1875, 5,
-                6.5, 1.75, 6.1875, 2.96875, 1.07031, 2.375, 7.625, 6.0625, 3.90625, 3.45312,
-                2.57812, 3.3125, 3.96875, 7.875, 4.75, 7, 6.5625, 9.75, 4.5, 1.82812,
-                4.375, 4.90625, 9.75, 7.84375, 8.125, 6.3125, 4.875, 2.71875, 2.5, 8.875,
-                2.17188, 4.0625, 2.84375, 9, 2.3125, 1.85938, 5.875, 4.5625, 3.32812, 6.71875,
-                5.125, 1.67188, 3.8125, 8.5, 5.375, 7.75, 6.5, 8.25, 1.49219, 7.25,
-                5.625, 5, 8.6875, 5.5625, 9, 7.375, 6.9375, 6.625, 1.82812, 2.75,
-                7.59375, 3.875, 4.78125, 6.5625, 3.03125, 7.15625, 9.5, 9.125, 1.59375, 8.5,
-                4.3125, 5.15625, 4.65625, 6.125, 6.5, 4.25, 1.98438, 7.96875, 5.25, 4.40625,
-                4.5625, 2.89062, 3, 7.375, 5.75, 8.125, 1.75, 1.5625, 3.40625, 6.125,
-                3.29688, 1.39062, 6.625, 1.5, 8.875, 8.5, 5.5, 5, 1.09375, 1.79688,
-                9.75, 2.375, 1.07031, 8.25, 9, 9.875, 7.6875, 1.23438, 8.375, 8.0625,
-                6.75, 8.25, 8.625, 2.21875, 8.5, 9.25, 4.4375, 4.40625, 8, 3.5,
-                3.8125, 7, 2.125, 9, 3.42188, 9.125, 4.1875, 3.04688, 7.65625, 5.9375,
-                5.75, 9.5, 4.65625, 6.875, 5.0625, 1.89062, 3.40625, 5.78125, 4.0625, 5.125,
-                9, 5.9375, 2.46875, 9.25, 6.875, 7, 8.375, 6.09375, 1.48438, 5.90625,
-                8.75, 6.25, 7.3125, 8.5625, 9.9375, 9.125, 1.46875, 9.1875, 1.26562, 9,
-                5.5, 6.1875, 1.58594, 7.3125, 7.875, 9.5625, 3.32812, 8, 8.25, 4.59375,
-                9.75, 1.125, 8.3125, 4.6875, 3.375, 3.92188, 6.125, 4.46875, 3.625, 2.03125,
-                1.625, 9.1875, 2.46875, 3.03125, 6.1875, 9.5625, 5.78125, 2.10938, 3.14062, 4.125,
-                5.75, 7.03125, 2.28125, 6.9375, 7.3125, 3.125, 6.0625, 7.75, 7.1875, 8.1875,
-                6.90625, 4.875, 8.875, 7.3125, 5.9375, 1.39062, 4.625, 7.75, 5.0625, 10},
-            std::vector<T>{
-                1, 7.25, 1.08594, 1.90625, 7.3125, 8.1875, 1.84375, 9.8125, 3.65625, 7.6875,
-                7.03125, 6.75, 9.875, 9, 2.28125, 4.625, 8.375, 8.125, 4.25, 9.9375,
-                2.125, 1.92969, 1.35938, 7.625, 5.6875, 2.65625, 6.9375, 8.0625, 2.53125, 7.375,
-                2.8125, 9.1875, 7.3125, 8.75, 7.15625, 7.15625, 3.8125, 6.75, 3.53125, 8.75,
-                9.875, 5.75, 7.1875, 5.65625, 7.375, 9.25, 6.03125, 9.75, 8.625, 1.07031,
-                6.8125, 2.90625, 6.1875, 4.6875, 7.25, 1.14062, 9.0625, 2.78125, 5.625, 6.875,
-                2.0625, 3.3125, 9.875, 8.9375, 5.6875, 5.875, 3.65625, 2.78125, 8.625, 4.1875,
-                7.125, 7.09375, 5.125, 2.625, 3.10938, 9.4375, 5.5625, 5.8125, 3.5625, 10},
-            std::vector<T>{
-                0.523438, 0.667969, 0.65625, 0.65625, 0.667969, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969,
+                1,       6.9375,  6.75,    6.1875,  2.4375,  3.67188, 6.9375,  3.57812, 4.25,    1.53906, 4.8125,
+                9,       6.1875,  7.3125,  9.5,     5.53125, 9.6875,  4.84375, 4.65625, 7.84375, 3.03125, 6.1875,
+                8.625,   9.875,   9.5,     9.0625,  8.125,   9.875,   4.875,   2.79688, 9.5,     4.4375,  1.55469,
+                2.78125, 8.75,    8.5,     2.34375, 2.90625, 6.25,    2.71875, 5.25,    6.875,   8,       7.375,
+                8.9375,  1.875,   3.0625,  5.75,    7.375,   7.75,    1.125,   6.75,    6.75,    3,       6.65625,
+                5.125,   3.84375, 6.625,   9.125,   3.92188, 7,       4.3125,  9.625,   5.53125, 7.6875,  1.85156,
+                7.03125, 7.375,   3.5,     5.9375,  9.125,   2.0625,  6.5625,  7.375,   3.4375,  3.17188, 1.25,
+                9,       2.75,    3.40625, 5.9375,  5.53125, 3.3125,  6.625,   8.25,    6.84375, 2.82812, 1.27344,
+                8.625,   5.1875,  1.79688, 1.97656, 2.125,   9.875,   2.73438, 2.40625, 6.625,   2.76562, 3.76562,
+                5.59375, 7.1875,  6.40625, 8.5625,  6.21875, 6.46875, 8.0625,  7.6875,  2.1875,  9.0625,  6.3125,
+                9.0625,  2.90625, 2.17188, 7.4375,  3.125,   1.40625, 8.25,    7.0625,  8.375,   4.6875,  5.125,
+                1.875,   8.375,   3.4375,  9.6875,  9.3125,  7.5,     8.3125,  4.5,     7.5625,  1.92188, 1.46094,
+                8.75,    3.34375, 7.9375,  6,       8.5,     1.23438, 2.75,    7.25,    7.4375,  4.09375, 8.625,
+                6.34375, 5.5,     6.3125,  1.23438, 7.875,   8.25,    7.25,    7.65625, 8.25,    9.25,    9.625,
+                4.3125,  9.125,   3.64062, 6.4375,  5.9375,  9.125,   6.1875,  6.625,   3,       1.65625, 5.75,
+                6.1875,  4.71875, 8.125,   6.25,    2.5,     3.40625, 3.20312, 9.1875,  9.8125,  8.125,   4.125,
+                1.08594, 4.78125, 9.5625,  5.0625,  5.625,   3.5,     8.25,    1.73438, 3.5625,  8.0625,  2.23438,
+                3.0625,  3.34375, 3.40625, 3.625,   9.75,    1.14062, 4.84375, 9.125,   5.5,     8,       9.5,
+                5.125,   7.25,    9.4375,  2.0625,  5.90625, 9.75,    6.1875,  6,       7.3125,  7.3125,  7.34375,
+                7.5625,  6.1875,  9.125,   7.28125, 7.75,    4.59375, 7.5,     7.71875, 9.75,    9.5,     9.9375,
+                5.90625, 1.20312, 1.75,    7.75,    8.8125,  3.5625,  8.5,     9.25,    8.375,   7.84375, 4.9375,
+                7.4375,  6.75,    1.46875, 3.53125, 7.15625, 6.0625,  3.8125,  5.34375, 1.60938, 9.6875,  8.4375,
+                4.65625, 5.46875, 3.65625, 5.125,   9.125,   1.23438, 6.875,   1.79688, 4.1875,  2.26562, 2.78125,
+                9.25,    3.28125, 6.5625,  7.3125,  8.1875,  8.9375,  4,       8.625,   5.3125,  9.875,   4.375,
+                4.09375, 1.125,   2.84375, 8.375,   7.90625, 4.75,    4.625,   4.75,    3.17188, 7.59375, 4.5,
+                2.46875, 4.03125, 3.26562, 2.5,     7.28125, 6.3125,  7.6875,  1.00781, 1.3125,  7.625,   4.375,
+                2.0625,  4.1875,  7.625,   4.40625, 3.6875,  8.75,    4.09375, 2.84375, 5.21875, 3.65625, 9.5625,
+                1.71875, 5.9375,  1.79688, 5.8125,  5.625,   1.46875, 1.32812, 1.95312, 4.3125,  1.41406, 3.125,
+                9.1875,  6.3125,  5.3125,  4.1875,  1.17969, 1.32031, 9.5,     9.875,   6.78125, 2.32812, 7.1875,
+                4.3125,  7.90625, 4.6875,  7.875,   3.59375, 4.6875,  1.3125,  1.71094, 3.98438, 8.75,    8.625,
+                2.21875, 9.5,     7.1875,  3.92188, 5.6875,  5.75,    8.75,    6.625,   1.34375, 1.99219, 8.3125,
+                1.73438, 5.5625,  7.84375, 1.15625, 2.125,   4.5,     5.75,    7,       3.5,     7.375,   4.1875,
+                5.3125,  7.0625,  3.8125,  1.85156, 9,       6.75,    4.3125,  9.9375,  8.125,   8.75,    1.09375,
+                9.875,   6.46875, 2.32812, 3.84375, 8.75,    6.6875,  3.17188, 4.75,    5.25,    5.875,   4.625,
+                5.59375, 7.25,    8.625,   2.84375, 7,       4.0625,  6.5,     3.15625, 6.5,     4.65625, 7.8125,
+                2.6875,  5.6875,  4,       5.9375,  5.53125, 6.96875, 5.78125, 9.125,   6.53125, 8.125,   2.90625,
+                5.625,   5.125,   7.4375,  3.78125, 5.5,     8,       9.4375,  8.75,    6.75,    5.59375, 8.375,
+                2.4375,  1.27344, 4.90625, 8.875,   9.5,     5.21875, 6.9375,  9,       3.0625,  3.25,    2.39062,
+                1.92188, 2.54688, 3.73438, 7.28125, 4.5,     5.09375, 7.5,     2.14062, 1.10938, 2.32812, 3.875,
+                4.8125,  1.95312, 1.98438, 6.34375, 4.8125,  6.84375, 5.3125,  9.1875,  8.3125,  6.5,     7.125,
+                2.59375, 4.0625,  1.27344, 5.09375, 5.75,    1.48438, 6.1875,  5.1875,  9.9375,  8.3125,  2.14062,
+                5.21875, 5.0625,  1.94531, 6.6875,  7.75,    8.625,   6.3125,  5.8125,  8.75,    6.375,   8.875,
+                1.16406, 6.125,   1,       3.71875, 3.1875,  6.96875, 1.14062, 6.09375, 8.75,    1.5,     5.25,
+                5.1875,  1.48438, 2.96875, 2.03125, 4.40625, 9.625,   4.125,   5,       2.45312, 9.25,    5.875,
+                5.9375,  4.6875,  8.25,    5.3125,  1.73438, 7.4375,  4.625,   7.6875,  3.4375,  6.53125, 2.64062,
+                8.75,    2.57812, 7.8125,  4.4375,  6.0625,  4.5,     9.125,   7.96875, 2.65625, 8.125,   8.8125,
+                5.25,    5.65625, 4.84375, 7.96875, 3.09375, 2.3125,  7.34375, 8.5,     6.25,    2.79688, 7.8125,
+                5.8125,  7.0625,  5.84375, 6.4375,  9.1875,  5.03125, 2.01562, 1.8125,  6.5625,  9.5625,  4.96875,
+                5.8125,  4.75,    6.6875,  9.625,   4.625,   7.71875, 4.6875,  6.4375,  3.59375, 2.25,    3.0625,
+                6.375,   2.0625,  6.9375,  1.0625,  9.25,    7.0625,  3.90625, 9.875,   3.09375, 6.125,   9.1875,
+                2.9375,  4.0625,  5.6875,  6.4375,  8.25,    8.5,     7.1875,  6.46875, 9.125,   3.71875, 5.1875,
+                9.25,    9.375,   6.25,    8.5,     1.67188, 2.09375, 5.78125, 1.78125, 5.8125,  4.84375, 8.125,
+                1.64062, 9,       7.8125,  4.5,     3.64062, 1.9375,  1.24219, 9.25,    4.4375,  1.48438, 1.67188,
+                8.25,    7.75,    2.875,   3.28125, 3.9375,  8.75,    5.4375,  2.875,   5.6875,  1.99219, 9.625,
+                1.39062, 4.46875, 9.5,     7.375,   9.875,   2.98438, 3.0625,  9.875,   9.5625,  1.14062, 4.6875,
+                5.53125, 2.98438, 4.5,     9.25,    4.5625,  7.625,   3.1875,  8.4375,  1.65625, 3,       6,
+                9.75,    5.3125,  4.375,   6.75,    3.8125,  2.65625, 8.75,    1.23438, 2.40625, 2.875,   2.20312,
+                8.8125,  3.42188, 5.25,    8,       8.375,   2.8125,  4.5625,  6.40625, 4.875,   4.25,    9,
+                2.25,    5.75,    7,       8.5,     6.4375,  7.1875,  5.59375, 2.48438, 1.53125, 8.1875,  2.15625,
+                2.01562, 9.25,    8.375,   6.1875,  8,       9.125,   3.8125,  6.6875,  8,       8.75,    7.625,
+                9.75,    4.8125,  6,       2.78125, 3.5625,  8.5625,  1.07812, 9.9375,  6.8125,  7.125,   7.3125,
+                4.5625,  1.50781, 1.15625, 3.79688, 2.8125,  8.6875,  6.28125, 8.1875,  7.75,    8.875,   7.8125,
+                5.21875, 5.53125, 9.125,   5.125,   4.125,   1.35938, 6.25,    3.1875,  8.375,   1,       8,
+                8.625,   5.25,    8.875,   3.75,    7.5,     1.32812, 1.80469, 4.5,     2.15625, 6.8125,  2.375,
+                4.4375,  9.5625,  6.9375,  6.4375,  2.10938, 2.5625,  9,       1.71875, 6.78125, 6,       2,
+                7,       7.09375, 4.5,     5.8125,  8.625,   7.59375, 6.6875,  4.625,   3.35938, 9,       8.625,
+                1.51562, 9.5625,  6.25,    3.03125, 3.59375, 1.85156, 5.5625,  8.3125,  7.375,   2.21875, 8.5625,
+                3.0625,  7.1875,  7,       2.59375, 3.92188, 8.125,   3.09375, 7.4375,  6.375,   7.375,   8.125,
+                6.75,    7.78125, 2.5,     5,       7.5625,  1.42188, 9.0625,  1.875,   4.8125,  3.09375, 5.34375,
+                3.34375, 1.92188, 10,      4.3125,  5.03125, 8.75,    6.40625, 9.25,    9.125,   9,       7.4375,
+                3.89062, 4.4375,  9,       6.34375, 9.25,    9.875,   1.79688, 5.0625,  9,       3.04688, 6.6875,
+                2.98438, 5.40625, 8.125,   9.75,    3.125,   4.125,   3.48438, 8.4375,  8.75,    4.375,   8.375,
+                6.4375,  3.5,     3.89062, 5.4375,  9.5,     4.03125, 7.5,     10},
+            std::vector<T>{
+                1,       5.96875, 3,       8.75,    2.46875, 8.6875,  6.1875,  3.09375, 5,       5.3125,  3.09375,
+                3.25,    7.96875, 8.625,   3.34375, 6.8125,  2.8125,  9.5,     3.84375, 1.14062, 3.8125,  1.09375,
+                3.375,   7.0625,  6.875,   9.5,     5.125,   2.25,    5.34375, 6.3125,  1.79688, 5.4375,  8,
+                6.0625,  7.46875, 7,       9.25,    1.74219, 7.25,    3.5625,  4.5625,  3.01562, 2.78125, 8.125,
+                8.375,   2.53125, 4.9375,  6.375,   7.5,     3.78125, 6,       2.89062, 2.75,    8.4375,  2.85938,
+                2,       9.4375,  1.32812, 10,      4.3125,  3.09375, 9.75,    6,       9.125,   7.0625,  5.46875,
+                9,       4.625,   3.40625, 9.75,    5.25,    6.75,    5.4375,  3.96875, 3,       6.15625, 9.0625,
+                5.59375, 2,       2.51562, 4.75,    7.5625,  4.75,    5.28125, 2.17188, 1.00781, 3.625,   6.1875,
+                1.96875, 8.625,   9.25,    9.1875,  2,       2.75,    4.25,    1,       5.46875, 4.5,     6.65625,
+                3.5,     7.90625, 7.4375,  6.9375,  5.1875,  8.875,   2.375,   4.46875, 7.1875,  4.125,   6.9375,
+                9.5,     1.92969, 6.5,     6.5625,  9.0625,  8.5,     4.75,    4.6875,  6.0625,  9.8125,  2.34375,
+                4.65625, 9,       9.5,     6.71875, 5.40625, 3.28125, 6.5625,  4.1875,  1.1875,  6.1875,  2.8125,
+                7.875,   8.625,   8.25,    5,       4.9375,  4.625,   5,       7.4375,  8.5625,  5.3125,  8.4375,
+                6.5,     1.98438, 2.0625,  5.625,   7.625,   9.5625,  9.5,     6.125,   8,       10,      2.625,
+                4.90625, 2.95312, 6.8125,  8.75,    8.9375,  6.5,     1.65625, 7.84375, 8,       4.125,   9,
+                8.0625,  5.375,   6.0625,  3.6875,  7.0625,  2.73438, 7.28125, 7.4375,  5.375,   4.84375, 2.03125,
+                6.375,   6.5625,  4.0625,  2.125,   1.84375, 3.0625,  6.03125, 9.375,   4.625,   9.375,   3.57812,
+                2.84375, 8.0625,  6.65625, 9.75,    5.125,   1.07812, 8.4375,  5.75,    7.25,    4.5625,  3.54688,
+                6.9375,  6.625,   8.875,   6.40625, 2.70312, 6.0625,  2.5,     5.6875,  8.0625,  4.4375,  1.875,
+                8.1875,  7.6875,  3.25,    8.125,   7.6875,  3.03125, 9.75,    2.84375, 9.6875,  1.34375, 6.375,
+                6.34375, 8.6875,  2.28125, 6.375,   9.9375,  8.375,   1.23438, 6.3125,  8.625,   7.625,   4.75,
+                9.6875,  9.125,   4.75,    6.375,   2.6875,  8.75,    2.60938, 5.75,    4.4375,  8.25,    6.4375,
+                2.64062, 6.5625,  6.125,   9.625,   3.84375, 2.5,     3.09375, 7.75,    7.25,    3.96875, 5.9375,
+                1.09375, 8.125,   5.625,   9.5,     9.25,    5.6875,  3.03125, 6.1875,  2.85938, 8.0625,  4.75,
+                2.84375, 7.375,   2,       4.0625,  8.375,   4.1875,  2.78125, 3.04688, 2.64062, 9.5,     6.625,
+                9.875,   1.70312, 6.6875,  4.8125,  7,       1.9375,  1.32031, 7.5,     2.21875, 6.6875,  3.34375,
+                7.625,   1.53125, 8.875,   1.75781, 3.35938, 4.8125,  4.40625, 5.46875, 7.5625,  3.29688, 3.21875,
+                6.25,    4.34375, 5,       2.34375, 4.875,   2.78125, 7.46875, 3.20312, 5.4375,  6.875,   2,
+                5.375,   6.71875, 5.5625,  3.34375, 3.78125, 9.625,   1.8125,  5.125,   2.90625, 1.80469, 3.625,
+                5.34375, 1.76562, 5.6875,  9.5625,  9.4375,  10,      1.17188, 7.125,   9.5,     3,       7.1875,
+                2.09375, 2.98438, 5.9375,  9.375,   1.9375,  1.89062, 5.75,    3.21875, 7.375,   2.46875, 6.125,
+                4.96875, 3.75,    1.0625,  3.53125, 7.875,   4.8125,  9.125,   4.28125, 9.125,   1.78906, 8.0625,
+                7.9375,  1.32812, 6.5625,  4.25,    7.375,   6.875,   6.0625,  6.53125, 3.5625,  4.4375,  4.5,
+                6.875,   7.9375,  9.625,   4.3125,  1.09375, 2.73438, 7.75,    6.3125,  9.75,    4.625,   4.71875,
+                3,       2.40625, 1.17188, 7.625,   5.28125, 6.6875,  8.125,   9.625,   2.23438, 4.84375, 4.6875,
+                7.96875, 4.9375,  3.46875, 3,       9.5,     7.21875, 6.25,    3.0625,  1.34375, 6.25,    1.39844,
+                5.5625,  5.34375, 2.96875, 9.375,   2.85938, 7,       7.6875,  4.6875,  8.875,   4.40625, 4.25,
+                8.625,   5.875,   8,       4.8125,  1.46875, 5.625,   3,       9.875,   2.03125, 3.82812, 6.375,
+                8.75,    4.5625,  9.625,   8.625,   1.625,   6.1875,  1.85938, 9.125,   1.42188, 5.0625,  8.625,
+                4.5625,  2.4375,  8.875,   6.84375, 7.3125,  1.63281, 3.28125, 6.25,    3.70312, 1.28125, 6.96875,
+                1.67969, 5.875,   9.625,   7.3125,  5.71875, 9.9375,  4.0625,  6.5625,  1.03125, 3.84375, 4.1875,
+                9.5,     4.21875, 5.25,    1.64062, 4.78125, 4.28125, 7.8125,  6.1875,  8,       1.85938, 5.375,
+                1.9375,  8.125,   6,       4.90625, 1.53125, 2.53125, 6.53125, 1.67188, 1.5625,  2.48438, 8.9375,
+                2.75,    4,       3.65625, 4.625,   5.5625,  8.75,    4.9375,  3.40625, 8.1875,  6.40625, 7.0625,
+                6.6875,  6.0625,  9.75,    8.375,   1.36719, 9.625,   8.625,   8.375,   5.28125, 7.90625, 4.25,
+                9.6875,  5.1875,  6.6875,  8.375,   3.71875, 5.25,    9.5,     2.25,    7.1875,  3.46875, 7.53125,
+                5.15625, 7.84375, 2.375,   4,       5.34375, 8.6875,  4.75,    7,       5.96875, 9,       4.125,
+                6.34375, 3.28125, 5,       7.1875,  7.8125,  1.48438, 2.40625, 3.15625, 1.03125, 8.625,   5.78125,
+                3.5,     8.0625,  4.71875, 9.75,    3.3125,  5.09375, 3.65625, 4.5,     4.625,   7.6875,  7.375,
+                9.5,     4.625,   2.46875, 3.625,   6.125,   1.36719, 8.375,   8.375,   6.53125, 3.125,   5.75,
+                9.625,   3.3125,  8.375,   2.65625, 3.375,   3.60938, 6.9375,  4.9375,  1.78906, 9.25,    3.20312,
+                6.4375,  2.375,   2.40625, 6.0625,  3.75,    1.3125,  4.3125,  9.125,   9.3125,  1.09375, 8.3125,
+                1.98438, 8.1875,  6.1875,  1.21094, 8.25,    6.75,    5.75,    9.25,    4.75,    7.0625,  4.84375,
+                4.0625,  7.78125, 2.1875,  2.90625, 3.01562, 9.1875,  5,       6.5,     1.75,    6.1875,  2.96875,
+                1.07031, 2.375,   7.625,   6.0625,  3.90625, 3.45312, 2.57812, 3.3125,  3.96875, 7.875,   4.75,
+                7,       6.5625,  9.75,    4.5,     1.82812, 4.375,   4.90625, 9.75,    7.84375, 8.125,   6.3125,
+                4.875,   2.71875, 2.5,     8.875,   2.17188, 4.0625,  2.84375, 9,       2.3125,  1.85938, 5.875,
+                4.5625,  3.32812, 6.71875, 5.125,   1.67188, 3.8125,  8.5,     5.375,   7.75,    6.5,     8.25,
+                1.49219, 7.25,    5.625,   5,       8.6875,  5.5625,  9,       7.375,   6.9375,  6.625,   1.82812,
+                2.75,    7.59375, 3.875,   4.78125, 6.5625,  3.03125, 7.15625, 9.5,     9.125,   1.59375, 8.5,
+                4.3125,  5.15625, 4.65625, 6.125,   6.5,     4.25,    1.98438, 7.96875, 5.25,    4.40625, 4.5625,
+                2.89062, 3,       7.375,   5.75,    8.125,   1.75,    1.5625,  3.40625, 6.125,   3.29688, 1.39062,
+                6.625,   1.5,     8.875,   8.5,     5.5,     5,       1.09375, 1.79688, 9.75,    2.375,   1.07031,
+                8.25,    9,       9.875,   7.6875,  1.23438, 8.375,   8.0625,  6.75,    8.25,    8.625,   2.21875,
+                8.5,     9.25,    4.4375,  4.40625, 8,       3.5,     3.8125,  7,       2.125,   9,       3.42188,
+                9.125,   4.1875,  3.04688, 7.65625, 5.9375,  5.75,    9.5,     4.65625, 6.875,   5.0625,  1.89062,
+                3.40625, 5.78125, 4.0625,  5.125,   9,       5.9375,  2.46875, 9.25,    6.875,   7,       8.375,
+                6.09375, 1.48438, 5.90625, 8.75,    6.25,    7.3125,  8.5625,  9.9375,  9.125,   1.46875, 9.1875,
+                1.26562, 9,       5.5,     6.1875,  1.58594, 7.3125,  7.875,   9.5625,  3.32812, 8,       8.25,
+                4.59375, 9.75,    1.125,   8.3125,  4.6875,  3.375,   3.92188, 6.125,   4.46875, 3.625,   2.03125,
+                1.625,   9.1875,  2.46875, 3.03125, 6.1875,  9.5625,  5.78125, 2.10938, 3.14062, 4.125,   5.75,
+                7.03125, 2.28125, 6.9375,  7.3125,  3.125,   6.0625,  7.75,    7.1875,  8.1875,  6.90625, 4.875,
+                8.875,   7.3125,  5.9375,  1.39062, 4.625,   7.75,    5.0625,  10},
+            std::vector<T>{1,       7.25,    1.08594, 1.90625, 7.3125,  8.1875,  1.84375, 9.8125,  3.65625, 7.6875,
+                           7.03125, 6.75,    9.875,   9,       2.28125, 4.625,   8.375,   8.125,   4.25,    9.9375,
+                           2.125,   1.92969, 1.35938, 7.625,   5.6875,  2.65625, 6.9375,  8.0625,  2.53125, 7.375,
+                           2.8125,  9.1875,  7.3125,  8.75,    7.15625, 7.15625, 3.8125,  6.75,    3.53125, 8.75,
+                           9.875,   5.75,    7.1875,  5.65625, 7.375,   9.25,    6.03125, 9.75,    8.625,   1.07031,
+                           6.8125,  2.90625, 6.1875,  4.6875,  7.25,    1.14062, 9.0625,  2.78125, 5.625,   6.875,
+                           2.0625,  3.3125,  9.875,   8.9375,  5.6875,  5.875,   3.65625, 2.78125, 8.625,   4.1875,
+                           7.125,   7.09375, 5.125,   2.625,   3.10938, 9.4375,  5.5625,  5.8125,  3.5625,  10},
+            std::vector<T>{
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+                0.664062, 0.664062, 0.625,    0.667969, 0.664062, 0.667969, 0.546875, 0.640625, 0.667969, 0.667969,
+                0.648438, 0.664062, 0.609375, 0.664062, 0.65625,  0.667969, 0.546875, 0.625,    0.667969, 0.667969,
+                0.632812, 0.648438, 0.59375,  0.65625,  0.640625, 0.664062, 0.554688, 0.609375, 0.664062, 0.664062,
+                0.617188, 0.632812, 0.585938, 0.648438, 0.625,    0.65625,  0.554688, 0.59375,  0.648438, 0.65625,
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-                0.554688, 0.640625, 0.609375, 0.632812, 0.640625, 0.632812, 0.5625, 0.648438, 0.617188, 0.65625,
-                0.554688, 0.648438, 0.625, 0.648438, 0.65625, 0.648438, 0.5625, 0.65625, 0.632812, 0.664062,
-                0.546875, 0.664062, 0.640625, 0.664062, 0.664062, 0.65625, 0.5625, 0.664062, 0.648438, 0.667969,
-                0.539062, 0.667969, 0.648438, 0.667969, 0.667969, 0.664062, 0.570312, 0.667969, 0.65625, 0.667969,
+                0.554688, 0.640625, 0.609375, 0.632812, 0.640625, 0.632812, 0.5625,   0.648438, 0.617188, 0.65625,
+                0.554688, 0.648438, 0.625,    0.648438, 0.65625,  0.648438, 0.5625,   0.65625,  0.632812, 0.664062,
+                0.546875, 0.664062, 0.640625, 0.664062, 0.664062, 0.65625,  0.5625,   0.664062, 0.648438, 0.667969,
+                0.539062, 0.667969, 0.648438, 0.667969, 0.667969, 0.664062, 0.570312, 0.667969, 0.65625,  0.667969,
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-                0.65625, 0.554688, 0.632812, 0.609375, 0.617188, 0.585938, 0.601562, 0.632812, 0.632812, 0.632812,
-                0.601562, 0.648438, 0.640625, 0.554688, 0.65625, 0.65625, 0.554688, 0.648438, 0.648438, 0.640625,
-                0.585938, 0.632812, 0.65625, 0.648438, 0.648438, 0.570312, 0.648438, 0.648438, 0.640625, 0.632812,
-                0.585938, 0.648438, 0.632812, 0.609375, 0.648438, 0.640625, 0.5625, 0.5625, 0.585938, 0.617188,
-                0.648438, 0.648438, 0.625, 0.585938, 0.65625, 0.617188, 0.59375, 0.65625, 0.59375, 0.554688,
+                0.554688, 0.65625,  0.601562, 0.59375,  0.632812, 0.648438, 0.640625, 0.585938, 0.625,    0.640625,
+                0.65625,  0.554688, 0.632812, 0.609375, 0.617188, 0.585938, 0.601562, 0.632812, 0.632812, 0.632812,
+                0.601562, 0.648438, 0.640625, 0.554688, 0.65625,  0.65625,  0.554688, 0.648438, 0.648438, 0.640625,
+                0.585938, 0.632812, 0.65625,  0.648438, 0.648438, 0.570312, 0.648438, 0.648438, 0.640625, 0.632812,
+                0.585938, 0.648438, 0.632812, 0.609375, 0.648438, 0.640625, 0.5625,   0.5625,   0.585938, 0.617188,
+                0.648438, 0.648438, 0.625,    0.585938, 0.65625,  0.617188, 0.59375,  0.65625,  0.59375,  0.554688,
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-                0.65625, 0.632812, 0.632812, 0.625, 0.632812, 0.640625, 0.625, 0.585938, 0.625, 0.609375,
+                0.65625,  0.632812, 0.632812, 0.625,    0.632812, 0.640625, 0.625,    0.585938, 0.625,    0.609375,
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-                0.554688, 0.640625, 0.609375, 0.632812, 0.640625, 0.632812, 0.5625, 0.648438, 0.617188, 0.65625},
-            std::vector<T>{
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-                2.35938, 1.1875, 1.84375, 1.57812, 1.60938, 1.375, 1.48438, 1.90625, 1.90625, 1.79688,
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-                1.35156, 2.10938, 1.90625, 1.5625, 2.23438, 1.98438, 1.24219, 1.22656, 1.375, 1.67188,
-                2.23438, 2.17188, 1.70312, 1.375, 2.3125, 1.60938, 1.45312, 2.35938, 1.4375, 1.21875,
-                2.23438, 1.78125, 2.0625, 1.57812, 1.5, 1.51562, 1.57812, 2.10938, 1.9375, 2.29688,
-                2.35938, 1.79688, 1.89062, 1.73438, 1.8125, 1.95312, 1.70312, 1.40625, 1.73438, 1.57812,
-                1.5, 1.64062, 1.32031, 1.79688, 1.54688, 2.03125, 1.20312, 1.35938, 1.9375, 1.95312,
-                1.1875, 1.9375, 1.54688, 1.89062, 2, 1.78125, 1.22656, 2.15625, 1.59375, 2.35938}),
+                0.554688, 0.640625, 0.609375, 0.632812, 0.640625, 0.632812, 0.5625,   0.648438, 0.617188, 0.65625},
+            std::vector<T>{1.1875,  2.3125,  1.5,     1.45312, 1.84375, 2.29688, 2.03125, 1.39062, 1.76562, 2.03125,
+                           2.35938, 1.1875,  1.84375, 1.57812, 1.60938, 1.375,   1.48438, 1.90625, 1.90625, 1.79688,
+                           1.48438, 2.0625,  1.92188, 1.19531, 2.35938, 2.35938, 1.20312, 2.0625,  2.0625,  1.9375,
+                           1.35156, 1.84375, 2.35938, 2.23438, 2.10938, 1.30469, 2.125,   2.23438, 1.92188, 1.84375,
+                           1.35156, 2.10938, 1.90625, 1.5625,  2.23438, 1.98438, 1.24219, 1.22656, 1.375,   1.67188,
+                           2.23438, 2.17188, 1.70312, 1.375,   2.3125,  1.60938, 1.45312, 2.35938, 1.4375,  1.21875,
+                           2.23438, 1.78125, 2.0625,  1.57812, 1.5,     1.51562, 1.57812, 2.10938, 1.9375,  2.29688,
+                           2.35938, 1.79688, 1.89062, 1.73438, 1.8125,  1.95312, 1.70312, 1.40625, 1.73438, 1.57812,
+                           1.5,     1.64062, 1.32031, 1.79688, 1.54688, 2.03125, 1.20312, 1.35938, 1.9375,  1.95312,
+                           1.1875,  1.9375,  1.54688, 1.89062, 2,       1.78125, 1.22656, 2.15625, 1.59375, 2.35938}),
     };
     return params;
 }
@@ -1838,755 +2005,716 @@ template <element::Type_t ET>
 std::vector<LSTMSequenceV1Params> generateV1Params() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<LSTMSequenceV1Params> params {
+    std::vector<LSTMSequenceV1Params> params{
         LSTMSequenceV1Params(
-            5, 10, 10, 10,
-            0.7f, false, op::RecurrentSequenceDirection::FORWARD,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            false,
+            op::RecurrentSequenceDirection::FORWARD,
             ET,
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
-                1.82401, 6.1306, 4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686,
-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 4.59474,
-                6.19214, 8.80766, 8.07546, 3.29232, 1.74029, 2.4198, 2.88544, 4.75644, 4.12921, 7.29896,
-                7.27759, 1.67252, 1.32823, 8.1046, 9.10476, 1.04197, 3.37783, 5.2064, 4.23835, 3.16196,
-                1.20852, 5.78501, 2.17175, 6.05313, 2.51048, 4.78967, 7.16219, 3.4651, 1.09, 2.9788,
-                1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892, 5.86648, 8.73895, 2.66603, 1.75192,
-                1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565, 7.35114, 3.1439, 1.39976,
-                3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637, 8.6232, 8.54902,
-                2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225, 3.99956, 1.08021, 5.54918, 7.05833,
-                1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
-                5.59325, 9.89258, 2.30223, 1.4347, 9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909,
-                1.00912, 6.62167, 2.80244, 6.626, 3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902,
-                6.26823, 9.72608, 3.73491, 3.8238, 3.03815, 7.05101, 8.0103, 5.61396, 6.53738, 1.41095,
-                5.0149, 9.71211, 4.23604, 5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328, 8.2817,
-                5.12336, 8.98577, 5.80541, 6.19552, 9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817,
-                8.57269, 5.99975, 3.42893, 5.38068, 3.48261, 3.02851, 6.82079, 9.2902, 2.80427, 8.91868,
-                5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755, 2.49121, 5.52697, 8.08823, 9.13242,
-                2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457, 5.55154, 7.24966, 5.1128,
-                4.25147, 8.34407, 1.4123, 4.49045, 5.12671, 7.62159, 9.18673, 3.49665, 8.35992, 6.90684,
-                1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283, 9.88249, 4.48422,
-                8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155, 9.94928, 6.88321, 1.33685,
-                7.4718, 7.19305, 6.47932, 1.9559, 3.52616, 7.98593, 9.0115, 5.59539, 7.44137, 1.70001,
-                6.53774, 8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153,
-                5.4073, 9.00437, 8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473,
-                7.95084, 2.11852, 9.28916, 1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549,
-                3.75218, 8.98228, 8.98158, 5.63695, 3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035,
-                8.37644, 8.54954, 5.70516, 2.45744, 9.54079, 1.53504, 8.9785, 6.1691, 4.40962, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
+                1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 8.6168,
+                3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.0055,  7.44373,
+                8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 7.03475, 6.33759, 7.04489,
+                4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 6.61627, 6.94572, 3.68646, 5.01521,
+                2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937,
+                1.40811, 2.2597,  8.13163, 1.26821, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069,
+                4.25135, 6.13908, 6.74053, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208,
+                1.10502, 5.48298, 1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224,
+                7.95465, 2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
+                1.63073, 5.25228, 7.68488, 2.7276,  5.1788,  3.07327, 5.57423, 2.87711, 1.44374, 5.66976, 2.55051,
+                4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,  1.82401, 6.1306,
+                4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686, 4.85031, 4.85544, 4.25714,
+                2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891, 2.16793, 3.64924, 4.24733, 3.47181,
+                1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016, 7.6686,  3.68812, 2.83922, 9.83581, 9.03719,
+                7.83414, 6.86009, 1.35715, 8.32489, 7.86316, 5.09754, 5.78644, 1.98402, 2.31429, 5.5791,  2.94085,
+                9.24799, 5.15937, 2.19041, 7.87817, 2.9146,  1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937,
+                9.37912, 6.18926, 8.55681, 6.60963, 3.92066, 7.5521,  5.70463, 7.6313,  2.48866, 7.18352, 4.8413,
+                7.55702, 7.80702, 4.5785,  9.3268,  2.83159, 1.07202, 9.33716, 3.6506,  2.50256, 1.21691, 5.06801,
+                8.27505, 4.31539, 6.48286, 1.31363, 4.1912,  1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
+                5.24875, 1.94852, 5.52768, 8.97121, 5.8094,  3.53329, 4.19126, 9.06652, 3.1734,  1.21496, 9.69154,
+                4.86971, 4.1166,  6.19361, 2.13874, 9.55039, 3.8225,  9.57548, 2.96554, 3.2383,  8.77422, 3.11741,
+                8.3359,  5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474,  4.59474, 6.19214, 8.80766, 8.07546,
+                3.29232, 1.74029, 2.4198,  2.88544, 4.75644, 4.12921, 7.29896, 7.27759, 1.67252, 1.32823, 8.1046,
+                9.10476, 1.04197, 3.37783, 5.2064,  4.23835, 3.16196, 1.20852, 5.78501, 2.17175, 6.05313, 2.51048,
+                4.78967, 7.16219, 3.4651,  1.09,    2.9788,  1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892,
+                5.86648, 8.73895, 2.66603, 1.75192, 1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565,
+                7.35114, 3.1439,  1.39976, 3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637,
+                8.6232,  8.54902, 2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225,  3.99956, 1.08021, 5.54918,
+                7.05833, 1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
+                5.59325, 9.89258, 2.30223, 1.4347,  9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909, 1.00912,
+                6.62167, 2.80244, 6.626,   3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902, 6.26823, 9.72608,
+                3.73491, 3.8238,  3.03815, 7.05101, 8.0103,  5.61396, 6.53738, 1.41095, 5.0149,  9.71211, 4.23604,
+                5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328,  8.2817,  5.12336, 8.98577, 5.80541, 6.19552,
+                9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817, 8.57269, 5.99975, 3.42893, 5.38068, 3.48261,
+                3.02851, 6.82079, 9.2902,  2.80427, 8.91868, 5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755,
+                2.49121, 5.52697, 8.08823, 9.13242, 2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457,
+                5.55154, 7.24966, 5.1128,  4.25147, 8.34407, 1.4123,  4.49045, 5.12671, 7.62159, 9.18673, 3.49665,
+                8.35992, 6.90684, 1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283,  9.88249,
+                4.48422, 8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155,  9.94928, 6.88321, 1.33685,
+                7.4718,  7.19305, 6.47932, 1.9559,  3.52616, 7.98593, 9.0115,  5.59539, 7.44137, 1.70001, 6.53774,
+                8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153, 5.4073,  9.00437,
+                8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473, 7.95084, 2.11852, 9.28916,
+                1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549, 3.75218, 8.98228, 8.98158, 5.63695,
+                3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035, 8.37644, 8.54954, 5.70516, 2.45744, 9.54079,
+                1.53504, 8.9785,  6.1691,  4.40962, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
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+                2.49121, 5.52697, 8.08823, 10},
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+                           0.562011, 0.573728, 0.56272,  0.585197, 0.587567},
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         LSTMSequenceV1Params(
-            5, 10, 10, 10,
-            0.7f, false, op::RecurrentSequenceDirection::REVERSE,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            false,
+            op::RecurrentSequenceDirection::REVERSE,
             ET,
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+                0.663659, 0.668187, 0.667878, 0.668141, 0.667739, 0.66697,  0.66724,  0.594272, 0.668184, 0.668187},
+            std::vector<T>{0.559698, 0.563643, 0.575276, 0.58701,  0.572904, 0.575772, 0.576994, 0.561768, 0.581308,
+                           0.577538, 0.577721, 0.585209, 0.585595, 0.565295, 0.580988, 0.560659, 0.566647, 0.569616,
+                           0.572781, 0.567475, 0.571076, 0.569599, 0.583098, 0.58192,  0.566985, 0.560831, 0.569929,
+                           0.584406, 0.567476, 0.58273,  0.575645, 0.585051, 0.576926, 0.579983, 0.580676, 0.561414,
+                           0.57526,  0.577421, 0.58672,  0.568884, 0.568706, 0.587492, 0.575078, 0.579316, 0.574221,
+                           0.571875, 0.572469, 0.56152,  0.584476, 0.587567},
+            std::vector<T>{1.2132,  1.23332, 1.297,   1.3692,  1.28344, 1.29988, 1.30703, 1.22367, 1.33299, 1.31023,
+                           1.31132, 1.35752, 1.36,    1.24196, 1.33102, 1.21804, 1.24912, 1.26516, 1.28275, 1.25354,
+                           1.2732,  1.26506, 1.34411, 1.33676, 1.25092, 1.21891, 1.26687, 1.35238, 1.25355, 1.34181,
+                           1.29914, 1.3565,  1.30662, 1.32489, 1.32911, 1.22187, 1.29691, 1.30955, 1.3673,  1.26116,
+                           1.26019, 1.37237, 1.29586, 1.32085, 1.29093, 1.27766, 1.28099, 1.22241, 1.35283, 1.37287}),
         LSTMSequenceV1Params(
-            5, 10, 10, 5,
-            0.7f, true, op::RecurrentSequenceDirection::BIDIRECTIONAL,
+            5,
+            10,
+            10,
+            5,
+            0.7f,
+            true,
+            op::RecurrentSequenceDirection::BIDIRECTIONAL,
             ET,
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-                4.72902, 8.18267, 2.2418, 3.35014, 3.04117, 5.79207, 7.25244, 3.19579, 2.75589, 10},
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-                7.45168, 4.64152, 6.15237, 9.08577, 2.87424, 8.64111, 2.93614, 2.41379, 4.12032, 10},
-            std::vector<T>{
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-                0.668186, 0.667977, 0.667567, 0.668108, 0.665593, 0.656946, 0.667394, 0.54513, 0.66818, 0.661847,
+                0.668097, 0.665613, 0.662901, 0.666844, 0.654514, 0.632229, 0.661961, 0.49883,  0.667912, 0.643509,
+                0.668186, 0.667977, 0.667567, 0.668108, 0.665593, 0.656946, 0.667394, 0.54513,  0.66818,  0.661847,
                 0.661547, 0.667282, 0.667096, 0.668178, 0.660535, 0.668076, 0.659185, 0.660516, 0.668175, 0.473006,
                 0.642746, 0.661391, 0.660491, 0.667864, 0.640257, 0.666507, 0.637108, 0.640212, 0.667785, 0.440135,
                 0.606897, 0.642355, 0.640151, 0.664764, 0.603065, 0.657937, 0.598393, 0.602997, 0.664228, 0.415812,
                 0.559969, 0.606286, 0.602906, 0.651762, 0.555663, 0.634343, 0.550536, 0.555588, 0.650103, 0.39848,
-                0.51225, 0.559276, 0.555486, 0.6221, 0.508292, 0.594429, 0.503649, 0.508223, 0.619113, 0.386411,
-                0.608718, 0.620998, 0.457879, 0.54662, 0.554179, 0.630205, 0.568834, 0.62793, 0.473801, 0.626594,
+                0.51225,  0.559276, 0.555486, 0.6221,   0.508292, 0.594429, 0.503649, 0.508223, 0.619113, 0.386411,
+                0.608718, 0.620998, 0.457879, 0.54662,  0.554179, 0.630205, 0.568834, 0.62793,  0.473801, 0.626594,
                 0.643899, 0.651157, 0.495954, 0.594746, 0.601725, 0.655966, 0.614515, 0.654831, 0.515734, 0.654148,
-                0.661998, 0.664572, 0.541864, 0.634567, 0.639366, 0.665997, 0.64744, 0.665683, 0.563712, 0.665487,
+                0.661998, 0.664572, 0.541864, 0.634567, 0.639366, 0.665997, 0.64744,  0.665683, 0.563712, 0.665487,
                 0.667401, 0.667837, 0.590227, 0.658041, 0.660161, 0.668022, 0.663313, 0.667985, 0.610158, 0.667961,
                 0.668152, 0.668177, 0.631318, 0.666532, 0.667025, 0.668184, 0.667638, 0.668183, 0.644798, 0.668182,
-                0.666934, 0.636465, 0.668176, 0.668177, 0.6627, 0.668186, 0.663435, 0.667808, 0.66818, 0.667477,
-                0.659751, 0.59746, 0.667824, 0.66784, 0.645753, 0.668092, 0.647783, 0.664381, 0.667904, 0.662402,
+                0.666934, 0.636465, 0.668176, 0.668177, 0.6627,   0.668186, 0.663435, 0.667808, 0.66818,  0.667477,
+                0.659751, 0.59746,  0.667824, 0.66784,  0.645753, 0.668092, 0.647783, 0.664381, 0.667904, 0.662402,
                 0.638407, 0.549527, 0.664483, 0.664596, 0.611711, 0.666671, 0.615095, 0.650567, 0.665048, 0.644956,
                 0.600299, 0.502744, 0.650882, 0.651231, 0.565521, 0.658614, 0.569527, 0.619937, 0.652675, 0.610413,
-                0.552612, 0.463272, 0.620503, 0.621133, 0.517435, 0.635826, 0.52124, 0.575428, 0.62379, 0.564008,
+                0.552612, 0.463272, 0.620503, 0.621133, 0.517435, 0.635826, 0.52124,  0.575428, 0.62379,  0.564008,
                 0.619111, 0.625883, 0.633724, 0.600854, 0.532704, 0.497421, 0.571602, 0.461671, 0.475281, 0.63631,
-                0.650102, 0.653779, 0.65765, 0.638782, 0.581251, 0.543534, 0.616817, 0.500738, 0.517531, 0.658831,
-                0.664228, 0.665379, 0.666436, 0.659912, 0.624548, 0.591824, 0.64879, 0.547281, 0.565623, 0.666723,
-                0.667785, 0.667947, 0.668069, 0.66697, 0.653078, 0.632479, 0.663785, 0.595367, 0.611798, 0.668097,
-                0.668175, 0.668182, 0.668186, 0.668119, 0.66517, 0.657065, 0.667716, 0.635005, 0.645806, 0.668186},
+                0.650102, 0.653779, 0.65765,  0.638782, 0.581251, 0.543534, 0.616817, 0.500738, 0.517531, 0.658831,
+                0.664228, 0.665379, 0.666436, 0.659912, 0.624548, 0.591824, 0.64879,  0.547281, 0.565623, 0.666723,
+                0.667785, 0.667947, 0.668069, 0.66697,  0.653078, 0.632479, 0.663785, 0.595367, 0.611798, 0.668097,
+                0.668175, 0.668182, 0.668186, 0.668119, 0.66517,  0.657065, 0.667716, 0.635005, 0.645806, 0.668186},
             std::vector<T>{
                 0.385148, 0.446733, 0.573404, 0.634552, 0.553825, 0.577138, 0.585828, 0.418653, 0.611283, 0.589475,
-                0.590675, 0.628293, 0.629709, 0.46966, 0.609654, 0.401027, 0.487158, 0.521658, 0.552734, 0.497312,
+                0.590675, 0.628293, 0.629709, 0.46966,  0.609654, 0.401027, 0.487158, 0.521658, 0.552734, 0.497312,
                 0.536694, 0.521472, 0.619718, 0.614293, 0.491353, 0.403801, 0.524983, 0.625194, 0.497325, 0.618077,
                 0.576187, 0.627698, 0.585362, 0.604275, 0.608023, 0.413104, 0.573282, 0.588705, 0.633605, 0.513641,
                 0.511639, 0.636078, 0.571877, 0.600486, 0.565051, 0.544415, 0.549923, 0.414776, 0.625475, 0.627521,
                 0.636308, 0.585028, 0.566575, 0.598958, 0.536327, 0.497101, 0.561873, 0.408877, 0.624184, 0.51352,
-                0.51225, 0.559276, 0.555486, 0.6221, 0.508292, 0.594429, 0.503649, 0.508223, 0.619113, 0.386411,
-                0.608718, 0.620998, 0.457879, 0.54662, 0.554179, 0.630205, 0.568834, 0.62793, 0.473801, 0.626594,
-                0.552612, 0.463272, 0.620503, 0.621133, 0.517435, 0.635826, 0.52124, 0.575428, 0.62379, 0.564008,
+                0.51225,  0.559276, 0.555486, 0.6221,   0.508292, 0.594429, 0.503649, 0.508223, 0.619113, 0.386411,
+                0.608718, 0.620998, 0.457879, 0.54662,  0.554179, 0.630205, 0.568834, 0.62793,  0.473801, 0.626594,
+                0.552612, 0.463272, 0.620503, 0.621133, 0.517435, 0.635826, 0.52124,  0.575428, 0.62379,  0.564008,
                 0.619111, 0.625883, 0.633724, 0.600854, 0.532704, 0.497421, 0.571602, 0.461671, 0.475281, 0.63631},
             std::vector<T>{
-                0.657064, 0.808159, 1.28627, 1.82832, 1.18444, 1.30787, 1.3615, 0.735716, 1.55641, 1.3856,
-                1.39376, 1.74058, 1.7592, 0.872984, 1.54166, 0.693415, 0.926748, 1.04718, 1.17924, 0.959985,
-                1.10759, 1.04646, 1.63992, 1.58476, 0.940282, 0.699929, 1.06005, 1.70199, 0.960028, 1.62263,
-                1.3023, 1.73294, 1.3585, 1.4956, 1.52728, 0.722161, 1.28558, 1.38043, 1.81407, 1.01716,
-                1.00988, 1.85212, 1.27767, 1.46531, 1.24067, 1.14104, 1.16607, 0.72622, 1.70537, 1.7307,
-                1.8558, 1.35635, 1.24873, 1.45354, 1.10604, 0.959278, 1.22421, 0.711984, 1.68998, 1.01672,
-                1.01209, 1.21108, 1.19243, 1.66604, 0.997881, 1.42007, 0.98159, 0.997636, 1.63348, 0.6599,
-                1.53336, 1.6538, 0.838953, 1.15094, 1.18613, 1.76588, 1.26089, 1.73591, 0.885339, 1.71907,
-                1.17867, 0.854332, 1.64838, 1.65528, 1.03119, 1.84811, 1.04557, 1.29788, 1.68537, 1.23522,
-                1.63346, 1.71032, 1.81584, 1.46818, 1.09099, 0.960351, 1.27613, 0.849735, 0.889806, 1.85583}),
+                0.657064, 0.808159, 1.28627,  1.82832,  1.18444,  1.30787,  1.3615,   0.735716, 1.55641,  1.3856,
+                1.39376,  1.74058,  1.7592,   0.872984, 1.54166,  0.693415, 0.926748, 1.04718,  1.17924,  0.959985,
+                1.10759,  1.04646,  1.63992,  1.58476,  0.940282, 0.699929, 1.06005,  1.70199,  0.960028, 1.62263,
+                1.3023,   1.73294,  1.3585,   1.4956,   1.52728,  0.722161, 1.28558,  1.38043,  1.81407,  1.01716,
+                1.00988,  1.85212,  1.27767,  1.46531,  1.24067,  1.14104,  1.16607,  0.72622,  1.70537,  1.7307,
+                1.8558,   1.35635,  1.24873,  1.45354,  1.10604,  0.959278, 1.22421,  0.711984, 1.68998,  1.01672,
+                1.01209,  1.21108,  1.19243,  1.66604,  0.997881, 1.42007,  0.98159,  0.997636, 1.63348,  0.6599,
+                1.53336,  1.6538,   0.838953, 1.15094,  1.18613,  1.76588,  1.26089,  1.73591,  0.885339, 1.71907,
+                1.17867,  0.854332, 1.64838,  1.65528,  1.03119,  1.84811,  1.04557,  1.29788,  1.68537,  1.23522,
+                1.63346,  1.71032,  1.81584,  1.46818,  1.09099,  0.960351, 1.27613,  0.849735, 0.889806, 1.85583}),
     };
     return params;
 }
@@ -2595,761 +2723,730 @@ template <element::Type_t ET>
 std::vector<LSTMSequenceV1Params> generateV1ParamsBF16() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<LSTMSequenceV1Params> params {
+    std::vector<LSTMSequenceV1Params> params{
         LSTMSequenceV1Params(
-            5, 10, 10, 10,
-            0.7f, false, op::RecurrentSequenceDirection::FORWARD,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            false,
+            op::RecurrentSequenceDirection::FORWARD,
             ET,
             std::vector<T>{
-                1, 9.375, 9, 3.84375, 2.17188, 2.65625, 1.35938, 2.84375, 8.4375, 6.125,
-                5.78125, 6.375, 9.625, 9.625, 5.15625, 6.875, 9.3125, 7.75, 4.375, 6.875,
-                2.39062, 7.71875, 9, 9.625, 1.23438, 1.07812, 3.625, 1.95312, 4.5625, 3.6875,
-                8.25, 6.90625, 6.625, 8.25, 9.125, 8.875, 6, 9.625, 8.5, 7.5,
-                1.45312, 6.78125, 8.25, 7.4375, 9.375, 5.1875, 4.25, 3.9375, 7.1875, 4.9375,
-                2.15625, 7.5625, 8.5, 9.9375, 3.85938, 7.0625, 7.625, 8.125, 6.375, 2.53125,
-                4.25, 1.23438, 8.125, 8.1875, 7.28125, 9.125, 8.375, 1.21875, 9.125, 5.4375,
-                8.5, 5.75, 9.1875, 6.375, 9.75, 1.46875, 6.875, 9, 8.25, 7.5625,
-                1.92188, 8.375, 3.125, 5.5, 4.40625, 8.25, 7.28125, 1.85938, 5.375, 2.96875,
-                4.75, 3.32812, 6.75, 5.1875, 7.8125, 5.125, 6, 7.375, 7.25, 2.59375,
-                9.25, 5.78125, 1.21875, 2.5, 8.5, 7.90625, 4.4375, 9.375, 3.6875, 6.5,
-                1.05469, 2.34375, 4.9375, 5.40625, 7.625, 4.375, 4.375, 8.625, 5.4375, 9.1875,
-                1.125, 4.4375, 3.25, 3.84375, 4.125, 6.125, 8.125, 2.6875, 9.4375, 2.125,
-                1.90625, 7.1875, 7.625, 8.1875, 9.75, 6.15625, 7.34375, 9.75, 9.5625, 6.6875,
-                9.375, 9, 4.6875, 5.4375, 4.03125, 4.15625, 7.9375, 7.4375, 4, 5.53125,
-                1.74219, 3.03125, 9.0625, 3.20312, 8.0625, 8.125, 7.4375, 5.4375, 5, 9.25,
-                7.75, 9.5, 6.90625, 5.8125, 4.25, 3.26562, 4.375, 7.5, 6.84375, 4.3125,
-                1.5, 5.5, 1.70312, 3.03125, 1.82812, 4.1875, 8.25, 6.84375, 1.58594, 3.8125,
-                3.01562, 7.90625, 2.375, 8, 7.125, 8.625, 2.125, 9.5, 3.3125, 1.96875,
-                4.9375, 9.1875, 1.98438, 4, 3.82812, 8.375, 4.15625, 9.0625, 7.84375, 1.38281,
-                1.89062, 2.75, 9.375, 3.65625, 3.9375, 6.625, 4.8125, 1.77344, 3.4375, 2.28125,
-                8.0625, 5.625, 5.0625, 7.1875, 1.75, 8.6875, 1.63281, 6.8125, 3.96875, 6.25,
-                2.71875, 7.375, 8.5, 3.26562, 1.55469, 9.125, 6, 4.96875, 6.125, 1.1875,
-                5.15625, 9.625, 9.5, 6.875, 4.09375, 5.625, 8.9375, 7.125, 4.875, 5.375,
-                9.9375, 9.3125, 8.1875, 5.625, 9.5, 1.64844, 4.40625, 6.09375, 4.625, 6.53125,
-                3.57812, 9.5, 5.0625, 4.75, 7.875, 3.375, 6.21875, 1.875, 4.375, 5.375,
-                6.59375, 5.1875, 7.625, 1.26562, 9.25, 7.25, 5.78125, 7.4375, 5.65625, 7.5625,
-                1.92188, 4.71875, 2.09375, 1.13281, 6.78125, 9.125, 5, 8.125, 1.6875, 2.48438,
-                2.375, 3.8125, 1.71875, 6.5, 8.875, 4.25, 2.45312, 2.40625, 9.25, 2.59375,
-                1.03125, 8.75, 8.25, 3.60938, 3.71875, 6.25, 3.1875, 5.0625, 7.90625, 4.6875,
-                7.3125, 8.9375, 9, 7.21875, 9.1875, 3.5, 3.03125, 1.57812, 4.78125, 2.78125,
-                2.5, 9.375, 2.89062, 8.6875, 8.5, 9.5625, 9.25, 1.46875, 7.125, 6.1875,
-                4.6875, 5.3125, 3, 1.19531, 8.5, 4.375, 8, 4.71875, 7.625, 6.4375,
-                8.75, 7.03125, 9.75, 8.5, 4.6875, 8, 6.375, 4.59375, 7.625, 8.125,
-                3.40625, 9, 7.875, 3.35938, 9.375, 9.875, 8.875, 8.625, 2.03125, 7.5625,
-                9.6875, 4.1875, 3.71875, 8.9375, 6.46875, 8.75, 2.5, 9.625, 8.75, 1,
-                7.53125, 1.14844, 1.58594, 3.8125, 5.65625, 9.9375, 6.34375, 2.34375, 5.125, 2.5,
-                6.3125, 7.8125, 3.875, 1.625, 8.375, 7.34375, 1.82812, 5.21875, 2.59375, 1.09375,
-                2.98438, 7.96875, 5.25, 8.125, 9.25, 2.34375, 9.875, 1.21094, 6.4375, 7.84375,
-                9.25, 3, 4.3125, 3.35938, 1.0625, 5.125, 6.875, 3.25, 2.5, 6.125,
-                5.4375, 8.625, 8.125, 4.375, 8.375, 4.875, 4.3125, 8.5, 2.15625, 4.3125,
-                2.78125, 1.35938, 1.1875, 6, 6.6875, 5.0625, 5.3125, 7.5, 2.90625, 4.375,
-                3.375, 8.5625, 2.6875, 5.21875, 9, 6.0625, 7.4375, 6.9375, 1.60938, 5.15625,
-                3.20312, 6.625, 9.25, 3, 2.84375, 7.59375, 5.1875, 4.4375, 7.875, 2.75,
-                5.78125, 3.4375, 5.9375, 3.25, 3.10938, 2.375, 3.46875, 7.9375, 1.14844, 3.29688,
-                4.8125, 2.14062, 1.42188, 7, 1.53125, 4.6875, 3.875, 7, 5, 6.9375,
-                2.51562, 3.75, 3.71875, 2.8125, 5.03125, 3, 5.25, 2.07812, 7.3125, 1.32812,
-                7.3125, 1.30469, 6.3125, 3.0625, 9.75, 3.0625, 6.9375, 6.625, 8.875, 9,
-                4.71875, 8, 8.125, 7.5, 2.23438, 3.78125, 3.34375, 4.25, 3.03125, 2.75,
-                5.78125, 9.375, 7.25, 6.0625, 3.1875, 8.375, 2.75, 4.125, 8.125, 10},
-            std::vector<T>{
-                1, 9.1875, 5.5625, 6.625, 2.65625, 8.125, 8.25, 4.875, 9.4375, 5.875,
-                1.26562, 4.71875, 8.0625, 1.76562, 2.46875, 8, 4.875, 5.375, 6.15625, 1.45312,
-                2.95312, 5.84375, 8.5, 1.375, 3.6875, 8.25, 4.25, 9.9375, 8.8125, 6.75,
-                1.10938, 9.5, 7.0625, 7.625, 5.3125, 8.375, 9.75, 2.03125, 2.90625, 7.625,
-                2.90625, 8.375, 9.5, 1.66406, 3.9375, 2.875, 9.875, 8.25, 4.9375, 10},
-            std::vector<T>{
-                1, 6.59375, 2.125, 2.89062, 5.71875, 5.0625, 9.75, 6, 4.9375, 3.21875,
-                5.875, 1.85156, 6.28125, 9.875, 1.59375, 3.40625, 7.75, 9.25, 6.46875, 8.75,
-                6.5, 4.0625, 9.125, 4.4375, 9.25, 5.5625, 2.625, 1.8125, 7.625, 1.875,
-                1.26562, 6.3125, 3.03125, 7.3125, 3.92188, 2.21875, 4.90625, 2.10938, 3.28125, 6.875,
-                4.375, 7.25, 3.92188, 3.09375, 8.375, 7.96875, 7.9375, 1.875, 3.125, 10},
+                1,       9.375,   9,       3.84375, 2.17188, 2.65625, 1.35938, 2.84375, 8.4375,  6.125,   5.78125,
+                6.375,   9.625,   9.625,   5.15625, 6.875,   9.3125,  7.75,    4.375,   6.875,   2.39062, 7.71875,
+                9,       9.625,   1.23438, 1.07812, 3.625,   1.95312, 4.5625,  3.6875,  8.25,    6.90625, 6.625,
+                8.25,    9.125,   8.875,   6,       9.625,   8.5,     7.5,     1.45312, 6.78125, 8.25,    7.4375,
+                9.375,   5.1875,  4.25,    3.9375,  7.1875,  4.9375,  2.15625, 7.5625,  8.5,     9.9375,  3.85938,
+                7.0625,  7.625,   8.125,   6.375,   2.53125, 4.25,    1.23438, 8.125,   8.1875,  7.28125, 9.125,
+                8.375,   1.21875, 9.125,   5.4375,  8.5,     5.75,    9.1875,  6.375,   9.75,    1.46875, 6.875,
+                9,       8.25,    7.5625,  1.92188, 8.375,   3.125,   5.5,     4.40625, 8.25,    7.28125, 1.85938,
+                5.375,   2.96875, 4.75,    3.32812, 6.75,    5.1875,  7.8125,  5.125,   6,       7.375,   7.25,
+                2.59375, 9.25,    5.78125, 1.21875, 2.5,     8.5,     7.90625, 4.4375,  9.375,   3.6875,  6.5,
+                1.05469, 2.34375, 4.9375,  5.40625, 7.625,   4.375,   4.375,   8.625,   5.4375,  9.1875,  1.125,
+                4.4375,  3.25,    3.84375, 4.125,   6.125,   8.125,   2.6875,  9.4375,  2.125,   1.90625, 7.1875,
+                7.625,   8.1875,  9.75,    6.15625, 7.34375, 9.75,    9.5625,  6.6875,  9.375,   9,       4.6875,
+                5.4375,  4.03125, 4.15625, 7.9375,  7.4375,  4,       5.53125, 1.74219, 3.03125, 9.0625,  3.20312,
+                8.0625,  8.125,   7.4375,  5.4375,  5,       9.25,    7.75,    9.5,     6.90625, 5.8125,  4.25,
+                3.26562, 4.375,   7.5,     6.84375, 4.3125,  1.5,     5.5,     1.70312, 3.03125, 1.82812, 4.1875,
+                8.25,    6.84375, 1.58594, 3.8125,  3.01562, 7.90625, 2.375,   8,       7.125,   8.625,   2.125,
+                9.5,     3.3125,  1.96875, 4.9375,  9.1875,  1.98438, 4,       3.82812, 8.375,   4.15625, 9.0625,
+                7.84375, 1.38281, 1.89062, 2.75,    9.375,   3.65625, 3.9375,  6.625,   4.8125,  1.77344, 3.4375,
+                2.28125, 8.0625,  5.625,   5.0625,  7.1875,  1.75,    8.6875,  1.63281, 6.8125,  3.96875, 6.25,
+                2.71875, 7.375,   8.5,     3.26562, 1.55469, 9.125,   6,       4.96875, 6.125,   1.1875,  5.15625,
+                9.625,   9.5,     6.875,   4.09375, 5.625,   8.9375,  7.125,   4.875,   5.375,   9.9375,  9.3125,
+                8.1875,  5.625,   9.5,     1.64844, 4.40625, 6.09375, 4.625,   6.53125, 3.57812, 9.5,     5.0625,
+                4.75,    7.875,   3.375,   6.21875, 1.875,   4.375,   5.375,   6.59375, 5.1875,  7.625,   1.26562,
+                9.25,    7.25,    5.78125, 7.4375,  5.65625, 7.5625,  1.92188, 4.71875, 2.09375, 1.13281, 6.78125,
+                9.125,   5,       8.125,   1.6875,  2.48438, 2.375,   3.8125,  1.71875, 6.5,     8.875,   4.25,
+                2.45312, 2.40625, 9.25,    2.59375, 1.03125, 8.75,    8.25,    3.60938, 3.71875, 6.25,    3.1875,
+                5.0625,  7.90625, 4.6875,  7.3125,  8.9375,  9,       7.21875, 9.1875,  3.5,     3.03125, 1.57812,
+                4.78125, 2.78125, 2.5,     9.375,   2.89062, 8.6875,  8.5,     9.5625,  9.25,    1.46875, 7.125,
+                6.1875,  4.6875,  5.3125,  3,       1.19531, 8.5,     4.375,   8,       4.71875, 7.625,   6.4375,
+                8.75,    7.03125, 9.75,    8.5,     4.6875,  8,       6.375,   4.59375, 7.625,   8.125,   3.40625,
+                9,       7.875,   3.35938, 9.375,   9.875,   8.875,   8.625,   2.03125, 7.5625,  9.6875,  4.1875,
+                3.71875, 8.9375,  6.46875, 8.75,    2.5,     9.625,   8.75,    1,       7.53125, 1.14844, 1.58594,
+                3.8125,  5.65625, 9.9375,  6.34375, 2.34375, 5.125,   2.5,     6.3125,  7.8125,  3.875,   1.625,
+                8.375,   7.34375, 1.82812, 5.21875, 2.59375, 1.09375, 2.98438, 7.96875, 5.25,    8.125,   9.25,
+                2.34375, 9.875,   1.21094, 6.4375,  7.84375, 9.25,    3,       4.3125,  3.35938, 1.0625,  5.125,
+                6.875,   3.25,    2.5,     6.125,   5.4375,  8.625,   8.125,   4.375,   8.375,   4.875,   4.3125,
+                8.5,     2.15625, 4.3125,  2.78125, 1.35938, 1.1875,  6,       6.6875,  5.0625,  5.3125,  7.5,
+                2.90625, 4.375,   3.375,   8.5625,  2.6875,  5.21875, 9,       6.0625,  7.4375,  6.9375,  1.60938,
+                5.15625, 3.20312, 6.625,   9.25,    3,       2.84375, 7.59375, 5.1875,  4.4375,  7.875,   2.75,
+                5.78125, 3.4375,  5.9375,  3.25,    3.10938, 2.375,   3.46875, 7.9375,  1.14844, 3.29688, 4.8125,
+                2.14062, 1.42188, 7,       1.53125, 4.6875,  3.875,   7,       5,       6.9375,  2.51562, 3.75,
+                3.71875, 2.8125,  5.03125, 3,       5.25,    2.07812, 7.3125,  1.32812, 7.3125,  1.30469, 6.3125,
+                3.0625,  9.75,    3.0625,  6.9375,  6.625,   8.875,   9,       4.71875, 8,       8.125,   7.5,
+                2.23438, 3.78125, 3.34375, 4.25,    3.03125, 2.75,    5.78125, 9.375,   7.25,    6.0625,  3.1875,
+                8.375,   2.75,    4.125,   8.125,   10},
+            std::vector<T>{1,       9.1875,  5.5625, 6.625,   2.65625, 8.125, 8.25,  4.875,   9.4375,  5.875,
+                           1.26562, 4.71875, 8.0625, 1.76562, 2.46875, 8,     4.875, 5.375,   6.15625, 1.45312,
+                           2.95312, 5.84375, 8.5,    1.375,   3.6875,  8.25,  4.25,  9.9375,  8.8125,  6.75,
+                           1.10938, 9.5,     7.0625, 7.625,   5.3125,  8.375, 9.75,  2.03125, 2.90625, 7.625,
+                           2.90625, 8.375,   9.5,    1.66406, 3.9375,  2.875, 9.875, 8.25,    4.9375,  10},
+            std::vector<T>{1,       6.59375, 2.125,   2.89062, 5.71875, 5.0625,  9.75,    6,       4.9375,  3.21875,
+                           5.875,   1.85156, 6.28125, 9.875,   1.59375, 3.40625, 7.75,    9.25,    6.46875, 8.75,
+                           6.5,     4.0625,  9.125,   4.4375,  9.25,    5.5625,  2.625,   1.8125,  7.625,   1.875,
+                           1.26562, 6.3125,  3.03125, 7.3125,  3.92188, 2.21875, 4.90625, 2.10938, 3.28125, 6.875,
+                           4.375,   7.25,    3.92188, 3.09375, 8.375,   7.96875, 7.9375,  1.875,   3.125,   10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 7.5, 1.57812, 10, 1.55469, 3.5, 9.0625, 7.5625, 9, 1.30469,
-                6, 7.1875, 2.20312, 9, 5.6875, 2, 5.5625, 5.5625, 6.21875, 3.09375,
-                3.82812, 7.28125, 9, 1.625, 6.78125, 9.875, 5.46875, 4.1875, 3.84375, 2.21875,
-                1.57812, 9.125, 6, 6, 9.5, 2.28125, 8.375, 9.875, 2.32812, 5.96875,
-                1.42969, 4.5625, 1.10156, 5.4375, 8.25, 1.625, 6.875, 4.6875, 6.15625, 6.15625,
-                8.625, 4.125, 6.1875, 1.375, 6.1875, 8.875, 6, 3.40625, 1.75781, 4.8125,
-                1.40625, 4.21875, 4, 6.4375, 6.5625, 4.1875, 8.25, 7.40625, 2.40625, 7,
-                5.5625, 7.9375, 7.625, 4.75, 7, 1.625, 9.25, 7, 7, 2.5,
-                5.9375, 7.1875, 6.875, 5.84375, 7.5625, 6.5, 2.09375, 6.0625, 2.4375, 3.34375,
-                3.76562, 2.1875, 3.51562, 5.875, 2.54688, 8.3125, 9.125, 2.96875, 1.9375, 3.76562,
-                4.1875, 6.28125, 4.84375, 7.5, 3.78125, 5.375, 2.84375, 8.5, 3.3125, 8.1875,
-                4.21875, 6.375, 8.375, 1.46875, 6.625, 6.5625, 9.0625, 2.90625, 9.4375, 5.375,
-                1.32812, 5.9375, 8.9375, 4.4375, 7.5625, 8.9375, 5.28125, 2.59375, 8.375, 5.15625,
-                6.8125, 9.25, 5.3125, 4.375, 1.46875, 7.5625, 8.3125, 2.82812, 7.25, 7.03125,
-                3.3125, 3.03125, 8.5, 3.21875, 8.875, 7, 9.6875, 5.28125, 3.65625, 1.8125,
-                2.5, 4.0625, 6.15625, 8, 5.1875, 2.45312, 6.1875, 1.375, 7.9375, 7.1875,
-                9.625, 7.5, 7.84375, 7.40625, 9.75, 7.09375, 2.0625, 1.5, 6.53125, 5,
-                9.875, 6.6875, 5.875, 6.8125, 5.53125, 9.25, 4.0625, 4.1875, 1.46875, 5,
-                8.6875, 3.70312, 1.85938, 1.21094, 2.71875, 1.82812, 9, 2.71875, 9.9375, 7.8125,
-                4.3125, 8.8125, 2.8125, 3.23438, 4.375, 4.1875, 8.375, 8.75, 6.625, 5.34375,
-                7.1875, 3.45312, 7.0625, 8.5, 5.8125, 4.875, 8.875, 3.5625, 3.84375, 6.1875,
-                3.90625, 4.9375, 4.5625, 6.625, 2.59375, 9.875, 2.90625, 1.82031, 1.25781, 6,
-                9.25, 4.09375, 9.125, 2.5625, 5.25, 2.34375, 5.90625, 7.90625, 9.75, 6.875,
-                7.3125, 1.14062, 9.125, 7.75, 5.5625, 2.8125, 1.32812, 7.5625, 9, 7.125,
-                8.625, 4.4375, 8.375, 6.375, 6.6875, 3.82812, 5.1875, 7.8125, 3.28125, 1.17188,
-                7.125, 8.9375, 6.6875, 5.4375, 6.21875, 4.125, 1.40625, 3.51562, 3.5, 3.0625,
-                1.03906, 7.28125, 2.64062, 8.125, 4.4375, 5.25, 1.75, 1.96875, 7.9375, 4.46875,
-                6.25, 8.75, 1.80469, 3.375, 2.4375, 8.9375, 4.1875, 4.1875, 7.15625, 6.65625,
-                8.375, 1.13281, 7.3125, 7.375, 3.3125, 1.36719, 7.40625, 6.375, 7.875, 4,
-                8.5, 8.5, 6.1875, 2.3125, 6.5625, 6.25, 7.03125, 7.625, 5.1875, 6.71875,
-                4.125, 7.4375, 1.09375, 5, 4.90625, 5.5625, 10, 8.0625, 2.625, 1.21875,
-                7.46875, 3.125, 4.0625, 8.3125, 1.11719, 5.40625, 4.96875, 1.35156, 2.04688, 2.5,
-                3.8125, 6.125, 3.78125, 2.82812, 8.9375, 6.90625, 3.6875, 1.95312, 9.8125, 7.25,
-                4.125, 4.875, 1.54688, 6.40625, 2.57812, 6.46875, 5.34375, 7.8125, 9.9375, 5.5625,
-                2.625, 7.1875, 8.375, 9.75, 1.67188, 3, 6.96875, 6, 1.53125, 2.09375,
-                6.15625, 5.3125, 7.25, 7.3125, 3.625, 1.10938, 7.53125, 1.375, 7.84375, 7.96875,
-                9.875, 9.8125, 5.78125, 7.9375, 4.3125, 8.0625, 7.8125, 6.5625, 2.21875, 4.0625,
-                3.1875, 4.75, 8.25, 6.125, 3.03125, 6.1875, 4.125, 7.71875, 4.4375, 1.46875,
-                4.40625, 6.375, 4.375, 1.48438, 2.65625, 1.80469, 7.5, 9.875, 7.25, 7.875,
-                8.1875, 5.4375, 2.70312, 3.39062, 2.23438, 2.5625, 9.875, 1.76562, 3.3125, 10},
-            std::vector<T>{
-                1, 6.125, 4.53125, 4.4375, 6.3125, 6.6875, 5.375, 8.25, 9.875, 9.375,
-                9.0625, 5.9375, 3.0625, 6.75, 9.75, 8.8125, 3.5, 2.40625, 7.625, 2.21875,
-                2.39062, 9.25, 6.1875, 4.0625, 6.25, 5.375, 8.25, 7.3125, 6.5, 7.8125,
-                2.65625, 2.10938, 8.375, 7.65625, 4.09375, 2.71875, 9.4375, 7.0625, 6.5625, 8.625,
-                7.625, 8.25, 2.10938, 8.625, 8.125, 7.40625, 4.5, 2.76562, 5.125, 9.625,
-                8.5625, 8.75, 7.46875, 9.625, 8.875, 4.40625, 2.26562, 9.3125, 1.67188, 9.1875,
-                6.1875, 4.78125, 5.5, 6.40625, 5.59375, 8.125, 7.65625, 1.75, 2.96875, 3.875,
-                8.75, 1.99219, 3.53125, 2.53125, 9.375, 2.1875, 2.875, 1.86719, 9.25, 7.125,
-                3.89062, 9.5, 1.92188, 5.4375, 4.5625, 1, 8, 3.96875, 9.375, 9.1875,
-                1.19531, 6.875, 3.21875, 8.5625, 7.0625, 8.6875, 9.875, 4.65625, 9.5, 6.25,
-                1.82812, 1.51562, 2.42188, 4.21875, 2.78125, 7.75, 4.96875, 3.89062, 2.76562, 9.25,
-                5.84375, 5.84375, 8.375, 3.34375, 9.875, 2.625, 2.15625, 1.73438, 6.25, 8.875,
-                4.0625, 7.8125, 4.625, 7.59375, 7.625, 2.71875, 4.25, 3.96875, 2, 2.9375,
-                6.25, 7.3125, 7.09375, 7.1875, 7.40625, 1.13281, 9.625, 5.90625, 9.9375, 1.0625,
-                2.10938, 9.5, 6.25, 5.1875, 3.3125, 9.4375, 6.84375, 8.25, 4.375, 4.59375,
-                1.79688, 9, 7.9375, 2.64062, 9.75, 8.75, 9.6875, 3.59375, 4, 10,
-                8.875, 2.82812, 9.0625, 8.8125, 1.76562, 2.23438, 6.625, 2.375, 3.70312, 8.375,
-                8.625, 4, 6.1875, 9.8125, 2.625, 2.60938, 9.375, 1.625, 2.03125, 9.5,
-                1.84375, 9.125, 7.75, 4.75, 2.0625, 2.375, 6.03125, 5.65625, 3.92188, 4.125,
-                9.625, 4.25, 5.4375, 1.34375, 5.1875, 7.53125, 3.96875, 4.875, 1.65625, 3.54688,
-                1.64062, 4.625, 1.51562, 4.4375, 4.375, 5.1875, 1.03906, 1.58594, 9.75, 2.78125,
-                1.27344, 6.25, 6.4375, 9.5625, 4.625, 3.89062, 8.875, 5.875, 9.875, 4,
-                9.625, 8.1875, 6, 6.5625, 3.1875, 5.9375, 1.17188, 6.375, 3.09375, 3.5,
-                5.34375, 6.625, 9.6875, 1.85938, 2.85938, 9.75, 5.5, 7.6875, 1.86719, 1.03125,
-                7.21875, 7.125, 7.75, 6.1875, 2, 2.59375, 2.46875, 8.25, 7.78125, 3.75,
-                7.875, 4.6875, 8.0625, 7.9375, 2.53125, 6.5, 2.48438, 6.75, 2.60938, 1.60938,
-                7.75, 2.28125, 8.75, 7.6875, 8.25, 8.0625, 1.23438, 6.0625, 1.53125, 6.96875,
-                4.9375, 5.21875, 1.5, 5.125, 7.5, 7.1875, 6, 2.71875, 6.5625, 9.875,
-                2.15625, 4.40625, 5.5, 3.98438, 5.5625, 8.875, 1.84375, 8.75, 8.875, 9.6875,
-                8.8125, 2.78125, 1.16406, 6.03125, 7.625, 2.73438, 6.5, 5.6875, 9.75, 8.125,
-                6.875, 7.34375, 9, 5.0625, 6.1875, 3.95312, 4.5, 2.35938, 4.6875, 9.875,
-                1.09375, 6.09375, 4, 9.75, 8.5, 1.70312, 6.9375, 1.29688, 5.6875, 7.8125,
-                9.625, 3.125, 7.1875, 6.6875, 7.84375, 1.21094, 1.71094, 5.875, 3.4375, 5.8125,
-                4.25, 4.125, 7.875, 5.1875, 9.3125, 9, 4.4375, 1.0625, 3.01562, 5.25,
-                3.09375, 7.375, 6.1875, 3.4375, 6.46875, 9.375, 5.625, 4.8125, 8.1875, 2.03125,
-                8.75, 4.21875, 9.25, 8.3125, 1.1875, 3.0625, 1.6875, 3.375, 5.09375, 1.95312,
-                1.25, 3.76562, 7.75, 5.09375, 6.1875, 4.625, 4.625, 1.49219, 4.96875, 9.875,
-                2, 9, 4.46875, 7.25, 1.36719, 7.9375, 1.79688, 3, 7.5625, 2.625,
-                7.5625, 1.92969, 2.32812, 3.25, 4.375, 1.125, 7.75, 2.4375, 3.34375, 5.6875,
-                1.30469, 7.9375, 8.75, 3.625, 6.3125, 6.75, 1.73438, 2.5, 3.09375, 10},
-            std::vector<T>{
-                1, 7.25, 1.08594, 1.90625, 7.3125, 8.1875, 1.84375, 9.8125, 3.65625, 7.6875,
-                7.03125, 6.75, 9.875, 9, 2.28125, 4.625, 8.375, 8.125, 4.25, 9.9375,
-                2.125, 1.92969, 1.35938, 7.625, 5.6875, 2.65625, 6.9375, 8.0625, 2.53125, 7.375,
-                2.8125, 9.1875, 7.3125, 8.75, 7.15625, 7.15625, 3.8125, 6.75, 3.53125, 10},
-            std::vector<T>{
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094},
-            std::vector<T>{
-                0.523438, 0.667969, 0.632812, 0.65625, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625,
+                1,       7.5,     1.57812, 10,      1.55469, 3.5,     9.0625,  7.5625,  9,       1.30469, 6,
+                7.1875,  2.20312, 9,       5.6875,  2,       5.5625,  5.5625,  6.21875, 3.09375, 3.82812, 7.28125,
+                9,       1.625,   6.78125, 9.875,   5.46875, 4.1875,  3.84375, 2.21875, 1.57812, 9.125,   6,
+                6,       9.5,     2.28125, 8.375,   9.875,   2.32812, 5.96875, 1.42969, 4.5625,  1.10156, 5.4375,
+                8.25,    1.625,   6.875,   4.6875,  6.15625, 6.15625, 8.625,   4.125,   6.1875,  1.375,   6.1875,
+                8.875,   6,       3.40625, 1.75781, 4.8125,  1.40625, 4.21875, 4,       6.4375,  6.5625,  4.1875,
+                8.25,    7.40625, 2.40625, 7,       5.5625,  7.9375,  7.625,   4.75,    7,       1.625,   9.25,
+                7,       7,       2.5,     5.9375,  7.1875,  6.875,   5.84375, 7.5625,  6.5,     2.09375, 6.0625,
+                2.4375,  3.34375, 3.76562, 2.1875,  3.51562, 5.875,   2.54688, 8.3125,  9.125,   2.96875, 1.9375,
+                3.76562, 4.1875,  6.28125, 4.84375, 7.5,     3.78125, 5.375,   2.84375, 8.5,     3.3125,  8.1875,
+                4.21875, 6.375,   8.375,   1.46875, 6.625,   6.5625,  9.0625,  2.90625, 9.4375,  5.375,   1.32812,
+                5.9375,  8.9375,  4.4375,  7.5625,  8.9375,  5.28125, 2.59375, 8.375,   5.15625, 6.8125,  9.25,
+                5.3125,  4.375,   1.46875, 7.5625,  8.3125,  2.82812, 7.25,    7.03125, 3.3125,  3.03125, 8.5,
+                3.21875, 8.875,   7,       9.6875,  5.28125, 3.65625, 1.8125,  2.5,     4.0625,  6.15625, 8,
+                5.1875,  2.45312, 6.1875,  1.375,   7.9375,  7.1875,  9.625,   7.5,     7.84375, 7.40625, 9.75,
+                7.09375, 2.0625,  1.5,     6.53125, 5,       9.875,   6.6875,  5.875,   6.8125,  5.53125, 9.25,
+                4.0625,  4.1875,  1.46875, 5,       8.6875,  3.70312, 1.85938, 1.21094, 2.71875, 1.82812, 9,
+                2.71875, 9.9375,  7.8125,  4.3125,  8.8125,  2.8125,  3.23438, 4.375,   4.1875,  8.375,   8.75,
+                6.625,   5.34375, 7.1875,  3.45312, 7.0625,  8.5,     5.8125,  4.875,   8.875,   3.5625,  3.84375,
+                6.1875,  3.90625, 4.9375,  4.5625,  6.625,   2.59375, 9.875,   2.90625, 1.82031, 1.25781, 6,
+                9.25,    4.09375, 9.125,   2.5625,  5.25,    2.34375, 5.90625, 7.90625, 9.75,    6.875,   7.3125,
+                1.14062, 9.125,   7.75,    5.5625,  2.8125,  1.32812, 7.5625,  9,       7.125,   8.625,   4.4375,
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+                           2.8125,  9.1875,  7.3125,  8.75,    7.15625, 7.15625, 3.8125,  6.75,   3.53125, 10},
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+                           0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094},
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-                1.21875, 1.29688, 1.24219, 1.32031, 1.25781, 1.22656, 1.28125, 1.22656, 1.25, 1.3125,
-                1.26562, 1.32031, 1.25781, 1.24219, 1.34375, 1.32812, 1.32812, 1.21875, 1.25, 1.375}),
+                0.617188, 0.601562, 0.632812, 0.601562, 0.632812, 0.617188, 0.578125, 0.570312, 0.625,    0.570312,
+                0.601562, 0.585938, 0.617188, 0.585938, 0.617188, 0.601562, 0.570312, 0.5625,   0.609375, 0.5625,
+                0.59375,  0.578125, 0.601562, 0.578125, 0.601562, 0.585938, 0.570312, 0.5625,   0.59375,  0.5625,
+                0.585938, 0.570312, 0.59375,  0.570312, 0.59375,  0.578125, 0.5625,   0.5625,   0.585938, 0.5625,
+                0.570312, 0.570312, 0.585938, 0.570312, 0.585938, 0.570312, 0.5625,   0.554688, 0.578125, 0.554688,
+                0.5625,   0.667969, 0.65625,  0.667969, 0.664062, 0.632812, 0.667969, 0.632812, 0.65625,  0.667969,
+                0.5625,   0.664062, 0.640625, 0.667969, 0.65625,  0.617188, 0.664062, 0.617188, 0.648438, 0.667969,
+                0.5625,   0.664062, 0.625,    0.664062, 0.640625, 0.601562, 0.65625,  0.601562, 0.632812, 0.664062,
+                0.554688, 0.648438, 0.609375, 0.65625,  0.625,    0.59375,  0.640625, 0.585938, 0.617188, 0.65625,
+                0.554688, 0.632812, 0.59375,  0.640625, 0.609375, 0.585938, 0.625,    0.578125, 0.601562, 0.640625,
+                0.554688, 0.617188, 0.585938, 0.625,    0.59375,  0.570312, 0.609375, 0.570312, 0.585938, 0.625,
+                0.554688, 0.601562, 0.578125, 0.609375, 0.585938, 0.570312, 0.59375,  0.570312, 0.578125, 0.609375,
+                0.554688, 0.585938, 0.570312, 0.59375,  0.578125, 0.5625,   0.585938, 0.5625,   0.570312, 0.59375,
+                0.554688, 0.578125, 0.570312, 0.585938, 0.570312, 0.5625,   0.578125, 0.5625,   0.570312, 0.585938,
+                0.554688, 0.570312, 0.5625,   0.578125, 0.570312, 0.5625,   0.570312, 0.5625,   0.5625,   0.578125,
+                0.664062, 0.667969, 0.664062, 0.65625,  0.667969, 0.667969, 0.667969, 0.617188, 0.65625,  0.667969,
+                0.65625,  0.667969, 0.65625,  0.648438, 0.667969, 0.667969, 0.667969, 0.601562, 0.648438, 0.667969,
+                0.648438, 0.664062, 0.640625, 0.625,    0.664062, 0.664062, 0.664062, 0.59375,  0.632812, 0.667969,
+                0.632812, 0.65625,  0.625,    0.609375, 0.65625,  0.65625,  0.65625,  0.585938, 0.617188, 0.664062,
+                0.617188, 0.640625, 0.609375, 0.59375,  0.648438, 0.648438, 0.648438, 0.570312, 0.601562, 0.65625,
+                0.601562, 0.625,    0.59375,  0.585938, 0.632812, 0.632812, 0.632812, 0.570312, 0.585938, 0.640625,
+                0.585938, 0.609375, 0.585938, 0.578125, 0.617188, 0.617188, 0.617188, 0.5625,   0.578125, 0.625,
+                0.578125, 0.59375,  0.578125, 0.570312, 0.601562, 0.601562, 0.601562, 0.5625,   0.570312, 0.609375,
+                0.570312, 0.585938, 0.570312, 0.570312, 0.585938, 0.585938, 0.585938, 0.5625,   0.570312, 0.59375,
+                0.570312, 0.578125, 0.570312, 0.5625,   0.578125, 0.578125, 0.578125, 0.554688, 0.5625,   0.585938},
+            std::vector<T>{0.554688, 0.570312, 0.5625,   0.5625,   0.570312, 0.570312, 0.585938, 0.570312, 0.570312,
+                           0.5625,   0.570312, 0.554688, 0.570312, 0.585938, 0.554688, 0.5625,   0.578125, 0.585938,
+                           0.570312, 0.578125, 0.570312, 0.570312, 0.585938, 0.570312, 0.585938, 0.570312, 0.5625,
+                           0.554688, 0.578125, 0.554688, 0.554688, 0.570312, 0.5625,   0.578125, 0.570312, 0.5625,
+                           0.570312, 0.5625,   0.5625,   0.578125, 0.570312, 0.578125, 0.570312, 0.5625,   0.578125,
+                           0.578125, 0.578125, 0.554688, 0.5625,   0.585938},
+            std::vector<T>{1.20312, 1.30469, 1.22656, 1.24219, 1.28906, 1.28125, 1.35938, 1.29688, 1.28125, 1.25,
+                           1.28906, 1.21875, 1.29688, 1.375,   1.21875, 1.25,    1.32812, 1.35156, 1.30469, 1.34375,
+                           1.30469, 1.26562, 1.35156, 1.26562, 1.35156, 1.28906, 1.23438, 1.21875, 1.32031, 1.21875,
+                           1.21875, 1.29688, 1.24219, 1.32031, 1.25781, 1.22656, 1.28125, 1.22656, 1.25,    1.3125,
+                           1.26562, 1.32031, 1.25781, 1.24219, 1.34375, 1.32812, 1.32812, 1.21875, 1.25,    1.375}),
         LSTMSequenceV1Params(
-            5, 10, 10, 10,
-            0.7f, false, op::RecurrentSequenceDirection::REVERSE,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            false,
+            op::RecurrentSequenceDirection::REVERSE,
             ET,
             std::vector<T>{
-                1, 9.375, 9, 3.84375, 2.17188, 2.65625, 1.35938, 2.84375, 8.4375, 6.125,
-                5.78125, 6.375, 9.625, 9.625, 5.15625, 6.875, 9.3125, 7.75, 4.375, 6.875,
-                2.39062, 7.71875, 9, 9.625, 1.23438, 1.07812, 3.625, 1.95312, 4.5625, 3.6875,
-                8.25, 6.90625, 6.625, 8.25, 9.125, 8.875, 6, 9.625, 8.5, 7.5,
-                1.45312, 6.78125, 8.25, 7.4375, 9.375, 5.1875, 4.25, 3.9375, 7.1875, 4.9375,
-                2.15625, 7.5625, 8.5, 9.9375, 3.85938, 7.0625, 7.625, 8.125, 6.375, 2.53125,
-                4.25, 1.23438, 8.125, 8.1875, 7.28125, 9.125, 8.375, 1.21875, 9.125, 5.4375,
-                8.5, 5.75, 9.1875, 6.375, 9.75, 1.46875, 6.875, 9, 8.25, 7.5625,
-                1.92188, 8.375, 3.125, 5.5, 4.40625, 8.25, 7.28125, 1.85938, 5.375, 2.96875,
-                4.75, 3.32812, 6.75, 5.1875, 7.8125, 5.125, 6, 7.375, 7.25, 2.59375,
-                9.25, 5.78125, 1.21875, 2.5, 8.5, 7.90625, 4.4375, 9.375, 3.6875, 6.5,
-                1.05469, 2.34375, 4.9375, 5.40625, 7.625, 4.375, 4.375, 8.625, 5.4375, 9.1875,
-                1.125, 4.4375, 3.25, 3.84375, 4.125, 6.125, 8.125, 2.6875, 9.4375, 2.125,
-                1.90625, 7.1875, 7.625, 8.1875, 9.75, 6.15625, 7.34375, 9.75, 9.5625, 6.6875,
-                9.375, 9, 4.6875, 5.4375, 4.03125, 4.15625, 7.9375, 7.4375, 4, 5.53125,
-                1.74219, 3.03125, 9.0625, 3.20312, 8.0625, 8.125, 7.4375, 5.4375, 5, 9.25,
-                7.75, 9.5, 6.90625, 5.8125, 4.25, 3.26562, 4.375, 7.5, 6.84375, 4.3125,
-                1.5, 5.5, 1.70312, 3.03125, 1.82812, 4.1875, 8.25, 6.84375, 1.58594, 3.8125,
-                3.01562, 7.90625, 2.375, 8, 7.125, 8.625, 2.125, 9.5, 3.3125, 1.96875,
-                4.9375, 9.1875, 1.98438, 4, 3.82812, 8.375, 4.15625, 9.0625, 7.84375, 1.38281,
-                1.89062, 2.75, 9.375, 3.65625, 3.9375, 6.625, 4.8125, 1.77344, 3.4375, 2.28125,
-                8.0625, 5.625, 5.0625, 7.1875, 1.75, 8.6875, 1.63281, 6.8125, 3.96875, 6.25,
-                2.71875, 7.375, 8.5, 3.26562, 1.55469, 9.125, 6, 4.96875, 6.125, 1.1875,
-                5.15625, 9.625, 9.5, 6.875, 4.09375, 5.625, 8.9375, 7.125, 4.875, 5.375,
-                9.9375, 9.3125, 8.1875, 5.625, 9.5, 1.64844, 4.40625, 6.09375, 4.625, 6.53125,
-                3.57812, 9.5, 5.0625, 4.75, 7.875, 3.375, 6.21875, 1.875, 4.375, 5.375,
-                6.59375, 5.1875, 7.625, 1.26562, 9.25, 7.25, 5.78125, 7.4375, 5.65625, 7.5625,
-                1.92188, 4.71875, 2.09375, 1.13281, 6.78125, 9.125, 5, 8.125, 1.6875, 2.48438,
-                2.375, 3.8125, 1.71875, 6.5, 8.875, 4.25, 2.45312, 2.40625, 9.25, 2.59375,
-                1.03125, 8.75, 8.25, 3.60938, 3.71875, 6.25, 3.1875, 5.0625, 7.90625, 4.6875,
-                7.3125, 8.9375, 9, 7.21875, 9.1875, 3.5, 3.03125, 1.57812, 4.78125, 2.78125,
-                2.5, 9.375, 2.89062, 8.6875, 8.5, 9.5625, 9.25, 1.46875, 7.125, 6.1875,
-                4.6875, 5.3125, 3, 1.19531, 8.5, 4.375, 8, 4.71875, 7.625, 6.4375,
-                8.75, 7.03125, 9.75, 8.5, 4.6875, 8, 6.375, 4.59375, 7.625, 8.125,
-                3.40625, 9, 7.875, 3.35938, 9.375, 9.875, 8.875, 8.625, 2.03125, 7.5625,
-                9.6875, 4.1875, 3.71875, 8.9375, 6.46875, 8.75, 2.5, 9.625, 8.75, 1,
-                7.53125, 1.14844, 1.58594, 3.8125, 5.65625, 9.9375, 6.34375, 2.34375, 5.125, 2.5,
-                6.3125, 7.8125, 3.875, 1.625, 8.375, 7.34375, 1.82812, 5.21875, 2.59375, 1.09375,
-                2.98438, 7.96875, 5.25, 8.125, 9.25, 2.34375, 9.875, 1.21094, 6.4375, 7.84375,
-                9.25, 3, 4.3125, 3.35938, 1.0625, 5.125, 6.875, 3.25, 2.5, 6.125,
-                5.4375, 8.625, 8.125, 4.375, 8.375, 4.875, 4.3125, 8.5, 2.15625, 4.3125,
-                2.78125, 1.35938, 1.1875, 6, 6.6875, 5.0625, 5.3125, 7.5, 2.90625, 4.375,
-                3.375, 8.5625, 2.6875, 5.21875, 9, 6.0625, 7.4375, 6.9375, 1.60938, 5.15625,
-                3.20312, 6.625, 9.25, 3, 2.84375, 7.59375, 5.1875, 4.4375, 7.875, 2.75,
-                5.78125, 3.4375, 5.9375, 3.25, 3.10938, 2.375, 3.46875, 7.9375, 1.14844, 3.29688,
-                4.8125, 2.14062, 1.42188, 7, 1.53125, 4.6875, 3.875, 7, 5, 6.9375,
-                2.51562, 3.75, 3.71875, 2.8125, 5.03125, 3, 5.25, 2.07812, 7.3125, 1.32812,
-                7.3125, 1.30469, 6.3125, 3.0625, 9.75, 3.0625, 6.9375, 6.625, 8.875, 9,
-                4.71875, 8, 8.125, 7.5, 2.23438, 3.78125, 3.34375, 4.25, 3.03125, 2.75,
-                5.78125, 9.375, 7.25, 6.0625, 3.1875, 8.375, 2.75, 4.125, 8.125, 10},
-            std::vector<T>{
-                1, 9.1875, 5.5625, 6.625, 2.65625, 8.125, 8.25, 4.875, 9.4375, 5.875,
-                1.26562, 4.71875, 8.0625, 1.76562, 2.46875, 8, 4.875, 5.375, 6.15625, 1.45312,
-                2.95312, 5.84375, 8.5, 1.375, 3.6875, 8.25, 4.25, 9.9375, 8.8125, 6.75,
-                1.10938, 9.5, 7.0625, 7.625, 5.3125, 8.375, 9.75, 2.03125, 2.90625, 7.625,
-                2.90625, 8.375, 9.5, 1.66406, 3.9375, 2.875, 9.875, 8.25, 4.9375, 10},
-            std::vector<T>{
-                1, 6.59375, 2.125, 2.89062, 5.71875, 5.0625, 9.75, 6, 4.9375, 3.21875,
-                5.875, 1.85156, 6.28125, 9.875, 1.59375, 3.40625, 7.75, 9.25, 6.46875, 8.75,
-                6.5, 4.0625, 9.125, 4.4375, 9.25, 5.5625, 2.625, 1.8125, 7.625, 1.875,
-                1.26562, 6.3125, 3.03125, 7.3125, 3.92188, 2.21875, 4.90625, 2.10938, 3.28125, 6.875,
-                4.375, 7.25, 3.92188, 3.09375, 8.375, 7.96875, 7.9375, 1.875, 3.125, 10},
+                1,       9.375,   9,       3.84375, 2.17188, 2.65625, 1.35938, 2.84375, 8.4375,  6.125,   5.78125,
+                6.375,   9.625,   9.625,   5.15625, 6.875,   9.3125,  7.75,    4.375,   6.875,   2.39062, 7.71875,
+                9,       9.625,   1.23438, 1.07812, 3.625,   1.95312, 4.5625,  3.6875,  8.25,    6.90625, 6.625,
+                8.25,    9.125,   8.875,   6,       9.625,   8.5,     7.5,     1.45312, 6.78125, 8.25,    7.4375,
+                9.375,   5.1875,  4.25,    3.9375,  7.1875,  4.9375,  2.15625, 7.5625,  8.5,     9.9375,  3.85938,
+                7.0625,  7.625,   8.125,   6.375,   2.53125, 4.25,    1.23438, 8.125,   8.1875,  7.28125, 9.125,
+                8.375,   1.21875, 9.125,   5.4375,  8.5,     5.75,    9.1875,  6.375,   9.75,    1.46875, 6.875,
+                9,       8.25,    7.5625,  1.92188, 8.375,   3.125,   5.5,     4.40625, 8.25,    7.28125, 1.85938,
+                5.375,   2.96875, 4.75,    3.32812, 6.75,    5.1875,  7.8125,  5.125,   6,       7.375,   7.25,
+                2.59375, 9.25,    5.78125, 1.21875, 2.5,     8.5,     7.90625, 4.4375,  9.375,   3.6875,  6.5,
+                1.05469, 2.34375, 4.9375,  5.40625, 7.625,   4.375,   4.375,   8.625,   5.4375,  9.1875,  1.125,
+                4.4375,  3.25,    3.84375, 4.125,   6.125,   8.125,   2.6875,  9.4375,  2.125,   1.90625, 7.1875,
+                7.625,   8.1875,  9.75,    6.15625, 7.34375, 9.75,    9.5625,  6.6875,  9.375,   9,       4.6875,
+                5.4375,  4.03125, 4.15625, 7.9375,  7.4375,  4,       5.53125, 1.74219, 3.03125, 9.0625,  3.20312,
+                8.0625,  8.125,   7.4375,  5.4375,  5,       9.25,    7.75,    9.5,     6.90625, 5.8125,  4.25,
+                3.26562, 4.375,   7.5,     6.84375, 4.3125,  1.5,     5.5,     1.70312, 3.03125, 1.82812, 4.1875,
+                8.25,    6.84375, 1.58594, 3.8125,  3.01562, 7.90625, 2.375,   8,       7.125,   8.625,   2.125,
+                9.5,     3.3125,  1.96875, 4.9375,  9.1875,  1.98438, 4,       3.82812, 8.375,   4.15625, 9.0625,
+                7.84375, 1.38281, 1.89062, 2.75,    9.375,   3.65625, 3.9375,  6.625,   4.8125,  1.77344, 3.4375,
+                2.28125, 8.0625,  5.625,   5.0625,  7.1875,  1.75,    8.6875,  1.63281, 6.8125,  3.96875, 6.25,
+                2.71875, 7.375,   8.5,     3.26562, 1.55469, 9.125,   6,       4.96875, 6.125,   1.1875,  5.15625,
+                9.625,   9.5,     6.875,   4.09375, 5.625,   8.9375,  7.125,   4.875,   5.375,   9.9375,  9.3125,
+                8.1875,  5.625,   9.5,     1.64844, 4.40625, 6.09375, 4.625,   6.53125, 3.57812, 9.5,     5.0625,
+                4.75,    7.875,   3.375,   6.21875, 1.875,   4.375,   5.375,   6.59375, 5.1875,  7.625,   1.26562,
+                9.25,    7.25,    5.78125, 7.4375,  5.65625, 7.5625,  1.92188, 4.71875, 2.09375, 1.13281, 6.78125,
+                9.125,   5,       8.125,   1.6875,  2.48438, 2.375,   3.8125,  1.71875, 6.5,     8.875,   4.25,
+                2.45312, 2.40625, 9.25,    2.59375, 1.03125, 8.75,    8.25,    3.60938, 3.71875, 6.25,    3.1875,
+                5.0625,  7.90625, 4.6875,  7.3125,  8.9375,  9,       7.21875, 9.1875,  3.5,     3.03125, 1.57812,
+                4.78125, 2.78125, 2.5,     9.375,   2.89062, 8.6875,  8.5,     9.5625,  9.25,    1.46875, 7.125,
+                6.1875,  4.6875,  5.3125,  3,       1.19531, 8.5,     4.375,   8,       4.71875, 7.625,   6.4375,
+                8.75,    7.03125, 9.75,    8.5,     4.6875,  8,       6.375,   4.59375, 7.625,   8.125,   3.40625,
+                9,       7.875,   3.35938, 9.375,   9.875,   8.875,   8.625,   2.03125, 7.5625,  9.6875,  4.1875,
+                3.71875, 8.9375,  6.46875, 8.75,    2.5,     9.625,   8.75,    1,       7.53125, 1.14844, 1.58594,
+                3.8125,  5.65625, 9.9375,  6.34375, 2.34375, 5.125,   2.5,     6.3125,  7.8125,  3.875,   1.625,
+                8.375,   7.34375, 1.82812, 5.21875, 2.59375, 1.09375, 2.98438, 7.96875, 5.25,    8.125,   9.25,
+                2.34375, 9.875,   1.21094, 6.4375,  7.84375, 9.25,    3,       4.3125,  3.35938, 1.0625,  5.125,
+                6.875,   3.25,    2.5,     6.125,   5.4375,  8.625,   8.125,   4.375,   8.375,   4.875,   4.3125,
+                8.5,     2.15625, 4.3125,  2.78125, 1.35938, 1.1875,  6,       6.6875,  5.0625,  5.3125,  7.5,
+                2.90625, 4.375,   3.375,   8.5625,  2.6875,  5.21875, 9,       6.0625,  7.4375,  6.9375,  1.60938,
+                5.15625, 3.20312, 6.625,   9.25,    3,       2.84375, 7.59375, 5.1875,  4.4375,  7.875,   2.75,
+                5.78125, 3.4375,  5.9375,  3.25,    3.10938, 2.375,   3.46875, 7.9375,  1.14844, 3.29688, 4.8125,
+                2.14062, 1.42188, 7,       1.53125, 4.6875,  3.875,   7,       5,       6.9375,  2.51562, 3.75,
+                3.71875, 2.8125,  5.03125, 3,       5.25,    2.07812, 7.3125,  1.32812, 7.3125,  1.30469, 6.3125,
+                3.0625,  9.75,    3.0625,  6.9375,  6.625,   8.875,   9,       4.71875, 8,       8.125,   7.5,
+                2.23438, 3.78125, 3.34375, 4.25,    3.03125, 2.75,    5.78125, 9.375,   7.25,    6.0625,  3.1875,
+                8.375,   2.75,    4.125,   8.125,   10},
+            std::vector<T>{1,       9.1875,  5.5625, 6.625,   2.65625, 8.125, 8.25,  4.875,   9.4375,  5.875,
+                           1.26562, 4.71875, 8.0625, 1.76562, 2.46875, 8,     4.875, 5.375,   6.15625, 1.45312,
+                           2.95312, 5.84375, 8.5,    1.375,   3.6875,  8.25,  4.25,  9.9375,  8.8125,  6.75,
+                           1.10938, 9.5,     7.0625, 7.625,   5.3125,  8.375, 9.75,  2.03125, 2.90625, 7.625,
+                           2.90625, 8.375,   9.5,    1.66406, 3.9375,  2.875, 9.875, 8.25,    4.9375,  10},
+            std::vector<T>{1,       6.59375, 2.125,   2.89062, 5.71875, 5.0625,  9.75,    6,       4.9375,  3.21875,
+                           5.875,   1.85156, 6.28125, 9.875,   1.59375, 3.40625, 7.75,    9.25,    6.46875, 8.75,
+                           6.5,     4.0625,  9.125,   4.4375,  9.25,    5.5625,  2.625,   1.8125,  7.625,   1.875,
+                           1.26562, 6.3125,  3.03125, 7.3125,  3.92188, 2.21875, 4.90625, 2.10938, 3.28125, 6.875,
+                           4.375,   7.25,    3.92188, 3.09375, 8.375,   7.96875, 7.9375,  1.875,   3.125,   10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 7.5, 1.57812, 10, 1.55469, 3.5, 9.0625, 7.5625, 9, 1.30469,
-                6, 7.1875, 2.20312, 9, 5.6875, 2, 5.5625, 5.5625, 6.21875, 3.09375,
-                3.82812, 7.28125, 9, 1.625, 6.78125, 9.875, 5.46875, 4.1875, 3.84375, 2.21875,
-                1.57812, 9.125, 6, 6, 9.5, 2.28125, 8.375, 9.875, 2.32812, 5.96875,
-                1.42969, 4.5625, 1.10156, 5.4375, 8.25, 1.625, 6.875, 4.6875, 6.15625, 6.15625,
-                8.625, 4.125, 6.1875, 1.375, 6.1875, 8.875, 6, 3.40625, 1.75781, 4.8125,
-                1.40625, 4.21875, 4, 6.4375, 6.5625, 4.1875, 8.25, 7.40625, 2.40625, 7,
-                5.5625, 7.9375, 7.625, 4.75, 7, 1.625, 9.25, 7, 7, 2.5,
-                5.9375, 7.1875, 6.875, 5.84375, 7.5625, 6.5, 2.09375, 6.0625, 2.4375, 3.34375,
-                3.76562, 2.1875, 3.51562, 5.875, 2.54688, 8.3125, 9.125, 2.96875, 1.9375, 3.76562,
-                4.1875, 6.28125, 4.84375, 7.5, 3.78125, 5.375, 2.84375, 8.5, 3.3125, 8.1875,
-                4.21875, 6.375, 8.375, 1.46875, 6.625, 6.5625, 9.0625, 2.90625, 9.4375, 5.375,
-                1.32812, 5.9375, 8.9375, 4.4375, 7.5625, 8.9375, 5.28125, 2.59375, 8.375, 5.15625,
-                6.8125, 9.25, 5.3125, 4.375, 1.46875, 7.5625, 8.3125, 2.82812, 7.25, 7.03125,
-                3.3125, 3.03125, 8.5, 3.21875, 8.875, 7, 9.6875, 5.28125, 3.65625, 1.8125,
-                2.5, 4.0625, 6.15625, 8, 5.1875, 2.45312, 6.1875, 1.375, 7.9375, 7.1875,
-                9.625, 7.5, 7.84375, 7.40625, 9.75, 7.09375, 2.0625, 1.5, 6.53125, 5,
-                9.875, 6.6875, 5.875, 6.8125, 5.53125, 9.25, 4.0625, 4.1875, 1.46875, 5,
-                8.6875, 3.70312, 1.85938, 1.21094, 2.71875, 1.82812, 9, 2.71875, 9.9375, 7.8125,
-                4.3125, 8.8125, 2.8125, 3.23438, 4.375, 4.1875, 8.375, 8.75, 6.625, 5.34375,
-                7.1875, 3.45312, 7.0625, 8.5, 5.8125, 4.875, 8.875, 3.5625, 3.84375, 6.1875,
-                3.90625, 4.9375, 4.5625, 6.625, 2.59375, 9.875, 2.90625, 1.82031, 1.25781, 6,
-                9.25, 4.09375, 9.125, 2.5625, 5.25, 2.34375, 5.90625, 7.90625, 9.75, 6.875,
-                7.3125, 1.14062, 9.125, 7.75, 5.5625, 2.8125, 1.32812, 7.5625, 9, 7.125,
-                8.625, 4.4375, 8.375, 6.375, 6.6875, 3.82812, 5.1875, 7.8125, 3.28125, 1.17188,
-                7.125, 8.9375, 6.6875, 5.4375, 6.21875, 4.125, 1.40625, 3.51562, 3.5, 3.0625,
-                1.03906, 7.28125, 2.64062, 8.125, 4.4375, 5.25, 1.75, 1.96875, 7.9375, 4.46875,
-                6.25, 8.75, 1.80469, 3.375, 2.4375, 8.9375, 4.1875, 4.1875, 7.15625, 6.65625,
-                8.375, 1.13281, 7.3125, 7.375, 3.3125, 1.36719, 7.40625, 6.375, 7.875, 4,
-                8.5, 8.5, 6.1875, 2.3125, 6.5625, 6.25, 7.03125, 7.625, 5.1875, 6.71875,
-                4.125, 7.4375, 1.09375, 5, 4.90625, 5.5625, 10, 8.0625, 2.625, 1.21875,
-                7.46875, 3.125, 4.0625, 8.3125, 1.11719, 5.40625, 4.96875, 1.35156, 2.04688, 2.5,
-                3.8125, 6.125, 3.78125, 2.82812, 8.9375, 6.90625, 3.6875, 1.95312, 9.8125, 7.25,
-                4.125, 4.875, 1.54688, 6.40625, 2.57812, 6.46875, 5.34375, 7.8125, 9.9375, 5.5625,
-                2.625, 7.1875, 8.375, 9.75, 1.67188, 3, 6.96875, 6, 1.53125, 2.09375,
-                6.15625, 5.3125, 7.25, 7.3125, 3.625, 1.10938, 7.53125, 1.375, 7.84375, 7.96875,
-                9.875, 9.8125, 5.78125, 7.9375, 4.3125, 8.0625, 7.8125, 6.5625, 2.21875, 4.0625,
-                3.1875, 4.75, 8.25, 6.125, 3.03125, 6.1875, 4.125, 7.71875, 4.4375, 1.46875,
-                4.40625, 6.375, 4.375, 1.48438, 2.65625, 1.80469, 7.5, 9.875, 7.25, 7.875,
-                8.1875, 5.4375, 2.70312, 3.39062, 2.23438, 2.5625, 9.875, 1.76562, 3.3125, 10},
-            std::vector<T>{
-                1, 6.125, 4.53125, 4.4375, 6.3125, 6.6875, 5.375, 8.25, 9.875, 9.375,
-                9.0625, 5.9375, 3.0625, 6.75, 9.75, 8.8125, 3.5, 2.40625, 7.625, 2.21875,
-                2.39062, 9.25, 6.1875, 4.0625, 6.25, 5.375, 8.25, 7.3125, 6.5, 7.8125,
-                2.65625, 2.10938, 8.375, 7.65625, 4.09375, 2.71875, 9.4375, 7.0625, 6.5625, 8.625,
-                7.625, 8.25, 2.10938, 8.625, 8.125, 7.40625, 4.5, 2.76562, 5.125, 9.625,
-                8.5625, 8.75, 7.46875, 9.625, 8.875, 4.40625, 2.26562, 9.3125, 1.67188, 9.1875,
-                6.1875, 4.78125, 5.5, 6.40625, 5.59375, 8.125, 7.65625, 1.75, 2.96875, 3.875,
-                8.75, 1.99219, 3.53125, 2.53125, 9.375, 2.1875, 2.875, 1.86719, 9.25, 7.125,
-                3.89062, 9.5, 1.92188, 5.4375, 4.5625, 1, 8, 3.96875, 9.375, 9.1875,
-                1.19531, 6.875, 3.21875, 8.5625, 7.0625, 8.6875, 9.875, 4.65625, 9.5, 6.25,
-                1.82812, 1.51562, 2.42188, 4.21875, 2.78125, 7.75, 4.96875, 3.89062, 2.76562, 9.25,
-                5.84375, 5.84375, 8.375, 3.34375, 9.875, 2.625, 2.15625, 1.73438, 6.25, 8.875,
-                4.0625, 7.8125, 4.625, 7.59375, 7.625, 2.71875, 4.25, 3.96875, 2, 2.9375,
-                6.25, 7.3125, 7.09375, 7.1875, 7.40625, 1.13281, 9.625, 5.90625, 9.9375, 1.0625,
-                2.10938, 9.5, 6.25, 5.1875, 3.3125, 9.4375, 6.84375, 8.25, 4.375, 4.59375,
-                1.79688, 9, 7.9375, 2.64062, 9.75, 8.75, 9.6875, 3.59375, 4, 10,
-                8.875, 2.82812, 9.0625, 8.8125, 1.76562, 2.23438, 6.625, 2.375, 3.70312, 8.375,
-                8.625, 4, 6.1875, 9.8125, 2.625, 2.60938, 9.375, 1.625, 2.03125, 9.5,
-                1.84375, 9.125, 7.75, 4.75, 2.0625, 2.375, 6.03125, 5.65625, 3.92188, 4.125,
-                9.625, 4.25, 5.4375, 1.34375, 5.1875, 7.53125, 3.96875, 4.875, 1.65625, 3.54688,
-                1.64062, 4.625, 1.51562, 4.4375, 4.375, 5.1875, 1.03906, 1.58594, 9.75, 2.78125,
-                1.27344, 6.25, 6.4375, 9.5625, 4.625, 3.89062, 8.875, 5.875, 9.875, 4,
-                9.625, 8.1875, 6, 6.5625, 3.1875, 5.9375, 1.17188, 6.375, 3.09375, 3.5,
-                5.34375, 6.625, 9.6875, 1.85938, 2.85938, 9.75, 5.5, 7.6875, 1.86719, 1.03125,
-                7.21875, 7.125, 7.75, 6.1875, 2, 2.59375, 2.46875, 8.25, 7.78125, 3.75,
-                7.875, 4.6875, 8.0625, 7.9375, 2.53125, 6.5, 2.48438, 6.75, 2.60938, 1.60938,
-                7.75, 2.28125, 8.75, 7.6875, 8.25, 8.0625, 1.23438, 6.0625, 1.53125, 6.96875,
-                4.9375, 5.21875, 1.5, 5.125, 7.5, 7.1875, 6, 2.71875, 6.5625, 9.875,
-                2.15625, 4.40625, 5.5, 3.98438, 5.5625, 8.875, 1.84375, 8.75, 8.875, 9.6875,
-                8.8125, 2.78125, 1.16406, 6.03125, 7.625, 2.73438, 6.5, 5.6875, 9.75, 8.125,
-                6.875, 7.34375, 9, 5.0625, 6.1875, 3.95312, 4.5, 2.35938, 4.6875, 9.875,
-                1.09375, 6.09375, 4, 9.75, 8.5, 1.70312, 6.9375, 1.29688, 5.6875, 7.8125,
-                9.625, 3.125, 7.1875, 6.6875, 7.84375, 1.21094, 1.71094, 5.875, 3.4375, 5.8125,
-                4.25, 4.125, 7.875, 5.1875, 9.3125, 9, 4.4375, 1.0625, 3.01562, 5.25,
-                3.09375, 7.375, 6.1875, 3.4375, 6.46875, 9.375, 5.625, 4.8125, 8.1875, 2.03125,
-                8.75, 4.21875, 9.25, 8.3125, 1.1875, 3.0625, 1.6875, 3.375, 5.09375, 1.95312,
-                1.25, 3.76562, 7.75, 5.09375, 6.1875, 4.625, 4.625, 1.49219, 4.96875, 9.875,
-                2, 9, 4.46875, 7.25, 1.36719, 7.9375, 1.79688, 3, 7.5625, 2.625,
-                7.5625, 1.92969, 2.32812, 3.25, 4.375, 1.125, 7.75, 2.4375, 3.34375, 5.6875,
-                1.30469, 7.9375, 8.75, 3.625, 6.3125, 6.75, 1.73438, 2.5, 3.09375, 10},
-            std::vector<T>{
-                1, 7.25, 1.08594, 1.90625, 7.3125, 8.1875, 1.84375, 9.8125, 3.65625, 7.6875,
-                7.03125, 6.75, 9.875, 9, 2.28125, 4.625, 8.375, 8.125, 4.25, 9.9375,
-                2.125, 1.92969, 1.35938, 7.625, 5.6875, 2.65625, 6.9375, 8.0625, 2.53125, 7.375,
-                2.8125, 9.1875, 7.3125, 8.75, 7.15625, 7.15625, 3.8125, 6.75, 3.53125, 10},
-            std::vector<T>{
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094},
-            std::vector<T>{
-                0.554688, 0.570312, 0.5625, 0.5625, 0.570312, 0.570312, 0.585938, 0.570312, 0.570312, 0.5625,
-                0.554688, 0.585938, 0.5625, 0.570312, 0.578125, 0.578125, 0.59375, 0.578125, 0.578125, 0.570312,
-                0.554688, 0.59375, 0.5625, 0.570312, 0.585938, 0.585938, 0.609375, 0.585938, 0.585938, 0.570312,
-                0.554688, 0.601562, 0.570312, 0.578125, 0.601562, 0.59375, 0.625, 0.601562, 0.59375, 0.578125,
+                1,       7.5,     1.57812, 10,      1.55469, 3.5,     9.0625,  7.5625,  9,       1.30469, 6,
+                7.1875,  2.20312, 9,       5.6875,  2,       5.5625,  5.5625,  6.21875, 3.09375, 3.82812, 7.28125,
+                9,       1.625,   6.78125, 9.875,   5.46875, 4.1875,  3.84375, 2.21875, 1.57812, 9.125,   6,
+                6,       9.5,     2.28125, 8.375,   9.875,   2.32812, 5.96875, 1.42969, 4.5625,  1.10156, 5.4375,
+                8.25,    1.625,   6.875,   4.6875,  6.15625, 6.15625, 8.625,   4.125,   6.1875,  1.375,   6.1875,
+                8.875,   6,       3.40625, 1.75781, 4.8125,  1.40625, 4.21875, 4,       6.4375,  6.5625,  4.1875,
+                8.25,    7.40625, 2.40625, 7,       5.5625,  7.9375,  7.625,   4.75,    7,       1.625,   9.25,
+                7,       7,       2.5,     5.9375,  7.1875,  6.875,   5.84375, 7.5625,  6.5,     2.09375, 6.0625,
+                2.4375,  3.34375, 3.76562, 2.1875,  3.51562, 5.875,   2.54688, 8.3125,  9.125,   2.96875, 1.9375,
+                3.76562, 4.1875,  6.28125, 4.84375, 7.5,     3.78125, 5.375,   2.84375, 8.5,     3.3125,  8.1875,
+                4.21875, 6.375,   8.375,   1.46875, 6.625,   6.5625,  9.0625,  2.90625, 9.4375,  5.375,   1.32812,
+                5.9375,  8.9375,  4.4375,  7.5625,  8.9375,  5.28125, 2.59375, 8.375,   5.15625, 6.8125,  9.25,
+                5.3125,  4.375,   1.46875, 7.5625,  8.3125,  2.82812, 7.25,    7.03125, 3.3125,  3.03125, 8.5,
+                3.21875, 8.875,   7,       9.6875,  5.28125, 3.65625, 1.8125,  2.5,     4.0625,  6.15625, 8,
+                5.1875,  2.45312, 6.1875,  1.375,   7.9375,  7.1875,  9.625,   7.5,     7.84375, 7.40625, 9.75,
+                7.09375, 2.0625,  1.5,     6.53125, 5,       9.875,   6.6875,  5.875,   6.8125,  5.53125, 9.25,
+                4.0625,  4.1875,  1.46875, 5,       8.6875,  3.70312, 1.85938, 1.21094, 2.71875, 1.82812, 9,
+                2.71875, 9.9375,  7.8125,  4.3125,  8.8125,  2.8125,  3.23438, 4.375,   4.1875,  8.375,   8.75,
+                6.625,   5.34375, 7.1875,  3.45312, 7.0625,  8.5,     5.8125,  4.875,   8.875,   3.5625,  3.84375,
+                6.1875,  3.90625, 4.9375,  4.5625,  6.625,   2.59375, 9.875,   2.90625, 1.82031, 1.25781, 6,
+                9.25,    4.09375, 9.125,   2.5625,  5.25,    2.34375, 5.90625, 7.90625, 9.75,    6.875,   7.3125,
+                1.14062, 9.125,   7.75,    5.5625,  2.8125,  1.32812, 7.5625,  9,       7.125,   8.625,   4.4375,
+                8.375,   6.375,   6.6875,  3.82812, 5.1875,  7.8125,  3.28125, 1.17188, 7.125,   8.9375,  6.6875,
+                5.4375,  6.21875, 4.125,   1.40625, 3.51562, 3.5,     3.0625,  1.03906, 7.28125, 2.64062, 8.125,
+                4.4375,  5.25,    1.75,    1.96875, 7.9375,  4.46875, 6.25,    8.75,    1.80469, 3.375,   2.4375,
+                8.9375,  4.1875,  4.1875,  7.15625, 6.65625, 8.375,   1.13281, 7.3125,  7.375,   3.3125,  1.36719,
+                7.40625, 6.375,   7.875,   4,       8.5,     8.5,     6.1875,  2.3125,  6.5625,  6.25,    7.03125,
+                7.625,   5.1875,  6.71875, 4.125,   7.4375,  1.09375, 5,       4.90625, 5.5625,  10,      8.0625,
+                2.625,   1.21875, 7.46875, 3.125,   4.0625,  8.3125,  1.11719, 5.40625, 4.96875, 1.35156, 2.04688,
+                2.5,     3.8125,  6.125,   3.78125, 2.82812, 8.9375,  6.90625, 3.6875,  1.95312, 9.8125,  7.25,
+                4.125,   4.875,   1.54688, 6.40625, 2.57812, 6.46875, 5.34375, 7.8125,  9.9375,  5.5625,  2.625,
+                7.1875,  8.375,   9.75,    1.67188, 3,       6.96875, 6,       1.53125, 2.09375, 6.15625, 5.3125,
+                7.25,    7.3125,  3.625,   1.10938, 7.53125, 1.375,   7.84375, 7.96875, 9.875,   9.8125,  5.78125,
+                7.9375,  4.3125,  8.0625,  7.8125,  6.5625,  2.21875, 4.0625,  3.1875,  4.75,    8.25,    6.125,
+                3.03125, 6.1875,  4.125,   7.71875, 4.4375,  1.46875, 4.40625, 6.375,   4.375,   1.48438, 2.65625,
+                1.80469, 7.5,     9.875,   7.25,    7.875,   8.1875,  5.4375,  2.70312, 3.39062, 2.23438, 2.5625,
+                9.875,   1.76562, 3.3125,  10},
+            std::vector<T>{
+                1,       6.125,   4.53125, 4.4375,  6.3125,  6.6875,  5.375,   8.25,    9.875,   9.375,   9.0625,
+                5.9375,  3.0625,  6.75,    9.75,    8.8125,  3.5,     2.40625, 7.625,   2.21875, 2.39062, 9.25,
+                6.1875,  4.0625,  6.25,    5.375,   8.25,    7.3125,  6.5,     7.8125,  2.65625, 2.10938, 8.375,
+                7.65625, 4.09375, 2.71875, 9.4375,  7.0625,  6.5625,  8.625,   7.625,   8.25,    2.10938, 8.625,
+                8.125,   7.40625, 4.5,     2.76562, 5.125,   9.625,   8.5625,  8.75,    7.46875, 9.625,   8.875,
+                4.40625, 2.26562, 9.3125,  1.67188, 9.1875,  6.1875,  4.78125, 5.5,     6.40625, 5.59375, 8.125,
+                7.65625, 1.75,    2.96875, 3.875,   8.75,    1.99219, 3.53125, 2.53125, 9.375,   2.1875,  2.875,
+                1.86719, 9.25,    7.125,   3.89062, 9.5,     1.92188, 5.4375,  4.5625,  1,       8,       3.96875,
+                9.375,   9.1875,  1.19531, 6.875,   3.21875, 8.5625,  7.0625,  8.6875,  9.875,   4.65625, 9.5,
+                6.25,    1.82812, 1.51562, 2.42188, 4.21875, 2.78125, 7.75,    4.96875, 3.89062, 2.76562, 9.25,
+                5.84375, 5.84375, 8.375,   3.34375, 9.875,   2.625,   2.15625, 1.73438, 6.25,    8.875,   4.0625,
+                7.8125,  4.625,   7.59375, 7.625,   2.71875, 4.25,    3.96875, 2,       2.9375,  6.25,    7.3125,
+                7.09375, 7.1875,  7.40625, 1.13281, 9.625,   5.90625, 9.9375,  1.0625,  2.10938, 9.5,     6.25,
+                5.1875,  3.3125,  9.4375,  6.84375, 8.25,    4.375,   4.59375, 1.79688, 9,       7.9375,  2.64062,
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+            std::vector<T>{1.20312, 1.30469, 1.22656, 1.24219, 1.28906, 1.28125, 1.35938, 1.29688, 1.28125, 1.25,
+                           1.28906, 1.21875, 1.29688, 1.375,   1.21875, 1.25,    1.32812, 1.35156, 1.30469, 1.34375,
+                           1.30469, 1.26562, 1.35156, 1.26562, 1.35156, 1.28906, 1.23438, 1.21875, 1.32031, 1.21875,
+                           1.21875, 1.29688, 1.24219, 1.32031, 1.25781, 1.22656, 1.28125, 1.22656, 1.25,    1.3125,
+                           1.26562, 1.32031, 1.25781, 1.24219, 1.34375, 1.32812, 1.32812, 1.21875, 1.25,    1.375}),
         LSTMSequenceV1Params(
-            5, 10, 10, 5,
-            0.7f, true, op::RecurrentSequenceDirection::BIDIRECTIONAL,
+            5,
+            10,
+            10,
+            5,
+            0.7f,
+            true,
+            op::RecurrentSequenceDirection::BIDIRECTIONAL,
             ET,
             std::vector<T>{
-                1, 9.375, 9, 3.84375, 2.17188, 2.65625, 1.35938, 2.84375, 8.4375, 6.125,
-                5.78125, 6.375, 9.625, 9.625, 5.15625, 6.875, 9.3125, 7.75, 4.375, 6.875,
-                2.39062, 7.71875, 9, 9.625, 1.23438, 1.07812, 3.625, 1.95312, 4.5625, 3.6875,
-                8.25, 6.90625, 6.625, 8.25, 9.125, 8.875, 6, 9.625, 8.5, 7.5,
-                1.45312, 6.78125, 8.25, 7.4375, 9.375, 5.1875, 4.25, 3.9375, 7.1875, 4.9375,
-                2.15625, 7.5625, 8.5, 9.9375, 3.85938, 7.0625, 7.625, 8.125, 6.375, 2.53125,
-                4.25, 1.23438, 8.125, 8.1875, 7.28125, 9.125, 8.375, 1.21875, 9.125, 5.4375,
-                8.5, 5.75, 9.1875, 6.375, 9.75, 1.46875, 6.875, 9, 8.25, 7.5625,
-                1.92188, 8.375, 3.125, 5.5, 4.40625, 8.25, 7.28125, 1.85938, 5.375, 2.96875,
-                4.75, 3.32812, 6.75, 5.1875, 7.8125, 5.125, 6, 7.375, 7.25, 2.59375,
-                9.25, 5.78125, 1.21875, 2.5, 8.5, 7.90625, 4.4375, 9.375, 3.6875, 6.5,
-                1.05469, 2.34375, 4.9375, 5.40625, 7.625, 4.375, 4.375, 8.625, 5.4375, 9.1875,
-                1.125, 4.4375, 3.25, 3.84375, 4.125, 6.125, 8.125, 2.6875, 9.4375, 2.125,
-                1.90625, 7.1875, 7.625, 8.1875, 9.75, 6.15625, 7.34375, 9.75, 9.5625, 6.6875,
-                9.375, 9, 4.6875, 5.4375, 4.03125, 4.15625, 7.9375, 7.4375, 4, 5.53125,
-                1.74219, 3.03125, 9.0625, 3.20312, 8.0625, 8.125, 7.4375, 5.4375, 5, 9.25,
-                7.75, 9.5, 6.90625, 5.8125, 4.25, 3.26562, 4.375, 7.5, 6.84375, 4.3125,
-                1.5, 5.5, 1.70312, 3.03125, 1.82812, 4.1875, 8.25, 6.84375, 1.58594, 3.8125,
-                3.01562, 7.90625, 2.375, 8, 7.125, 8.625, 2.125, 9.5, 3.3125, 1.96875,
-                4.9375, 9.1875, 1.98438, 4, 3.82812, 8.375, 4.15625, 9.0625, 7.84375, 1.38281,
-                1.89062, 2.75, 9.375, 3.65625, 3.9375, 6.625, 4.8125, 1.77344, 3.4375, 2.28125,
-                8.0625, 5.625, 5.0625, 7.1875, 1.75, 8.6875, 1.63281, 6.8125, 3.96875, 6.25,
-                2.71875, 7.375, 8.5, 3.26562, 1.55469, 9.125, 6, 4.96875, 6.125, 1.1875,
-                5.15625, 9.625, 9.5, 6.875, 4.09375, 5.625, 8.9375, 7.125, 4.875, 5.375,
-                9.9375, 9.3125, 8.1875, 5.625, 9.5, 1.64844, 4.40625, 6.09375, 4.625, 10},
-            std::vector<T>{
-                1, 9.1875, 5.5625, 6.625, 2.65625, 8.125, 8.25, 4.875, 9.4375, 5.875,
-                1.26562, 4.71875, 8.0625, 1.76562, 2.46875, 8, 4.875, 5.375, 6.15625, 1.45312,
-                2.95312, 5.84375, 8.5, 1.375, 3.6875, 8.25, 4.25, 9.9375, 8.8125, 6.75,
-                1.10938, 9.5, 7.0625, 7.625, 5.3125, 8.375, 9.75, 2.03125, 2.90625, 7.625,
-                2.90625, 8.375, 9.5, 1.66406, 3.9375, 2.875, 9.875, 8.25, 4.9375, 9.25,
-                9.6875, 2.34375, 3.3125, 9.625, 7.8125, 4.34375, 2.71875, 7.4375, 3.53125, 1.9375,
-                7.9375, 8.875, 1.07031, 6.25, 4.1875, 7.125, 3.09375, 9, 4.4375, 2.60938,
-                1.98438, 2.76562, 4.65625, 5.125, 4.625, 8.375, 7.9375, 6.6875, 8.5625, 6.8125,
-                4.53125, 5.09375, 5.1875, 6.0625, 1.9375, 7, 2.71875, 6.8125, 7.0625, 1.42188,
-                5.25, 3.34375, 8.1875, 1.07812, 3.21875, 8.6875, 7.6875, 1.27344, 7.0625, 10},
-            std::vector<T>{
-                1, 6.59375, 2.125, 2.89062, 5.71875, 5.0625, 9.75, 6, 4.9375, 3.21875,
-                5.875, 1.85156, 6.28125, 9.875, 1.59375, 3.40625, 7.75, 9.25, 6.46875, 8.75,
-                6.5, 4.0625, 9.125, 4.4375, 9.25, 5.5625, 2.625, 1.8125, 7.625, 1.875,
-                1.26562, 6.3125, 3.03125, 7.3125, 3.92188, 2.21875, 4.90625, 2.10938, 3.28125, 6.875,
-                4.375, 7.25, 3.92188, 3.09375, 8.375, 7.96875, 7.9375, 1.875, 3.125, 4.9375,
-                1.32031, 3.67188, 4, 7.4375, 8.875, 6.75, 3.28125, 1.71875, 8.25, 2.39062,
-                5.84375, 6.84375, 9.0625, 1.71875, 6.25, 7, 7.28125, 3.8125, 7.53125, 6.0625,
-                1.48438, 2.64062, 5.6875, 2.34375, 6.4375, 9.375, 9.625, 7.25, 3.70312, 7.5,
-                3.65625, 8.375, 10, 6.5, 5.65625, 5.9375, 7.0625, 5.5625, 5.375, 9,
-                4.625, 7.3125, 4.8125, 1.71875, 1.51562, 2.3125, 8.875, 8.625, 9, 10},
+                1,       9.375,   9,       3.84375, 2.17188, 2.65625, 1.35938, 2.84375, 8.4375,  6.125,   5.78125,
+                6.375,   9.625,   9.625,   5.15625, 6.875,   9.3125,  7.75,    4.375,   6.875,   2.39062, 7.71875,
+                9,       9.625,   1.23438, 1.07812, 3.625,   1.95312, 4.5625,  3.6875,  8.25,    6.90625, 6.625,
+                8.25,    9.125,   8.875,   6,       9.625,   8.5,     7.5,     1.45312, 6.78125, 8.25,    7.4375,
+                9.375,   5.1875,  4.25,    3.9375,  7.1875,  4.9375,  2.15625, 7.5625,  8.5,     9.9375,  3.85938,
+                7.0625,  7.625,   8.125,   6.375,   2.53125, 4.25,    1.23438, 8.125,   8.1875,  7.28125, 9.125,
+                8.375,   1.21875, 9.125,   5.4375,  8.5,     5.75,    9.1875,  6.375,   9.75,    1.46875, 6.875,
+                9,       8.25,    7.5625,  1.92188, 8.375,   3.125,   5.5,     4.40625, 8.25,    7.28125, 1.85938,
+                5.375,   2.96875, 4.75,    3.32812, 6.75,    5.1875,  7.8125,  5.125,   6,       7.375,   7.25,
+                2.59375, 9.25,    5.78125, 1.21875, 2.5,     8.5,     7.90625, 4.4375,  9.375,   3.6875,  6.5,
+                1.05469, 2.34375, 4.9375,  5.40625, 7.625,   4.375,   4.375,   8.625,   5.4375,  9.1875,  1.125,
+                4.4375,  3.25,    3.84375, 4.125,   6.125,   8.125,   2.6875,  9.4375,  2.125,   1.90625, 7.1875,
+                7.625,   8.1875,  9.75,    6.15625, 7.34375, 9.75,    9.5625,  6.6875,  9.375,   9,       4.6875,
+                5.4375,  4.03125, 4.15625, 7.9375,  7.4375,  4,       5.53125, 1.74219, 3.03125, 9.0625,  3.20312,
+                8.0625,  8.125,   7.4375,  5.4375,  5,       9.25,    7.75,    9.5,     6.90625, 5.8125,  4.25,
+                3.26562, 4.375,   7.5,     6.84375, 4.3125,  1.5,     5.5,     1.70312, 3.03125, 1.82812, 4.1875,
+                8.25,    6.84375, 1.58594, 3.8125,  3.01562, 7.90625, 2.375,   8,       7.125,   8.625,   2.125,
+                9.5,     3.3125,  1.96875, 4.9375,  9.1875,  1.98438, 4,       3.82812, 8.375,   4.15625, 9.0625,
+                7.84375, 1.38281, 1.89062, 2.75,    9.375,   3.65625, 3.9375,  6.625,   4.8125,  1.77344, 3.4375,
+                2.28125, 8.0625,  5.625,   5.0625,  7.1875,  1.75,    8.6875,  1.63281, 6.8125,  3.96875, 6.25,
+                2.71875, 7.375,   8.5,     3.26562, 1.55469, 9.125,   6,       4.96875, 6.125,   1.1875,  5.15625,
+                9.625,   9.5,     6.875,   4.09375, 5.625,   8.9375,  7.125,   4.875,   5.375,   9.9375,  9.3125,
+                8.1875,  5.625,   9.5,     1.64844, 4.40625, 6.09375, 4.625,   10},
+            std::vector<T>{1,       9.1875,  5.5625,  6.625,   2.65625, 8.125,   8.25,    4.875,   9.4375,  5.875,
+                           1.26562, 4.71875, 8.0625,  1.76562, 2.46875, 8,       4.875,   5.375,   6.15625, 1.45312,
+                           2.95312, 5.84375, 8.5,     1.375,   3.6875,  8.25,    4.25,    9.9375,  8.8125,  6.75,
+                           1.10938, 9.5,     7.0625,  7.625,   5.3125,  8.375,   9.75,    2.03125, 2.90625, 7.625,
+                           2.90625, 8.375,   9.5,     1.66406, 3.9375,  2.875,   9.875,   8.25,    4.9375,  9.25,
+                           9.6875,  2.34375, 3.3125,  9.625,   7.8125,  4.34375, 2.71875, 7.4375,  3.53125, 1.9375,
+                           7.9375,  8.875,   1.07031, 6.25,    4.1875,  7.125,   3.09375, 9,       4.4375,  2.60938,
+                           1.98438, 2.76562, 4.65625, 5.125,   4.625,   8.375,   7.9375,  6.6875,  8.5625,  6.8125,
+                           4.53125, 5.09375, 5.1875,  6.0625,  1.9375,  7,       2.71875, 6.8125,  7.0625,  1.42188,
+                           5.25,    3.34375, 8.1875,  1.07812, 3.21875, 8.6875,  7.6875,  1.27344, 7.0625,  10},
+            std::vector<T>{1,       6.59375, 2.125,   2.89062, 5.71875, 5.0625,  9.75,    6,       4.9375,  3.21875,
+                           5.875,   1.85156, 6.28125, 9.875,   1.59375, 3.40625, 7.75,    9.25,    6.46875, 8.75,
+                           6.5,     4.0625,  9.125,   4.4375,  9.25,    5.5625,  2.625,   1.8125,  7.625,   1.875,
+                           1.26562, 6.3125,  3.03125, 7.3125,  3.92188, 2.21875, 4.90625, 2.10938, 3.28125, 6.875,
+                           4.375,   7.25,    3.92188, 3.09375, 8.375,   7.96875, 7.9375,  1.875,   3.125,   4.9375,
+                           1.32031, 3.67188, 4,       7.4375,  8.875,   6.75,    3.28125, 1.71875, 8.25,    2.39062,
+                           5.84375, 6.84375, 9.0625,  1.71875, 6.25,    7,       7.28125, 3.8125,  7.53125, 6.0625,
+                           1.48438, 2.64062, 5.6875,  2.34375, 6.4375,  9.375,   9.625,   7.25,    3.70312, 7.5,
+                           3.65625, 8.375,   10,      6.5,     5.65625, 5.9375,  7.0625,  5.5625,  5.375,   9,
+                           4.625,   7.3125,  4.8125,  1.71875, 1.51562, 2.3125,  8.875,   8.625,   9,       10},
             std::vector<int64_t>{5, 5, 5, 5, 5},
             std::vector<T>{
-                1, 7.5, 1.57812, 10, 1.55469, 3.5, 9.0625, 7.5625, 9, 1.30469,
-                6, 7.1875, 2.20312, 9, 5.6875, 2, 5.5625, 5.5625, 6.21875, 3.09375,
-                3.82812, 7.28125, 9, 1.625, 6.78125, 9.875, 5.46875, 4.1875, 3.84375, 2.21875,
-                1.57812, 9.125, 6, 6, 9.5, 2.28125, 8.375, 9.875, 2.32812, 5.96875,
-                1.42969, 4.5625, 1.10156, 5.4375, 8.25, 1.625, 6.875, 4.6875, 6.15625, 6.15625,
-                8.625, 4.125, 6.1875, 1.375, 6.1875, 8.875, 6, 3.40625, 1.75781, 4.8125,
-                1.40625, 4.21875, 4, 6.4375, 6.5625, 4.1875, 8.25, 7.40625, 2.40625, 7,
-                5.5625, 7.9375, 7.625, 4.75, 7, 1.625, 9.25, 7, 7, 2.5,
-                5.9375, 7.1875, 6.875, 5.84375, 7.5625, 6.5, 2.09375, 6.0625, 2.4375, 3.34375,
-                3.76562, 2.1875, 3.51562, 5.875, 2.54688, 8.3125, 9.125, 2.96875, 1.9375, 3.76562,
-                4.1875, 6.28125, 4.84375, 7.5, 3.78125, 5.375, 2.84375, 8.5, 3.3125, 8.1875,
-                4.21875, 6.375, 8.375, 1.46875, 6.625, 6.5625, 9.0625, 2.90625, 9.4375, 5.375,
-                1.32812, 5.9375, 8.9375, 4.4375, 7.5625, 8.9375, 5.28125, 2.59375, 8.375, 5.15625,
-                6.8125, 9.25, 5.3125, 4.375, 1.46875, 7.5625, 8.3125, 2.82812, 7.25, 7.03125,
-                3.3125, 3.03125, 8.5, 3.21875, 8.875, 7, 9.6875, 5.28125, 3.65625, 1.8125,
-                2.5, 4.0625, 6.15625, 8, 5.1875, 2.45312, 6.1875, 1.375, 7.9375, 7.1875,
-                9.625, 7.5, 7.84375, 7.40625, 9.75, 7.09375, 2.0625, 1.5, 6.53125, 5,
-                9.875, 6.6875, 5.875, 6.8125, 5.53125, 9.25, 4.0625, 4.1875, 1.46875, 5,
-                8.6875, 3.70312, 1.85938, 1.21094, 2.71875, 1.82812, 9, 2.71875, 9.9375, 7.8125,
-                4.3125, 8.8125, 2.8125, 3.23438, 4.375, 4.1875, 8.375, 8.75, 6.625, 5.34375,
-                7.1875, 3.45312, 7.0625, 8.5, 5.8125, 4.875, 8.875, 3.5625, 3.84375, 6.1875,
-                3.90625, 4.9375, 4.5625, 6.625, 2.59375, 9.875, 2.90625, 1.82031, 1.25781, 6,
-                9.25, 4.09375, 9.125, 2.5625, 5.25, 2.34375, 5.90625, 7.90625, 9.75, 6.875,
-                7.3125, 1.14062, 9.125, 7.75, 5.5625, 2.8125, 1.32812, 7.5625, 9, 7.125,
-                8.625, 4.4375, 8.375, 6.375, 6.6875, 3.82812, 5.1875, 7.8125, 3.28125, 1.17188,
-                7.125, 8.9375, 6.6875, 5.4375, 6.21875, 4.125, 1.40625, 3.51562, 3.5, 3.0625,
-                1.03906, 7.28125, 2.64062, 8.125, 4.4375, 5.25, 1.75, 1.96875, 7.9375, 4.46875,
-                6.25, 8.75, 1.80469, 3.375, 2.4375, 8.9375, 4.1875, 4.1875, 7.15625, 6.65625,
-                8.375, 1.13281, 7.3125, 7.375, 3.3125, 1.36719, 7.40625, 6.375, 7.875, 4,
-                8.5, 8.5, 6.1875, 2.3125, 6.5625, 6.25, 7.03125, 7.625, 5.1875, 6.71875,
-                4.125, 7.4375, 1.09375, 5, 4.90625, 5.5625, 10, 8.0625, 2.625, 1.21875,
-                7.46875, 3.125, 4.0625, 8.3125, 1.11719, 5.40625, 4.96875, 1.35156, 2.04688, 2.5,
-                3.8125, 6.125, 3.78125, 2.82812, 8.9375, 6.90625, 3.6875, 1.95312, 9.8125, 7.25,
-                4.125, 4.875, 1.54688, 6.40625, 2.57812, 6.46875, 5.34375, 7.8125, 9.9375, 5.5625,
-                2.625, 7.1875, 8.375, 9.75, 1.67188, 3, 6.96875, 6, 1.53125, 2.09375,
-                6.15625, 5.3125, 7.25, 7.3125, 3.625, 1.10938, 7.53125, 1.375, 7.84375, 7.96875,
-                9.875, 9.8125, 5.78125, 7.9375, 4.3125, 8.0625, 7.8125, 6.5625, 2.21875, 4.0625,
-                3.1875, 4.75, 8.25, 6.125, 3.03125, 6.1875, 4.125, 7.71875, 4.4375, 1.46875,
-                4.40625, 6.375, 4.375, 1.48438, 2.65625, 1.80469, 7.5, 9.875, 7.25, 7.875,
-                8.1875, 5.4375, 2.70312, 3.39062, 2.23438, 2.5625, 9.875, 1.76562, 3.3125, 3.10938,
-                2.78125, 6.9375, 7.3125, 5.59375, 1.03125, 5.9375, 3.15625, 6.1875, 3.15625, 7.5,
-                4.625, 5.65625, 2.89062, 2.71875, 8.75, 1.85938, 3.8125, 2.71875, 4.03125, 6.25,
-                5.0625, 8, 7.4375, 5.625, 3, 1.1875, 6.75, 4.4375, 5.6875, 7.625,
-                5.125, 9.625, 5.4375, 3.28125, 1.78125, 2.03125, 6.65625, 6.875, 3.85938, 7.0625,
-                8.1875, 2.15625, 6.8125, 3.84375, 5.15625, 8.875, 7.09375, 8.375, 8.875, 8.75,
-                2.79688, 3.1875, 2.0625, 9.75, 9.4375, 4.3125, 5.5625, 8.8125, 5.09375, 4,
-                5.375, 7.375, 4.75, 8.875, 6.5, 1.25, 5.9375, 8.125, 7.4375, 5.625,
-                7.34375, 9.75, 8.625, 7.125, 3.5625, 1.67969, 6.75, 3.35938, 2.375, 5.9375,
-                8.375, 1.95312, 4.8125, 4.0625, 4.5625, 1.21875, 3.10938, 1.96094, 4.625, 3.4375,
-                1.97656, 2.32812, 6.28125, 5.0625, 4.5625, 1.375, 2.53125, 1.23438, 8.125, 9.75,
-                1.59375, 4.6875, 1.89062, 2.625, 7.3125, 5.5, 2.15625, 6.84375, 4.0625, 9.875,
-                8.9375, 5.4375, 9.9375, 3.96875, 9.75, 7.5, 6.59375, 2.96875, 6.625, 1.05469,
-                8.125, 7.6875, 5, 3.92188, 8.3125, 6.65625, 9.4375, 8.125, 1.53125, 3.75,
-                4.875, 9.375, 9, 5.53125, 3.65625, 2.29688, 6.125, 4.21875, 9.375, 1.39062,
-                6.125, 8, 1.34375, 6.90625, 6.84375, 6.4375, 1.26562, 4.375, 5.875, 5.0625,
-                6.375, 2.73438, 9.4375, 7.90625, 6.15625, 6.3125, 1.46875, 6.125, 2.32812, 2.53125,
-                4.71875, 7.40625, 2.57812, 1.9375, 8.75, 5.0625, 2.25, 1.95312, 2.79688, 3.40625,
-                6.53125, 3.98438, 9.75, 4.875, 2.67188, 9.25, 1.5, 6.9375, 9.25, 2.46875,
-                6.6875, 2.1875, 2.48438, 6.40625, 2.9375, 1.25, 8.875, 3.8125, 9.5, 2.375,
-                2.53125, 8.5, 3.28125, 7.4375, 2.9375, 6.53125, 2.0625, 3.45312, 3.5, 1.60938,
-                8, 5.25, 6.5, 8.875, 2.89062, 4.5625, 9.4375, 9.625, 9.375, 3.4375,
-                5, 7.46875, 3.71875, 2.875, 1.09375, 6.0625, 5.4375, 4.4375, 8.375, 9.25,
-                4.9375, 9.625, 4.5, 4.28125, 9.0625, 1.92188, 3.5625, 6.15625, 7.84375, 7.09375,
-                9.25, 3.04688, 8.875, 7.5, 3.90625, 6.40625, 8.875, 8.9375, 7.125, 9.5,
-                7.375, 8.875, 6, 1.03125, 9.875, 1.27344, 5.9375, 3.8125, 7.96875, 5.6875,
-                7.1875, 9.625, 2.07812, 2.5, 4.1875, 6.375, 7.125, 6.4375, 5.09375, 9.375,
-                5.5625, 6.40625, 7.5625, 3.3125, 2.09375, 1.07812, 8.25, 9.0625, 5.4375, 8.375,
-                5.0625, 2.5, 7.1875, 1.04688, 3.40625, 7, 9.125, 1.21875, 2.46875, 2.53125,
-                7.5625, 6.125, 3.04688, 9.375, 4.75, 10, 6.15625, 2.0625, 5.4375, 8.5,
-                6.375, 7.875, 5.5, 3.375, 9.75, 7.9375, 2.03125, 2.0625, 6.03125, 5.5625,
-                1.625, 1.13281, 1.22656, 7.09375, 8.5625, 1.77344, 8.625, 7.6875, 7.5, 7.34375,
-                7.65625, 3.20312, 5.9375, 6.1875, 1.01562, 5.65625, 5.78125, 2.21875, 9, 2.04688,
-                5.71875, 5.125, 4.96875, 2.53125, 1.33594, 4.1875, 9.75, 3.0625, 9, 7.1875,
-                3.46875, 3.75, 3.09375, 2.85938, 9.125, 1.35938, 7.84375, 3.82812, 8.1875, 4.75,
-                2.65625, 1.40625, 8.5, 5.375, 6.75, 1.69531, 5.875, 6.75, 4.59375, 2.625,
-                4.125, 5.375, 4.125, 9.375, 6.25, 7.3125, 8.375, 1.55469, 8.3125, 5.125,
-                9.4375, 5.03125, 1.3125, 8.625, 3.15625, 1.30469, 9, 7.90625, 7.875, 7.8125,
-                1.45312, 5.4375, 2.84375, 1.23438, 4.96875, 7.59375, 4.65625, 2.04688, 8.25, 4.21875,
-                9.4375, 5.9375, 2.64062, 5.75, 3.15625, 9.5, 1.42188, 8.4375, 5.3125, 5,
-                9.25, 7.875, 8.875, 4, 6.875, 8.625, 2.875, 2.54688, 8.75, 10},
-            std::vector<T>{
-                1, 6.125, 4.53125, 4.4375, 6.3125, 6.6875, 5.375, 8.25, 9.875, 9.375,
-                9.0625, 5.9375, 3.0625, 6.75, 9.75, 8.8125, 3.5, 2.40625, 7.625, 2.21875,
-                2.39062, 9.25, 6.1875, 4.0625, 6.25, 5.375, 8.25, 7.3125, 6.5, 7.8125,
-                2.65625, 2.10938, 8.375, 7.65625, 4.09375, 2.71875, 9.4375, 7.0625, 6.5625, 8.625,
-                7.625, 8.25, 2.10938, 8.625, 8.125, 7.40625, 4.5, 2.76562, 5.125, 9.625,
-                8.5625, 8.75, 7.46875, 9.625, 8.875, 4.40625, 2.26562, 9.3125, 1.67188, 9.1875,
-                6.1875, 4.78125, 5.5, 6.40625, 5.59375, 8.125, 7.65625, 1.75, 2.96875, 3.875,
-                8.75, 1.99219, 3.53125, 2.53125, 9.375, 2.1875, 2.875, 1.86719, 9.25, 7.125,
-                3.89062, 9.5, 1.92188, 5.4375, 4.5625, 1, 8, 3.96875, 9.375, 9.1875,
-                1.19531, 6.875, 3.21875, 8.5625, 7.0625, 8.6875, 9.875, 4.65625, 9.5, 6.25,
-                1.82812, 1.51562, 2.42188, 4.21875, 2.78125, 7.75, 4.96875, 3.89062, 2.76562, 9.25,
-                5.84375, 5.84375, 8.375, 3.34375, 9.875, 2.625, 2.15625, 1.73438, 6.25, 8.875,
-                4.0625, 7.8125, 4.625, 7.59375, 7.625, 2.71875, 4.25, 3.96875, 2, 2.9375,
-                6.25, 7.3125, 7.09375, 7.1875, 7.40625, 1.13281, 9.625, 5.90625, 9.9375, 1.0625,
-                2.10938, 9.5, 6.25, 5.1875, 3.3125, 9.4375, 6.84375, 8.25, 4.375, 4.59375,
-                1.79688, 9, 7.9375, 2.64062, 9.75, 8.75, 9.6875, 3.59375, 4, 10,
-                8.875, 2.82812, 9.0625, 8.8125, 1.76562, 2.23438, 6.625, 2.375, 3.70312, 8.375,
-                8.625, 4, 6.1875, 9.8125, 2.625, 2.60938, 9.375, 1.625, 2.03125, 9.5,
-                1.84375, 9.125, 7.75, 4.75, 2.0625, 2.375, 6.03125, 5.65625, 3.92188, 4.125,
-                9.625, 4.25, 5.4375, 1.34375, 5.1875, 7.53125, 3.96875, 4.875, 1.65625, 3.54688,
-                1.64062, 4.625, 1.51562, 4.4375, 4.375, 5.1875, 1.03906, 1.58594, 9.75, 2.78125,
-                1.27344, 6.25, 6.4375, 9.5625, 4.625, 3.89062, 8.875, 5.875, 9.875, 4,
-                9.625, 8.1875, 6, 6.5625, 3.1875, 5.9375, 1.17188, 6.375, 3.09375, 3.5,
-                5.34375, 6.625, 9.6875, 1.85938, 2.85938, 9.75, 5.5, 7.6875, 1.86719, 1.03125,
-                7.21875, 7.125, 7.75, 6.1875, 2, 2.59375, 2.46875, 8.25, 7.78125, 3.75,
-                7.875, 4.6875, 8.0625, 7.9375, 2.53125, 6.5, 2.48438, 6.75, 2.60938, 1.60938,
-                7.75, 2.28125, 8.75, 7.6875, 8.25, 8.0625, 1.23438, 6.0625, 1.53125, 6.96875,
-                4.9375, 5.21875, 1.5, 5.125, 7.5, 7.1875, 6, 2.71875, 6.5625, 9.875,
-                2.15625, 4.40625, 5.5, 3.98438, 5.5625, 8.875, 1.84375, 8.75, 8.875, 9.6875,
-                8.8125, 2.78125, 1.16406, 6.03125, 7.625, 2.73438, 6.5, 5.6875, 9.75, 8.125,
-                6.875, 7.34375, 9, 5.0625, 6.1875, 3.95312, 4.5, 2.35938, 4.6875, 9.875,
-                1.09375, 6.09375, 4, 9.75, 8.5, 1.70312, 6.9375, 1.29688, 5.6875, 7.8125,
-                9.625, 3.125, 7.1875, 6.6875, 7.84375, 1.21094, 1.71094, 5.875, 3.4375, 5.8125,
-                4.25, 4.125, 7.875, 5.1875, 9.3125, 9, 4.4375, 1.0625, 3.01562, 5.25,
-                3.09375, 7.375, 6.1875, 3.4375, 6.46875, 9.375, 5.625, 4.8125, 8.1875, 2.03125,
-                8.75, 4.21875, 9.25, 8.3125, 1.1875, 3.0625, 1.6875, 3.375, 5.09375, 1.95312,
-                1.25, 3.76562, 7.75, 5.09375, 6.1875, 4.625, 4.625, 1.49219, 4.96875, 9.875,
-                2, 9, 4.46875, 7.25, 1.36719, 7.9375, 1.79688, 3, 7.5625, 2.625,
-                7.5625, 1.92969, 2.32812, 3.25, 4.375, 1.125, 7.75, 2.4375, 3.34375, 5.6875,
-                1.30469, 7.9375, 8.75, 3.625, 6.3125, 6.75, 1.73438, 2.5, 3.09375, 1.28906,
-                1.75, 8.4375, 4.875, 3.5, 7.78125, 6.8125, 1.42188, 5.125, 7.6875, 3.90625,
-                4.125, 9.8125, 2.4375, 4.625, 9.9375, 9.75, 7.625, 5.875, 9.5, 9.125,
-                9.5, 1.03125, 1.15625, 8.5625, 5.34375, 2.75, 5.6875, 6.03125, 2.6875, 3.15625,
-                9.75, 2.04688, 8.875, 4.6875, 4.40625, 5, 3.78125, 1.17188, 7, 3.92188,
-                3.48438, 9.0625, 4.0625, 3.34375, 3.5625, 6.6875, 5.5625, 8.875, 5.25, 2.34375,
-                1.48438, 1.14844, 7.21875, 7.25, 5.375, 7.1875, 3.34375, 1.5625, 8.1875, 1.95312,
-                7.21875, 1.48438, 8.625, 9.25, 1.14062, 4.65625, 5.15625, 9.75, 2.28125, 1.71875,
-                6.8125, 9.25, 6.125, 2.84375, 7.21875, 4.09375, 9, 4.8125, 6.15625, 7.625,
-                6.625, 6, 7.5, 2.46875, 6.125, 1.33594, 8.25, 5.125, 3.53125, 6.875,
-                4.4375, 3.10938, 7.5625, 9.25, 7.1875, 1.15625, 7.875, 3.21875, 7.40625, 6.46875,
-                4.875, 5.3125, 7.09375, 9.375, 8.75, 3.75, 9.3125, 2.25, 9.5, 3.375,
-                7.3125, 6.875, 8.5625, 6.5, 5.09375, 6.4375, 6.625, 4.28125, 6.75, 2.65625,
-                8.25, 7, 4.1875, 5.4375, 8.125, 2.71875, 4.3125, 8, 2.65625, 6.375,
-                3.67188, 3.6875, 8.125, 8.125, 4.09375, 2.25, 9.6875, 1.04688, 5.375, 1.96875,
-                3.03125, 2.42188, 7.75, 5.125, 8.25, 6.9375, 6.8125, 8.375, 8.5, 1.04688,
-                1.39062, 4.21875, 2.03125, 5.40625, 8.25, 9, 6.5625, 4.25, 8.5, 4.9375,
-                7.875, 5.875, 5.75, 9.4375, 6.84375, 4.0625, 9, 3.375, 4.84375, 4.375,
-                9.75, 6.5, 7.125, 9.375, 4.5, 1.40625, 2.71875, 8.75, 5.59375, 8.875,
-                8.5625, 4.375, 9.625, 5.5625, 7.0625, 9, 5.9375, 4.1875, 2.1875, 8.75,
-                2.90625, 6.5, 5.96875, 5.15625, 4.4375, 7.25, 5.0625, 1.65625, 4.1875, 5.46875,
-                5.03125, 2.59375, 3.78125, 7.84375, 3.125, 2.46875, 4.03125, 4.5625, 6.0625, 9.25,
-                2.6875, 6.75, 3.14062, 3.71875, 9.875, 5.9375, 1.96875, 4.375, 6.6875, 7.6875,
-                7.1875, 6.375, 6.8125, 1.76562, 8.125, 8.625, 7.96875, 2.45312, 2.20312, 1.65625,
-                6.625, 7.8125, 4.65625, 5.25, 4.875, 3.71875, 8.8125, 7.3125, 1.54688, 4.3125,
-                5.34375, 1.8125, 1.03125, 7.84375, 2.09375, 1.8125, 5.6875, 4.3125, 3.8125, 8.25,
-                1.48438, 2.75, 8.75, 6.4375, 7, 1.67188, 9.125, 7.875, 9.625, 7.875,
-                1.46875, 10, 2.15625, 7.28125, 5.03125, 4.34375, 7.4375, 8.1875, 5.21875, 2.625,
-                9.625, 10, 7.6875, 7.75, 8.75, 2.25, 4.71875, 6.375, 5.84375, 8.8125,
-                1.54688, 6.4375, 7.125, 7.25, 8.875, 5.25, 8.25, 10, 1.03125, 1.45312,
-                6.5625, 4.5625, 4.125, 4.125, 7.53125, 8.75, 1.53125, 7.4375, 6.125, 2.71875,
-                4.9375, 6.25, 6.5, 2.95312, 9.375, 9.625, 4.5, 5.40625, 1.16406, 2.71875,
-                1.08594, 8.875, 5.3125, 2.34375, 7.09375, 8.875, 4.71875, 3.95312, 3.79688, 5.375,
-                2.59375, 9.0625, 6.125, 8.25, 3.5625, 5.375, 9.5, 7.5625, 8.75, 3.75,
-                1.125, 3.21875, 5.5625, 3.59375, 4.625, 8.5, 7.71875, 3.15625, 8, 8.25,
-                8.6875, 4.78125, 2.625, 4.28125, 5.6875, 1.625, 6.375, 2.4375, 8.625, 5.75,
-                9, 2.39062, 1.76562, 1.5, 8.6875, 3.96875, 6.75, 2.40625, 6.4375, 8.8125,
-                3.375, 2.15625, 8.75, 3.625, 4.9375, 7.9375, 9.625, 8.125, 2.96875, 9.625,
-                4.4375, 9.4375, 2.6875, 3.625, 3.59375, 9.25, 4.1875, 2.6875, 5.9375, 7.875,
-                7.1875, 8, 7.90625, 4.28125, 6.0625, 8.875, 3.90625, 1.69531, 3.5, 3.34375,
-                7.75, 2.46875, 6.875, 4.1875, 8.5625, 5.1875, 5.34375, 6.15625, 9.375, 10},
-            std::vector<T>{
-                1, 7.25, 1.08594, 1.90625, 7.3125, 8.1875, 1.84375, 9.8125, 3.65625, 7.6875,
-                7.03125, 6.75, 9.875, 9, 2.28125, 4.625, 8.375, 8.125, 4.25, 9.9375,
-                2.125, 1.92969, 1.35938, 7.625, 5.6875, 2.65625, 6.9375, 8.0625, 2.53125, 7.375,
-                2.8125, 9.1875, 7.3125, 8.75, 7.15625, 7.15625, 3.8125, 6.75, 3.53125, 8.75,
-                9.875, 5.75, 7.1875, 5.65625, 7.375, 9.25, 6.03125, 9.75, 8.625, 1.07031,
-                6.8125, 2.90625, 6.1875, 4.6875, 7.25, 1.14062, 9.0625, 2.78125, 5.625, 6.875,
-                2.0625, 3.3125, 9.875, 8.9375, 5.6875, 5.875, 3.65625, 2.78125, 8.625, 4.1875,
-                7.125, 7.09375, 5.125, 2.625, 3.10938, 9.4375, 5.5625, 5.8125, 3.5625, 10},
-            std::vector<T>{
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-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
-                0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094},
+                1,       7.5,     1.57812, 10,      1.55469, 3.5,     9.0625,  7.5625,  9,       1.30469, 6,
+                7.1875,  2.20312, 9,       5.6875,  2,       5.5625,  5.5625,  6.21875, 3.09375, 3.82812, 7.28125,
+                9,       1.625,   6.78125, 9.875,   5.46875, 4.1875,  3.84375, 2.21875, 1.57812, 9.125,   6,
+                6,       9.5,     2.28125, 8.375,   9.875,   2.32812, 5.96875, 1.42969, 4.5625,  1.10156, 5.4375,
+                8.25,    1.625,   6.875,   4.6875,  6.15625, 6.15625, 8.625,   4.125,   6.1875,  1.375,   6.1875,
+                8.875,   6,       3.40625, 1.75781, 4.8125,  1.40625, 4.21875, 4,       6.4375,  6.5625,  4.1875,
+                8.25,    7.40625, 2.40625, 7,       5.5625,  7.9375,  7.625,   4.75,    7,       1.625,   9.25,
+                7,       7,       2.5,     5.9375,  7.1875,  6.875,   5.84375, 7.5625,  6.5,     2.09375, 6.0625,
+                2.4375,  3.34375, 3.76562, 2.1875,  3.51562, 5.875,   2.54688, 8.3125,  9.125,   2.96875, 1.9375,
+                3.76562, 4.1875,  6.28125, 4.84375, 7.5,     3.78125, 5.375,   2.84375, 8.5,     3.3125,  8.1875,
+                4.21875, 6.375,   8.375,   1.46875, 6.625,   6.5625,  9.0625,  2.90625, 9.4375,  5.375,   1.32812,
+                5.9375,  8.9375,  4.4375,  7.5625,  8.9375,  5.28125, 2.59375, 8.375,   5.15625, 6.8125,  9.25,
+                5.3125,  4.375,   1.46875, 7.5625,  8.3125,  2.82812, 7.25,    7.03125, 3.3125,  3.03125, 8.5,
+                3.21875, 8.875,   7,       9.6875,  5.28125, 3.65625, 1.8125,  2.5,     4.0625,  6.15625, 8,
+                5.1875,  2.45312, 6.1875,  1.375,   7.9375,  7.1875,  9.625,   7.5,     7.84375, 7.40625, 9.75,
+                7.09375, 2.0625,  1.5,     6.53125, 5,       9.875,   6.6875,  5.875,   6.8125,  5.53125, 9.25,
+                4.0625,  4.1875,  1.46875, 5,       8.6875,  3.70312, 1.85938, 1.21094, 2.71875, 1.82812, 9,
+                2.71875, 9.9375,  7.8125,  4.3125,  8.8125,  2.8125,  3.23438, 4.375,   4.1875,  8.375,   8.75,
+                6.625,   5.34375, 7.1875,  3.45312, 7.0625,  8.5,     5.8125,  4.875,   8.875,   3.5625,  3.84375,
+                6.1875,  3.90625, 4.9375,  4.5625,  6.625,   2.59375, 9.875,   2.90625, 1.82031, 1.25781, 6,
+                9.25,    4.09375, 9.125,   2.5625,  5.25,    2.34375, 5.90625, 7.90625, 9.75,    6.875,   7.3125,
+                1.14062, 9.125,   7.75,    5.5625,  2.8125,  1.32812, 7.5625,  9,       7.125,   8.625,   4.4375,
+                8.375,   6.375,   6.6875,  3.82812, 5.1875,  7.8125,  3.28125, 1.17188, 7.125,   8.9375,  6.6875,
+                5.4375,  6.21875, 4.125,   1.40625, 3.51562, 3.5,     3.0625,  1.03906, 7.28125, 2.64062, 8.125,
+                4.4375,  5.25,    1.75,    1.96875, 7.9375,  4.46875, 6.25,    8.75,    1.80469, 3.375,   2.4375,
+                8.9375,  4.1875,  4.1875,  7.15625, 6.65625, 8.375,   1.13281, 7.3125,  7.375,   3.3125,  1.36719,
+                7.40625, 6.375,   7.875,   4,       8.5,     8.5,     6.1875,  2.3125,  6.5625,  6.25,    7.03125,
+                7.625,   5.1875,  6.71875, 4.125,   7.4375,  1.09375, 5,       4.90625, 5.5625,  10,      8.0625,
+                2.625,   1.21875, 7.46875, 3.125,   4.0625,  8.3125,  1.11719, 5.40625, 4.96875, 1.35156, 2.04688,
+                2.5,     3.8125,  6.125,   3.78125, 2.82812, 8.9375,  6.90625, 3.6875,  1.95312, 9.8125,  7.25,
+                4.125,   4.875,   1.54688, 6.40625, 2.57812, 6.46875, 5.34375, 7.8125,  9.9375,  5.5625,  2.625,
+                7.1875,  8.375,   9.75,    1.67188, 3,       6.96875, 6,       1.53125, 2.09375, 6.15625, 5.3125,
+                7.25,    7.3125,  3.625,   1.10938, 7.53125, 1.375,   7.84375, 7.96875, 9.875,   9.8125,  5.78125,
+                7.9375,  4.3125,  8.0625,  7.8125,  6.5625,  2.21875, 4.0625,  3.1875,  4.75,    8.25,    6.125,
+                3.03125, 6.1875,  4.125,   7.71875, 4.4375,  1.46875, 4.40625, 6.375,   4.375,   1.48438, 2.65625,
+                1.80469, 7.5,     9.875,   7.25,    7.875,   8.1875,  5.4375,  2.70312, 3.39062, 2.23438, 2.5625,
+                9.875,   1.76562, 3.3125,  3.10938, 2.78125, 6.9375,  7.3125,  5.59375, 1.03125, 5.9375,  3.15625,
+                6.1875,  3.15625, 7.5,     4.625,   5.65625, 2.89062, 2.71875, 8.75,    1.85938, 3.8125,  2.71875,
+                4.03125, 6.25,    5.0625,  8,       7.4375,  5.625,   3,       1.1875,  6.75,    4.4375,  5.6875,
+                7.625,   5.125,   9.625,   5.4375,  3.28125, 1.78125, 2.03125, 6.65625, 6.875,   3.85938, 7.0625,
+                8.1875,  2.15625, 6.8125,  3.84375, 5.15625, 8.875,   7.09375, 8.375,   8.875,   8.75,    2.79688,
+                3.1875,  2.0625,  9.75,    9.4375,  4.3125,  5.5625,  8.8125,  5.09375, 4,       5.375,   7.375,
+                4.75,    8.875,   6.5,     1.25,    5.9375,  8.125,   7.4375,  5.625,   7.34375, 9.75,    8.625,
+                7.125,   3.5625,  1.67969, 6.75,    3.35938, 2.375,   5.9375,  8.375,   1.95312, 4.8125,  4.0625,
+                4.5625,  1.21875, 3.10938, 1.96094, 4.625,   3.4375,  1.97656, 2.32812, 6.28125, 5.0625,  4.5625,
+                1.375,   2.53125, 1.23438, 8.125,   9.75,    1.59375, 4.6875,  1.89062, 2.625,   7.3125,  5.5,
+                2.15625, 6.84375, 4.0625,  9.875,   8.9375,  5.4375,  9.9375,  3.96875, 9.75,    7.5,     6.59375,
+                2.96875, 6.625,   1.05469, 8.125,   7.6875,  5,       3.92188, 8.3125,  6.65625, 9.4375,  8.125,
+                1.53125, 3.75,    4.875,   9.375,   9,       5.53125, 3.65625, 2.29688, 6.125,   4.21875, 9.375,
+                1.39062, 6.125,   8,       1.34375, 6.90625, 6.84375, 6.4375,  1.26562, 4.375,   5.875,   5.0625,
+                6.375,   2.73438, 9.4375,  7.90625, 6.15625, 6.3125,  1.46875, 6.125,   2.32812, 2.53125, 4.71875,
+                7.40625, 2.57812, 1.9375,  8.75,    5.0625,  2.25,    1.95312, 2.79688, 3.40625, 6.53125, 3.98438,
+                9.75,    4.875,   2.67188, 9.25,    1.5,     6.9375,  9.25,    2.46875, 6.6875,  2.1875,  2.48438,
+                6.40625, 2.9375,  1.25,    8.875,   3.8125,  9.5,     2.375,   2.53125, 8.5,     3.28125, 7.4375,
+                2.9375,  6.53125, 2.0625,  3.45312, 3.5,     1.60938, 8,       5.25,    6.5,     8.875,   2.89062,
+                4.5625,  9.4375,  9.625,   9.375,   3.4375,  5,       7.46875, 3.71875, 2.875,   1.09375, 6.0625,
+                5.4375,  4.4375,  8.375,   9.25,    4.9375,  9.625,   4.5,     4.28125, 9.0625,  1.92188, 3.5625,
+                6.15625, 7.84375, 7.09375, 9.25,    3.04688, 8.875,   7.5,     3.90625, 6.40625, 8.875,   8.9375,
+                7.125,   9.5,     7.375,   8.875,   6,       1.03125, 9.875,   1.27344, 5.9375,  3.8125,  7.96875,
+                5.6875,  7.1875,  9.625,   2.07812, 2.5,     4.1875,  6.375,   7.125,   6.4375,  5.09375, 9.375,
+                5.5625,  6.40625, 7.5625,  3.3125,  2.09375, 1.07812, 8.25,    9.0625,  5.4375,  8.375,   5.0625,
+                2.5,     7.1875,  1.04688, 3.40625, 7,       9.125,   1.21875, 2.46875, 2.53125, 7.5625,  6.125,
+                3.04688, 9.375,   4.75,    10,      6.15625, 2.0625,  5.4375,  8.5,     6.375,   7.875,   5.5,
+                3.375,   9.75,    7.9375,  2.03125, 2.0625,  6.03125, 5.5625,  1.625,   1.13281, 1.22656, 7.09375,
+                8.5625,  1.77344, 8.625,   7.6875,  7.5,     7.34375, 7.65625, 3.20312, 5.9375,  6.1875,  1.01562,
+                5.65625, 5.78125, 2.21875, 9,       2.04688, 5.71875, 5.125,   4.96875, 2.53125, 1.33594, 4.1875,
+                9.75,    3.0625,  9,       7.1875,  3.46875, 3.75,    3.09375, 2.85938, 9.125,   1.35938, 7.84375,
+                3.82812, 8.1875,  4.75,    2.65625, 1.40625, 8.5,     5.375,   6.75,    1.69531, 5.875,   6.75,
+                4.59375, 2.625,   4.125,   5.375,   4.125,   9.375,   6.25,    7.3125,  8.375,   1.55469, 8.3125,
+                5.125,   9.4375,  5.03125, 1.3125,  8.625,   3.15625, 1.30469, 9,       7.90625, 7.875,   7.8125,
+                1.45312, 5.4375,  2.84375, 1.23438, 4.96875, 7.59375, 4.65625, 2.04688, 8.25,    4.21875, 9.4375,
+                5.9375,  2.64062, 5.75,    3.15625, 9.5,     1.42188, 8.4375,  5.3125,  5,       9.25,    7.875,
+                8.875,   4,       6.875,   8.625,   2.875,   2.54688, 8.75,    10},
+            std::vector<T>{
+                1,       6.125,   4.53125, 4.4375,  6.3125,  6.6875,  5.375,   8.25,    9.875,   9.375,   9.0625,
+                5.9375,  3.0625,  6.75,    9.75,    8.8125,  3.5,     2.40625, 7.625,   2.21875, 2.39062, 9.25,
+                6.1875,  4.0625,  6.25,    5.375,   8.25,    7.3125,  6.5,     7.8125,  2.65625, 2.10938, 8.375,
+                7.65625, 4.09375, 2.71875, 9.4375,  7.0625,  6.5625,  8.625,   7.625,   8.25,    2.10938, 8.625,
+                8.125,   7.40625, 4.5,     2.76562, 5.125,   9.625,   8.5625,  8.75,    7.46875, 9.625,   8.875,
+                4.40625, 2.26562, 9.3125,  1.67188, 9.1875,  6.1875,  4.78125, 5.5,     6.40625, 5.59375, 8.125,
+                7.65625, 1.75,    2.96875, 3.875,   8.75,    1.99219, 3.53125, 2.53125, 9.375,   2.1875,  2.875,
+                1.86719, 9.25,    7.125,   3.89062, 9.5,     1.92188, 5.4375,  4.5625,  1,       8,       3.96875,
+                9.375,   9.1875,  1.19531, 6.875,   3.21875, 8.5625,  7.0625,  8.6875,  9.875,   4.65625, 9.5,
+                6.25,    1.82812, 1.51562, 2.42188, 4.21875, 2.78125, 7.75,    4.96875, 3.89062, 2.76562, 9.25,
+                5.84375, 5.84375, 8.375,   3.34375, 9.875,   2.625,   2.15625, 1.73438, 6.25,    8.875,   4.0625,
+                7.8125,  4.625,   7.59375, 7.625,   2.71875, 4.25,    3.96875, 2,       2.9375,  6.25,    7.3125,
+                7.09375, 7.1875,  7.40625, 1.13281, 9.625,   5.90625, 9.9375,  1.0625,  2.10938, 9.5,     6.25,
+                5.1875,  3.3125,  9.4375,  6.84375, 8.25,    4.375,   4.59375, 1.79688, 9,       7.9375,  2.64062,
+                9.75,    8.75,    9.6875,  3.59375, 4,       10,      8.875,   2.82812, 9.0625,  8.8125,  1.76562,
+                2.23438, 6.625,   2.375,   3.70312, 8.375,   8.625,   4,       6.1875,  9.8125,  2.625,   2.60938,
+                9.375,   1.625,   2.03125, 9.5,     1.84375, 9.125,   7.75,    4.75,    2.0625,  2.375,   6.03125,
+                5.65625, 3.92188, 4.125,   9.625,   4.25,    5.4375,  1.34375, 5.1875,  7.53125, 3.96875, 4.875,
+                1.65625, 3.54688, 1.64062, 4.625,   1.51562, 4.4375,  4.375,   5.1875,  1.03906, 1.58594, 9.75,
+                2.78125, 1.27344, 6.25,    6.4375,  9.5625,  4.625,   3.89062, 8.875,   5.875,   9.875,   4,
+                9.625,   8.1875,  6,       6.5625,  3.1875,  5.9375,  1.17188, 6.375,   3.09375, 3.5,     5.34375,
+                6.625,   9.6875,  1.85938, 2.85938, 9.75,    5.5,     7.6875,  1.86719, 1.03125, 7.21875, 7.125,
+                7.75,    6.1875,  2,       2.59375, 2.46875, 8.25,    7.78125, 3.75,    7.875,   4.6875,  8.0625,
+                7.9375,  2.53125, 6.5,     2.48438, 6.75,    2.60938, 1.60938, 7.75,    2.28125, 8.75,    7.6875,
+                8.25,    8.0625,  1.23438, 6.0625,  1.53125, 6.96875, 4.9375,  5.21875, 1.5,     5.125,   7.5,
+                7.1875,  6,       2.71875, 6.5625,  9.875,   2.15625, 4.40625, 5.5,     3.98438, 5.5625,  8.875,
+                1.84375, 8.75,    8.875,   9.6875,  8.8125,  2.78125, 1.16406, 6.03125, 7.625,   2.73438, 6.5,
+                5.6875,  9.75,    8.125,   6.875,   7.34375, 9,       5.0625,  6.1875,  3.95312, 4.5,     2.35938,
+                4.6875,  9.875,   1.09375, 6.09375, 4,       9.75,    8.5,     1.70312, 6.9375,  1.29688, 5.6875,
+                7.8125,  9.625,   3.125,   7.1875,  6.6875,  7.84375, 1.21094, 1.71094, 5.875,   3.4375,  5.8125,
+                4.25,    4.125,   7.875,   5.1875,  9.3125,  9,       4.4375,  1.0625,  3.01562, 5.25,    3.09375,
+                7.375,   6.1875,  3.4375,  6.46875, 9.375,   5.625,   4.8125,  8.1875,  2.03125, 8.75,    4.21875,
+                9.25,    8.3125,  1.1875,  3.0625,  1.6875,  3.375,   5.09375, 1.95312, 1.25,    3.76562, 7.75,
+                5.09375, 6.1875,  4.625,   4.625,   1.49219, 4.96875, 9.875,   2,       9,       4.46875, 7.25,
+                1.36719, 7.9375,  1.79688, 3,       7.5625,  2.625,   7.5625,  1.92969, 2.32812, 3.25,    4.375,
+                1.125,   7.75,    2.4375,  3.34375, 5.6875,  1.30469, 7.9375,  8.75,    3.625,   6.3125,  6.75,
+                1.73438, 2.5,     3.09375, 1.28906, 1.75,    8.4375,  4.875,   3.5,     7.78125, 6.8125,  1.42188,
+                5.125,   7.6875,  3.90625, 4.125,   9.8125,  2.4375,  4.625,   9.9375,  9.75,    7.625,   5.875,
+                9.5,     9.125,   9.5,     1.03125, 1.15625, 8.5625,  5.34375, 2.75,    5.6875,  6.03125, 2.6875,
+                3.15625, 9.75,    2.04688, 8.875,   4.6875,  4.40625, 5,       3.78125, 1.17188, 7,       3.92188,
+                3.48438, 9.0625,  4.0625,  3.34375, 3.5625,  6.6875,  5.5625,  8.875,   5.25,    2.34375, 1.48438,
+                1.14844, 7.21875, 7.25,    5.375,   7.1875,  3.34375, 1.5625,  8.1875,  1.95312, 7.21875, 1.48438,
+                8.625,   9.25,    1.14062, 4.65625, 5.15625, 9.75,    2.28125, 1.71875, 6.8125,  9.25,    6.125,
+                2.84375, 7.21875, 4.09375, 9,       4.8125,  6.15625, 7.625,   6.625,   6,       7.5,     2.46875,
+                6.125,   1.33594, 8.25,    5.125,   3.53125, 6.875,   4.4375,  3.10938, 7.5625,  9.25,    7.1875,
+                1.15625, 7.875,   3.21875, 7.40625, 6.46875, 4.875,   5.3125,  7.09375, 9.375,   8.75,    3.75,
+                9.3125,  2.25,    9.5,     3.375,   7.3125,  6.875,   8.5625,  6.5,     5.09375, 6.4375,  6.625,
+                4.28125, 6.75,    2.65625, 8.25,    7,       4.1875,  5.4375,  8.125,   2.71875, 4.3125,  8,
+                2.65625, 6.375,   3.67188, 3.6875,  8.125,   8.125,   4.09375, 2.25,    9.6875,  1.04688, 5.375,
+                1.96875, 3.03125, 2.42188, 7.75,    5.125,   8.25,    6.9375,  6.8125,  8.375,   8.5,     1.04688,
+                1.39062, 4.21875, 2.03125, 5.40625, 8.25,    9,       6.5625,  4.25,    8.5,     4.9375,  7.875,
+                5.875,   5.75,    9.4375,  6.84375, 4.0625,  9,       3.375,   4.84375, 4.375,   9.75,    6.5,
+                7.125,   9.375,   4.5,     1.40625, 2.71875, 8.75,    5.59375, 8.875,   8.5625,  4.375,   9.625,
+                5.5625,  7.0625,  9,       5.9375,  4.1875,  2.1875,  8.75,    2.90625, 6.5,     5.96875, 5.15625,
+                4.4375,  7.25,    5.0625,  1.65625, 4.1875,  5.46875, 5.03125, 2.59375, 3.78125, 7.84375, 3.125,
+                2.46875, 4.03125, 4.5625,  6.0625,  9.25,    2.6875,  6.75,    3.14062, 3.71875, 9.875,   5.9375,
+                1.96875, 4.375,   6.6875,  7.6875,  7.1875,  6.375,   6.8125,  1.76562, 8.125,   8.625,   7.96875,
+                2.45312, 2.20312, 1.65625, 6.625,   7.8125,  4.65625, 5.25,    4.875,   3.71875, 8.8125,  7.3125,
+                1.54688, 4.3125,  5.34375, 1.8125,  1.03125, 7.84375, 2.09375, 1.8125,  5.6875,  4.3125,  3.8125,
+                8.25,    1.48438, 2.75,    8.75,    6.4375,  7,       1.67188, 9.125,   7.875,   9.625,   7.875,
+                1.46875, 10,      2.15625, 7.28125, 5.03125, 4.34375, 7.4375,  8.1875,  5.21875, 2.625,   9.625,
+                10,      7.6875,  7.75,    8.75,    2.25,    4.71875, 6.375,   5.84375, 8.8125,  1.54688, 6.4375,
+                7.125,   7.25,    8.875,   5.25,    8.25,    10,      1.03125, 1.45312, 6.5625,  4.5625,  4.125,
+                4.125,   7.53125, 8.75,    1.53125, 7.4375,  6.125,   2.71875, 4.9375,  6.25,    6.5,     2.95312,
+                9.375,   9.625,   4.5,     5.40625, 1.16406, 2.71875, 1.08594, 8.875,   5.3125,  2.34375, 7.09375,
+                8.875,   4.71875, 3.95312, 3.79688, 5.375,   2.59375, 9.0625,  6.125,   8.25,    3.5625,  5.375,
+                9.5,     7.5625,  8.75,    3.75,    1.125,   3.21875, 5.5625,  3.59375, 4.625,   8.5,     7.71875,
+                3.15625, 8,       8.25,    8.6875,  4.78125, 2.625,   4.28125, 5.6875,  1.625,   6.375,   2.4375,
+                8.625,   5.75,    9,       2.39062, 1.76562, 1.5,     8.6875,  3.96875, 6.75,    2.40625, 6.4375,
+                8.8125,  3.375,   2.15625, 8.75,    3.625,   4.9375,  7.9375,  9.625,   8.125,   2.96875, 9.625,
+                4.4375,  9.4375,  2.6875,  3.625,   3.59375, 9.25,    4.1875,  2.6875,  5.9375,  7.875,   7.1875,
+                8,       7.90625, 4.28125, 6.0625,  8.875,   3.90625, 1.69531, 3.5,     3.34375, 7.75,    2.46875,
+                6.875,   4.1875,  8.5625,  5.1875,  5.34375, 6.15625, 9.375,   10},
+            std::vector<T>{1,       7.25,    1.08594, 1.90625, 7.3125,  8.1875,  1.84375, 9.8125,  3.65625, 7.6875,
+                           7.03125, 6.75,    9.875,   9,       2.28125, 4.625,   8.375,   8.125,   4.25,    9.9375,
+                           2.125,   1.92969, 1.35938, 7.625,   5.6875,  2.65625, 6.9375,  8.0625,  2.53125, 7.375,
+                           2.8125,  9.1875,  7.3125,  8.75,    7.15625, 7.15625, 3.8125,  6.75,    3.53125, 8.75,
+                           9.875,   5.75,    7.1875,  5.65625, 7.375,   9.25,    6.03125, 9.75,    8.625,   1.07031,
+                           6.8125,  2.90625, 6.1875,  4.6875,  7.25,    1.14062, 9.0625,  2.78125, 5.625,   6.875,
+                           2.0625,  3.3125,  9.875,   8.9375,  5.6875,  5.875,   3.65625, 2.78125, 8.625,   4.1875,
+                           7.125,   7.09375, 5.125,   2.625,   3.10938, 9.4375,  5.5625,  5.8125,  3.5625,  10},
+            std::vector<T>{0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
+                           0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
+                           0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
+                           0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
+                           0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
+                           0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
+                           0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094, 0.0996094,
+                           0.0996094, 0.0996094, 0.0996094, 0.0996094},
             std::vector<T>{
                 0.466797, 0.667969, 0.617188, 0.648438, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625,
-                0.433594, 0.664062, 0.570312, 0.617188, 0.664062, 0.65625, 0.667969, 0.664062, 0.65625, 0.625,
-                0.410156, 0.65625, 0.523438, 0.570312, 0.648438, 0.632812, 0.664062, 0.648438, 0.632812, 0.585938,
-                0.390625, 0.625, 0.480469, 0.523438, 0.617188, 0.601562, 0.65625, 0.617188, 0.601562, 0.539062,
+                0.433594, 0.664062, 0.570312, 0.617188, 0.664062, 0.65625,  0.667969, 0.664062, 0.65625,  0.625,
+                0.410156, 0.65625,  0.523438, 0.570312, 0.648438, 0.632812, 0.664062, 0.648438, 0.632812, 0.585938,
+                0.390625, 0.625,    0.480469, 0.523438, 0.617188, 0.601562, 0.65625,  0.617188, 0.601562, 0.539062,
                 0.380859, 0.585938, 0.443359, 0.480469, 0.570312, 0.554688, 0.632812, 0.578125, 0.554688, 0.490234,
-                0.570312, 0.427734, 0.578125, 0.632812, 0.417969, 0.5, 0.609375, 0.625, 0.585938, 0.617188,
-                0.617188, 0.458984, 0.625, 0.65625, 0.443359, 0.546875, 0.640625, 0.648438, 0.625, 0.648438,
-                0.648438, 0.5, 0.648438, 0.664062, 0.476562, 0.59375, 0.664062, 0.664062, 0.65625, 0.664062,
+                0.570312, 0.427734, 0.578125, 0.632812, 0.417969, 0.5,      0.609375, 0.625,    0.585938, 0.617188,
+                0.617188, 0.458984, 0.625,    0.65625,  0.443359, 0.546875, 0.640625, 0.648438, 0.625,    0.648438,
+                0.648438, 0.5,      0.648438, 0.664062, 0.476562, 0.59375,  0.664062, 0.664062, 0.65625,  0.664062,
                 0.664062, 0.546875, 0.664062, 0.667969, 0.523438, 0.632812, 0.667969, 0.667969, 0.664062, 0.667969,
-                0.667969, 0.59375, 0.667969, 0.667969, 0.570312, 0.65625, 0.667969, 0.667969, 0.667969, 0.667969,
+                0.667969, 0.59375,  0.667969, 0.667969, 0.570312, 0.65625,  0.667969, 0.667969, 0.667969, 0.667969,
                 0.667969, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969, 0.640625, 0.585938, 0.667969, 0.59375,
                 0.664062, 0.648438, 0.667969, 0.648438, 0.667969, 0.664062, 0.601562, 0.539062, 0.667969, 0.546875,
-                0.65625, 0.617188, 0.664062, 0.625, 0.664062, 0.648438, 0.554688, 0.496094, 0.65625, 0.5,
-                0.625, 0.570312, 0.648438, 0.578125, 0.648438, 0.609375, 0.507812, 0.458984, 0.640625, 0.464844,
-                0.585938, 0.523438, 0.625, 0.53125, 0.625, 0.5625, 0.466797, 0.427734, 0.601562, 0.433594,
+                0.65625,  0.617188, 0.664062, 0.625,    0.664062, 0.648438, 0.554688, 0.496094, 0.65625,  0.5,
+                0.625,    0.570312, 0.648438, 0.578125, 0.648438, 0.609375, 0.507812, 0.458984, 0.640625, 0.464844,
+                0.585938, 0.523438, 0.625,    0.53125,  0.625,    0.5625,   0.466797, 0.427734, 0.601562, 0.433594,
                 0.396484, 0.578125, 0.484375, 0.601562, 0.515625, 0.449219, 0.546875, 0.443359, 0.492188, 0.59375,
-                0.417969, 0.625, 0.53125, 0.632812, 0.5625, 0.484375, 0.59375, 0.480469, 0.539062, 0.632812,
-                0.443359, 0.648438, 0.578125, 0.65625, 0.609375, 0.53125, 0.632812, 0.523438, 0.585938, 0.65625,
-                0.476562, 0.664062, 0.625, 0.667969, 0.648438, 0.578125, 0.65625, 0.570312, 0.632812, 0.664062,
-                0.523438, 0.667969, 0.648438, 0.667969, 0.664062, 0.625, 0.667969, 0.617188, 0.65625, 0.667969,
-                0.664062, 0.667969, 0.664062, 0.648438, 0.667969, 0.667969, 0.667969, 0.59375, 0.648438, 0.667969,
-                0.648438, 0.667969, 0.648438, 0.625, 0.667969, 0.667969, 0.667969, 0.546875, 0.625, 0.65625,
-                0.625, 0.65625, 0.609375, 0.578125, 0.664062, 0.664062, 0.664062, 0.5, 0.578125, 0.632812,
-                0.578125, 0.632812, 0.5625, 0.53125, 0.648438, 0.648438, 0.648438, 0.464844, 0.53125, 0.601562,
-                0.53125, 0.601562, 0.515625, 0.484375, 0.617188, 0.609375, 0.609375, 0.433594, 0.484375, 0.554688,
-                0.398438, 0.507812, 0.523438, 0.601562, 0.625, 0.585938, 0.492188, 0.421875, 0.617188, 0.458984,
+                0.417969, 0.625,    0.53125,  0.632812, 0.5625,   0.484375, 0.59375,  0.480469, 0.539062, 0.632812,
+                0.443359, 0.648438, 0.578125, 0.65625,  0.609375, 0.53125,  0.632812, 0.523438, 0.585938, 0.65625,
+                0.476562, 0.664062, 0.625,    0.667969, 0.648438, 0.578125, 0.65625,  0.570312, 0.632812, 0.664062,
+                0.523438, 0.667969, 0.648438, 0.667969, 0.664062, 0.625,    0.667969, 0.617188, 0.65625,  0.667969,
+                0.664062, 0.667969, 0.664062, 0.648438, 0.667969, 0.667969, 0.667969, 0.59375,  0.648438, 0.667969,
+                0.648438, 0.667969, 0.648438, 0.625,    0.667969, 0.667969, 0.667969, 0.546875, 0.625,    0.65625,
+                0.625,    0.65625,  0.609375, 0.578125, 0.664062, 0.664062, 0.664062, 0.5,      0.578125, 0.632812,
+                0.578125, 0.632812, 0.5625,   0.53125,  0.648438, 0.648438, 0.648438, 0.464844, 0.53125,  0.601562,
+                0.53125,  0.601562, 0.515625, 0.484375, 0.617188, 0.609375, 0.609375, 0.433594, 0.484375, 0.554688,
+                0.398438, 0.507812, 0.523438, 0.601562, 0.625,    0.585938, 0.492188, 0.421875, 0.617188, 0.458984,
                 0.417969, 0.554688, 0.570312, 0.640625, 0.648438, 0.632812, 0.539062, 0.449219, 0.648438, 0.496094,
-                0.445312, 0.601562, 0.617188, 0.65625, 0.664062, 0.65625, 0.585938, 0.484375, 0.664062, 0.539062,
-                0.484375, 0.640625, 0.648438, 0.667969, 0.667969, 0.664062, 0.632812, 0.53125, 0.667969, 0.585938,
-                0.523438, 0.65625, 0.664062, 0.667969, 0.667969, 0.667969, 0.65625, 0.578125, 0.667969, 0.632812,
+                0.445312, 0.601562, 0.617188, 0.65625,  0.664062, 0.65625,  0.585938, 0.484375, 0.664062, 0.539062,
+                0.484375, 0.640625, 0.648438, 0.667969, 0.667969, 0.664062, 0.632812, 0.53125,  0.667969, 0.585938,
+                0.523438, 0.65625,  0.664062, 0.667969, 0.667969, 0.667969, 0.65625,  0.578125, 0.667969, 0.632812,
                 0.667969, 0.667969, 0.667969, 0.578125, 0.667969, 0.667969, 0.667969, 0.664062, 0.667969, 0.667969,
-                0.664062, 0.664062, 0.667969, 0.53125, 0.664062, 0.664062, 0.667969, 0.640625, 0.667969, 0.664062,
-                0.648438, 0.65625, 0.664062, 0.484375, 0.648438, 0.65625, 0.65625, 0.609375, 0.65625, 0.648438,
-                0.617188, 0.632812, 0.648438, 0.449219, 0.625, 0.632812, 0.632812, 0.554688, 0.640625, 0.625,
-                0.570312, 0.59375, 0.625, 0.421875, 0.578125, 0.59375, 0.601562, 0.507812, 0.601562, 0.578125,
-                0.410156, 0.46875, 0.570312, 0.453125, 0.585938, 0.625, 0.632812, 0.601562, 0.507812, 0.601562,
-                0.433594, 0.507812, 0.617188, 0.490234, 0.625, 0.65625, 0.65625, 0.632812, 0.554688, 0.640625,
-                0.464844, 0.554688, 0.648438, 0.539062, 0.65625, 0.664062, 0.664062, 0.65625, 0.601562, 0.65625,
+                0.664062, 0.664062, 0.667969, 0.53125,  0.664062, 0.664062, 0.667969, 0.640625, 0.667969, 0.664062,
+                0.648438, 0.65625,  0.664062, 0.484375, 0.648438, 0.65625,  0.65625,  0.609375, 0.65625,  0.648438,
+                0.617188, 0.632812, 0.648438, 0.449219, 0.625,    0.632812, 0.632812, 0.554688, 0.640625, 0.625,
+                0.570312, 0.59375,  0.625,    0.421875, 0.578125, 0.59375,  0.601562, 0.507812, 0.601562, 0.578125,
+                0.410156, 0.46875,  0.570312, 0.453125, 0.585938, 0.625,    0.632812, 0.601562, 0.507812, 0.601562,
+                0.433594, 0.507812, 0.617188, 0.490234, 0.625,    0.65625,  0.65625,  0.632812, 0.554688, 0.640625,
+                0.464844, 0.554688, 0.648438, 0.539062, 0.65625,  0.664062, 0.664062, 0.65625,  0.601562, 0.65625,
                 0.507812, 0.601562, 0.664062, 0.585938, 0.664062, 0.667969, 0.667969, 0.667969, 0.640625, 0.667969,
-                0.554688, 0.640625, 0.667969, 0.625, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625, 0.667969,
-                0.65625, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969,
+                0.554688, 0.640625, 0.667969, 0.625,    0.667969, 0.667969, 0.667969, 0.667969, 0.65625,  0.667969,
+                0.65625,  0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969,
                 0.640625, 0.667969, 0.667969, 0.664062, 0.664062, 0.664062, 0.664062, 0.664062, 0.664062, 0.667969,
-                0.601562, 0.664062, 0.664062, 0.65625, 0.648438, 0.648438, 0.65625, 0.648438, 0.640625, 0.664062,
-                0.554688, 0.648438, 0.65625, 0.625, 0.617188, 0.617188, 0.632812, 0.609375, 0.609375, 0.648438,
-                0.507812, 0.617188, 0.632812, 0.585938, 0.570312, 0.578125, 0.59375, 0.5625, 0.554688, 0.625,
-                0.539062, 0.601562, 0.546875, 0.421875, 0.412109, 0.453125, 0.625, 0.617188, 0.625, 0.632812,
-                0.585938, 0.632812, 0.59375, 0.449219, 0.4375, 0.490234, 0.648438, 0.648438, 0.648438, 0.65625,
-                0.632812, 0.65625, 0.632812, 0.484375, 0.46875, 0.539062, 0.664062, 0.664062, 0.664062, 0.664062,
-                0.65625, 0.667969, 0.65625, 0.53125, 0.507812, 0.585938, 0.667969, 0.667969, 0.667969, 0.667969,
-                0.664062, 0.667969, 0.664062, 0.578125, 0.554688, 0.625, 0.667969, 0.667969, 0.667969, 0.667969},
+                0.601562, 0.664062, 0.664062, 0.65625,  0.648438, 0.648438, 0.65625,  0.648438, 0.640625, 0.664062,
+                0.554688, 0.648438, 0.65625,  0.625,    0.617188, 0.617188, 0.632812, 0.609375, 0.609375, 0.648438,
+                0.507812, 0.617188, 0.632812, 0.585938, 0.570312, 0.578125, 0.59375,  0.5625,   0.554688, 0.625,
+                0.539062, 0.601562, 0.546875, 0.421875, 0.412109, 0.453125, 0.625,    0.617188, 0.625,    0.632812,
+                0.585938, 0.632812, 0.59375,  0.449219, 0.4375,   0.490234, 0.648438, 0.648438, 0.648438, 0.65625,
+                0.632812, 0.65625,  0.632812, 0.484375, 0.46875,  0.539062, 0.664062, 0.664062, 0.664062, 0.664062,
+                0.65625,  0.667969, 0.65625,  0.53125,  0.507812, 0.585938, 0.667969, 0.667969, 0.667969, 0.667969,
+                0.664062, 0.667969, 0.664062, 0.578125, 0.554688, 0.625,    0.667969, 0.667969, 0.667969, 0.667969},
             std::vector<T>{
                 0.380859, 0.585938, 0.443359, 0.480469, 0.570312, 0.554688, 0.632812, 0.578125, 0.554688, 0.490234,
-                0.570312, 0.427734, 0.578125, 0.632812, 0.417969, 0.5, 0.609375, 0.625, 0.585938, 0.617188,
-                0.585938, 0.523438, 0.625, 0.53125, 0.625, 0.5625, 0.466797, 0.427734, 0.601562, 0.433594,
+                0.570312, 0.427734, 0.578125, 0.632812, 0.417969, 0.5,      0.609375, 0.625,    0.585938, 0.617188,
+                0.585938, 0.523438, 0.625,    0.53125,  0.625,    0.5625,   0.466797, 0.427734, 0.601562, 0.433594,
                 0.396484, 0.578125, 0.484375, 0.601562, 0.515625, 0.449219, 0.546875, 0.443359, 0.492188, 0.59375,
-                0.53125, 0.601562, 0.515625, 0.484375, 0.617188, 0.609375, 0.609375, 0.433594, 0.484375, 0.554688,
-                0.398438, 0.507812, 0.523438, 0.601562, 0.625, 0.585938, 0.492188, 0.421875, 0.617188, 0.458984,
-                0.570312, 0.59375, 0.625, 0.421875, 0.578125, 0.59375, 0.601562, 0.507812, 0.601562, 0.578125,
-                0.410156, 0.46875, 0.570312, 0.453125, 0.585938, 0.625, 0.632812, 0.601562, 0.507812, 0.601562,
-                0.507812, 0.617188, 0.632812, 0.585938, 0.570312, 0.578125, 0.59375, 0.5625, 0.554688, 0.625,
-                0.539062, 0.601562, 0.546875, 0.421875, 0.412109, 0.453125, 0.625, 0.617188, 0.625, 0.632812},
-            std::vector<T>{
-                0.648438, 1.375, 0.800781, 0.902344, 1.28125, 1.17969, 1.78125, 1.3125, 1.17969, 0.945312,
-                1.29688, 0.761719, 1.34375, 1.8125, 0.730469, 0.972656, 1.53125, 1.71875, 1.375, 1.65625,
-                1.375, 1.05469, 1.71875, 1.09375, 1.71875, 1.25, 0.867188, 0.761719, 1.51562, 0.769531,
-                0.6875, 1.34375, 0.925781, 1.46875, 1.03125, 0.816406, 1.17188, 0.800781, 0.949219, 1.42188,
-                1.09375, 1.46875, 1.03125, 0.929688, 1.625, 1.57812, 1.57812, 0.769531, 0.929688, 1.17969,
-                0.691406, 1, 1.05469, 1.5, 1.6875, 1.40625, 0.949219, 0.746094, 1.625, 0.839844,
-                1.29688, 1.42188, 1.71875, 0.746094, 1.34375, 1.4375, 1.46875, 1.01562, 1.5, 1.32812,
-                0.714844, 0.878906, 1.28125, 0.832031, 1.375, 1.75, 1.78125, 1.46875, 1.01562, 1.5,
-                1, 1.625, 1.82812, 1.375, 1.26562, 1.3125, 1.4375, 1.25, 1.21875, 1.6875,
-                1.125, 1.46875, 1.15625, 0.746094, 0.722656, 0.832031, 1.6875, 1.65625, 1.6875, 1.82812}),
+                0.53125,  0.601562, 0.515625, 0.484375, 0.617188, 0.609375, 0.609375, 0.433594, 0.484375, 0.554688,
+                0.398438, 0.507812, 0.523438, 0.601562, 0.625,    0.585938, 0.492188, 0.421875, 0.617188, 0.458984,
+                0.570312, 0.59375,  0.625,    0.421875, 0.578125, 0.59375,  0.601562, 0.507812, 0.601562, 0.578125,
+                0.410156, 0.46875,  0.570312, 0.453125, 0.585938, 0.625,    0.632812, 0.601562, 0.507812, 0.601562,
+                0.507812, 0.617188, 0.632812, 0.585938, 0.570312, 0.578125, 0.59375,  0.5625,   0.554688, 0.625,
+                0.539062, 0.601562, 0.546875, 0.421875, 0.412109, 0.453125, 0.625,    0.617188, 0.625,    0.632812},
+            std::vector<T>{
+                0.648438, 1.375,    0.800781, 0.902344, 1.28125,  1.17969,  1.78125,  1.3125,   1.17969,  0.945312,
+                1.29688,  0.761719, 1.34375,  1.8125,   0.730469, 0.972656, 1.53125,  1.71875,  1.375,    1.65625,
+                1.375,    1.05469,  1.71875,  1.09375,  1.71875,  1.25,     0.867188, 0.761719, 1.51562,  0.769531,
+                0.6875,   1.34375,  0.925781, 1.46875,  1.03125,  0.816406, 1.17188,  0.800781, 0.949219, 1.42188,
+                1.09375,  1.46875,  1.03125,  0.929688, 1.625,    1.57812,  1.57812,  0.769531, 0.929688, 1.17969,
+                0.691406, 1,        1.05469,  1.5,      1.6875,   1.40625,  0.949219, 0.746094, 1.625,    0.839844,
+                1.29688,  1.42188,  1.71875,  0.746094, 1.34375,  1.4375,   1.46875,  1.01562,  1.5,      1.32812,
+                0.714844, 0.878906, 1.28125,  0.832031, 1.375,    1.75,     1.78125,  1.46875,  1.01562,  1.5,
+                1,        1.625,    1.82812,  1.375,    1.26562,  1.3125,   1.4375,   1.25,     1.21875,  1.6875,
+                1.125,    1.46875,  1.15625,  0.746094, 0.722656, 0.832031, 1.6875,   1.65625,  1.6875,   1.82812}),
     };
     return params;
 }
 
 std::vector<LSTMSequenceParams> generateCombinedParams() {
-    const std::vector<std::vector<LSTMSequenceParams>> generatedParams {
+    const std::vector<std::vector<LSTMSequenceParams>> generatedParams{
         generateParams<element::Type_t::f64>(),
         generateParams<element::Type_t::f32>(),
         generateParamsBF16<element::Type_t::f16>(),
@@ -3364,7 +3461,7 @@ std::vector<LSTMSequenceParams> generateCombinedParams() {
 }
 
 std::vector<LSTMSequenceV1Params> generateV1CombinedParams() {
-    const std::vector<std::vector<LSTMSequenceV1Params>> generatedParams {
+    const std::vector<std::vector<LSTMSequenceV1Params>> generatedParams{
         generateV1Params<element::Type_t::f64>(),
         generateV1Params<element::Type_t::f32>(),
         generateV1Params<element::Type_t::f16>(),
@@ -3378,10 +3475,14 @@ std::vector<LSTMSequenceV1Params> generateV1CombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_LSTMSequence_With_Hardcoded_Refs, ReferenceLSTMSequenceTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceLSTMSequenceTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_LSTMSequence_With_Hardcoded_Refs,
+                         ReferenceLSTMSequenceTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceLSTMSequenceTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_LSTMSequence_With_Hardcoded_Refs, ReferenceLSTMSequenceV1Test,
-    testing::ValuesIn(generateV1CombinedParams()), ReferenceLSTMSequenceV1Test::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_LSTMSequence_With_Hardcoded_Refs,
+                         ReferenceLSTMSequenceV1Test,
+                         testing::ValuesIn(generateV1CombinedParams()),
+                         ReferenceLSTMSequenceV1Test::getTestCaseName);
 
-} // namespace
\ No newline at end of file
+}  // namespace
\ No newline at end of file
diff --git a/src/plugins/template/tests/functional/op_reference/matmul.cpp b/src/plugins/template/tests/functional/op_reference/matmul.cpp
index a59eb87b3660ec..7b8d9551f68486 100644
--- a/src/plugins/template/tests/functional/op_reference/matmul.cpp
+++ b/src/plugins/template/tests/functional/op_reference/matmul.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/matmul.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/matmul.hpp"
 
 using namespace reference_tests;
 using namespace ov;
diff --git a/src/plugins/template/tests/functional/op_reference/matrix_nms.cpp b/src/plugins/template/tests/functional/op_reference/matrix_nms.cpp
index 95bbd6ebcac3d6..4c2fd3ee50755c 100644
--- a/src/plugins/template/tests/functional/op_reference/matrix_nms.cpp
+++ b/src/plugins/template/tests/functional/op_reference/matrix_nms.cpp
@@ -4,24 +4,29 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset8.hpp"
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
+#include "openvino/opsets/opset8.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct MatrixNmsParams {
-    MatrixNmsParams(
-        const opset8::MatrixNms::Attributes& attrs,
-        const reference_tests::Tensor& boxes, const reference_tests::Tensor& scores,
-        const reference_tests::Tensor& expectedSelectedScores, const reference_tests::Tensor& expectedSelectedIndices,
-        const reference_tests::Tensor& expectedValidOutputs, const std::string& testcaseName = "") :
-        attrs(attrs),
-        boxes(boxes), scores(scores),
-        expectedSelectedScores(expectedSelectedScores), expectedSelectedIndices(expectedSelectedIndices),
-        expectedValidOutputs(expectedValidOutputs), testcaseName(testcaseName) {}
+    MatrixNmsParams(const opset8::MatrixNms::Attributes& attrs,
+                    const reference_tests::Tensor& boxes,
+                    const reference_tests::Tensor& scores,
+                    const reference_tests::Tensor& expectedSelectedScores,
+                    const reference_tests::Tensor& expectedSelectedIndices,
+                    const reference_tests::Tensor& expectedValidOutputs,
+                    const std::string& testcaseName = "")
+        : attrs(attrs),
+          boxes(boxes),
+          scores(scores),
+          expectedSelectedScores(expectedSelectedScores),
+          expectedSelectedIndices(expectedSelectedIndices),
+          expectedValidOutputs(expectedValidOutputs),
+          testcaseName(testcaseName) {}
 
     opset8::MatrixNms::Attributes attrs;
     reference_tests::Tensor boxes;
@@ -83,384 +88,489 @@ std::vector<MatrixNmsParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<MatrixNmsParams> params {
+    std::vector<MatrixNmsParams> params{
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                0,                                          // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                0,                                         // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.0f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {3, 6}, std::vector<T_TH>{
-                1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.8, 0.00,
-                10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0, 0.1, 1.0, 1.1}),             // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{0, 3, 1}),                        // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),  // boxes
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 2, 6},
+                std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH,
+                                    {3, 6},
+                                    std::vector<T_TH>{1.00,
+                                                      0.95,
+                                                      0.00,
+                                                      0.00,
+                                                      1.00,
+                                                      1.00,
+                                                      1.00,
+                                                      0.8,
+                                                      0.00,
+                                                      10.00,
+                                                      1.00,
+                                                      11.00,
+                                                      1.00,
+                                                      0.13636364,
+                                                      0.0,
+                                                      0.1,
+                                                      1.0,
+                                                      1.1}),                       // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{0, 3, 1}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),           // expected_valid_outputs
             "matrix_nms_output_type_i64"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                0,                                          // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                0,                                         // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.0f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {3, 6}, std::vector<T_TH>{
-                1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.8, 0.00,
-                10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0, 0.1, 1.0, 1.1}),             // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{0, 3, 1}),                        // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),  // boxes
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 2, 6},
+                std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH,
+                                    {3, 6},
+                                    std::vector<T_TH>{1.00,
+                                                      0.95,
+                                                      0.00,
+                                                      0.00,
+                                                      1.00,
+                                                      1.00,
+                                                      1.00,
+                                                      0.8,
+                                                      0.00,
+                                                      10.00,
+                                                      1.00,
+                                                      11.00,
+                                                      1.00,
+                                                      0.13636364,
+                                                      0.0,
+                                                      0.1,
+                                                      1.0,
+                                                      1.1}),                       // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{0, 3, 1}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),           // expected_valid_outputs
             "matrix_nms_output_type_i32"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                0,                                          // background_class
-                opset8::MatrixNms::DecayFunction::GAUSSIAN, // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,    // sort_result_type
+                false,                                       // sort_result_across_batch
+                ET_IND,                                      // output_type
+                0.0f,                                        // score_threshold
+                3,                                           // nms_top_k
+                -1,                                          // keep_top_k
+                0,                                           // background_class
+                opset8::MatrixNms::DecayFunction::GAUSSIAN,  // decay_function
+                2.0f,                                        // gaussian_sigma
+                0.0f,                                        // post_threshold
+                true,                                        // normalized
             },
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {3, 6}, std::vector<T_TH>{
-                1.00,  0.95, 0.00,  0.00, 1.00,      1.00, 1.00, 0.8, 0.00,
-                10.00, 1.00, 11.00, 1.00, 0.1966116, 0.0,  0.1,  1.0, 1.1}),            // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{0, 3, 1}),                        // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),  // boxes
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 2, 6},
+                std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH,
+                                    {3, 6},
+                                    std::vector<T_TH>{1.00,
+                                                      0.95,
+                                                      0.00,
+                                                      0.00,
+                                                      1.00,
+                                                      1.00,
+                                                      1.00,
+                                                      0.8,
+                                                      0.00,
+                                                      10.00,
+                                                      1.00,
+                                                      11.00,
+                                                      1.00,
+                                                      0.1966116,
+                                                      0.0,
+                                                      0.1,
+                                                      1.0,
+                                                      1.1}),                       // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{0, 3, 1}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),           // expected_valid_outputs
             "matrix_nms_gaussian"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                0,                                          // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                0,                                         // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.0f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {6, 6}, std::vector<T_TH>{
-                1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.8, 0.00, 10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0, 0.1, 1.0, 1.1,
-                1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.8, 0.00, 10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0, 0.1, 1.0, 1.1}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {6, 1}, std::vector<T_IND>{0, 3, 1, 6, 9, 7}),               // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{3, 3}),                              // expected_valid_outputs
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH,
+                                    {6, 6},
+                                    std::vector<T_TH>{1.00,  0.95, 0.00,  0.00, 1.00,       1.00, 1.00, 0.8, 0.00,
+                                                      10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0,  0.1,  1.0, 1.1,
+                                                      1.00,  0.95, 0.00,  0.00, 1.00,       1.00, 1.00, 0.8, 0.00,
+                                                      10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0,  0.1,  1.0, 1.1}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {6, 1}, std::vector<T_IND>{0, 3, 1, 6, 9, 7}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{3, 3}),                 // expected_valid_outputs
             "matrix_nms_two_batches_two_classes"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                true,                                       // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.5f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                true,                                      // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                -1,                                        // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.5f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {8, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),                                 // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {8, 1}, std::vector<T_IND>{3, 0, 9, 6, 0, 6, 3, 9}),         // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),                              // expected_valid_outputs
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {8, 6},
+                std::vector<T_TH>{
+                    0.00,  0.95, 0.00,  10.00, 1.00,  11.00, 1.00,  0.95, 0.00, 0.00, 1.00, 1.00, 0.00,
+                    0.95,  0.00, 10.00, 1.00,  11.00, 1.00,  0.95,  0.00, 0.00, 1.00, 1.00, 0.00, 0.90,
+                    0.00,  0.00, 1.00,  1.00,  0.00,  0.90,  0.00,  0.00, 1.00, 1.00, 1.00, 0.80, 0.00,
+                    10.00, 1.00, 11.00, 1.00,  0.80,  0.00,  10.00, 1.00, 11.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND,
+                                    {8, 1},
+                                    std::vector<T_IND>{3, 0, 9, 6, 0, 6, 3, 9}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),       // expected_valid_outputs
             "matrix_nms_two_batches_two_classes_by_score_cross_batch"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::CLASSID, // sort_result_type
-                true,                                       // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.5f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::CLASSID,  // sort_result_type
+                true,                                        // sort_result_across_batch
+                ET_IND,                                      // output_type
+                0.0f,                                        // score_threshold
+                3,                                           // nms_top_k
+                -1,                                          // keep_top_k
+                -1,                                          // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,    // decay_function
+                2.0f,                                        // gaussian_sigma
+                0.5f,                                        // post_threshold
+                true,                                        // normalized
             },
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {8, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),                                 // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {8, 1}, std::vector<T_IND>{3, 0, 9, 6, 0, 3, 6, 9}),         // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),                              // expected_valid_outputs
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {8, 6},
+                std::vector<T_TH>{
+                    0.00, 0.95, 0.00,  10.00, 1.00,  11.00, 0.00,  0.90,  0.00, 0.00,  1.00, 1.00, 0.00,
+                    0.95, 0.00, 10.00, 1.00,  11.00, 0.00,  0.90,  0.00,  0.00, 1.00,  1.00, 1.00, 0.95,
+                    0.00, 0.00, 1.00,  1.00,  1.00,  0.80,  0.00,  10.00, 1.00, 11.00, 1.00, 0.95, 0.00,
+                    0.00, 1.00, 1.00,  1.00,  0.80,  0.00,  10.00, 1.00,  11.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND,
+                                    {8, 1},
+                                    std::vector<T_IND>{3, 0, 9, 6, 0, 3, 6, 9}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),       // expected_valid_outputs
             "matrix_nms_two_batches_two_classes_by_classid_cross_batch"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::CLASSID, // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                3,                                          // keep_top_k
-                0,                                          // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::CLASSID,  // sort_result_type
+                false,                                       // sort_result_across_batch
+                ET_IND,                                      // output_type
+                0.0f,                                        // score_threshold
+                3,                                           // nms_top_k
+                3,                                           // keep_top_k
+                0,                                           // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,    // decay_function
+                2.0f,                                        // gaussian_sigma
+                0.0f,                                        // post_threshold
+                true,                                        // normalized
             },
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {6, 6}, std::vector<T_TH>{
-                1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.8, 0.00, 10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0, 0.1, 1.0, 1.1,
-                1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.8, 0.00, 10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0, 0.1, 1.0, 1.1}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {6, 1}, std::vector<T_IND>{0, 3, 1, 6, 9, 7}),               // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{3, 3}),                              // expected_valid_outputs
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH,
+                                    {6, 6},
+                                    std::vector<T_TH>{1.00,  0.95, 0.00,  0.00, 1.00,       1.00, 1.00, 0.8, 0.00,
+                                                      10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0,  0.1,  1.0, 1.1,
+                                                      1.00,  0.95, 0.00,  0.00, 1.00,       1.00, 1.00, 0.8, 0.00,
+                                                      10.00, 1.00, 11.00, 1.00, 0.13636364, 0.0,  0.1,  1.0, 1.1}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {6, 1}, std::vector<T_IND>{0, 3, 1, 6, 9, 7}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{3, 3}),                 // expected_valid_outputs
             "matrix_nms_by_keep_top_k"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                -1,                                        // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.0f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {6, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.0, 10.0, 1.0, 11.0, 1.00, 0.95,       0.0, 0.0, 1.0, 1.0, 0.00, 0.9,        0.0, 0.0, 1.0, 1.0,
-                1.00, 0.8,  0.0, 10.0, 1.0, 11.0, 0.00, 0.13636364, 0.0, 0.1, 1.0, 1.1, 1.00, 0.13636364, 0.0, 0.1, 1.0, 1.1}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {6, 1}, std::vector<T_IND>{3, 0, 0, 3, 1, 1}),               // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{6}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),  // boxes
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 2, 6},
+                std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {6, 6},
+                std::vector<T_TH>{0.00, 0.95,       0.0, 10.0, 1.0, 11.0, 1.00, 0.95,       0.0, 0.0,  1.0, 1.0,
+                                  0.00, 0.9,        0.0, 0.0,  1.0, 1.0,  1.00, 0.8,        0.0, 10.0, 1.0, 11.0,
+                                  0.00, 0.13636364, 0.0, 0.1,  1.0, 1.1,  1.00, 0.13636364, 0.0, 0.1,  1.0, 1.1}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {6, 1}, std::vector<T_IND>{3, 0, 0, 3, 1, 1}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{6}),                    // expected_valid_outputs
             "matrix_nms_background"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                -1,                                        // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.0f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                1.0, 1.0,  0.0, 0.0,  0.0, 0.1,  1.0, 1.1,  0.0, 0.9,   1.0, -0.1,
-                0.0, 10.0, 1.0, 11.0, 1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {3, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.0, 10.0, 1.0, 11.0, 0.00, 0.9, 1.0, 1.0, 0.0, 0.0, 0.00, 0.75, 0.0, 0.1, 1.0, 1.1}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{3, 0, 1}),                        // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{1.0, 1.0,  0.0,  0.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  0.9, 1.0,  -0.1, 0.0,   10.0, 1.0,  11.0, 1.0, 10.1,
+                                                                  0.0, 11.1, 1.0,  101.0, 0.0,  100.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH,
+                                    {3, 6},
+                                    std::vector<T_TH>{0.00,
+                                                      0.95,
+                                                      0.0,
+                                                      10.0,
+                                                      1.0,
+                                                      11.0,
+                                                      0.00,
+                                                      0.9,
+                                                      1.0,
+                                                      1.0,
+                                                      0.0,
+                                                      0.0,
+                                                      0.00,
+                                                      0.75,
+                                                      0.0,
+                                                      0.1,
+                                                      1.0,
+                                                      1.1}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{3, 0, 1}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),           // expected_valid_outputs
             "matrix_nms_flipped_coordinates"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.8f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                -1,                                        // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.8f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {2, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.9, 0.00, 0.00, 1.00, 1.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {2, 1}, std::vector<T_IND>{3, 0}),                           // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {2, 6},
+                std::vector<T_TH>{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.9, 0.00, 0.00, 1.00, 1.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {2, 1}, std::vector<T_IND>{3, 0}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}),        // expected_valid_outputs
             "matrix_nms_post_threshold"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.3f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                -1,                                        // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.3f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,
-                1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}),           // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 10}, std::vector<T_TH>{
-                0.4, 0.01, 0.2, 0.09, 0.15, 0.05, 0.02, 0.03, 0.05, 0.0}),              // scores
-            reference_tests::Tensor(ET_TH, {1, 6}, std::vector<T_TH>{
-                0.00, 0.40, 0.00, 0.00, 1.00, 1.00}),                                   // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{0}),                              // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                   0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                   0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                   0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                   0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}),  // boxes
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 1, 10},
+                std::vector<T_TH>{0.4, 0.01, 0.2, 0.09, 0.15, 0.05, 0.02, 0.03, 0.05, 0.0}),  // scores
+            reference_tests::Tensor(ET_TH,
+                                    {1, 6},
+                                    std::vector<T_TH>{0.00, 0.40, 0.00, 0.00, 1.00, 1.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{0}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),     // expected_valid_outputs
             "matrix_nms_identical_boxes"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                2,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                2,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                -1,                                        // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.0f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {2, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {2, 1}, std::vector<T_IND>{3, 0}),                           // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {2, 6},
+                std::vector<T_TH>{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {2, 1}, std::vector<T_IND>{3, 0}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}),        // expected_valid_outputs
             "matrix_nms_nms_top_k"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                0.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                0.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                -1,                                        // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.0f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}),                  // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 1}, std::vector<T_TH>{0.9}),                           // scores
-            reference_tests::Tensor(ET_TH, {1, 6}, std::vector<T_TH>{
-                0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),                                   // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{0}),                              // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 1}, std::vector<T_TH>{0.9}),           // scores
+            reference_tests::Tensor(ET_TH,
+                                    {1, 6},
+                                    std::vector<T_TH>{0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{0}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),     // expected_valid_outputs
             "matrix_nms_single_box"),
         MatrixNmsParams(
             {
-                opset8::MatrixNms::SortResultType::SCORE,   // sort_result_type
-                false,                                      // sort_result_across_batch
-                ET_IND,                                     // output_type
-                2.0f,                                       // score_threshold
-                3,                                          // nms_top_k
-                -1,                                         // keep_top_k
-                -1,                                         // background_class
-                opset8::MatrixNms::DecayFunction::LINEAR,   // decay_function
-                2.0f,                                       // gaussian_sigma
-                0.0f,                                       // post_threshold
-                true,                                       // normalized
+                opset8::MatrixNms::SortResultType::SCORE,  // sort_result_type
+                false,                                     // sort_result_across_batch
+                ET_IND,                                    // output_type
+                2.0f,                                      // score_threshold
+                3,                                         // nms_top_k
+                -1,                                        // keep_top_k
+                -1,                                        // background_class
+                opset8::MatrixNms::DecayFunction::LINEAR,  // decay_function
+                2.0f,                                      // gaussian_sigma
+                0.0f,                                      // post_threshold
+                true,                                      // normalized
             },
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {0, 6}, std::vector<T_TH>{}),                                 // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {0, 1}, std::vector<T_IND>{}),                               // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{0}),                                 // expected_valid_outputs
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH, {0, 6}, std::vector<T_TH>{}),    // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {0, 1}, std::vector<T_IND>{}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{0}),    // expected_valid_outputs
             "matrix_nms_no_output"),
     };
     return params;
 }
 
 std::vector<MatrixNmsParams> generateCombinedParams() {
-    const std::vector<std::vector<MatrixNmsParams>> generatedParams {
+    const std::vector<std::vector<MatrixNmsParams>> generatedParams{
         generateParams<element::Type_t::bf16, element::Type_t::bf16, element::Type_t::i32>(),
         generateParams<element::Type_t::f16, element::Type_t::f16, element::Type_t::i32>(),
         generateParams<element::Type_t::f32, element::Type_t::f32, element::Type_t::i32>(),
@@ -476,6 +586,8 @@ std::vector<MatrixNmsParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_MatrixNms_With_Hardcoded_Refs, ReferenceMatrixNmsTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceMatrixNmsTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_MatrixNms_With_Hardcoded_Refs,
+                         ReferenceMatrixNmsTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceMatrixNmsTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/max_pool.cpp b/src/plugins/template/tests/functional/op_reference/max_pool.cpp
index 1ae548a93ee471..2a599eb58315d8 100644
--- a/src/plugins/template/tests/functional/op_reference/max_pool.cpp
+++ b/src/plugins/template/tests/functional/op_reference/max_pool.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/max_pool.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/max_pool.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
diff --git a/src/plugins/template/tests/functional/op_reference/maximum.cpp b/src/plugins/template/tests/functional/op_reference/maximum.cpp
index faf8e328a1323c..1fafa5499d0f9f 100644
--- a/src/plugins/template/tests/functional/op_reference/maximum.cpp
+++ b/src/plugins/template/tests/functional/op_reference/maximum.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/maximum.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/maximum.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,11 +16,11 @@ namespace {
 struct MaximumParams {
     template <class IT>
     MaximumParams(const PartialShape& iShape1,
-              const PartialShape& iShape2,
-              const element::Type& iType,
-              const std::vector<IT>& iValues1,
-              const std::vector<IT>& iValues2,
-              const std::vector<IT>& oValues)
+                  const PartialShape& iShape2,
+                  const element::Type& iType,
+                  const std::vector<IT>& iValues1,
+                  const std::vector<IT>& iValues2,
+                  const std::vector<IT>& oValues)
         : pshape1(iShape1),
           pshape2(iShape2),
           inType(iType),
@@ -57,9 +59,9 @@ class ReferenceMaximumLayerTest : public testing::TestWithParam<MaximumParams>,
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto maximum = std::make_shared<op::v1::Maximum>(in1, in2);
@@ -76,14 +78,12 @@ template <element::Type_t IN_ET>
 std::vector<MaximumParams> generateParamsForMaximumFloat() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<MaximumParams> params{
-        MaximumParams(ov::PartialShape{2, 2, 2},
-                       ov::PartialShape{2, 2, 2},
-                       IN_ET,
-                       std::vector<T>{1, 8, -8, 17, -0.5, 0.5, 2, 1},
-                       std::vector<T>{1, 2, 4, 8, 0, 0, 1, 1.5},
-                       std::vector<T>{1, 8, 4, 17, 0, 0.5, 2, 1.5})
-    };
+    std::vector<MaximumParams> params{MaximumParams(ov::PartialShape{2, 2, 2},
+                                                    ov::PartialShape{2, 2, 2},
+                                                    IN_ET,
+                                                    std::vector<T>{1, 8, -8, 17, -0.5, 0.5, 2, 1},
+                                                    std::vector<T>{1, 2, 4, 8, 0, 0, 1, 1.5},
+                                                    std::vector<T>{1, 8, 4, 17, 0, 0.5, 2, 1.5})};
     return params;
 }
 
@@ -91,14 +91,12 @@ template <element::Type_t IN_ET>
 std::vector<MaximumParams> generateParamsForMaximumInt32() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<MaximumParams> params{
-        MaximumParams(ov::PartialShape{2, 2},
-                       ov::PartialShape{2, 2},
-                       IN_ET,
-                       std::vector<T>{0x40000140, 0x40000001, -8, 17},
-                       std::vector<T>{0x40000170, 0x40000000, 4, 8},
-                       std::vector<T>{0x40000170, 0x40000001, 4, 17})
-    };
+    std::vector<MaximumParams> params{MaximumParams(ov::PartialShape{2, 2},
+                                                    ov::PartialShape{2, 2},
+                                                    IN_ET,
+                                                    std::vector<T>{0x40000140, 0x40000001, -8, 17},
+                                                    std::vector<T>{0x40000170, 0x40000000, 4, 8},
+                                                    std::vector<T>{0x40000170, 0x40000001, 4, 17})};
     return params;
 }
 
@@ -106,14 +104,12 @@ template <element::Type_t IN_ET>
 std::vector<MaximumParams> generateParamsForMaximumInt64() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<MaximumParams> params{
-        MaximumParams(ov::PartialShape{2, 2, 2},
-                       ov::PartialShape{2, 2, 2},
-                       IN_ET,
-                       std::vector<T>{1, 8, -8, 17, -5, 67635216, 2, 17179887632},
-                       std::vector<T>{1, 2, 4, 8, 0, 18448, 1, 28059},
-                       std::vector<T>{1, 8, 4, 17, 0, 67635216, 2, 17179887632})
-    };
+    std::vector<MaximumParams> params{MaximumParams(ov::PartialShape{2, 2, 2},
+                                                    ov::PartialShape{2, 2, 2},
+                                                    IN_ET,
+                                                    std::vector<T>{1, 8, -8, 17, -5, 67635216, 2, 17179887632},
+                                                    std::vector<T>{1, 2, 4, 8, 0, 18448, 1, 28059},
+                                                    std::vector<T>{1, 8, 4, 17, 0, 67635216, 2, 17179887632})};
     return params;
 }
 
@@ -121,22 +117,18 @@ template <element::Type_t IN_ET>
 std::vector<MaximumParams> generateParamsForMaximumUnsignedInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<MaximumParams> params{
-        MaximumParams(ov::PartialShape{2, 2, 2},
-                       ov::PartialShape{2, 2, 2},
-                       IN_ET,
-                       std::vector<T>{1, 8, 7, 17, 5, 67635216, 2, 17179887},
-                       std::vector<T>{1, 2, 4, 8, 0, 18448, 1, 28059},
-                       std::vector<T>{1, 8, 7, 17, 5, 67635216, 2, 17179887})
-    };
+    std::vector<MaximumParams> params{MaximumParams(ov::PartialShape{2, 2, 2},
+                                                    ov::PartialShape{2, 2, 2},
+                                                    IN_ET,
+                                                    std::vector<T>{1, 8, 7, 17, 5, 67635216, 2, 17179887},
+                                                    std::vector<T>{1, 2, 4, 8, 0, 18448, 1, 28059},
+                                                    std::vector<T>{1, 8, 7, 17, 5, 67635216, 2, 17179887})};
     return params;
 }
 
 std::vector<MaximumParams> generateCombinedParamsForMaximumFloat() {
-    const std::vector<std::vector<MaximumParams>> allTypeParams{
-        generateParamsForMaximumFloat<element::Type_t::f32>(),
-        generateParamsForMaximumFloat<element::Type_t::f16>()
-    };
+    const std::vector<std::vector<MaximumParams>> allTypeParams{generateParamsForMaximumFloat<element::Type_t::f32>(),
+                                                                generateParamsForMaximumFloat<element::Type_t::f16>()};
 
     std::vector<MaximumParams> combinedParams;
 
@@ -148,9 +140,7 @@ std::vector<MaximumParams> generateCombinedParamsForMaximumFloat() {
 }
 
 std::vector<MaximumParams> generateCombinedParamsForMaximumInt32() {
-    const std::vector<std::vector<MaximumParams>> allTypeParams{
-        generateParamsForMaximumInt32<element::Type_t::i32>()
-    };
+    const std::vector<std::vector<MaximumParams>> allTypeParams{generateParamsForMaximumInt32<element::Type_t::i32>()};
 
     std::vector<MaximumParams> combinedParams;
 
@@ -162,9 +152,7 @@ std::vector<MaximumParams> generateCombinedParamsForMaximumInt32() {
 }
 
 std::vector<MaximumParams> generateCombinedParamsForMaximumInt64() {
-    const std::vector<std::vector<MaximumParams>> allTypeParams{
-        generateParamsForMaximumInt64<element::Type_t::i64>()
-    };
+    const std::vector<std::vector<MaximumParams>> allTypeParams{generateParamsForMaximumInt64<element::Type_t::i64>()};
 
     std::vector<MaximumParams> combinedParams;
 
@@ -178,8 +166,7 @@ std::vector<MaximumParams> generateCombinedParamsForMaximumInt64() {
 std::vector<MaximumParams> generateCombinedParamsForMaximumUnsignedInt() {
     const std::vector<std::vector<MaximumParams>> allTypeParams{
         generateParamsForMaximumUnsignedInt<element::Type_t::u64>(),
-        generateParamsForMaximumUnsignedInt<element::Type_t::u32>()
-    };
+        generateParamsForMaximumUnsignedInt<element::Type_t::u32>()};
 
     std::vector<MaximumParams> combinedParams;
 
@@ -190,28 +177,24 @@ std::vector<MaximumParams> generateCombinedParamsForMaximumUnsignedInt() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Maximum_Float_With_Hardcoded_Refs,
-    ReferenceMaximumLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForMaximumFloat()),
-    ReferenceMaximumLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Maximum_Int32_With_Hardcoded_Refs,
-    ReferenceMaximumLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForMaximumInt32()),
-    ReferenceMaximumLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Maximume_Int64_With_Hardcoded_Refs,
-    ReferenceMaximumLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForMaximumInt64()),
-    ReferenceMaximumLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Maximume_UnsignedInt_With_Hardcoded_Refs,
-    ReferenceMaximumLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForMaximumUnsignedInt()),
-    ReferenceMaximumLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Maximum_Float_With_Hardcoded_Refs,
+                         ReferenceMaximumLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForMaximumFloat()),
+                         ReferenceMaximumLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Maximum_Int32_With_Hardcoded_Refs,
+                         ReferenceMaximumLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForMaximumInt32()),
+                         ReferenceMaximumLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Maximume_Int64_With_Hardcoded_Refs,
+                         ReferenceMaximumLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForMaximumInt64()),
+                         ReferenceMaximumLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Maximume_UnsignedInt_With_Hardcoded_Refs,
+                         ReferenceMaximumLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForMaximumUnsignedInt()),
+                         ReferenceMaximumLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/memory.cpp b/src/plugins/template/tests/functional/op_reference/memory.cpp
index 01c7a321b53e5e..b2fb97d6acc76e 100644
--- a/src/plugins/template/tests/functional/op_reference/memory.cpp
+++ b/src/plugins/template/tests/functional/op_reference/memory.cpp
@@ -699,7 +699,6 @@ INSTANTIATE_TEST_SUITE_P(smoke_Memory_With_Hardcoded_Refs,
                          ::testing::ValuesIn(generateCombinedParamsForReadValueAssignAddReset()),
                          ReferenceReadValueAssignAddResetLayerTest::getTestCaseName);
 
-
 class ReferenceReadValueAssignAddModifyLayerTest : public ReferenceMemoryTest {
 protected:
     std::shared_ptr<ov::Model> CreateFunction(const ov::Shape& input_shape,
@@ -861,7 +860,6 @@ INSTANTIATE_TEST_SUITE_P(smoke_Memory_With_Hardcoded_Refs,
                          ::testing::ValuesIn(generateCombinedParamsForReadValueAssignAddModify()),
                          ReferenceReadValueAssignAddModifyLayerTest::getTestCaseName);
 
-
 class ReferenceReadValueAssignAddMultiVariableModifyLayerTest : public ReferenceMemoryTest {
 protected:
     std::shared_ptr<ov::Model> CreateFunction(const ov::Shape& input_shape,
@@ -923,20 +921,20 @@ std::vector<MemoryTestParams> generateParamsForReadValueAssignAddMultiVariableMo
     }
 
     std::transform(first_result_shape1.begin(),
-                first_result_shape1.end(),
-                first_result_shape1.begin(),
-                first_result_shape1.begin(),
-                std::plus<T>());
+                   first_result_shape1.end(),
+                   first_result_shape1.begin(),
+                   first_result_shape1.begin(),
+                   std::plus<T>());
     std::transform(first_result_shape22.begin(),
-                first_result_shape22.end(),
-                first_result_shape22.begin(),
-                first_result_shape22.begin(),
-                std::plus<T>());
+                   first_result_shape22.end(),
+                   first_result_shape22.begin(),
+                   first_result_shape22.begin(),
+                   std::plus<T>());
     std::transform(first_result_shape123.begin(),
-                first_result_shape123.end(),
-                first_result_shape123.begin(),
-                first_result_shape123.begin(),
-                std::plus<T>());
+                   first_result_shape123.end(),
+                   first_result_shape123.begin(),
+                   first_result_shape123.begin(),
+                   std::plus<T>());
 
     for (size_t i = count_runs - reset_on_run; i < count_runs; i++) {
         std::transform(new_result_shape1.begin(),
diff --git a/src/plugins/template/tests/functional/op_reference/minimum.cpp b/src/plugins/template/tests/functional/op_reference/minimum.cpp
index 852d299cbe7ec6..f955c76190eebe 100644
--- a/src/plugins/template/tests/functional/op_reference/minimum.cpp
+++ b/src/plugins/template/tests/functional/op_reference/minimum.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/minimum.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/minimum.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -13,8 +14,10 @@ using namespace reference_tests;
 struct MinimumParams {
     template <class IT, class OT>
     MinimumParams(const PartialShape& s,
-                  const element::Type& iType, const element::Type& oType,
-                  const std::vector<IT>& iValues1, const std::vector<IT>& iValues2,
+                  const element::Type& iType,
+                  const element::Type& oType,
+                  const std::vector<IT>& iValues1,
+                  const std::vector<IT>& iValues2,
                   const std::vector<OT>& oValues)
         : pshape(s),
           inType(iType),
@@ -60,47 +63,48 @@ TEST_P(ReferenceMinimumLayerTest, CompareWithHardcodedRefs) {
 }
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Minimum, ReferenceMinimumLayerTest, ::testing::Values(
-        MinimumParams(PartialShape {8},
-                   element::u8,
-                   element::u8,
-                   std::vector<uint8_t> {1, 8, 8, 17, 5, 5, 2, 3},
-                   std::vector<uint8_t> {1, 2, 4, 8, 0, 2, 1, 200},
-                   std::vector<uint8_t> {1, 2, 4, 8, 0, 2, 1, 3}),
-        MinimumParams(PartialShape {8},
-                   element::u16,
-                   element::u16,
-                   std::vector<uint16_t> {1, 8, 8, 17, 5, 7, 123, 3},
-                   std::vector<uint16_t> {1, 2, 4, 8, 0, 2, 1, 1037},
-                   std::vector<uint16_t> {1, 2, 4, 8, 0, 2, 1, 3}),
-        MinimumParams(PartialShape {8},
-                   element::u32,
-                   element::u32,
-                   std::vector<uint32_t> {1, 8, 8, 17, 5, 5, 2, 1},
-                   std::vector<uint32_t> {1, 2, 4, 8, 0, 2, 1, 222},
-                   std::vector<uint32_t> {1, 2, 4, 8, 0, 2, 1, 1}),
-        MinimumParams(PartialShape {8},
-                   element::u64,
-                   element::u64,
-                   std::vector<uint64_t> {1, 8, 8, 17, 5, 5, 2, 13},
-                   std::vector<uint64_t> {1, 2, 4, 8, 0, 2, 1, 2222},
-                   std::vector<uint64_t> {1, 2, 4, 8, 0, 2, 1, 13}),
-        MinimumParams(PartialShape {8},
-                   element::f32,
-                   element::f32,
-                   std::vector<float> {1, 8, -8, 17, -0.5, 0.5, 2, 1},
-                   std::vector<float> {1, 2, 4, 8, 0, 0, 1, 1.5},
-                   std::vector<float> {1, 2, -8, 8, -.5, 0, 1, 1}),
-        MinimumParams(PartialShape {8},
-                   element::i32,
-                   element::i32,
-                   std::vector<int32_t> {1, 8, -8, 17, -5, 67635216, 2, 1},
-                   std::vector<int32_t> {1, 2, 4, 8, 0, 18448, 1, 6},
-                   std::vector<int32_t> {1, 2, -8, 8, -5, 18448, 1, 1}),
-        MinimumParams(PartialShape {8},
-                   element::i64,
-                   element::i64,
-                   std::vector<int64_t> {1, 8, -8, 17, -5, 67635216, 2, 17179887632},
-                   std::vector<int64_t> {1, 2, 4, 8, 0, 18448, 1, 280592},
-                   std::vector<int64_t> {1, 2, -8, 8, -5, 18448, 1, 280592})),
-        ReferenceMinimumLayerTest::getTestCaseName);
+    smoke_Minimum,
+    ReferenceMinimumLayerTest,
+    ::testing::Values(MinimumParams(PartialShape{8},
+                                    element::u8,
+                                    element::u8,
+                                    std::vector<uint8_t>{1, 8, 8, 17, 5, 5, 2, 3},
+                                    std::vector<uint8_t>{1, 2, 4, 8, 0, 2, 1, 200},
+                                    std::vector<uint8_t>{1, 2, 4, 8, 0, 2, 1, 3}),
+                      MinimumParams(PartialShape{8},
+                                    element::u16,
+                                    element::u16,
+                                    std::vector<uint16_t>{1, 8, 8, 17, 5, 7, 123, 3},
+                                    std::vector<uint16_t>{1, 2, 4, 8, 0, 2, 1, 1037},
+                                    std::vector<uint16_t>{1, 2, 4, 8, 0, 2, 1, 3}),
+                      MinimumParams(PartialShape{8},
+                                    element::u32,
+                                    element::u32,
+                                    std::vector<uint32_t>{1, 8, 8, 17, 5, 5, 2, 1},
+                                    std::vector<uint32_t>{1, 2, 4, 8, 0, 2, 1, 222},
+                                    std::vector<uint32_t>{1, 2, 4, 8, 0, 2, 1, 1}),
+                      MinimumParams(PartialShape{8},
+                                    element::u64,
+                                    element::u64,
+                                    std::vector<uint64_t>{1, 8, 8, 17, 5, 5, 2, 13},
+                                    std::vector<uint64_t>{1, 2, 4, 8, 0, 2, 1, 2222},
+                                    std::vector<uint64_t>{1, 2, 4, 8, 0, 2, 1, 13}),
+                      MinimumParams(PartialShape{8},
+                                    element::f32,
+                                    element::f32,
+                                    std::vector<float>{1, 8, -8, 17, -0.5, 0.5, 2, 1},
+                                    std::vector<float>{1, 2, 4, 8, 0, 0, 1, 1.5},
+                                    std::vector<float>{1, 2, -8, 8, -.5, 0, 1, 1}),
+                      MinimumParams(PartialShape{8},
+                                    element::i32,
+                                    element::i32,
+                                    std::vector<int32_t>{1, 8, -8, 17, -5, 67635216, 2, 1},
+                                    std::vector<int32_t>{1, 2, 4, 8, 0, 18448, 1, 6},
+                                    std::vector<int32_t>{1, 2, -8, 8, -5, 18448, 1, 1}),
+                      MinimumParams(PartialShape{8},
+                                    element::i64,
+                                    element::i64,
+                                    std::vector<int64_t>{1, 8, -8, 17, -5, 67635216, 2, 17179887632},
+                                    std::vector<int64_t>{1, 2, 4, 8, 0, 18448, 1, 280592},
+                                    std::vector<int64_t>{1, 2, -8, 8, -5, 18448, 1, 280592})),
+    ReferenceMinimumLayerTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/op_reference/mish.cpp b/src/plugins/template/tests/functional/op_reference/mish.cpp
index 9557e6ef61b194..d78b90d02e1104 100644
--- a/src/plugins/template/tests/functional/op_reference/mish.cpp
+++ b/src/plugins/template/tests/functional/op_reference/mish.cpp
@@ -2,10 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/mish.hpp"
+
 #include <gtest/gtest.h>
 
 #include <random>
-#include "openvino/op/mish.hpp"
+
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -14,8 +16,11 @@ using namespace ov;
 namespace {
 struct MishParams {
     template <class IT>
-    MishParams(const ov::PartialShape& dynamicShape, const ov::Shape& inputShape,
-               const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
+    MishParams(const ov::PartialShape& dynamicShape,
+               const ov::Shape& inputShape,
+               const ov::element::Type& iType,
+               const std::vector<IT>& iValues,
+               const std::vector<IT>& oValues,
                const std::string& test_name = "")
         : dynamicShape(dynamicShape),
           inputShape(inputShape),
@@ -61,7 +66,7 @@ class ReferenceMishLayerTest : public testing::TestWithParam<MishParams>, public
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Mish = std::make_shared<op::v4::Mish>(in);
-        return std::make_shared<ov::Model>(NodeVector {Mish}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Mish}, ParameterVector{in});
     }
 };
 
@@ -70,7 +75,9 @@ TEST_P(ReferenceMishLayerTest, CompareWithRefs) {
 }
 
 template <element::Type_t IN_ET>
-std::vector<MishParams> generateMishFloatParams(const PartialShape& dynamicShape, const Shape& staticShape, const std::string& test_name = "") {
+std::vector<MishParams> generateMishFloatParams(const PartialShape& dynamicShape,
+                                                const Shape& staticShape,
+                                                const std::string& test_name = "") {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     // generate input tensor (with possible type conversion)
@@ -92,28 +99,27 @@ std::vector<MishParams> generateMishFloatParams(const PartialShape& dynamicShape
     std::vector<MishParams> mishParams;
 
     if (test_name != "") {
-        mishParams = {
-            MishParams(dynamicShape, staticShape, IN_ET, input, expected, test_name)
-        };
+        mishParams = {MishParams(dynamicShape, staticShape, IN_ET, input, expected, test_name)};
     } else {
-        mishParams = {
-            MishParams(dynamicShape, staticShape, IN_ET, input, expected)
-        };
+        mishParams = {MishParams(dynamicShape, staticShape, IN_ET, input, expected)};
     }
     return mishParams;
 }
 
 std::vector<MishParams> generateMishCombinedParams() {
-    const std::vector<std::vector<MishParams>> mishTypeParams {
+    const std::vector<std::vector<MishParams>> mishTypeParams{
         generateMishFloatParams<element::Type_t::f32>({2, 5}, {2, 5}),
         generateMishFloatParams<element::Type_t::f32>({2, 3, 4, 5}, {2, 3, 4, 5}),
         generateMishFloatParams<element::Type_t::f32>(PartialShape::dynamic(), {2, 3, 4, 5}),
-        generateMishFloatParams<element::Type_t::f32>({2, Dimension::dynamic(), 4, 5}, {2, 3, 4, 5}, "dimensionDynamic"),
+        generateMishFloatParams<element::Type_t::f32>({2, Dimension::dynamic(), 4, 5},
+                                                      {2, 3, 4, 5},
+                                                      "dimensionDynamic"),
         generateMishFloatParams<element::Type_t::f16>({2, 5}, {2, 5}),
         generateMishFloatParams<element::Type_t::f16>({2, 3, 4, 5}, {2, 3, 4, 5}),
         generateMishFloatParams<element::Type_t::f16>(PartialShape::dynamic(), {2, 3, 4, 5}),
-        generateMishFloatParams<element::Type_t::f16>({2, Dimension::dynamic(), 4, 5}, {2, 3, 4, 5}, "dimensionDynamic")
-        };
+        generateMishFloatParams<element::Type_t::f16>({2, Dimension::dynamic(), 4, 5},
+                                                      {2, 3, 4, 5},
+                                                      "dimensionDynamic")};
     std::vector<MishParams> combinedParams;
 
     for (const auto& params : mishTypeParams) {
@@ -122,7 +128,9 @@ std::vector<MishParams> generateMishCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Mish_With_Hardcoded_Refs, ReferenceMishLayerTest,
-    testing::ValuesIn(generateMishCombinedParams()), ReferenceMishLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Mish_With_Hardcoded_Refs,
+                         ReferenceMishLayerTest,
+                         testing::ValuesIn(generateMishCombinedParams()),
+                         ReferenceMishLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/mod.cpp b/src/plugins/template/tests/functional/op_reference/mod.cpp
index f1283194571d07..e72c725b78ea31 100644
--- a/src/plugins/template/tests/functional/op_reference/mod.cpp
+++ b/src/plugins/template/tests/functional/op_reference/mod.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/mod.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/mod.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -57,9 +59,9 @@ class ReferenceModLayerTest : public testing::TestWithParam<ModParams>, public C
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto mod = std::make_shared<op::v1::Mod>(in1, in2);
@@ -89,9 +91,9 @@ class ReferenceModInPlaceLayerTest : public testing::TestWithParam<ModParams>, p
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         auto mod = std::make_shared<op::v1::Mod>(in1, in2);
@@ -113,38 +115,36 @@ template <element::Type_t IN_ET>
 std::vector<ModParams> generateParamsForMod() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ModParams> params{
-        ModParams(ov::PartialShape{1, 2},
-                       ov::PartialShape{1, 2},
-                       IN_ET,
-                       std::vector<T>{256, 56},
-                       std::vector<T>{256, 56},
-                       std::vector<T>{0, 0}),
-        ModParams(ov::PartialShape{2, 2},
-                       ov::PartialShape{2, 2},
-                       IN_ET,
-                       std::vector<T>{256, 56, 21, 14},
-                       std::vector<T>{112, 56, 6, 8},
-                       std::vector<T>{32, 0, 3, 6}),
-        ModParams(ov::PartialShape{1, 2},
-                       ov::PartialShape{3, 2, 2},
-                       IN_ET,
-                       std::vector<T>{1, 2},
-                       std::vector<T>{5, 6, 7, 8, 2, 3, 1, 5, 6, 7, 1, 3},
-                       std::vector<T>{1, 2, 1, 2, 1, 2, 0, 2, 1, 2, 0, 2}),
-        ModParams(ov::PartialShape{1},
-                       ov::PartialShape{1},
-                       IN_ET,
-                       std::vector<T>{57},
-                       std::vector<T>{13},
-                       std::vector<T>{5}),
-        ModParams(ov::PartialShape{2, 2},
-                       ov::PartialShape{1},
-                       IN_ET,
-                       std::vector<T>{2, 4, 7, 8},
-                       std::vector<T>{8},
-                       std::vector<T>{2, 4, 7, 0})
-    };
+    std::vector<ModParams> params{ModParams(ov::PartialShape{1, 2},
+                                            ov::PartialShape{1, 2},
+                                            IN_ET,
+                                            std::vector<T>{256, 56},
+                                            std::vector<T>{256, 56},
+                                            std::vector<T>{0, 0}),
+                                  ModParams(ov::PartialShape{2, 2},
+                                            ov::PartialShape{2, 2},
+                                            IN_ET,
+                                            std::vector<T>{256, 56, 21, 14},
+                                            std::vector<T>{112, 56, 6, 8},
+                                            std::vector<T>{32, 0, 3, 6}),
+                                  ModParams(ov::PartialShape{1, 2},
+                                            ov::PartialShape{3, 2, 2},
+                                            IN_ET,
+                                            std::vector<T>{1, 2},
+                                            std::vector<T>{5, 6, 7, 8, 2, 3, 1, 5, 6, 7, 1, 3},
+                                            std::vector<T>{1, 2, 1, 2, 1, 2, 0, 2, 1, 2, 0, 2}),
+                                  ModParams(ov::PartialShape{1},
+                                            ov::PartialShape{1},
+                                            IN_ET,
+                                            std::vector<T>{57},
+                                            std::vector<T>{13},
+                                            std::vector<T>{5}),
+                                  ModParams(ov::PartialShape{2, 2},
+                                            ov::PartialShape{1},
+                                            IN_ET,
+                                            std::vector<T>{2, 4, 7, 8},
+                                            std::vector<T>{8},
+                                            std::vector<T>{2, 4, 7, 0})};
     return params;
 }
 
@@ -152,14 +152,12 @@ template <element::Type_t IN_ET>
 std::vector<ModParams> generateParamsForModNegative() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ModParams> params{
-        ModParams(ov::PartialShape{2, 2},
-                       ov::PartialShape{2, 2},
-                       IN_ET,
-                       std::vector<T>{-57, -14, -12, -6},
-                       std::vector<T>{13, -7, 5, -5},
-                       std::vector<T>{-5, 0, -2, -1})
-    };
+    std::vector<ModParams> params{ModParams(ov::PartialShape{2, 2},
+                                            ov::PartialShape{2, 2},
+                                            IN_ET,
+                                            std::vector<T>{-57, -14, -12, -6},
+                                            std::vector<T>{13, -7, 5, -5},
+                                            std::vector<T>{-5, 0, -2, -1})};
     return params;
 }
 
@@ -167,24 +165,20 @@ template <element::Type_t IN_ET>
 std::vector<ModParams> generateParamsForModInPlace() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ModParams> params{
-        ModParams(ov::PartialShape{2, 2},
-                       ov::PartialShape{2, 2},
-                       IN_ET,
-                       std::vector<T>{1, 2, 3, 4},
-                       std::vector<T>{5, 6, 7, 8},
-                       std::vector<T>{0, 0, 0, 0})
-    };
+    std::vector<ModParams> params{ModParams(ov::PartialShape{2, 2},
+                                            ov::PartialShape{2, 2},
+                                            IN_ET,
+                                            std::vector<T>{1, 2, 3, 4},
+                                            std::vector<T>{5, 6, 7, 8},
+                                            std::vector<T>{0, 0, 0, 0})};
     return params;
 }
 
 std::vector<ModParams> generateCombinedParamsForMod() {
-    const std::vector<std::vector<ModParams>> allTypeParams{
-        generateParamsForMod<element::Type_t::f32>(),
-        generateParamsForMod<element::Type_t::f16>(),
-        generateParamsForMod<element::Type_t::i64>(),
-        generateParamsForMod<element::Type_t::i32>()
-    };
+    const std::vector<std::vector<ModParams>> allTypeParams{generateParamsForMod<element::Type_t::f32>(),
+                                                            generateParamsForMod<element::Type_t::f16>(),
+                                                            generateParamsForMod<element::Type_t::i64>(),
+                                                            generateParamsForMod<element::Type_t::i32>()};
 
     std::vector<ModParams> combinedParams;
 
@@ -196,12 +190,10 @@ std::vector<ModParams> generateCombinedParamsForMod() {
 }
 
 std::vector<ModParams> generateCombinedParamsForModNegative() {
-    const std::vector<std::vector<ModParams>> allTypeParams{
-        generateParamsForModNegative<element::Type_t::f32>(),
-        generateParamsForModNegative<element::Type_t::f16>(),
-        generateParamsForModNegative<element::Type_t::i64>(),
-        generateParamsForModNegative<element::Type_t::i32>()
-    };
+    const std::vector<std::vector<ModParams>> allTypeParams{generateParamsForModNegative<element::Type_t::f32>(),
+                                                            generateParamsForModNegative<element::Type_t::f16>(),
+                                                            generateParamsForModNegative<element::Type_t::i64>(),
+                                                            generateParamsForModNegative<element::Type_t::i32>()};
 
     std::vector<ModParams> combinedParams;
 
@@ -212,14 +204,11 @@ std::vector<ModParams> generateCombinedParamsForModNegative() {
     return combinedParams;
 }
 
-
 std::vector<ModParams> generateCombinedParamsForModInPlace() {
-    const std::vector<std::vector<ModParams>> allTypeParams{
-        generateParamsForModInPlace<element::Type_t::f32>(),
-        generateParamsForModInPlace<element::Type_t::f16>(),
-        generateParamsForModInPlace<element::Type_t::i64>(),
-        generateParamsForModInPlace<element::Type_t::i32>()
-    };
+    const std::vector<std::vector<ModParams>> allTypeParams{generateParamsForModInPlace<element::Type_t::f32>(),
+                                                            generateParamsForModInPlace<element::Type_t::f16>(),
+                                                            generateParamsForModInPlace<element::Type_t::i64>(),
+                                                            generateParamsForModInPlace<element::Type_t::i32>()};
 
     std::vector<ModParams> combinedParams;
 
@@ -230,22 +219,19 @@ std::vector<ModParams> generateCombinedParamsForModInPlace() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Mod_With_Hardcoded_Refs,
-    ReferenceModLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForMod()),
-    ReferenceModLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Mod_Negative_With_Hardcoded_Refs,
-    ReferenceModLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForModNegative()),
-    ReferenceModLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Mod_InPlace_With_Hardcoded_Refs,
-    ReferenceModInPlaceLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForModInPlace()),
-    ReferenceModInPlaceLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Mod_With_Hardcoded_Refs,
+                         ReferenceModLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForMod()),
+                         ReferenceModLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Mod_Negative_With_Hardcoded_Refs,
+                         ReferenceModLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForModNegative()),
+                         ReferenceModLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Mod_InPlace_With_Hardcoded_Refs,
+                         ReferenceModInPlaceLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForModInPlace()),
+                         ReferenceModInPlaceLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/multiclass_nms.cpp b/src/plugins/template/tests/functional/op_reference/multiclass_nms.cpp
index 890051dec755be..0610af6c45982f 100644
--- a/src/plugins/template/tests/functional/op_reference/multiclass_nms.cpp
+++ b/src/plugins/template/tests/functional/op_reference/multiclass_nms.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/multiclass_nms.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/multiclass_nms.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,33 +13,38 @@ using namespace ov;
 
 namespace {
 struct MulticlassNmsParams {
-    MulticlassNmsParams(
-        const int nms_top_k,
-        const float iou_threshold,
-        const float score_threshold,
-        const op::v8::MulticlassNms::SortResultType sort_result_type,
-        const int keep_top_k,
-        const int background_class,
-        const float nms_eta,
-        const ov::element::Type output_type,
-        const bool sort_result_across_batch,
-        const bool normalized,
-        const reference_tests::Tensor& boxes, const reference_tests::Tensor& scores,
-        const reference_tests::Tensor& expectedSelectedScores, const reference_tests::Tensor& expectedSelectedIndices,
-        const reference_tests::Tensor& expectedValidOutputs, const std::string& testcaseName = "") :
-        nms_top_k(nms_top_k),
-        iou_threshold(iou_threshold),
-        score_threshold(score_threshold),
-        sort_result_type(sort_result_type),
-        keep_top_k(keep_top_k),
-        background_class(background_class),
-        nms_eta(nms_eta),
-        output_type(output_type),
-        sort_result_across_batch(sort_result_across_batch),
-        normalized(normalized),
-        boxes(boxes), scores(scores),
-        expectedSelectedScores(expectedSelectedScores), expectedSelectedIndices(expectedSelectedIndices),
-        expectedValidOutputs(expectedValidOutputs), testcaseName(testcaseName) {}
+    MulticlassNmsParams(const int nms_top_k,
+                        const float iou_threshold,
+                        const float score_threshold,
+                        const op::v8::MulticlassNms::SortResultType sort_result_type,
+                        const int keep_top_k,
+                        const int background_class,
+                        const float nms_eta,
+                        const ov::element::Type output_type,
+                        const bool sort_result_across_batch,
+                        const bool normalized,
+                        const reference_tests::Tensor& boxes,
+                        const reference_tests::Tensor& scores,
+                        const reference_tests::Tensor& expectedSelectedScores,
+                        const reference_tests::Tensor& expectedSelectedIndices,
+                        const reference_tests::Tensor& expectedValidOutputs,
+                        const std::string& testcaseName = "")
+        : nms_top_k(nms_top_k),
+          iou_threshold(iou_threshold),
+          score_threshold(score_threshold),
+          sort_result_type(sort_result_type),
+          keep_top_k(keep_top_k),
+          background_class(background_class),
+          nms_eta(nms_eta),
+          output_type(output_type),
+          sort_result_across_batch(sort_result_across_batch),
+          normalized(normalized),
+          boxes(boxes),
+          scores(scores),
+          expectedSelectedScores(expectedSelectedScores),
+          expectedSelectedIndices(expectedSelectedIndices),
+          expectedValidOutputs(expectedValidOutputs),
+          testcaseName(testcaseName) {}
 
     int nms_top_k;
     float iou_threshold;
@@ -122,431 +128,498 @@ std::vector<MulticlassNmsParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<MulticlassNmsParams> params {
+    std::vector<MulticlassNmsParams> params{
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {4, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 1.00, 0.95,
-                0.00, 0.00, 1.00, 1.00,  0.00, 0.90,  0.00, 0.00,
-                1.00, 1.00, 1.00, 0.80,  0.00, 10.00, 1.00, 11.00}),                    // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {4, 1}, std::vector<T_IND>{3, 0, 0, 3}),                     // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}),                                 // expected_valid_outputs
+            3,                                             // nms_top_k
+            0.5f,                                          // iou_threshold
+            0.0f,                                          // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            false,                                         // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),  // boxes
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 2, 6},
+                std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH, {4, 6}, std::vector<T_TH>{0.00,  0.95, 0.00, 10.00, 1.00, 11.00, 1.00,
+                                                                     0.95,  0.00, 0.00, 1.00,  1.00, 0.00,  0.90,
+                                                                     0.00,  0.00, 1.00, 1.00,  1.00, 0.80,  0.00,
+                                                                     10.00, 1.00, 11.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {4, 1}, std::vector<T_IND>{3, 0, 0, 3}),        // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}),                    // expected_valid_outputs
             "multiclass_nms_by_score"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::CLASSID, // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {4, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90,
-                0.00, 0.00, 1.00, 1.00,  1.00, 0.95,  0.00, 0.00,
-                1.00, 1.00, 1.00, 0.80,  0.00, 10.00, 1.00, 11.00}),                    // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {4, 1}, std::vector<T_IND>{3, 0, 0, 3}),                     // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}),                                 // expected_valid_outputs
+            3,                                               // nms_top_k
+            0.5f,                                            // iou_threshold
+            0.0f,                                            // score_threshold
+            op::v8::MulticlassNms::SortResultType::CLASSID,  // sort_result_type
+            -1,                                              // keep_top_k
+            -1,                                              // background_class
+            1.0f,                                            // nms_eta
+            ET_IND,                                          // output_type
+            false,                                           // sort_result_across_batch
+            true,                                            // normalized
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),  // boxes
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 2, 6},
+                std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH, {4, 6}, std::vector<T_TH>{0.00,  0.95, 0.00, 10.00, 1.00, 11.00, 0.00,
+                                                                     0.90,  0.00, 0.00, 1.00,  1.00, 1.00,  0.95,
+                                                                     0.00,  0.00, 1.00, 1.00,  1.00, 0.80,  0.00,
+                                                                     10.00, 1.00, 11.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {4, 1}, std::vector<T_IND>{3, 0, 0, 3}),        // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}),                    // expected_valid_outputs
             "multiclass_nms_by_class_id"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::CLASSID, // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {4, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90,
-                0.00, 0.00, 1.00, 1.00,  1.00, 0.95,  0.00, 0.00,
-                1.00, 1.00, 1.00, 0.80,  0.00, 10.00, 1.00, 11.00}),                    // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {4, 1}, std::vector<T_IND>{3, 0, 0, 3}),                     // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}),                                 // expected_valid_outputs
+            3,                                               // nms_top_k
+            0.5f,                                            // iou_threshold
+            0.0f,                                            // score_threshold
+            op::v8::MulticlassNms::SortResultType::CLASSID,  // sort_result_type
+            -1,                                              // keep_top_k
+            -1,                                              // background_class
+            1.0f,                                            // nms_eta
+            ET_IND,                                          // output_type
+            false,                                           // sort_result_across_batch
+            true,                                            // normalized
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),  // boxes
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 2, 6},
+                std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH, {4, 6}, std::vector<T_TH>{0.00,  0.95, 0.00, 10.00, 1.00, 11.00, 0.00,
+                                                                     0.90,  0.00, 0.00, 1.00,  1.00, 1.00,  0.95,
+                                                                     0.00,  0.00, 1.00, 1.00,  1.00, 0.80,  0.00,
+                                                                     10.00, 1.00, 11.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {4, 1}, std::vector<T_IND>{3, 0, 0, 3}),        // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}),                    // expected_valid_outputs
             "multiclass_nms_output_type_i32"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {8, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,  1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,  1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {8, 1}, std::vector<T_IND>{3, 0, 0, 3, 9, 6, 6, 9}),         // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),                              // expected_valid_outputs
+            3,                                             // nms_top_k
+            0.5f,                                          // iou_threshold
+            0.0f,                                          // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            false,                                         // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {8, 6},
+                std::vector<T_TH>{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
+                                  0.00, 0.90, 0.00, 0.00,  1.00, 1.00,  1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
+                                  0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
+                                  0.00, 0.90, 0.00, 0.00,  1.00, 1.00,  1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND,
+                                    {8, 1},
+                                    std::vector<T_IND>{3, 0, 0, 3, 9, 6, 6, 9}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),       // expected_valid_outputs
             "multiclass_nms_two_batches_two_classes_by_score"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::CLASSID, // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {8, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,  1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,  1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {8, 1}, std::vector<T_IND>{3, 0, 0, 3, 9, 6, 6, 9}),         // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),                              // expected_valid_outputs
+            3,                                               // nms_top_k
+            0.5f,                                            // iou_threshold
+            0.0f,                                            // score_threshold
+            op::v8::MulticlassNms::SortResultType::CLASSID,  // sort_result_type
+            -1,                                              // keep_top_k
+            -1,                                              // background_class
+            1.0f,                                            // nms_eta
+            ET_IND,                                          // output_type
+            false,                                           // sort_result_across_batch
+            true,                                            // normalized
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {8, 6},
+                std::vector<T_TH>{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
+                                  1.00, 0.95, 0.00, 0.00,  1.00, 1.00,  1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
+                                  0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
+                                  1.00, 0.95, 0.00, 0.00,  1.00, 1.00,  1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND,
+                                    {8, 1},
+                                    std::vector<T_IND>{3, 0, 0, 3, 9, 6, 6, 9}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),       // expected_valid_outputs
             "multiclass_nms_two_batches_two_classes_by_class_id"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            true,                                           // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {8, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),                                 // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {8, 1}, std::vector<T_IND>{3, 0, 9, 6, 0, 6, 3, 9}),         // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),                              // expected_valid_outputs
+            3,                                             // nms_top_k
+            0.5f,                                          // iou_threshold
+            0.0f,                                          // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            true,                                          // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {8, 6},
+                std::vector<T_TH>{
+                    0.00,  0.95, 0.00,  10.00, 1.00,  11.00, 1.00,  0.95, 0.00, 0.00, 1.00, 1.00, 0.00,
+                    0.95,  0.00, 10.00, 1.00,  11.00, 1.00,  0.95,  0.00, 0.00, 1.00, 1.00, 0.00, 0.90,
+                    0.00,  0.00, 1.00,  1.00,  0.00,  0.90,  0.00,  0.00, 1.00, 1.00, 1.00, 0.80, 0.00,
+                    10.00, 1.00, 11.00, 1.00,  0.80,  0.00,  10.00, 1.00, 11.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND,
+                                    {8, 1},
+                                    std::vector<T_IND>{3, 0, 9, 6, 0, 6, 3, 9}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),       // expected_valid_outputs
             "multiclass_nms_two_batches_two_classes_by_score_cross_batch"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::CLASSID, // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            true,                                           // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {8, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00,
-                0.00, 0.90, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
-                1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),                                 // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {8, 1}, std::vector<T_IND>{3, 0, 9, 6, 0, 3, 6, 9}),         // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),                              // expected_valid_outputs
+            3,                                               // nms_top_k
+            0.5f,                                            // iou_threshold
+            0.0f,                                            // score_threshold
+            op::v8::MulticlassNms::SortResultType::CLASSID,  // sort_result_type
+            -1,                                              // keep_top_k
+            -1,                                              // background_class
+            1.0f,                                            // nms_eta
+            ET_IND,                                          // output_type
+            true,                                            // sort_result_across_batch
+            true,                                            // normalized
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {8, 6},
+                std::vector<T_TH>{
+                    0.00, 0.95, 0.00,  10.00, 1.00,  11.00, 0.00,  0.90,  0.00, 0.00,  1.00, 1.00, 0.00,
+                    0.95, 0.00, 10.00, 1.00,  11.00, 0.00,  0.90,  0.00,  0.00, 1.00,  1.00, 1.00, 0.95,
+                    0.00, 0.00, 1.00,  1.00,  1.00,  0.80,  0.00,  10.00, 1.00, 11.00, 1.00, 0.95, 0.00,
+                    0.00, 1.00, 1.00,  1.00,  0.80,  0.00,  10.00, 1.00,  11.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND,
+                                    {8, 1},
+                                    std::vector<T_IND>{3, 0, 9, 6, 0, 3, 6, 9}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{4, 4}),       // expected_valid_outputs
             "multiclass_nms_two_batches_two_classes_by_class_id_cross_batch"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                1.0, 1.0,  0.0, 0.0,  0.0, 0.1,  1.0, 1.1,  0.0, 0.9,   1.0, -0.1,
-                0.0, 10.0, 1.0, 11.0, 1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {3, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 1.00, 1.00, 0.00, 0.00, 0.00, 0.75, 0.00, 0.10, 1.00, 1.10}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{3, 0, 1}),                        // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),                                 // expected_valid_outputs
+            3,                                             // nms_top_k
+            0.5f,                                          // iou_threshold
+            0.0f,                                          // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            false,                                         // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{1.0, 1.0,  0.0,  0.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  0.9, 1.0,  -0.1, 0.0,   10.0, 1.0,  11.0, 1.0, 10.1,
+                                                                  0.0, 11.1, 1.0,  101.0, 0.0,  100.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH,
+                                    {3, 6},
+                                    std::vector<T_TH>{0.00,
+                                                      0.95,
+                                                      0.00,
+                                                      10.00,
+                                                      1.00,
+                                                      11.00,
+                                                      0.00,
+                                                      0.90,
+                                                      1.00,
+                                                      1.00,
+                                                      0.00,
+                                                      0.00,
+                                                      0.00,
+                                                      0.75,
+                                                      0.00,
+                                                      0.10,
+                                                      1.00,
+                                                      1.10}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {3, 1}, std::vector<T_IND>{3, 0, 1}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}),           // expected_valid_outputs
             "multiclass_nms_flipped_coordinates"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,
-                1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}),           // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 10}, std::vector<T_TH>{
-                0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}),                     // scores
-            reference_tests::Tensor(ET_TH, {1, 6}, std::vector<T_TH>{
-                0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{0}),                              // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),                                 // expected_valid_outputs
+            3,                                             // nms_top_k
+            0.5f,                                          // iou_threshold
+            0.0f,                                          // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            false,                                         // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(
+                ET,
+                {1, 10, 4},
+                std::vector<T>{0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,
+                               1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                               0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}),  // boxes
+            reference_tests::Tensor(ET_TH,
+                                    {1, 1, 10},
+                                    std::vector<T_TH>{0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}),  // scores
+            reference_tests::Tensor(ET_TH, {1, 6}, std::vector<T_TH>{0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{0}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),     // expected_valid_outputs
             "multiclass_nms_identical_boxes"),
         MulticlassNmsParams(
-            2,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {2, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {2, 1}, std::vector<T_IND>{3, 0}),                           // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}),                                 // expected_valid_outputs
+            2,                                             // nms_top_k
+            0.5f,                                          // iou_threshold
+            0.0f,                                          // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            false,                                         // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {2, 6},
+                std::vector<T_TH>{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {2, 1}, std::vector<T_IND>{3, 0}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}),        // expected_valid_outputs
             "multiclass_nms_limit_output_size"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}),                  // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 1}, std::vector<T_TH>{0.9}),                           // scores
-            reference_tests::Tensor(ET_TH, {1, 6}, std::vector<T_TH>{
-                0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),                                   // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{0}),                              // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),                                 // expected_valid_outputs
+            3,                                                                           // nms_top_k
+            0.5f,                                                                        // iou_threshold
+            0.0f,                                                                        // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,                                // sort_result_type
+            -1,                                                                          // keep_top_k
+            -1,                                                                          // background_class
+            1.0f,                                                                        // nms_eta
+            ET_IND,                                                                      // output_type
+            false,                                                                       // sort_result_across_batch
+            true,                                                                        // normalized
+            reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 1}, std::vector<T_TH>{0.9}),           // scores
+            reference_tests::Tensor(ET_TH,
+                                    {1, 6},
+                                    std::vector<T_TH>{0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),  // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{0}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),     // expected_valid_outputs
             "multiclass_nms_single_box"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.2f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {2, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {2, 1}, std::vector<T_IND>{3, 0}),                           // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}),                                 // expected_valid_outputs
+            3,                                             // nms_top_k
+            0.2f,                                          // iou_threshold
+            0.0f,                                          // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            false,                                         // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {2, 6},
+                std::vector<T_TH>{0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00, 0.00, 1.00, 1.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {2, 1}, std::vector<T_IND>{3, 0}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}),        // expected_valid_outputs
             "multiclass_nms_by_IOU"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.95f,                                          // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE,   // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.96, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {1, 6}, std::vector<T_TH>{
-                0.00, 0.96, 0.00, 10.00, 1.00, 11.00}),                                 // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{3}),                              // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),                                 // expected_valid_outputs
+            3,                                             // nms_top_k
+            0.5f,                                          // iou_threshold
+            0.95f,                                         // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            false,                                         // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.96, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {1, 6},
+                std::vector<T_TH>{0.00, 0.96, 0.00, 10.00, 1.00, 11.00}),    // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {1, 1}, std::vector<T_IND>{3}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}),     // expected_valid_outputs
             "multiclass_nms_by_IOU_and_scores"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            2.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::SCORE, // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),                                       // scores
-            reference_tests::Tensor(ET_TH, {0, 6}, std::vector<T_TH>{}),                                 // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {0, 1}, std::vector<T_IND>{}),                               // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{0}),                                 // expected_valid_outputs
+            3,                                             // nms_top_k
+            0.5f,                                          // iou_threshold
+            2.0f,                                          // score_threshold
+            op::v8::MulticlassNms::SortResultType::SCORE,  // sort_result_type
+            -1,                                            // keep_top_k
+            -1,                                            // background_class
+            1.0f,                                          // nms_eta
+            ET_IND,                                        // output_type
+            false,                                         // sort_result_across_batch
+            true,                                          // normalized
+            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0,  0.0,  1.0, 1.0,   0.0,  0.1,  1.0,  1.1, 0.0,
+                                                                  -0.1, 1.0,  0.9, 0.0,   10.0, 1.0,  11.0, 0.0, 10.1,
+                                                                  1.0,  11.1, 0.0, 100.0, 1.0,  101.0}),   // boxes
+            reference_tests::Tensor(ET_TH, {1, 1, 6}, std::vector<T_TH>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH, {0, 6}, std::vector<T_TH>{}),    // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {0, 1}, std::vector<T_IND>{}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{0}),    // expected_valid_outputs
             "multiclass_nms_no_output"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::CLASSID, // sort_result_type
-            -1,                                             // keep_top_k
-            0,                                              // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {4, 6}, std::vector<T_TH>{
-                1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
-                1.00, 0.95, 0.00, 0.00, 1.00, 1.00, 1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {4, 1}, std::vector<T_IND>{0, 3, 6, 9}),                     // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{2, 2}),                              // expected_valid_outputs
+            3,                                               // nms_top_k
+            0.5f,                                            // iou_threshold
+            0.0f,                                            // score_threshold
+            op::v8::MulticlassNms::SortResultType::CLASSID,  // sort_result_type
+            -1,                                              // keep_top_k
+            0,                                               // background_class
+            1.0f,                                            // nms_eta
+            ET_IND,                                          // output_type
+            false,                                           // sort_result_across_batch
+            true,                                            // normalized
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(ET_TH, {4, 6}, std::vector<T_TH>{1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
+                                                                     1.00, 0.80, 0.00, 10.00, 1.00, 11.00,
+                                                                     1.00, 0.95, 0.00, 0.00,  1.00, 1.00,
+                                                                     1.00, 0.80, 0.00, 10.00, 1.00, 11.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {4, 1}, std::vector<T_IND>{0, 3, 6, 9}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{2, 2}),           // expected_valid_outputs
             "multiclass_nms_by_background"),
         MulticlassNmsParams(
-            3,                                              // nms_top_k
-            0.5f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::CLASSID, // sort_result_type
-            3,                                              // keep_top_k
-            -1,                                             // background_class
-            1.0f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {6, 6}, std::vector<T_TH>{
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00,
-                0.00, 1.00, 1.00, 1.00,  0.95, 0.00,  0.00, 1.00, 1.00,
-                0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00,
-                0.00, 1.00, 1.00, 1.00,  0.95, 0.00,  0.00, 1.00, 1.00}),               // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {6, 1}, std::vector<T_IND>{3, 0, 0, 9, 6, 6}),               // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{3, 3}),                              // expected_valid_outputs
+            3,                                               // nms_top_k
+            0.5f,                                            // iou_threshold
+            0.0f,                                            // score_threshold
+            op::v8::MulticlassNms::SortResultType::CLASSID,  // sort_result_type
+            3,                                               // keep_top_k
+            -1,                                              // background_class
+            1.0f,                                            // nms_eta
+            ET_IND,                                          // output_type
+            false,                                           // sort_result_across_batch
+            true,                                            // normalized
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {6, 6},
+                std::vector<T_TH>{
+                    0.00, 0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90, 0.00,  0.00, 1.00,  1.00, 1.00,
+                    0.95, 0.00, 0.00, 1.00,  1.00, 0.00,  0.95, 0.00, 10.00, 1.00, 11.00, 0.00, 0.90,
+                    0.00, 0.00, 1.00, 1.00,  1.00, 0.95,  0.00, 0.00, 1.00,  1.00}),        // expected_selected_scores
+            reference_tests::Tensor(ET_IND, {6, 1}, std::vector<T_IND>{3, 0, 0, 9, 6, 6}),  // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{3, 3}),                 // expected_valid_outputs
             "multiclass_nms_by_keep_top_k"),
         MulticlassNmsParams(
-            -1,                                             // nms_top_k
-            1.0f,                                           // iou_threshold
-            0.0f,                                           // score_threshold
-            op::v8::MulticlassNms::SortResultType::CLASSID, // sort_result_type
-            -1,                                             // keep_top_k
-            -1,                                             // background_class
-            0.1f,                                           // nms_eta
-            ET_IND,                                         // output_type
-            false,                                          // sort_result_across_batch
-            true,                                           // normalized
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),   // boxes
-            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),      // scores
-            reference_tests::Tensor(ET_TH, {12, 6}, std::vector<T_TH>{
-                0.00,   0.95, 0.00,   10.00,  1.00, 11.00,  0.00,   0.90, 0.00,   0.00,   1.00, 1.00,  0.00,  0.30, 0.00,
-                100.00, 1.00, 101.00, 1.00,   0.95, 0.00,   0.00,   1.00, 1.00,   1.00,   0.80, 0.00,  10.00, 1.00, 11.00,
-                1.00,   0.30, 0.00,   100.00, 1.00, 101.00, 0.00,   0.95, 0.00,   10.00,  1.00, 11.00, 0.00,  0.90, 0.00,
-                0.00,   1.00, 1.00,   0.00,   0.30, 0.00,   100.00, 1.00, 101.00, 1.00,   0.95, 0.00,  0.00,  1.00, 1.00,
-                1.00,   0.80, 0.00,   10.00,  1.00, 11.00,  1.00,   0.30, 0.00,   100.00, 1.00, 101.00}),
-                                                                                        // expected_selected_scores
-            reference_tests::Tensor(ET_IND, {12, 1}, std::vector<T_IND>{
-                3, 0, 5, 0, 3, 5, 9, 6, 11, 6, 9, 11}),                                 // expected_selected_indices
-            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{6, 6}),                              // expected_valid_outputs
+            -1,                                              // nms_top_k
+            1.0f,                                            // iou_threshold
+            0.0f,                                            // score_threshold
+            op::v8::MulticlassNms::SortResultType::CLASSID,  // sort_result_type
+            -1,                                              // keep_top_k
+            -1,                                              // background_class
+            0.1f,                                            // nms_eta
+            ET_IND,                                          // output_type
+            false,                                           // sort_result_across_batch
+            true,                                            // normalized
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 4},
+                std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                               0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
+                               0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}),  // boxes
+            reference_tests::Tensor(ET_TH, {2, 2, 6}, std::vector<T_TH>{0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3,
+                                                                        0.9,  0.75, 0.6, 0.95, 0.5, 0.3,
+                                                                        0.95, 0.75, 0.6, 0.80, 0.5, 0.3}),  // scores
+            reference_tests::Tensor(
+                ET_TH,
+                {12, 6},
+                std::vector<T_TH>{0.00, 0.95, 0.00, 10.00,  1.00, 11.00,  0.00, 0.90, 0.00, 0.00,   1.00, 1.00,
+                                  0.00, 0.30, 0.00, 100.00, 1.00, 101.00, 1.00, 0.95, 0.00, 0.00,   1.00, 1.00,
+                                  1.00, 0.80, 0.00, 10.00,  1.00, 11.00,  1.00, 0.30, 0.00, 100.00, 1.00, 101.00,
+                                  0.00, 0.95, 0.00, 10.00,  1.00, 11.00,  0.00, 0.90, 0.00, 0.00,   1.00, 1.00,
+                                  0.00, 0.30, 0.00, 100.00, 1.00, 101.00, 1.00, 0.95, 0.00, 0.00,   1.00, 1.00,
+                                  1.00, 0.80, 0.00, 10.00,  1.00, 11.00,  1.00, 0.30, 0.00, 100.00, 1.00, 101.00}),
+            // expected_selected_scores
+            reference_tests::Tensor(
+                ET_IND,
+                {12, 1},
+                std::vector<T_IND>{3, 0, 5, 0, 3, 5, 9, 6, 11, 6, 9, 11}),   // expected_selected_indices
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{6, 6}),  // expected_valid_outputs
             "multiclass_nms_by_nms_eta"),
     };
     return params;
 }
 
 std::vector<MulticlassNmsParams> generateCombinedParams() {
-    const std::vector<std::vector<MulticlassNmsParams>> generatedParams {
+    const std::vector<std::vector<MulticlassNmsParams>> generatedParams{
         generateParams<element::Type_t::bf16, element::Type_t::bf16, element::Type_t::i32>(),
         generateParams<element::Type_t::f16, element::Type_t::f16, element::Type_t::i32>(),
         generateParams<element::Type_t::f32, element::Type_t::f32, element::Type_t::i32>(),
@@ -562,6 +635,8 @@ std::vector<MulticlassNmsParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_MulticlassNms_With_Hardcoded_Refs, ReferenceMulticlassNmsTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceMulticlassNmsTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_MulticlassNms_With_Hardcoded_Refs,
+                         ReferenceMulticlassNmsTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceMulticlassNmsTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/multiply.cpp b/src/plugins/template/tests/functional/op_reference/multiply.cpp
index 607ff5dc0e7efb..bd3b27f500aeac 100644
--- a/src/plugins/template/tests/functional/op_reference/multiply.cpp
+++ b/src/plugins/template/tests/functional/op_reference/multiply.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/multiply.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/multiply.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,11 +16,11 @@ namespace {
 struct MultiplyParams {
     template <class IT>
     MultiplyParams(const PartialShape& iShape1,
-              const PartialShape& iShape2,
-              const element::Type& iType,
-              const std::vector<IT>& iValues1,
-              const std::vector<IT>& iValues2,
-              const std::vector<IT>& oValues)
+                   const PartialShape& iShape2,
+                   const element::Type& iType,
+                   const std::vector<IT>& iValues1,
+                   const std::vector<IT>& iValues2,
+                   const std::vector<IT>& oValues)
         : pshape1(iShape1),
           pshape2(iShape2),
           inType(iType),
@@ -57,9 +59,9 @@ class ReferenceMultiplyLayerTest : public testing::TestWithParam<MultiplyParams>
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto multiply = std::make_shared<op::v1::Multiply>(in1, in2);
@@ -83,21 +85,20 @@ std::vector<MultiplyParams> generateParamsForMultiply() {
                        std::vector<T>{1, 2, 3, 4},
                        std::vector<T>{5, 6, 7, 8},
                        std::vector<T>{5, 12, 21, 32}),
-        MultiplyParams(ov::PartialShape{3, 2, 1},
-                       ov::PartialShape{1, 6},
-                       IN_ET,
-                       std::vector<T>{12, 24, 36, 48, 60, 72},
-                       std::vector<T>{1, 2, 3, 4, 6, 1},
-                       std::vector<T>{12, 24,  36,  48,  72,  12, 24, 48,  72,  96,  144, 24,
-                                      36, 72,  108, 144, 216, 36, 48, 96,  144, 192, 288, 48,
-                                      60, 120, 180, 240, 360, 60, 72, 144, 216, 288, 432, 72}),
+        MultiplyParams(
+            ov::PartialShape{3, 2, 1},
+            ov::PartialShape{1, 6},
+            IN_ET,
+            std::vector<T>{12, 24, 36, 48, 60, 72},
+            std::vector<T>{1, 2, 3, 4, 6, 1},
+            std::vector<T>{12, 24, 36,  48,  72,  12, 24, 48,  72,  96,  144, 24, 36, 72,  108, 144, 216, 36,
+                           48, 96, 144, 192, 288, 48, 60, 120, 180, 240, 360, 60, 72, 144, 216, 288, 432, 72}),
         MultiplyParams(ov::PartialShape{1},
                        ov::PartialShape{1},
                        IN_ET,
                        std::vector<T>{2},
                        std::vector<T>{8},
-                       std::vector<T>{16})
-    };
+                       std::vector<T>{16})};
     return params;
 }
 
@@ -105,27 +106,23 @@ template <element::Type_t IN_ET>
 std::vector<MultiplyParams> generateParamsForMultiplyFloat() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<MultiplyParams> params{
-        MultiplyParams(ov::PartialShape{1},
-                       ov::PartialShape{1},
-                       IN_ET,
-                       std::vector<T>{3.1},
-                       std::vector<T>{8},
-                       std::vector<T>{24.8})
-    };
+    std::vector<MultiplyParams> params{MultiplyParams(ov::PartialShape{1},
+                                                      ov::PartialShape{1},
+                                                      IN_ET,
+                                                      std::vector<T>{3.1},
+                                                      std::vector<T>{8},
+                                                      std::vector<T>{24.8})};
     return params;
 }
 
 std::vector<MultiplyParams> generateCombinedParamsForMultiply() {
-    const std::vector<std::vector<MultiplyParams>> allTypeParams{
-        generateParamsForMultiply<element::Type_t::f32>(),
-        generateParamsForMultiply<element::Type_t::f16>(),
-        generateParamsForMultiply<element::Type_t::bf16>(),
-        generateParamsForMultiply<element::Type_t::i64>(),
-        generateParamsForMultiply<element::Type_t::i32>(),
-        generateParamsForMultiply<element::Type_t::u64>(),
-        generateParamsForMultiply<element::Type_t::u32>()
-    };
+    const std::vector<std::vector<MultiplyParams>> allTypeParams{generateParamsForMultiply<element::Type_t::f32>(),
+                                                                 generateParamsForMultiply<element::Type_t::f16>(),
+                                                                 generateParamsForMultiply<element::Type_t::bf16>(),
+                                                                 generateParamsForMultiply<element::Type_t::i64>(),
+                                                                 generateParamsForMultiply<element::Type_t::i32>(),
+                                                                 generateParamsForMultiply<element::Type_t::u64>(),
+                                                                 generateParamsForMultiply<element::Type_t::u32>()};
 
     std::vector<MultiplyParams> combinedParams;
 
@@ -139,8 +136,7 @@ std::vector<MultiplyParams> generateCombinedParamsForMultiply() {
 std::vector<MultiplyParams> generateCombinedParamsForMultiplyFloat() {
     const std::vector<std::vector<MultiplyParams>> allTypeParams{
         generateParamsForMultiplyFloat<element::Type_t::f32>(),
-        generateParamsForMultiplyFloat<element::Type_t::f16>()
-    };
+        generateParamsForMultiplyFloat<element::Type_t::f16>()};
 
     std::vector<MultiplyParams> combinedParams;
 
@@ -151,16 +147,14 @@ std::vector<MultiplyParams> generateCombinedParamsForMultiplyFloat() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Multiply_With_Hardcoded_Refs,
-    ReferenceMultiplyLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForMultiply()),
-    ReferenceMultiplyLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Multiply_Float_With_Hardcoded_Refs,
-    ReferenceMultiplyLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForMultiplyFloat()),
-    ReferenceMultiplyLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Multiply_With_Hardcoded_Refs,
+                         ReferenceMultiplyLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForMultiply()),
+                         ReferenceMultiplyLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Multiply_Float_With_Hardcoded_Refs,
+                         ReferenceMultiplyLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForMultiplyFloat()),
+                         ReferenceMultiplyLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/mvn.cpp b/src/plugins/template/tests/functional/op_reference/mvn.cpp
index 5816351c2daf03..d16c7a9a76131b 100644
--- a/src/plugins/template/tests/functional/op_reference/mvn.cpp
+++ b/src/plugins/template/tests/functional/op_reference/mvn.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/mvn.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/mvn.hpp"
 #include "base_reference_test.hpp"
 #include "shared_test_classes/base/layer_test_utils.hpp"
 
@@ -14,8 +15,12 @@ using namespace reference_tests;
 // ------------------------------ V0 ------------------------------
 
 struct MVN1Params {
-    MVN1Params(const reference_tests::Tensor& paramInput, const ov::AxisSet& paramReductionAxes, const bool paramAcrossChannels, const bool paramNormalizeVariance,
-               const double paramEps, const reference_tests::Tensor& paramExpected)
+    MVN1Params(const reference_tests::Tensor& paramInput,
+               const ov::AxisSet& paramReductionAxes,
+               const bool paramAcrossChannels,
+               const bool paramNormalizeVariance,
+               const double paramEps,
+               const reference_tests::Tensor& paramExpected)
         : input(paramInput),
           reductionAxes(paramReductionAxes),
           acrossChannels(paramAcrossChannels),
@@ -34,7 +39,11 @@ class ReferenceMVN1LayerTest : public testing::TestWithParam<MVN1Params>, public
 public:
     void SetUp() override {
         auto params = GetParam();
-        function = CreateFunction(params.input, params.reductionAxes, params.acrossChannels, params.normalizeVariance, params.eps);
+        function = CreateFunction(params.input,
+                                  params.reductionAxes,
+                                  params.acrossChannels,
+                                  params.normalizeVariance,
+                                  params.eps);
         inputData = {params.input.data};
         refOutData = {params.expected.data};
     }
@@ -54,14 +63,17 @@ class ReferenceMVN1LayerTest : public testing::TestWithParam<MVN1Params>, public
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const reference_tests::Tensor& input, const ov::AxisSet& reductionAxes, const bool acrossChannels,
-                                                    const bool normalizeVariance, const double eps) {
+    static std::shared_ptr<Model> CreateFunction(const reference_tests::Tensor& input,
+                                                 const ov::AxisSet& reductionAxes,
+                                                 const bool acrossChannels,
+                                                 const bool normalizeVariance,
+                                                 const double eps) {
         const auto in = std::make_shared<op::v0::Parameter>(input.type, input.shape);
         auto mvn = std::make_shared<op::v0::MVN>(in, acrossChannels, normalizeVariance, eps);
         if (!reductionAxes.empty()) {
             mvn = std::make_shared<op::v0::MVN>(in, reductionAxes, normalizeVariance, eps);
         }
-        return std::make_shared<ov::Model>(NodeVector {mvn}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{mvn}, ParameterVector{in});
     }
 };
 
@@ -69,79 +81,110 @@ TEST_P(ReferenceMVN1LayerTest, CompareWithHardcodedRefs) {
     Exec();
 }
 
-const ov::AxisSet emptyReductionAxes {};
+const ov::AxisSet emptyReductionAxes{};
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_MVN1_With_Hardcoded_Refs, ReferenceMVN1LayerTest,
+    smoke_MVN1_With_Hardcoded_Refs,
+    ReferenceMVN1LayerTest,
     ::testing::Values(
         // across_channels=false, variance=false
-        MVN1Params(reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
-                                                                                   6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
+        MVN1Params(reference_tests::Tensor{{1, 3, 3, 3},
+                                           ov::element::f32,
+                                           std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
+                                                              6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
                    emptyReductionAxes,
                    false,
                    false,
                    1e-9,
-                   reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {-4, -3, -2, -1, 0,  1,  2,  3,  4, -4, -3, -2, -1, 0,
-                                                                                   1,  2,  3,  4,  -4, -3, -2, -1, 0, 1,  2,  3,  4}}),
+                   reference_tests::Tensor{{1, 3, 3, 3},
+                                           ov::element::f32,
+                                           std::vector<float>{-4, -3, -2, -1, 0,  1,  2,  3,  4, -4, -3, -2, -1, 0,
+                                                              1,  2,  3,  4,  -4, -3, -2, -1, 0, 1,  2,  3,  4}}),
         // across_channels=true, variance=false
         MVN1Params(
-            reference_tests::Tensor {{1, 3, 2, 2}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3}},
+            reference_tests::Tensor{{1, 3, 2, 2},
+                                    ov::element::f32,
+                                    std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3}},
             emptyReductionAxes,
             true,
             false,
             1e-9,
-            reference_tests::Tensor {{1, 3, 2, 2}, ov::element::f32, std::vector<float> {-3.25, -2.25, -1.25, -0.25, 0.75, 1.75, 2.75, 3.75, 4.75, -3.25, -2.25, -1.25}}),
+            reference_tests::Tensor{
+                {1, 3, 2, 2},
+                ov::element::f32,
+                std::vector<float>{-3.25, -2.25, -1.25, -0.25, 0.75, 1.75, 2.75, 3.75, 4.75, -3.25, -2.25, -1.25}}),
         // across_channels=false, variance=true
-        MVN1Params(reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
-                                                                                   6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
-                   emptyReductionAxes,
-                   false,
-                   true,
-                   1e-9,
-                   reference_tests::Tensor {{1, 3, 3, 3},
-                           ov::element::f32,
-                           std::vector<float> {-1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934}}),
+        MVN1Params(
+            reference_tests::Tensor{{1, 3, 3, 3}, ov::element::f32, std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9}},
+            emptyReductionAxes,
+            false,
+            true,
+            1e-9,
+            reference_tests::Tensor{
+                {1, 3, 3, 3},
+                ov::element::f32,
+                std::vector<float>{-1.5491934,  -1.161895, -0.7745967, -0.38729835, 0.,         0.38729835,  0.7745967,
+                                   1.161895,    1.5491934, -1.5491934, -1.161895,   -0.7745967, -0.38729835, 0.,
+                                   0.38729835,  0.7745967, 1.161895,   1.5491934,   -1.5491934, -1.161895,   -0.7745967,
+                                   -0.38729835, 0.,        0.38729835, 0.7745967,   1.161895,   1.5491934}}),
         // across_channels=true, variance=true
-        MVN1Params(reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
-                                                                                   6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
-                   emptyReductionAxes,
-                   true,
-                   true,
-                   1e-9,
-                   reference_tests::Tensor {{1, 3, 3, 3},
-                           ov::element::f32,
-                           std::vector<float> {-1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934}}),
+        MVN1Params(
+            reference_tests::Tensor{{1, 3, 3, 3}, ov::element::f32, std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9}},
+            emptyReductionAxes,
+            true,
+            true,
+            1e-9,
+            reference_tests::Tensor{
+                {1, 3, 3, 3},
+                ov::element::f32,
+                std::vector<float>{-1.5491934,  -1.161895, -0.7745967, -0.38729835, 0.,         0.38729835,  0.7745967,
+                                   1.161895,    1.5491934, -1.5491934, -1.161895,   -0.7745967, -0.38729835, 0.,
+                                   0.38729835,  0.7745967, 1.161895,   1.5491934,   -1.5491934, -1.161895,   -0.7745967,
+                                   -0.38729835, 0.,        0.38729835, 0.7745967,   1.161895,   1.5491934}}),
         // reductionAxes, variance=false
         MVN1Params(
-            reference_tests::Tensor {{1, 3, 2, 2}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3}},
+            reference_tests::Tensor{{1, 3, 2, 2},
+                                    ov::element::f32,
+                                    std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3}},
             {1, 2, 3},
             false,
             false,
             1e-9,
-            reference_tests::Tensor {{1, 3, 2, 2}, ov::element::f32, std::vector<float> {-3.25, -2.25, -1.25, -0.25, 0.75, 1.75, 2.75, 3.75, 4.75, -3.25, -2.25, -1.25}}),
+            reference_tests::Tensor{
+                {1, 3, 2, 2},
+                ov::element::f32,
+                std::vector<float>{-3.25, -2.25, -1.25, -0.25, 0.75, 1.75, 2.75, 3.75, 4.75, -3.25, -2.25, -1.25}}),
         // reductionAxes, variance=true
-        MVN1Params(reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
-                                                                                   6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
-                   {2, 3},
-                   false,
-                   true,
-                   1e-9,
-                   reference_tests::Tensor {{1, 3, 3, 3},
-                           ov::element::f32,
-                           std::vector<float> {-1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934}})),
+        MVN1Params(
+            reference_tests::Tensor{{1, 3, 3, 3}, ov::element::f32, std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9}},
+            {2, 3},
+            false,
+            true,
+            1e-9,
+            reference_tests::Tensor{
+                {1, 3, 3, 3},
+                ov::element::f32,
+                std::vector<float>{-1.5491934,  -1.161895, -0.7745967, -0.38729835, 0.,         0.38729835,  0.7745967,
+                                   1.161895,    1.5491934, -1.5491934, -1.161895,   -0.7745967, -0.38729835, 0.,
+                                   0.38729835,  0.7745967, 1.161895,   1.5491934,   -1.5491934, -1.161895,   -0.7745967,
+                                   -0.38729835, 0.,        0.38729835, 0.7745967,   1.161895,   1.5491934}})),
     ReferenceMVN1LayerTest::getTestCaseName);
 
 // ------------------------------ V6 ------------------------------
 
 struct MVN6Params {
-    MVN6Params(const reference_tests::Tensor& paramInput, const reference_tests::Tensor& paramReductionAxes, const bool paramNormalizeVariance, const double paramEps,
-               const op::MVNEpsMode mode, const reference_tests::Tensor& paramExpected)
+    MVN6Params(const reference_tests::Tensor& paramInput,
+               const reference_tests::Tensor& paramReductionAxes,
+               const bool paramNormalizeVariance,
+               const double paramEps,
+               const op::MVNEpsMode mode,
+               const reference_tests::Tensor& paramExpected)
         : input(paramInput),
           reductionAxes(paramReductionAxes),
           normalizeVariance(paramNormalizeVariance),
@@ -160,7 +203,8 @@ class ReferenceMVN6LayerTest : public testing::TestWithParam<MVN6Params>, public
 public:
     void SetUp() override {
         auto params = GetParam();
-        function = CreateFunction(params.input, params.reductionAxes, params.normalizeVariance, params.eps, params.epsMode);
+        function =
+            CreateFunction(params.input, params.reductionAxes, params.normalizeVariance, params.eps, params.epsMode);
         inputData = {params.input.data};
         refOutData = {params.expected.data};
     }
@@ -177,8 +221,11 @@ class ReferenceMVN6LayerTest : public testing::TestWithParam<MVN6Params>, public
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const reference_tests::Tensor& input, const reference_tests::Tensor& reductionAxes, const bool normalizeVariance, const double eps,
-                                                    const op::MVNEpsMode epsMode) {
+    static std::shared_ptr<Model> CreateFunction(const reference_tests::Tensor& input,
+                                                 const reference_tests::Tensor& reductionAxes,
+                                                 const bool normalizeVariance,
+                                                 const double eps,
+                                                 const op::MVNEpsMode epsMode) {
         std::vector<int64_t> dataVector(reductionAxes.shape[0]);
         const auto in = std::make_shared<op::v0::Parameter>(input.type, input.shape);
         const auto refBuffer = reductionAxes.data.data<const std::int64_t>();
@@ -187,7 +234,7 @@ class ReferenceMVN6LayerTest : public testing::TestWithParam<MVN6Params>, public
         }
         const auto axes = std::make_shared<op::v0::Constant>(reductionAxes.type, reductionAxes.shape, dataVector);
         auto mvn = std::make_shared<op::v6::MVN>(in, axes, normalizeVariance, static_cast<float>(eps), epsMode);
-        return std::make_shared<ov::Model>(NodeVector {mvn}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{mvn}, ParameterVector{in});
     }
 };
 
@@ -196,51 +243,68 @@ TEST_P(ReferenceMVN6LayerTest, CompareWithHardcodedRefs) {
 }
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_MVN6_With_Hardcoded_Refs, ReferenceMVN6LayerTest,
+    smoke_MVN6_With_Hardcoded_Refs,
+    ReferenceMVN6LayerTest,
     ::testing::Values(
         // variance=false, OUTSIDE_SQRT
-        MVN6Params(reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
-                                                                                   6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
-                   reference_tests::Tensor {Shape {2}, ov::element::i64, std::vector<int64_t> {2, 3}},
+        MVN6Params(reference_tests::Tensor{{1, 3, 3, 3},
+                                           ov::element::f32,
+                                           std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
+                                                              6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
+                   reference_tests::Tensor{Shape{2}, ov::element::i64, std::vector<int64_t>{2, 3}},
                    false,
                    1e-9,
                    op::MVNEpsMode::OUTSIDE_SQRT,
-                   reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {-4, -3, -2, -1, 0,  1,  2,  3,  4, -4, -3, -2, -1, 0,
-                                                                                   1,  2,  3,  4,  -4, -3, -2, -1, 0, 1,  2,  3,  4}}),
+                   reference_tests::Tensor{{1, 3, 3, 3},
+                                           ov::element::f32,
+                                           std::vector<float>{-4, -3, -2, -1, 0,  1,  2,  3,  4, -4, -3, -2, -1, 0,
+                                                              1,  2,  3,  4,  -4, -3, -2, -1, 0, 1,  2,  3,  4}}),
         // variance=true, OUTSIDE_SQRT
-        MVN6Params(reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
-                                                                                   6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
-                   reference_tests::Tensor {Shape {2}, ov::element::i64, std::vector<int64_t> {2, 3}},
-                   true,
-                   1e-9,
-                   op::MVNEpsMode::OUTSIDE_SQRT,
-                   reference_tests::Tensor {{1, 3, 3, 3},
-                           ov::element::f32,
-                           std::vector<float> {-1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934}}),
+        MVN6Params(
+            reference_tests::Tensor{{1, 3, 3, 3}, ov::element::f32, std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9}},
+            reference_tests::Tensor{Shape{2}, ov::element::i64, std::vector<int64_t>{2, 3}},
+            true,
+            1e-9,
+            op::MVNEpsMode::OUTSIDE_SQRT,
+            reference_tests::Tensor{
+                {1, 3, 3, 3},
+                ov::element::f32,
+                std::vector<float>{-1.5491934,  -1.161895, -0.7745967, -0.38729835, 0.,         0.38729835,  0.7745967,
+                                   1.161895,    1.5491934, -1.5491934, -1.161895,   -0.7745967, -0.38729835, 0.,
+                                   0.38729835,  0.7745967, 1.161895,   1.5491934,   -1.5491934, -1.161895,   -0.7745967,
+                                   -0.38729835, 0.,        0.38729835, 0.7745967,   1.161895,   1.5491934}}),
         // variance=true, INSIDE_SQRT
-        MVN6Params(reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
-                                                                                   6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9}},
-                   reference_tests::Tensor {Shape {2}, ov::element::i64, std::vector<int64_t> {2, 3}},
-                   true,
-                   1e-9,
-                   op::MVNEpsMode::INSIDE_SQRT,
-                   reference_tests::Tensor {{1, 3, 3, 3},
-                           ov::element::f32,
-                           std::vector<float> {-1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934}}),
+        MVN6Params(
+            reference_tests::Tensor{{1, 3, 3, 3}, ov::element::f32, std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                       1, 2, 3, 4, 5, 6, 7, 8, 9}},
+            reference_tests::Tensor{Shape{2}, ov::element::i64, std::vector<int64_t>{2, 3}},
+            true,
+            1e-9,
+            op::MVNEpsMode::INSIDE_SQRT,
+            reference_tests::Tensor{
+                {1, 3, 3, 3},
+                ov::element::f32,
+                std::vector<float>{-1.5491934,  -1.161895, -0.7745967, -0.38729835, 0.,         0.38729835,  0.7745967,
+                                   1.161895,    1.5491934, -1.5491934, -1.161895,   -0.7745967, -0.38729835, 0.,
+                                   0.38729835,  0.7745967, 1.161895,   1.5491934,   -1.5491934, -1.161895,   -0.7745967,
+                                   -0.38729835, 0.,        0.38729835, 0.7745967,   1.161895,   1.5491934}}),
         // variance=true, another reductionAxes, OUTSIDE_SQRT
-        MVN6Params(reference_tests::Tensor {{1, 3, 3, 3}, ov::element::f32, std::vector<float>({1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 2, 3, 4, 5,
-                                                                                   6, 7, 8, 9, 1, 2, 3, 4, 5, 6, 7, 8, 9})},
-                   reference_tests::Tensor {Shape {3}, ov::element::i64, std::vector<int64_t>({1, 2, 3})},
-                   true,
-                   1e-9,
-                   op::MVNEpsMode::OUTSIDE_SQRT,
-                   reference_tests::Tensor {{1, 3, 3, 3},
-                           ov::element::f32,
-                           std::vector<float> {-1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934,
-                                               -1.5491934, -1.161895, -0.7745967, -0.38729835, 0., 0.38729835, 0.7745967, 1.161895, 1.5491934}})),
+        MVN6Params(
+            reference_tests::Tensor{{1, 3, 3, 3}, ov::element::f32, std::vector<float>({1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                        1, 2, 3, 4, 5, 6, 7, 8, 9,
+                                                                                        1, 2, 3, 4, 5, 6, 7, 8, 9})},
+            reference_tests::Tensor{Shape{3}, ov::element::i64, std::vector<int64_t>({1, 2, 3})},
+            true,
+            1e-9,
+            op::MVNEpsMode::OUTSIDE_SQRT,
+            reference_tests::Tensor{
+                {1, 3, 3, 3},
+                ov::element::f32,
+                std::vector<float>{-1.5491934,  -1.161895, -0.7745967, -0.38729835, 0.,         0.38729835,  0.7745967,
+                                   1.161895,    1.5491934, -1.5491934, -1.161895,   -0.7745967, -0.38729835, 0.,
+                                   0.38729835,  0.7745967, 1.161895,   1.5491934,   -1.5491934, -1.161895,   -0.7745967,
+                                   -0.38729835, 0.,        0.38729835, 0.7745967,   1.161895,   1.5491934}})),
     ReferenceMVN6LayerTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/op_reference/negative.cpp b/src/plugins/template/tests/functional/op_reference/negative.cpp
index caf94a0fbc0cc6..89cda5cfe3c85a 100644
--- a/src/plugins/template/tests/functional/op_reference/negative.cpp
+++ b/src/plugins/template/tests/functional/op_reference/negative.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/negative.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/negative.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,9 +16,9 @@ namespace {
 struct NegativeParams {
     template <class IT>
     NegativeParams(const PartialShape& shape,
-                  const element::Type& iType,
-                  const std::vector<IT>& iValues,
-                  const std::vector<IT>& oValues)
+                   const element::Type& iType,
+                   const std::vector<IT>& iValues,
+                   const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -50,8 +52,8 @@ class ReferenceNegativeLayerTest : public testing::TestWithParam<NegativeParams>
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto negative = std::make_shared<op::v0::Negative>(in);
         return std::make_shared<Model>(NodeVector{negative}, ParameterVector{in});
@@ -66,12 +68,10 @@ template <element::Type_t IN_ET>
 std::vector<NegativeParams> generateParamsForNegativeFloat() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<NegativeParams> params{
-        NegativeParams(ov::PartialShape{6},
-                       IN_ET,
-                       std::vector<T>{1, -2, 0, -4.75f, 8.75f, -8.75f},
-                       std::vector<T>{-1, 2, 0, 4.75f, -8.75f, 8.75f})
-    };
+    std::vector<NegativeParams> params{NegativeParams(ov::PartialShape{6},
+                                                      IN_ET,
+                                                      std::vector<T>{1, -2, 0, -4.75f, 8.75f, -8.75f},
+                                                      std::vector<T>{-1, 2, 0, 4.75f, -8.75f, 8.75f})};
     return params;
 }
 
@@ -79,12 +79,10 @@ template <element::Type_t IN_ET>
 std::vector<NegativeParams> generateParamsForNegativeInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<NegativeParams> params{
-        NegativeParams(ov::PartialShape{10},
-                       IN_ET,
-                       std::vector<T>{1, 8, -8, 17, -2, 1, 8, -8, 17, -1},
-                       std::vector<T>{-1, -8, 8, -17, 2, -1, -8, 8, -17, 1})
-    };
+    std::vector<NegativeParams> params{NegativeParams(ov::PartialShape{10},
+                                                      IN_ET,
+                                                      std::vector<T>{1, 8, -8, 17, -2, 1, 8, -8, 17, -1},
+                                                      std::vector<T>{-1, -8, 8, -17, 2, -1, -8, 8, -17, 1})};
     return params;
 }
 
@@ -94,8 +92,7 @@ std::vector<NegativeParams> generateCombinedParamsForNegative() {
         generateParamsForNegativeFloat<element::Type_t::f16>(),
         generateParamsForNegativeFloat<element::Type_t::bf16>(),
         generateParamsForNegativeInt<element::Type_t::i64>(),
-        generateParamsForNegativeInt<element::Type_t::i32>()
-    };
+        generateParamsForNegativeInt<element::Type_t::i32>()};
 
     std::vector<NegativeParams> combinedParams;
 
@@ -106,9 +103,8 @@ std::vector<NegativeParams> generateCombinedParamsForNegative() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Negative_With_Hardcoded_Refs,
-    ReferenceNegativeLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForNegative()),
-    ReferenceNegativeLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Negative_With_Hardcoded_Refs,
+                         ReferenceNegativeLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForNegative()),
+                         ReferenceNegativeLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/non_max_suppression.cpp b/src/plugins/template/tests/functional/op_reference/non_max_suppression.cpp
index 5e309f4e6e9743..333ea4cf0d2845 100644
--- a/src/plugins/template/tests/functional/op_reference/non_max_suppression.cpp
+++ b/src/plugins/template/tests/functional/op_reference/non_max_suppression.cpp
@@ -4,11 +4,11 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset5.hpp"
-#include "openvino/opsets/opset4.hpp"
-#include "openvino/opsets/opset3.hpp"
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
+#include "openvino/opsets/opset3.hpp"
+#include "openvino/opsets/opset4.hpp"
+#include "openvino/opsets/opset5.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -42,7 +42,8 @@ struct Builder : ParamsBuilder<NonMaxSuppressionParams> {
     REFERENCE_TESTS_ADD_SET_PARAM(Builder, testcaseName);
 };
 
-class ReferenceNonMaxSuppressionTest : public testing::TestWithParam<NonMaxSuppressionParams>, public CommonReferenceTest {
+class ReferenceNonMaxSuppressionTest : public testing::TestWithParam<NonMaxSuppressionParams>,
+                                       public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -76,14 +77,19 @@ class ReferenceNonMaxSuppressionTest : public testing::TestWithParam<NonMaxSuppr
     static std::shared_ptr<Model> CreateFunction(const NonMaxSuppressionParams& params) {
         const auto boxes = std::make_shared<opset1::Parameter>(params.boxes.type, params.boxes.shape);
         const auto scores = std::make_shared<opset1::Parameter>(params.scores.type, params.scores.shape);
-        const auto max_output_boxes_per_class = std::make_shared<opset1::Constant>(
-            params.maxOutputBoxesPerClass.type, params.maxOutputBoxesPerClass.shape, params.maxOutputBoxesPerClass.data.data());
-        const auto iou_threshold = std::make_shared<opset1::Constant>(
-            params.iouThreshold.type, params.iouThreshold.shape, params.iouThreshold.data.data());
-        const auto score_threshold = std::make_shared<opset1::Constant>(
-            params.scoreThreshold.type, params.scoreThreshold.shape, params.scoreThreshold.data.data());
-        const auto soft_nms_sigma = std::make_shared<opset1::Constant>(
-            params.softNmsSigma.type, params.softNmsSigma.shape, params.softNmsSigma.data.data());
+        const auto max_output_boxes_per_class =
+            std::make_shared<opset1::Constant>(params.maxOutputBoxesPerClass.type,
+                                               params.maxOutputBoxesPerClass.shape,
+                                               params.maxOutputBoxesPerClass.data.data());
+        const auto iou_threshold = std::make_shared<opset1::Constant>(params.iouThreshold.type,
+                                                                      params.iouThreshold.shape,
+                                                                      params.iouThreshold.data.data());
+        const auto score_threshold = std::make_shared<opset1::Constant>(params.scoreThreshold.type,
+                                                                        params.scoreThreshold.shape,
+                                                                        params.scoreThreshold.data.data());
+        const auto soft_nms_sigma = std::make_shared<opset1::Constant>(params.softNmsSigma.type,
+                                                                       params.softNmsSigma.shape,
+                                                                       params.softNmsSigma.data.data());
         const auto nms = std::make_shared<opset5::NonMaxSuppression>(boxes,
                                                                      scores,
                                                                      max_output_boxes_per_class,
@@ -103,8 +109,12 @@ class ReferenceNonMaxSuppressionTestWithoutConstants : public ReferenceNonMaxSup
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.boxes.data, params.scores.data, params.maxOutputBoxesPerClass.data,
-                     params.iouThreshold.data, params.scoreThreshold.data, params.softNmsSigma.data};
+        inputData = {params.boxes.data,
+                     params.scores.data,
+                     params.maxOutputBoxesPerClass.data,
+                     params.iouThreshold.data,
+                     params.scoreThreshold.data,
+                     params.softNmsSigma.data};
         refOutData = {params.expectedSelectedIndices.data,
                       params.expectedSelectedScores.data,
                       params.expectedValidOutputs.data};
@@ -114,14 +124,15 @@ class ReferenceNonMaxSuppressionTestWithoutConstants : public ReferenceNonMaxSup
     static std::shared_ptr<Model> CreateFunction(const NonMaxSuppressionParams& params) {
         const auto boxes = std::make_shared<opset1::Parameter>(params.boxes.type, params.boxes.shape);
         const auto scores = std::make_shared<opset1::Parameter>(params.scores.type, params.scores.shape);
-        const auto max_output_boxes_per_class = std::make_shared<opset1::Parameter>(
-            params.maxOutputBoxesPerClass.type, params.maxOutputBoxesPerClass.shape);
-        const auto iou_threshold = std::make_shared<opset1::Parameter>(
-            params.iouThreshold.type, params.iouThreshold.shape);
-        const auto score_threshold = std::make_shared<opset1::Parameter>(
-            params.scoreThreshold.type, params.scoreThreshold.shape);
-        const auto soft_nms_sigma = std::make_shared<opset1::Parameter>(
-            params.softNmsSigma.type, params.softNmsSigma.shape);
+        const auto max_output_boxes_per_class =
+            std::make_shared<opset1::Parameter>(params.maxOutputBoxesPerClass.type,
+                                                params.maxOutputBoxesPerClass.shape);
+        const auto iou_threshold =
+            std::make_shared<opset1::Parameter>(params.iouThreshold.type, params.iouThreshold.shape);
+        const auto score_threshold =
+            std::make_shared<opset1::Parameter>(params.scoreThreshold.type, params.scoreThreshold.shape);
+        const auto soft_nms_sigma =
+            std::make_shared<opset1::Parameter>(params.softNmsSigma.type, params.softNmsSigma.shape);
         const auto nms = std::make_shared<opset5::NonMaxSuppression>(boxes,
                                                                      scores,
                                                                      max_output_boxes_per_class,
@@ -131,9 +142,9 @@ class ReferenceNonMaxSuppressionTestWithoutConstants : public ReferenceNonMaxSup
                                                                      params.boxEncoding,
                                                                      false,
                                                                      params.expectedSelectedIndices.type);
-        const auto f = std::make_shared<Model>(nms->outputs(),
-                                               ParameterVector{boxes, scores, max_output_boxes_per_class,
-                                                               iou_threshold, score_threshold, soft_nms_sigma});
+        const auto f = std::make_shared<Model>(
+            nms->outputs(),
+            ParameterVector{boxes, scores, max_output_boxes_per_class, iou_threshold, score_threshold, soft_nms_sigma});
         return f;
     }
 };
@@ -152,268 +163,174 @@ std::vector<NonMaxSuppressionParams> generateParams() {
     using T_BOX = typename element_type_traits<ET_BOX>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<NonMaxSuppressionParams> params {
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.5, 0.5,  1.0, 1.0, 0.5, 0.6,  1.0, 1.0, 0.5, 0.4,   1.0, 1.0,
-                0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CENTER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {3, 3}, std::vector<T_TH>{
-                0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 0.0, 0.0, 0.3}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}))
-        .testcaseName(
-            "nonmaxsuppression_center_point_box_format"),
-
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                1.0, 1.0,  0.0, 0.0,  0.0, 0.1,  1.0, 1.1,  0.0, 0.9,   1.0, -0.1,
-                0.0, 10.0, 1.0, 11.0, 1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {3, 3}, std::vector<T_TH>{
-                0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 0.0, 0.0, 0.3}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}))
-        .testcaseName(
-            "nonmaxsuppression_flipped_coordinates"),
-
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,
-                1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{
-                0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {1, 3}, std::vector<T_TH>{0.0, 0.0, 0.9}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}))
-        .testcaseName(
-            "nonmaxsuppression_identical_boxes"),
-
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {2, 3}, std::vector<T_TH>{
-                0.0, 0.0, 0.95, 0.0, 0.0, 0.9}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}))
-        .testcaseName(
-            "nonmaxsuppression_limit_output_size"),
-
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{0.9}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {1, 3}, std::vector<T_TH>{0.0, 0.0, 0.9}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}))
-        .testcaseName(
-            "nonmaxsuppression_single_box"),
-
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {3, 3}, std::vector<T_TH>{
-                0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 0.0, 0.0, 0.3}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU"),
-
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {2, 3}, std::vector<T_TH>{
-                0.0, 0.0, 0.95, 0.0, 0.0, 0.9}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU_and_scores"),
-
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {2, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 1, 0, 3, 1, 0, 0}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {4, 3}, std::vector<T_TH>{
-                0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 1.0, 0.0, 0.95, 1.0, 0.0, 0.9}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}))
-        .testcaseName(
-            "nonmaxsuppression_two_batches"),
-
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 2, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 1, 3, 0, 1, 0}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {4, 3}, std::vector<T_TH>{
-                0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 0.0, 1.0, 0.95, 0.0, 1.0, 0.9}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}))
-        .testcaseName(
-            "nonmaxsuppression_two_classes"),
+    std::vector<NonMaxSuppressionParams> params{
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.5, 0.5,  1.0, 1.0, 0.5, 0.6,   1.0, 1.0,
+                                                                         0.5, 0.4,  1.0, 1.0, 0.5, 10.5,  1.0, 1.0,
+                                                                         0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CENTER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .expectedSelectedScores(
+                reference_tests::Tensor(ET_TH, {3, 3}, std::vector<T_TH>{0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 0.0, 0.0, 0.3}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}))
+            .testcaseName("nonmaxsuppression_center_point_box_format"),
+
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{1.0, 1.0,  0.0, 0.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, 0.9,  1.0, -0.1, 0.0, 10.0,  1.0, 11.0,
+                                                                         1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .expectedSelectedScores(
+                reference_tests::Tensor(ET_TH, {3, 3}, std::vector<T_TH>{0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 0.0, 0.0, 0.3}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}))
+            .testcaseName("nonmaxsuppression_flipped_coordinates"),
+
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET,
+                                            {1, 1, 10},
+                                            std::vector<T>{0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
+            .expectedSelectedScores(reference_tests::Tensor(ET_TH, {1, 3}, std::vector<T_TH>{0.0, 0.0, 0.9}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}))
+            .testcaseName("nonmaxsuppression_identical_boxes"),
+
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
+            .expectedSelectedScores(
+                reference_tests::Tensor(ET_TH, {2, 3}, std::vector<T_TH>{0.0, 0.0, 0.95, 0.0, 0.0, 0.9}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}))
+            .testcaseName("nonmaxsuppression_limit_output_size"),
+
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{0.9}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
+            .expectedSelectedScores(reference_tests::Tensor(ET_TH, {1, 3}, std::vector<T_TH>{0.0, 0.0, 0.9}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}))
+            .testcaseName("nonmaxsuppression_single_box"),
+
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .expectedSelectedScores(
+                reference_tests::Tensor(ET_TH, {3, 3}, std::vector<T_TH>{0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 0.0, 0.0, 0.3}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{3}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU"),
+
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
+            .expectedSelectedScores(
+                reference_tests::Tensor(ET_TH, {2, 3}, std::vector<T_TH>{0.0, 0.0, 0.95, 0.0, 0.0, 0.9}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{2}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU_and_scores"),
+
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                                                                         0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(
+                reference_tests::Tensor(ET,
+                                        {2, 1, 6},
+                                        std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 1, 0, 3, 1, 0, 0}))
+            .expectedSelectedScores(reference_tests::Tensor(
+                ET_TH,
+                {4, 3},
+                std::vector<T_TH>{0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 1.0, 0.0, 0.95, 1.0, 0.0, 0.9}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}))
+            .testcaseName("nonmaxsuppression_two_batches"),
+
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(
+                reference_tests::Tensor(ET,
+                                        {1, 2, 6},
+                                        std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 1, 3, 0, 1, 0}))
+            .expectedSelectedScores(reference_tests::Tensor(
+                ET_TH,
+                {4, 3},
+                std::vector<T_TH>{0.0, 0.0, 0.95, 0.0, 0.0, 0.9, 0.0, 1.0, 0.95, 0.0, 1.0, 0.9}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{4}))
+            .testcaseName("nonmaxsuppression_two_classes"),
     };
     return params;
 }
 
 std::vector<NonMaxSuppressionParams> generateCombinedParams() {
-    const std::vector<std::vector<NonMaxSuppressionParams>> generatedParams {
+    const std::vector<std::vector<NonMaxSuppressionParams>> generatedParams{
         generateParams<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
         generateParams<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
         generateParams<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
@@ -435,45 +352,52 @@ std::vector<NonMaxSuppressionParams> generateParamsWithoutConstants() {
     using T_BOX = typename element_type_traits<ET_BOX>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<NonMaxSuppressionParams> params {
-        Builder {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0f, 0.0f,  1.0f, 1.0f,  0.0f, 0.1f,  1.0f, 1.1f,  0.0f, -0.1f,  1.0f, 0.9f,
-                0.0f, 10.0f, 1.0f, 11.0f, 0.0f, 10.1f, 1.0f, 11.1f, 0.0f, 100.0f, 1.0f, 101.0f}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9f, 0.75f, 0.6f, 0.95f, 0.5f, 0.3f}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {1}, std::vector<T_BOX>{1}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {1}, std::vector<T_TH>{0.4f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {1}, std::vector<T_TH>{0.2f}))
-        .softNmsSigma(
-            reference_tests::Tensor(ET_TH, {1}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset5::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 3}))
-        .expectedSelectedScores(
-            reference_tests::Tensor(ET_TH, {1, 3}, std::vector<T_TH>{0.0f, 0.0f, 0.95f}))
-        .expectedValidOutputs(
-            reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU_and_scores_without_constants"),
+    std::vector<NonMaxSuppressionParams> params{
+        Builder{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0f, 0.0f,  1.0f, 1.0f,   0.0f, 0.1f,
+                                                                         1.0f, 1.1f,  0.0f, -0.1f,  1.0f, 0.9f,
+                                                                         0.0f, 10.0f, 1.0f, 11.0f,  0.0f, 10.1f,
+                                                                         1.0f, 11.1f, 0.0f, 100.0f, 1.0f, 101.0f}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9f, 0.75f, 0.6f, 0.95f, 0.5f, 0.3f}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {1}, std::vector<T_BOX>{1}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {1}, std::vector<T_TH>{0.4f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {1}, std::vector<T_TH>{0.2f}))
+            .softNmsSigma(reference_tests::Tensor(ET_TH, {1}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset5::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 3}))
+            .expectedSelectedScores(reference_tests::Tensor(ET_TH, {1, 3}, std::vector<T_TH>{0.0f, 0.0f, 0.95f}))
+            .expectedValidOutputs(reference_tests::Tensor(ET_IND, {1}, std::vector<T_IND>{1}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU_and_scores_without_constants"),
     };
     return params;
 }
 
 std::vector<NonMaxSuppressionParams> generateCombinedParamsWithoutConstants() {
-    const std::vector<std::vector<NonMaxSuppressionParams>> generatedParams {
-        generateParamsWithoutConstants<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParamsWithoutConstants<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParamsWithoutConstants<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParamsWithoutConstants<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
-        generateParamsWithoutConstants<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
-        generateParamsWithoutConstants<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
+    const std::vector<std::vector<NonMaxSuppressionParams>> generatedParams{
+        generateParamsWithoutConstants<element::Type_t::bf16,
+                                       element::Type_t::i32,
+                                       element::Type_t::f32,
+                                       element::Type_t::i32>(),
+        generateParamsWithoutConstants<element::Type_t::f16,
+                                       element::Type_t::i32,
+                                       element::Type_t::f32,
+                                       element::Type_t::i32>(),
+        generateParamsWithoutConstants<element::Type_t::f32,
+                                       element::Type_t::i32,
+                                       element::Type_t::f32,
+                                       element::Type_t::i32>(),
+        generateParamsWithoutConstants<element::Type_t::bf16,
+                                       element::Type_t::i32,
+                                       element::Type_t::f32,
+                                       element::Type_t::i64>(),
+        generateParamsWithoutConstants<element::Type_t::f16,
+                                       element::Type_t::i32,
+                                       element::Type_t::f32,
+                                       element::Type_t::i64>(),
+        generateParamsWithoutConstants<element::Type_t::f32,
+                                       element::Type_t::i32,
+                                       element::Type_t::f32,
+                                       element::Type_t::i64>(),
     };
     std::vector<NonMaxSuppressionParams> combinedParams;
 
@@ -483,11 +407,14 @@ std::vector<NonMaxSuppressionParams> generateCombinedParamsWithoutConstants() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs, ReferenceNonMaxSuppressionTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceNonMaxSuppressionTest::getTestCaseName);
-INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs, ReferenceNonMaxSuppressionTestWithoutConstants,
-    testing::ValuesIn(generateCombinedParamsWithoutConstants()), ReferenceNonMaxSuppressionTestWithoutConstants::getTestCaseName);
-
+INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs,
+                         ReferenceNonMaxSuppressionTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceNonMaxSuppressionTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs,
+                         ReferenceNonMaxSuppressionTestWithoutConstants,
+                         testing::ValuesIn(generateCombinedParamsWithoutConstants()),
+                         ReferenceNonMaxSuppressionTestWithoutConstants::getTestCaseName);
 
 struct NonMaxSuppression4Params {
     reference_tests::Tensor boxes;
@@ -511,7 +438,8 @@ struct Builder4 : ParamsBuilder<NonMaxSuppression4Params> {
     REFERENCE_TESTS_ADD_SET_PARAM(Builder4, testcaseName);
 };
 
-class ReferenceNonMaxSuppression4Test : public testing::TestWithParam<NonMaxSuppression4Params>, public CommonReferenceTest {
+class ReferenceNonMaxSuppression4Test : public testing::TestWithParam<NonMaxSuppression4Params>,
+                                        public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -539,12 +467,16 @@ class ReferenceNonMaxSuppression4Test : public testing::TestWithParam<NonMaxSupp
     static std::shared_ptr<Model> CreateFunction(const NonMaxSuppression4Params& params) {
         const auto boxes = std::make_shared<opset1::Parameter>(params.boxes.type, params.boxes.shape);
         const auto scores = std::make_shared<opset1::Parameter>(params.scores.type, params.scores.shape);
-        const auto max_output_boxes_per_class = std::make_shared<opset1::Constant>(
-            params.maxOutputBoxesPerClass.type, params.maxOutputBoxesPerClass.shape, params.maxOutputBoxesPerClass.data.data());
-        const auto iou_threshold = std::make_shared<opset1::Constant>(
-            params.iouThreshold.type, params.iouThreshold.shape, params.iouThreshold.data.data());
-        const auto score_threshold = std::make_shared<opset1::Constant>(
-            params.scoreThreshold.type, params.scoreThreshold.shape, params.scoreThreshold.data.data());
+        const auto max_output_boxes_per_class =
+            std::make_shared<opset1::Constant>(params.maxOutputBoxesPerClass.type,
+                                               params.maxOutputBoxesPerClass.shape,
+                                               params.maxOutputBoxesPerClass.data.data());
+        const auto iou_threshold = std::make_shared<opset1::Constant>(params.iouThreshold.type,
+                                                                      params.iouThreshold.shape,
+                                                                      params.iouThreshold.data.data());
+        const auto score_threshold = std::make_shared<opset1::Constant>(params.scoreThreshold.type,
+                                                                        params.scoreThreshold.shape,
+                                                                        params.scoreThreshold.data.data());
         const auto nms = std::make_shared<opset4::NonMaxSuppression>(boxes,
                                                                      scores,
                                                                      max_output_boxes_per_class,
@@ -563,8 +495,11 @@ class ReferenceNonMaxSuppression4TestWithoutConstants : public ReferenceNonMaxSu
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.boxes.data, params.scores.data, params.maxOutputBoxesPerClass.data,
-                     params.iouThreshold.data, params.scoreThreshold.data};
+        inputData = {params.boxes.data,
+                     params.scores.data,
+                     params.maxOutputBoxesPerClass.data,
+                     params.iouThreshold.data,
+                     params.scoreThreshold.data};
         refOutData = {params.expectedSelectedIndices.data};
     }
 
@@ -572,12 +507,13 @@ class ReferenceNonMaxSuppression4TestWithoutConstants : public ReferenceNonMaxSu
     static std::shared_ptr<Model> CreateFunction(const NonMaxSuppression4Params& params) {
         const auto boxes = std::make_shared<opset1::Parameter>(params.boxes.type, params.boxes.shape);
         const auto scores = std::make_shared<opset1::Parameter>(params.scores.type, params.scores.shape);
-        const auto max_output_boxes_per_class = std::make_shared<opset1::Parameter>(
-            params.maxOutputBoxesPerClass.type, params.maxOutputBoxesPerClass.shape);
-        const auto iou_threshold = std::make_shared<opset1::Parameter>(
-            params.iouThreshold.type, params.iouThreshold.shape);
-        const auto score_threshold = std::make_shared<opset1::Parameter>(
-            params.scoreThreshold.type, params.scoreThreshold.shape);
+        const auto max_output_boxes_per_class =
+            std::make_shared<opset1::Parameter>(params.maxOutputBoxesPerClass.type,
+                                                params.maxOutputBoxesPerClass.shape);
+        const auto iou_threshold =
+            std::make_shared<opset1::Parameter>(params.iouThreshold.type, params.iouThreshold.shape);
+        const auto score_threshold =
+            std::make_shared<opset1::Parameter>(params.scoreThreshold.type, params.scoreThreshold.shape);
         const auto nms = std::make_shared<opset4::NonMaxSuppression>(boxes,
                                                                      scores,
                                                                      max_output_boxes_per_class,
@@ -586,9 +522,9 @@ class ReferenceNonMaxSuppression4TestWithoutConstants : public ReferenceNonMaxSu
                                                                      params.boxEncoding,
                                                                      false,
                                                                      params.expectedSelectedIndices.type);
-        const auto f = std::make_shared<Model>(nms->outputs(),
-                                               ParameterVector{boxes, scores, max_output_boxes_per_class,
-                                                               iou_threshold, score_threshold});
+        const auto f = std::make_shared<Model>(
+            nms->outputs(),
+            ParameterVector{boxes, scores, max_output_boxes_per_class, iou_threshold, score_threshold});
         return f;
     }
 };
@@ -607,207 +543,136 @@ std::vector<NonMaxSuppression4Params> generateParams4() {
     using T_BOX = typename element_type_traits<ET_BOX>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<NonMaxSuppression4Params> params {
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.5, 0.5,  1.0, 1.0, 0.5, 0.6,  1.0, 1.0, 0.5, 0.4,   1.0, 1.0,
-                0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CENTER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_center_point_box_format"),
-
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                1.0, 1.0,  0.0, 0.0,  0.0, 0.1,  1.0, 1.1,  0.0, 0.9,   1.0, -0.1,
-                0.0, 10.0, 1.0, 11.0, 1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_flipped_coordinates"),
-
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,
-                1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{
-                0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_identical_boxes"),
-
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_limit_output_size"),
-
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{0.9}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_single_box"),
-
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU"),
-
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU_and_scores"),
-
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {2, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 1, 0, 3, 1, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_two_batches"),
-
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 2, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 1, 3, 0, 1, 0}))
-        .testcaseName(
-            "nonmaxsuppression_two_classes"),
+    std::vector<NonMaxSuppression4Params> params{
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.5, 0.5,  1.0, 1.0, 0.5, 0.6,   1.0, 1.0,
+                                                                         0.5, 0.4,  1.0, 1.0, 0.5, 10.5,  1.0, 1.0,
+                                                                         0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CENTER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_center_point_box_format"),
+
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{1.0, 1.0,  0.0, 0.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, 0.9,  1.0, -0.1, 0.0, 10.0,  1.0, 11.0,
+                                                                         1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_flipped_coordinates"),
+
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET,
+                                            {1, 1, 10},
+                                            std::vector<T>{0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
+            .testcaseName("nonmaxsuppression_identical_boxes"),
+
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
+            .testcaseName("nonmaxsuppression_limit_output_size"),
+
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{0.9}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
+            .testcaseName("nonmaxsuppression_single_box"),
+
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU"),
+
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU_and_scores"),
+
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {2, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0,
+                                                                         0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(
+                reference_tests::Tensor(ET,
+                                        {2, 1, 6},
+                                        std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 1, 0, 3, 1, 0, 0}))
+            .testcaseName("nonmaxsuppression_two_batches"),
+
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(
+                reference_tests::Tensor(ET,
+                                        {1, 2, 6},
+                                        std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 1, 3, 0, 1, 0}))
+            .testcaseName("nonmaxsuppression_two_classes"),
     };
     return params;
 }
 
 std::vector<NonMaxSuppression4Params> generateCombinedParams4() {
-    const std::vector<std::vector<NonMaxSuppression4Params>> generatedParams {
+    const std::vector<std::vector<NonMaxSuppression4Params>> generatedParams{
         generateParams4<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
         generateParams4<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
         generateParams4<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
@@ -829,39 +694,49 @@ std::vector<NonMaxSuppression4Params> generateParams4WithoutConstants() {
     using T_BOX = typename element_type_traits<ET_BOX>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<NonMaxSuppression4Params> params {
-        Builder4 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0f, 0.0f,  1.0f, 1.0f,  0.0f, 0.1f,  1.0f, 1.1f,  0.0f, -0.1f,  1.0f, 0.9f,
-                0.0f, 10.0f, 1.0f, 11.0f, 0.0f, 10.1f, 1.0f, 11.1f, 0.0f, 100.0f, 1.0f, 101.0f}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9f, 0.75f, 0.6f, 0.95f, 0.5f, 0.3f}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.2f}))
-        .boxEncoding(
-            opset4::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 3}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU_and_scores_without_constants"),
+    std::vector<NonMaxSuppression4Params> params{
+        Builder4{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0f, 0.0f,  1.0f, 1.0f,   0.0f, 0.1f,
+                                                                         1.0f, 1.1f,  0.0f, -0.1f,  1.0f, 0.9f,
+                                                                         0.0f, 10.0f, 1.0f, 11.0f,  0.0f, 10.1f,
+                                                                         1.0f, 11.1f, 0.0f, 100.0f, 1.0f, 101.0f}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9f, 0.75f, 0.6f, 0.95f, 0.5f, 0.3f}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.2f}))
+            .boxEncoding(opset4::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 3}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU_and_scores_without_constants"),
     };
     return params;
 }
 
 std::vector<NonMaxSuppression4Params> generateCombinedParams4WithoutConstants() {
-    const std::vector<std::vector<NonMaxSuppression4Params>> generatedParams {
-        generateParams4WithoutConstants<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParams4WithoutConstants<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParams4WithoutConstants<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParams4WithoutConstants<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
-        generateParams4WithoutConstants<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
-        generateParams4WithoutConstants<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
+    const std::vector<std::vector<NonMaxSuppression4Params>> generatedParams{
+        generateParams4WithoutConstants<element::Type_t::bf16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i32>(),
+        generateParams4WithoutConstants<element::Type_t::f16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i32>(),
+        generateParams4WithoutConstants<element::Type_t::f32,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i32>(),
+        generateParams4WithoutConstants<element::Type_t::bf16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
+        generateParams4WithoutConstants<element::Type_t::f16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
+        generateParams4WithoutConstants<element::Type_t::f32,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
     };
     std::vector<NonMaxSuppression4Params> combinedParams;
 
@@ -871,11 +746,14 @@ std::vector<NonMaxSuppression4Params> generateCombinedParams4WithoutConstants()
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs, ReferenceNonMaxSuppression4Test,
-    testing::ValuesIn(generateCombinedParams4()), ReferenceNonMaxSuppression4Test::getTestCaseName);
-INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs, ReferenceNonMaxSuppression4TestWithoutConstants,
-    testing::ValuesIn(generateCombinedParams4WithoutConstants()), ReferenceNonMaxSuppression4TestWithoutConstants::getTestCaseName);
-
+INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs,
+                         ReferenceNonMaxSuppression4Test,
+                         testing::ValuesIn(generateCombinedParams4()),
+                         ReferenceNonMaxSuppression4Test::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs,
+                         ReferenceNonMaxSuppression4TestWithoutConstants,
+                         testing::ValuesIn(generateCombinedParams4WithoutConstants()),
+                         ReferenceNonMaxSuppression4TestWithoutConstants::getTestCaseName);
 
 struct NonMaxSuppression3Params {
     reference_tests::Tensor boxes;
@@ -899,7 +777,8 @@ struct Builder3 : ParamsBuilder<NonMaxSuppression3Params> {
     REFERENCE_TESTS_ADD_SET_PARAM(Builder3, testcaseName);
 };
 
-class ReferenceNonMaxSuppression3Test : public testing::TestWithParam<NonMaxSuppression3Params>, public CommonReferenceTest {
+class ReferenceNonMaxSuppression3Test : public testing::TestWithParam<NonMaxSuppression3Params>,
+                                        public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -927,12 +806,16 @@ class ReferenceNonMaxSuppression3Test : public testing::TestWithParam<NonMaxSupp
     static std::shared_ptr<Model> CreateFunction(const NonMaxSuppression3Params& params) {
         const auto boxes = std::make_shared<opset1::Parameter>(params.boxes.type, params.boxes.shape);
         const auto scores = std::make_shared<opset1::Parameter>(params.scores.type, params.scores.shape);
-        const auto max_output_boxes_per_class = std::make_shared<opset1::Constant>(
-            params.maxOutputBoxesPerClass.type, params.maxOutputBoxesPerClass.shape, params.maxOutputBoxesPerClass.data.data());
-        const auto iou_threshold = std::make_shared<opset1::Constant>(
-            params.iouThreshold.type, params.iouThreshold.shape, params.iouThreshold.data.data());
-        const auto score_threshold = std::make_shared<opset1::Constant>(
-            params.scoreThreshold.type, params.scoreThreshold.shape, params.scoreThreshold.data.data());
+        const auto max_output_boxes_per_class =
+            std::make_shared<opset1::Constant>(params.maxOutputBoxesPerClass.type,
+                                               params.maxOutputBoxesPerClass.shape,
+                                               params.maxOutputBoxesPerClass.data.data());
+        const auto iou_threshold = std::make_shared<opset1::Constant>(params.iouThreshold.type,
+                                                                      params.iouThreshold.shape,
+                                                                      params.iouThreshold.data.data());
+        const auto score_threshold = std::make_shared<opset1::Constant>(params.scoreThreshold.type,
+                                                                        params.scoreThreshold.shape,
+                                                                        params.scoreThreshold.data.data());
         const auto nms = std::make_shared<opset3::NonMaxSuppression>(boxes,
                                                                      scores,
                                                                      max_output_boxes_per_class,
@@ -951,8 +834,11 @@ class ReferenceNonMaxSuppression3TestWithoutConstants : public ReferenceNonMaxSu
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.boxes.data, params.scores.data, params.maxOutputBoxesPerClass.data,
-                     params.iouThreshold.data, params.scoreThreshold.data};
+        inputData = {params.boxes.data,
+                     params.scores.data,
+                     params.maxOutputBoxesPerClass.data,
+                     params.iouThreshold.data,
+                     params.scoreThreshold.data};
         refOutData = {params.expectedSelectedIndices.data};
     }
 
@@ -960,12 +846,13 @@ class ReferenceNonMaxSuppression3TestWithoutConstants : public ReferenceNonMaxSu
     static std::shared_ptr<Model> CreateFunction(const NonMaxSuppression3Params& params) {
         const auto boxes = std::make_shared<opset1::Parameter>(params.boxes.type, params.boxes.shape);
         const auto scores = std::make_shared<opset1::Parameter>(params.scores.type, params.scores.shape);
-        const auto max_output_boxes_per_class = std::make_shared<opset1::Parameter>(
-            params.maxOutputBoxesPerClass.type, params.maxOutputBoxesPerClass.shape);
-        const auto iou_threshold = std::make_shared<opset1::Parameter>(
-            params.iouThreshold.type, params.iouThreshold.shape);
-        const auto score_threshold = std::make_shared<opset1::Parameter>(
-            params.scoreThreshold.type, params.scoreThreshold.shape);
+        const auto max_output_boxes_per_class =
+            std::make_shared<opset1::Parameter>(params.maxOutputBoxesPerClass.type,
+                                                params.maxOutputBoxesPerClass.shape);
+        const auto iou_threshold =
+            std::make_shared<opset1::Parameter>(params.iouThreshold.type, params.iouThreshold.shape);
+        const auto score_threshold =
+            std::make_shared<opset1::Parameter>(params.scoreThreshold.type, params.scoreThreshold.shape);
         const auto nms = std::make_shared<opset3::NonMaxSuppression>(boxes,
                                                                      scores,
                                                                      max_output_boxes_per_class,
@@ -974,9 +861,9 @@ class ReferenceNonMaxSuppression3TestWithoutConstants : public ReferenceNonMaxSu
                                                                      params.boxEncoding,
                                                                      false,
                                                                      params.expectedSelectedIndices.type);
-        const auto f = std::make_shared<Model>(nms->outputs(),
-                                               ParameterVector{boxes, scores, max_output_boxes_per_class,
-                                                               iou_threshold, score_threshold});
+        const auto f = std::make_shared<Model>(
+            nms->outputs(),
+            ParameterVector{boxes, scores, max_output_boxes_per_class, iou_threshold, score_threshold});
         return f;
     }
 };
@@ -995,183 +882,117 @@ std::vector<NonMaxSuppression3Params> generateParams3() {
     using T_BOX = typename element_type_traits<ET_BOX>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<NonMaxSuppression3Params> params {
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.5, 0.5,  1.0, 1.0, 0.5, 0.6,  1.0, 1.0, 0.5, 0.4,   1.0, 1.0,
-                0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CENTER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_center_point_box_format"),
-
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                1.0, 1.0,  0.0, 0.0,  0.0, 0.1,  1.0, 1.1,  0.0, 0.9,   1.0, -0.1,
-                0.0, 10.0, 1.0, 11.0, 1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_flipped_coordinates"),
-
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,
-                1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{
-                0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_identical_boxes"),
-
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_limit_output_size"),
-
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{0.9}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_single_box"),
-
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU"),
-
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU_and_scores"),
-
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 2, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 1, 3, 0, 1, 0}))
-        .testcaseName(
-            "nonmaxsuppression_two_classes"),
+    std::vector<NonMaxSuppression3Params> params{
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.5, 0.5,  1.0, 1.0, 0.5, 0.6,   1.0, 1.0,
+                                                                         0.5, 0.4,  1.0, 1.0, 0.5, 10.5,  1.0, 1.0,
+                                                                         0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CENTER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_center_point_box_format"),
+
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{1.0, 1.0,  0.0, 0.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, 0.9,  1.0, -0.1, 0.0, 10.0,  1.0, 11.0,
+                                                                         1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_flipped_coordinates"),
+
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET,
+                                            {1, 1, 10},
+                                            std::vector<T>{0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
+            .testcaseName("nonmaxsuppression_identical_boxes"),
+
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
+            .testcaseName("nonmaxsuppression_limit_output_size"),
+
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{0.9}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
+            .testcaseName("nonmaxsuppression_single_box"),
+
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU"),
+
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU_and_scores"),
+
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(
+                reference_tests::Tensor(ET,
+                                        {1, 2, 6},
+                                        std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 1, 3, 0, 1, 0}))
+            .testcaseName("nonmaxsuppression_two_classes"),
     };
     return params;
 }
 
 std::vector<NonMaxSuppression3Params> generateCombinedParams3() {
-    const std::vector<std::vector<NonMaxSuppression3Params>> generatedParams {
+    const std::vector<std::vector<NonMaxSuppression3Params>> generatedParams{
         generateParams3<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
         generateParams3<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
         generateParams3<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
@@ -1193,39 +1014,49 @@ std::vector<NonMaxSuppression3Params> generateParams3WithoutConstants() {
     using T_BOX = typename element_type_traits<ET_BOX>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<NonMaxSuppression3Params> params {
-        Builder3 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0f, 0.0f,  1.0f, 1.0f,  0.0f, 0.1f,  1.0f, 1.1f,  0.0f, -0.1f,  1.0f, 0.9f,
-                0.0f, 10.0f, 1.0f, 11.0f, 0.0f, 10.1f, 1.0f, 11.1f, 0.0f, 100.0f, 1.0f, 101.0f}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9f, 0.75f, 0.6f, 0.95f, 0.5f, 0.3f}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.2f}))
-        .boxEncoding(
-            opset3::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 3}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU_and_scores_without_constants"),
+    std::vector<NonMaxSuppression3Params> params{
+        Builder3{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0f, 0.0f,  1.0f, 1.0f,   0.0f, 0.1f,
+                                                                         1.0f, 1.1f,  0.0f, -0.1f,  1.0f, 0.9f,
+                                                                         0.0f, 10.0f, 1.0f, 11.0f,  0.0f, 10.1f,
+                                                                         1.0f, 11.1f, 0.0f, 100.0f, 1.0f, 101.0f}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9f, 0.75f, 0.6f, 0.95f, 0.5f, 0.3f}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.2f}))
+            .boxEncoding(opset3::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 3}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU_and_scores_without_constants"),
     };
     return params;
 }
 
 std::vector<NonMaxSuppression3Params> generateCombinedParams3WithoutConstants() {
-    const std::vector<std::vector<NonMaxSuppression3Params>> generatedParams {
-        generateParams3WithoutConstants<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParams3WithoutConstants<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParams3WithoutConstants<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i32>(),
-        generateParams3WithoutConstants<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
-        generateParams3WithoutConstants<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
-        generateParams3WithoutConstants<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
+    const std::vector<std::vector<NonMaxSuppression3Params>> generatedParams{
+        generateParams3WithoutConstants<element::Type_t::bf16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i32>(),
+        generateParams3WithoutConstants<element::Type_t::f16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i32>(),
+        generateParams3WithoutConstants<element::Type_t::f32,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i32>(),
+        generateParams3WithoutConstants<element::Type_t::bf16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
+        generateParams3WithoutConstants<element::Type_t::f16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
+        generateParams3WithoutConstants<element::Type_t::f32,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
     };
     std::vector<NonMaxSuppression3Params> combinedParams;
 
@@ -1235,11 +1066,14 @@ std::vector<NonMaxSuppression3Params> generateCombinedParams3WithoutConstants()
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs, ReferenceNonMaxSuppression3Test,
-    testing::ValuesIn(generateCombinedParams3()), ReferenceNonMaxSuppression3Test::getTestCaseName);
-INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs, ReferenceNonMaxSuppression3TestWithoutConstants,
-    testing::ValuesIn(generateCombinedParams3WithoutConstants()), ReferenceNonMaxSuppression3TestWithoutConstants::getTestCaseName);
-
+INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs,
+                         ReferenceNonMaxSuppression3Test,
+                         testing::ValuesIn(generateCombinedParams3()),
+                         ReferenceNonMaxSuppression3Test::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs,
+                         ReferenceNonMaxSuppression3TestWithoutConstants,
+                         testing::ValuesIn(generateCombinedParams3WithoutConstants()),
+                         ReferenceNonMaxSuppression3TestWithoutConstants::getTestCaseName);
 
 struct NonMaxSuppression1Params {
     reference_tests::Tensor boxes;
@@ -1263,7 +1097,8 @@ struct Builder1 : ParamsBuilder<NonMaxSuppression1Params> {
     REFERENCE_TESTS_ADD_SET_PARAM(Builder1, testcaseName);
 };
 
-class ReferenceNonMaxSuppression1Test : public testing::TestWithParam<NonMaxSuppression1Params>, public CommonReferenceTest {
+class ReferenceNonMaxSuppression1Test : public testing::TestWithParam<NonMaxSuppression1Params>,
+                                        public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -1291,12 +1126,16 @@ class ReferenceNonMaxSuppression1Test : public testing::TestWithParam<NonMaxSupp
     static std::shared_ptr<Model> CreateFunction(const NonMaxSuppression1Params& params) {
         const auto boxes = std::make_shared<opset1::Parameter>(params.boxes.type, params.boxes.shape);
         const auto scores = std::make_shared<opset1::Parameter>(params.scores.type, params.scores.shape);
-        const auto max_output_boxes_per_class = std::make_shared<opset1::Constant>(
-            params.maxOutputBoxesPerClass.type, params.maxOutputBoxesPerClass.shape, params.maxOutputBoxesPerClass.data.data());
-        const auto iou_threshold = std::make_shared<opset1::Constant>(
-            params.iouThreshold.type, params.iouThreshold.shape, params.iouThreshold.data.data());
-        const auto score_threshold = std::make_shared<opset1::Constant>(
-            params.scoreThreshold.type, params.scoreThreshold.shape, params.scoreThreshold.data.data());
+        const auto max_output_boxes_per_class =
+            std::make_shared<opset1::Constant>(params.maxOutputBoxesPerClass.type,
+                                               params.maxOutputBoxesPerClass.shape,
+                                               params.maxOutputBoxesPerClass.data.data());
+        const auto iou_threshold = std::make_shared<opset1::Constant>(params.iouThreshold.type,
+                                                                      params.iouThreshold.shape,
+                                                                      params.iouThreshold.data.data());
+        const auto score_threshold = std::make_shared<opset1::Constant>(params.scoreThreshold.type,
+                                                                        params.scoreThreshold.shape,
+                                                                        params.scoreThreshold.data.data());
         const auto nms = std::make_shared<opset1::NonMaxSuppression>(boxes,
                                                                      scores,
                                                                      max_output_boxes_per_class,
@@ -1314,8 +1153,11 @@ class ReferenceNonMaxSuppression1TestWithoutConstants : public ReferenceNonMaxSu
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.boxes.data, params.scores.data, params.maxOutputBoxesPerClass.data,
-                     params.iouThreshold.data, params.scoreThreshold.data};
+        inputData = {params.boxes.data,
+                     params.scores.data,
+                     params.maxOutputBoxesPerClass.data,
+                     params.iouThreshold.data,
+                     params.scoreThreshold.data};
         refOutData = {params.expectedSelectedIndices.data};
     }
 
@@ -1323,12 +1165,13 @@ class ReferenceNonMaxSuppression1TestWithoutConstants : public ReferenceNonMaxSu
     static std::shared_ptr<Model> CreateFunction(const NonMaxSuppression1Params& params) {
         const auto boxes = std::make_shared<opset1::Parameter>(params.boxes.type, params.boxes.shape);
         const auto scores = std::make_shared<opset1::Parameter>(params.scores.type, params.scores.shape);
-        const auto max_output_boxes_per_class = std::make_shared<opset1::Parameter>(
-            params.maxOutputBoxesPerClass.type, params.maxOutputBoxesPerClass.shape);
-        const auto iou_threshold = std::make_shared<opset1::Parameter>(
-            params.iouThreshold.type, params.iouThreshold.shape);
-        const auto score_threshold = std::make_shared<opset1::Parameter>(
-            params.scoreThreshold.type, params.scoreThreshold.shape);
+        const auto max_output_boxes_per_class =
+            std::make_shared<opset1::Parameter>(params.maxOutputBoxesPerClass.type,
+                                                params.maxOutputBoxesPerClass.shape);
+        const auto iou_threshold =
+            std::make_shared<opset1::Parameter>(params.iouThreshold.type, params.iouThreshold.shape);
+        const auto score_threshold =
+            std::make_shared<opset1::Parameter>(params.scoreThreshold.type, params.scoreThreshold.shape);
         const auto nms = std::make_shared<opset1::NonMaxSuppression>(boxes,
                                                                      scores,
                                                                      max_output_boxes_per_class,
@@ -1336,9 +1179,9 @@ class ReferenceNonMaxSuppression1TestWithoutConstants : public ReferenceNonMaxSu
                                                                      score_threshold,
                                                                      params.boxEncoding,
                                                                      false);
-        const auto f = std::make_shared<Model>(nms->outputs(),
-                                               ParameterVector{boxes, scores, max_output_boxes_per_class,
-                                                               iou_threshold, score_threshold});
+        const auto f = std::make_shared<Model>(
+            nms->outputs(),
+            ParameterVector{boxes, scores, max_output_boxes_per_class, iou_threshold, score_threshold});
         return f;
     }
 };
@@ -1357,183 +1200,117 @@ std::vector<NonMaxSuppression1Params> generateParams1() {
     using T_BOX = typename element_type_traits<ET_BOX>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<NonMaxSuppression1Params> params {
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.5, 0.5,  1.0, 1.0, 0.5, 0.6,  1.0, 1.0, 0.5, 0.4,   1.0, 1.0,
-                0.5, 10.5, 1.0, 1.0, 0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CENTER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_center_point_box_format"),
-
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                1.0, 1.0,  0.0, 0.0,  0.0, 0.1,  1.0, 1.1,  0.0, 0.9,   1.0, -0.1,
-                0.0, 10.0, 1.0, 11.0, 1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_flipped_coordinates"),
-
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0,
-                1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
-                0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 10}, std::vector<T>{
-                0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_identical_boxes"),
-
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_limit_output_size"),
-
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{0.9}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_single_box"),
-
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 0, 5}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU"),
-
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU_and_scores"),
-
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0, 0.0,  1.0, 1.0,  0.0, 0.1,  1.0, 1.1,  0.0, -0.1,  1.0, 0.9,
-                0.0, 10.0, 1.0, 11.0, 0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 2, 6}, std::vector<T>{
-                0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{
-                0, 0, 3, 0, 0, 0, 0, 1, 3, 0, 1, 0}))
-        .testcaseName(
-            "nonmaxsuppression_two_classes"),
+    std::vector<NonMaxSuppression1Params> params{
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.5, 0.5,  1.0, 1.0, 0.5, 0.6,   1.0, 1.0,
+                                                                         0.5, 0.4,  1.0, 1.0, 0.5, 10.5,  1.0, 1.0,
+                                                                         0.5, 10.6, 1.0, 1.0, 0.5, 100.5, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CENTER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_center_point_box_format"),
+
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{1.0, 1.0,  0.0, 0.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, 0.9,  1.0, -0.1, 0.0, 10.0,  1.0, 11.0,
+                                                                         1.0, 10.1, 0.0, 11.1, 1.0, 101.0, 0.0, 100.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_flipped_coordinates"),
+
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 10, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0,
+                                                                          0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET,
+                                            {1, 1, 10},
+                                            std::vector<T>{0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
+            .testcaseName("nonmaxsuppression_identical_boxes"),
+
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
+            .testcaseName("nonmaxsuppression_limit_output_size"),
+
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 1, 4}, std::vector<T>{0.0, 0.0, 1.0, 1.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 1}, std::vector<T>{0.9}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 0}))
+            .testcaseName("nonmaxsuppression_single_box"),
+
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{3}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {3, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 0, 5}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU"),
+
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {2, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU_and_scores"),
+
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0, 0.0,  1.0, 1.0,  0.0, 0.1,   1.0, 1.1,
+                                                                         0.0, -0.1, 1.0, 0.9,  0.0, 10.0,  1.0, 11.0,
+                                                                         0.0, 10.1, 1.0, 11.1, 0.0, 100.0, 1.0, 101.0}))
+            .scores(
+                reference_tests::Tensor(ET,
+                                        {1, 2, 6},
+                                        std::vector<T>{0.9, 0.75, 0.6, 0.95, 0.5, 0.3, 0.9, 0.75, 0.6, 0.95, 0.5, 0.3}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{2}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.5f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.0f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(
+                reference_tests::Tensor(ET_IND, {4, 3}, std::vector<T_IND>{0, 0, 3, 0, 0, 0, 0, 1, 3, 0, 1, 0}))
+            .testcaseName("nonmaxsuppression_two_classes"),
     };
     return params;
 }
 
 std::vector<NonMaxSuppression1Params> generateCombinedParams1() {
-    const std::vector<std::vector<NonMaxSuppression1Params>> generatedParams {
+    const std::vector<std::vector<NonMaxSuppression1Params>> generatedParams{
         generateParams1<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
         generateParams1<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
         generateParams1<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
@@ -1552,36 +1329,37 @@ std::vector<NonMaxSuppression1Params> generateParams1WithoutConstants() {
     using T_BOX = typename element_type_traits<ET_BOX>::value_type;
     using T_TH = typename element_type_traits<ET_TH>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<NonMaxSuppression1Params> params {
-        Builder1 {}
-        .boxes(
-            reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{
-                0.0f, 0.0f,  1.0f, 1.0f,  0.0f, 0.1f,  1.0f, 1.1f,  0.0f, -0.1f,  1.0f, 0.9f,
-                0.0f, 10.0f, 1.0f, 11.0f, 0.0f, 10.1f, 1.0f, 11.1f, 0.0f, 100.0f, 1.0f, 101.0f}))
-        .scores(
-            reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{
-                0.9f, 0.75f, 0.6f, 0.95f, 0.5f, 0.3f}))
-        .maxOutputBoxesPerClass(
-            reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
-        .iouThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
-        .scoreThreshold(
-            reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.2f}))
-        .boxEncoding(
-            opset1::NonMaxSuppression::BoxEncodingType::CORNER)
-        .expectedSelectedIndices(
-            reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 3}))
-        .testcaseName(
-            "nonmaxsuppression_suppress_by_IOU_and_scores_without_constants"),
+    std::vector<NonMaxSuppression1Params> params{
+        Builder1{}
+            .boxes(reference_tests::Tensor(ET, {1, 6, 4}, std::vector<T>{0.0f, 0.0f,  1.0f, 1.0f,   0.0f, 0.1f,
+                                                                         1.0f, 1.1f,  0.0f, -0.1f,  1.0f, 0.9f,
+                                                                         0.0f, 10.0f, 1.0f, 11.0f,  0.0f, 10.1f,
+                                                                         1.0f, 11.1f, 0.0f, 100.0f, 1.0f, 101.0f}))
+            .scores(reference_tests::Tensor(ET, {1, 1, 6}, std::vector<T>{0.9f, 0.75f, 0.6f, 0.95f, 0.5f, 0.3f}))
+            .maxOutputBoxesPerClass(reference_tests::Tensor(ET_BOX, {}, std::vector<T_BOX>{1}))
+            .iouThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.4f}))
+            .scoreThreshold(reference_tests::Tensor(ET_TH, {}, std::vector<T_TH>{0.2f}))
+            .boxEncoding(opset1::NonMaxSuppression::BoxEncodingType::CORNER)
+            .expectedSelectedIndices(reference_tests::Tensor(ET_IND, {1, 3}, std::vector<T_IND>{0, 0, 3}))
+            .testcaseName("nonmaxsuppression_suppress_by_IOU_and_scores_without_constants"),
     };
     return params;
 }
 
 std::vector<NonMaxSuppression1Params> generateCombinedParams1WithoutConstants() {
-    const std::vector<std::vector<NonMaxSuppression1Params>> generatedParams {
-        generateParams1WithoutConstants<element::Type_t::bf16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
-        generateParams1WithoutConstants<element::Type_t::f16, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
-        generateParams1WithoutConstants<element::Type_t::f32, element::Type_t::i32, element::Type_t::f32, element::Type_t::i64>(),
+    const std::vector<std::vector<NonMaxSuppression1Params>> generatedParams{
+        generateParams1WithoutConstants<element::Type_t::bf16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
+        generateParams1WithoutConstants<element::Type_t::f16,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
+        generateParams1WithoutConstants<element::Type_t::f32,
+                                        element::Type_t::i32,
+                                        element::Type_t::f32,
+                                        element::Type_t::i64>(),
     };
     std::vector<NonMaxSuppression1Params> combinedParams;
 
@@ -1591,8 +1369,12 @@ std::vector<NonMaxSuppression1Params> generateCombinedParams1WithoutConstants()
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs, ReferenceNonMaxSuppression1Test,
-    testing::ValuesIn(generateCombinedParams1()), ReferenceNonMaxSuppression1Test::getTestCaseName);
-INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs, ReferenceNonMaxSuppression1TestWithoutConstants,
-    testing::ValuesIn(generateCombinedParams1WithoutConstants()), ReferenceNonMaxSuppression1TestWithoutConstants::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs,
+                         ReferenceNonMaxSuppression1Test,
+                         testing::ValuesIn(generateCombinedParams1()),
+                         ReferenceNonMaxSuppression1Test::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_NonMaxSuppression_With_Hardcoded_Refs,
+                         ReferenceNonMaxSuppression1TestWithoutConstants,
+                         testing::ValuesIn(generateCombinedParams1WithoutConstants()),
+                         ReferenceNonMaxSuppression1TestWithoutConstants::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/nonzero.cpp b/src/plugins/template/tests/functional/op_reference/nonzero.cpp
index f8baa42bbe2f82..88d0faec87eb80 100644
--- a/src/plugins/template/tests/functional/op_reference/nonzero.cpp
+++ b/src/plugins/template/tests/functional/op_reference/nonzero.cpp
@@ -5,8 +5,9 @@
 #include <gtest/gtest.h>
 
 #include <random>
-#include "openvino/op/non_zero.hpp"
+
 #include "base_reference_test.hpp"
+#include "openvino/op/non_zero.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -14,10 +15,13 @@ using namespace ov;
 namespace {
 struct NonZeroParams {
     template <class IT, class OT>
-    NonZeroParams(const PartialShape& dynamicShape, const PartialShape& inputShape,
-               const element::Type& inType, const element::Type& refType,
-               const std::vector<IT>& inputData, const std::vector<OT>& refData,
-               const std::string& test_name = "")
+    NonZeroParams(const PartialShape& dynamicShape,
+                  const PartialShape& inputShape,
+                  const element::Type& inType,
+                  const element::Type& refType,
+                  const std::vector<IT>& inputData,
+                  const std::vector<OT>& refData,
+                  const std::string& test_name = "")
         : dynamicShape(dynamicShape),
           inputShape(inputShape),
           inType(inType),
@@ -60,11 +64,12 @@ class ReferenceNonZeroLayerTest : public testing::TestWithParam<NonZeroParams>,
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto NonZero = std::make_shared<op::v3::NonZero>(in, output_type);
-        return std::make_shared<Model>(NodeVector {NonZero}, ParameterVector {in});
+        return std::make_shared<Model>(NodeVector{NonZero}, ParameterVector{in});
     }
 };
 
@@ -72,191 +77,191 @@ TEST_P(ReferenceNonZeroLayerTest, CompareWithHardcodedRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_NonZero_With_Hardcoded_Refs, ReferenceNonZeroLayerTest,
-                         ::testing::Values(
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i32,
-                                           element::i32,
-                                           std::vector<int32_t>{1, 1, 1, 1, 1, 1},
-                                           std::vector<int32_t>{0, 0, 1, 1, 2, 2, 0, 1, 0, 1, 0, 1},
-                                           "all_1s"),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i32,
-                                           element::i32,
-                                           std::vector<int32_t>{0, 0, 0, 0, 0, 0},
-                                           std::vector<int32_t>{},
-                                           "all_0s"),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i32,
-                                           element::i64,
-                                           std::vector<int32_t>{1, 1, 1, 1, 1, 1},
-                                           std::vector<int64_t>{0, 0, 1, 1, 2, 2, 0, 1, 0, 1, 0, 1},
-                                           "all_1s_int64"),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i32,
-                                           element::i64,
-                                           std::vector<int32_t>{0, 0, 0, 0, 0, 0},
-                                           std::vector<int64_t>{},
-                                           "all_0s_int64"),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::boolean,
-                                           element::i32,
-                                           std::vector<char>{false, false, false, false, true, true},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i8,
-                                           element::i32,
-                                           std::vector<int8_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i16,
-                                           element::i32,
-                                           std::vector<int16_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i32,
-                                           element::i32,
-                                           std::vector<int32_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i64,
-                                           element::i32,
-                                           std::vector<int64_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::u8,
-                                           element::i32,
-                                           std::vector<uint8_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::u16,
-                                           element::i32,
-                                           std::vector<uint16_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::u32,
-                                           element::i32,
-                                           std::vector<uint32_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::u64,
-                                           element::i32,
-                                           std::vector<uint64_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::bf16,
-                                           element::i32,
-                                           std::vector<bfloat16>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::f16,
-                                           element::i32,
-                                           std::vector<float16>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::f32,
-                                           element::i32,
-                                           std::vector<float>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::f64,
-                                           element::i32,
-                                           std::vector<double>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
-                                           std::vector<int32_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::boolean,
-                                           element::i64,
-                                           std::vector<char>{false, false, false, false, true, true},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i8,
-                                           element::i64,
-                                           std::vector<int8_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i16,
-                                           element::i64,
-                                           std::vector<int16_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i32,
-                                           element::i64,
-                                           std::vector<int32_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::i64,
-                                           element::i64,
-                                           std::vector<int64_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::u8,
-                                           element::i64,
-                                           std::vector<uint8_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::u16,
-                                           element::i64,
-                                           std::vector<uint16_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::u32,
-                                           element::i64,
-                                           std::vector<uint32_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::u64,
-                                           element::i64,
-                                           std::vector<uint64_t>{0, 0, 0, 0, 1, 3},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::bf16,
-                                           element::i64,
-                                           std::vector<bfloat16>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::f16,
-                                           element::i64,
-                                           std::vector<float16>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::f32,
-                                           element::i64,
-                                           std::vector<float>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
-                                           std::vector<int64_t>{2, 2, 0, 1}),
-                             NonZeroParams(PartialShape{3, 2},
-                                           PartialShape{3, 2},
-                                           element::f64,
-                                           element::i64,
-                                           std::vector<double>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
-                                           std::vector<int64_t>{2, 2, 0, 1})),
+INSTANTIATE_TEST_SUITE_P(smoke_NonZero_With_Hardcoded_Refs,
+                         ReferenceNonZeroLayerTest,
+                         ::testing::Values(NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i32,
+                                                         element::i32,
+                                                         std::vector<int32_t>{1, 1, 1, 1, 1, 1},
+                                                         std::vector<int32_t>{0, 0, 1, 1, 2, 2, 0, 1, 0, 1, 0, 1},
+                                                         "all_1s"),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i32,
+                                                         element::i32,
+                                                         std::vector<int32_t>{0, 0, 0, 0, 0, 0},
+                                                         std::vector<int32_t>{},
+                                                         "all_0s"),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i32,
+                                                         element::i64,
+                                                         std::vector<int32_t>{1, 1, 1, 1, 1, 1},
+                                                         std::vector<int64_t>{0, 0, 1, 1, 2, 2, 0, 1, 0, 1, 0, 1},
+                                                         "all_1s_int64"),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i32,
+                                                         element::i64,
+                                                         std::vector<int32_t>{0, 0, 0, 0, 0, 0},
+                                                         std::vector<int64_t>{},
+                                                         "all_0s_int64"),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::boolean,
+                                                         element::i32,
+                                                         std::vector<char>{false, false, false, false, true, true},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i8,
+                                                         element::i32,
+                                                         std::vector<int8_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i16,
+                                                         element::i32,
+                                                         std::vector<int16_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i32,
+                                                         element::i32,
+                                                         std::vector<int32_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i64,
+                                                         element::i32,
+                                                         std::vector<int64_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::u8,
+                                                         element::i32,
+                                                         std::vector<uint8_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::u16,
+                                                         element::i32,
+                                                         std::vector<uint16_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::u32,
+                                                         element::i32,
+                                                         std::vector<uint32_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::u64,
+                                                         element::i32,
+                                                         std::vector<uint64_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::bf16,
+                                                         element::i32,
+                                                         std::vector<bfloat16>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::f16,
+                                                         element::i32,
+                                                         std::vector<float16>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::f32,
+                                                         element::i32,
+                                                         std::vector<float>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::f64,
+                                                         element::i32,
+                                                         std::vector<double>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
+                                                         std::vector<int32_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::boolean,
+                                                         element::i64,
+                                                         std::vector<char>{false, false, false, false, true, true},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i8,
+                                                         element::i64,
+                                                         std::vector<int8_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i16,
+                                                         element::i64,
+                                                         std::vector<int16_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i32,
+                                                         element::i64,
+                                                         std::vector<int32_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::i64,
+                                                         element::i64,
+                                                         std::vector<int64_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::u8,
+                                                         element::i64,
+                                                         std::vector<uint8_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::u16,
+                                                         element::i64,
+                                                         std::vector<uint16_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::u32,
+                                                         element::i64,
+                                                         std::vector<uint32_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::u64,
+                                                         element::i64,
+                                                         std::vector<uint64_t>{0, 0, 0, 0, 1, 3},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::bf16,
+                                                         element::i64,
+                                                         std::vector<bfloat16>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::f16,
+                                                         element::i64,
+                                                         std::vector<float16>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::f32,
+                                                         element::i64,
+                                                         std::vector<float>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
+                                                         std::vector<int64_t>{2, 2, 0, 1}),
+                                           NonZeroParams(PartialShape{3, 2},
+                                                         PartialShape{3, 2},
+                                                         element::f64,
+                                                         element::i64,
+                                                         std::vector<double>{0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 3.0f},
+                                                         std::vector<int64_t>{2, 2, 0, 1})),
                          ReferenceNonZeroLayerTest::getTestCaseName);
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/normalize_l2.cpp b/src/plugins/template/tests/functional/op_reference/normalize_l2.cpp
index da26e601685c17..76789cb4d00f2d 100644
--- a/src/plugins/template/tests/functional/op_reference/normalize_l2.cpp
+++ b/src/plugins/template/tests/functional/op_reference/normalize_l2.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/normalize_l2.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/normalize_l2.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -78,11 +79,8 @@ class ReferenceNormalizeL2LayerTest : public testing::TestWithParam<NormalizeL2P
 public:
     void SetUp() override {
         const auto params = GetParam();
-        function = CreateFunction(params.m_input_shape,
-                                  params.m_input_type,
-                                  params.m_axes,
-                                  params.m_eps_mode,
-                                  params.m_eps);
+        function =
+            CreateFunction(params.m_input_shape, params.m_input_type, params.m_axes, params.m_eps_mode, params.m_eps);
         inputData = {params.m_input_value};
         refOutData = {params.m_expected_value};
     }
@@ -105,10 +103,10 @@ class ReferenceNormalizeL2LayerTest : public testing::TestWithParam<NormalizeL2P
 
 private:
     static std::shared_ptr<Model> CreateFunction(const Shape& input_shape,
-                                                    const element::Type_t& input_type,
-                                                    const std::vector<int32_t>& axes,
-                                                    const op::EpsMode& eps_mode,
-                                                    const float& eps) {
+                                                 const element::Type_t& input_type,
+                                                 const std::vector<int32_t>& axes,
+                                                 const op::EpsMode& eps_mode,
+                                                 const float& eps) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto axes_data = std::make_shared<op::v0::Constant>(element::Type_t::i32, Shape{axes.size()}, axes);
         auto normalize = std::make_shared<op::v0::NormalizeL2>(in, axes_data, eps, eps_mode);
@@ -306,273 +304,305 @@ std::vector<NormalizeL2Params> generateParamsForNormalizeL2() {
                           0.1,
                           "normalize_l2_4D_axes_empty_max"),
         NormalizeL2Params(
-                          Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.0399648, 0.0766909, 0.110424, 0.141413, 0.169897, 0.196106, 0.22025,
-                                        0.242524, 0.263106,  0.282155,  0.299815, 0.316217, 0.331475, 0.345695, 0.358969,
-                                        0.371381, 0.383005,  0.39391,   0.404155, 0.413794, 0.422877, 0.431447, 0.439545,
-                                        0.999913, 0.999121,  0.996981,  0.993816, 0.989888, 0.985403, 0.980528, 0.975393,
-                                        0.970098, 0.964723,  0.959327,  0.953958, 0.94865,  0.94343,  0.938315, 0.933319,
-                                        0.928452, 0.923719,  0.919123,  0.914666, 0.910347, 0.906165, 0.902117, 0.8982},
-                          std::vector<int32_t>{0},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_4D_axes_0_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.03996804, 0.07669649, 0.11043153, 0.14142135, 0.1699069,  0.19611612, 0.22026087,
-                                         0.2425356,  0.26311737, 0.2821663,  0.2998266,  0.31622776, 0.331486,   0.34570533, 0.35897905,
-                                         0.37139067, 0.38301498, 0.3939193,  0.40416384, 0.41380292, 0.42288542, 0.43145543, 0.43955287,
-                                         0.99999994, 0.9992009,  0.9970544,  0.9938838,  0.98994946, 0.98546,    0.9805806,  0.97544104,
-                                         0.9701424,  0.96476364, 0.9593654,  0.95399374, 0.9486833,  0.9434601,  0.93834305, 0.93334556,
-                                         0.9284767,  0.923742,   0.919145,   0.91468656, 0.9103665,  0.90618306, 0.90213406, 0.8982167},
-                          std::vector<int32_t>{0},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_4D_axes_0_max"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.07667395, 0.14138602, 0.19607423, 0.24249104, 0.28212142, 0.31618387, 0.3456632,
-                                         0.37135068, 0.3938816,  0.41376755, 0.43142232, 0.9996529,  0.9967614,  0.9897021,  0.9803712,
-                                         0.96996415, 0.9592128,  0.94855154, 0.93822867, 0.9283767,  0.9190571,  0.9102886,  0.9020648,
-                                         0.5546854,  0.55984336, 0.56467056, 0.56919736, 0.5734503,  0.57745326, 0.58122724, 0.5847912,
-                                         0.58816177, 0.59135413, 0.594382,   0.59725744, 0.8320281,  0.8285682,  0.82528776, 0.82217395,
-                                         0.8192147,  0.8163994,  0.8137182,  0.81116194, 0.8087224,  0.806392,   0.8041638,  0.8020314},
-                          std::vector<int32_t>{1},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_4D_axes_1_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.07669649, 0.14142135, 0.19611612, 0.2425356,  0.2821663,  0.31622776, 0.34570533,
-                                         0.37139067, 0.3939193,  0.41380292, 0.43145543, 0.99999994, 0.9970544,  0.98994946, 0.9805806,
-                                         0.9701424,  0.9593654,  0.9486833,  0.93834305, 0.9284767,  0.919145,   0.9103665,  0.90213406,
-                                         0.5547002,  0.55985737, 0.56468385, 0.5692099,  0.57346237, 0.57746464, 0.58123815, 0.5848015,
-                                         0.58817166, 0.59136367, 0.59439105, 0.5972662,  0.83205026, 0.82858896, 0.8253072,  0.8221921,
-                                         0.8192319,  0.81641555, 0.8137334,  0.8111763,  0.808736,   0.80640495, 0.8041761,  0.8020432},
-                          std::vector<int32_t>{1},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_4D_axes_1_max"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0,        0.0966285, 0.168971, 0.224168, 0.446934, 0.483143, 0.506912, 0.523058,
-                                         0.893869, 0.869657,  0.844853, 0.821949, 0.424238, 0.43355,  0.441814, 0.449194,
-                                         0.56565,  0.56695,   0.568047, 0.56898,  0.707063, 0.70035,  0.694279, 0.688765,
-                                         0.491529, 0.494579,  0.497422, 0.500077, 0.57345,  0.573712, 0.573949, 0.574163,
-                                         0.655372, 0.652845,  0.650475, 0.648248, 0.517886, 0.519373, 0.520787, 0.522135,
-                                         0.575429, 0.575521,  0.575607, 0.575687, 0.632972, 0.63167,  0.630427, 0.629239},
-                          std::vector<int32_t>{2},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_4D_axes_2_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.09667365, 0.16903085, 0.22423053, 0.4472136,  0.48336822, 0.50709254, 0.52320457,
-                                         0.8944272,  0.8700628,  0.8451542,  0.8221786,  0.42426404, 0.4335743,  0.4418361,  0.4492145,
-                                         0.5656854,  0.5669818,  0.56807494, 0.569005,   0.7071067,  0.70038927, 0.6943139,  0.68879557,
-                                         0.49153918, 0.4945891,  0.49743116, 0.5000857,  0.57346237, 0.5737234,  0.57395905, 0.5741725,
-                                         0.65538555, 0.6528576,  0.6504869,  0.6482592,  0.51789176, 0.5193782,  0.52079225, 0.5221394,
-                                         0.5754353,  0.5755272,  0.57561255, 0.5756921,  0.63297886, 0.6316762,  0.6304327,  0.62924486},
-                          std::vector<int32_t>{2},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_4D_axes_2_max"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0,        0.266312, 0.532624, 0.798935, 0.356207, 0.445259, 0.534311, 0.623362,
-                                        0.41811,  0.470373, 0.522637, 0.574901, 0.442898, 0.479806, 0.516714, 0.553622,
-                                        0.456194, 0.484706, 0.513219, 0.541731, 0.464476, 0.4877,   0.510924, 0.534148,
-                                        0.470128, 0.489716, 0.509305, 0.528893, 0.474229, 0.491166, 0.508102, 0.525039,
-                                        0.477341, 0.492258, 0.507175, 0.522092, 0.479783, 0.49311,  0.506437, 0.519764,
-                                        0.481749, 0.493793, 0.505837, 0.517881, 0.483368, 0.494353, 0.505339, 0.516325},
-                          std::vector<int32_t>{3},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_4D_axes_3_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.26726124, 0.5345225,  0.8017837,  0.3563483,  0.44543537, 0.5345225,  0.62360954,
-                                         0.41816667, 0.4704375,  0.52270836, 0.5749792,  0.44292808, 0.47983873, 0.5167494,  0.5536601,
-                                         0.45621273, 0.484726,   0.5132393,  0.54175264, 0.4644887,  0.4877131,  0.5109376,  0.534162,
-                                         0.47013652, 0.48972553, 0.50931454, 0.5289036,  0.47423577, 0.49117276, 0.50810975, 0.5250467,
-                                         0.47734618, 0.49226326, 0.50718033, 0.5220974,  0.4797868,  0.49311423, 0.50644165, 0.5197691,
-                                         0.48175293, 0.49379677, 0.5058406,  0.51788443, 0.48337057, 0.49435627, 0.50534195, 0.5163277},
-                          std::vector<int32_t>{3},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_4D_axes_3_max"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.04445103, 0.08890206, 0.1333531,  0.17780413, 0.22225516, 0.2667062,  0.31115723,
-                                         0.35560825, 0.40005928, 0.4445103,  0.48896134, 0.19420375, 0.2103874,  0.22657104, 0.24275468,
-                                         0.2589383,  0.275122,   0.29130563, 0.30748928, 0.32367292, 0.33985656, 0.3560402,  0.37222385,
-                                         0.2332616,  0.24298084, 0.25270006, 0.2624193,  0.27213854, 0.2818578,  0.291577,   0.30129623,
-                                         0.3110155,  0.3207347,  0.33045393, 0.34017318, 0.2495545,  0.25648656, 0.26341864, 0.27035072,
-                                         0.27728277, 0.28421485, 0.29114693, 0.29807898, 0.30501106, 0.3119431,  0.3188752,  0.32580727},
-                          std::vector<int32_t>{2, 3},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_4D_axes_23_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.04445542, 0.08891085, 0.13336627, 0.1778217,  0.22227712, 0.26673254, 0.31118798,
-                                         0.3556434,  0.4000988,  0.44455424, 0.48900968, 0.19420628, 0.21039014, 0.226574,   0.24275786,
-                                         0.2589417,  0.27512556, 0.29130942, 0.30749327, 0.32367712, 0.339861,   0.35604486, 0.3722287,
-                                         0.23326269, 0.24298197, 0.25270125, 0.26242054, 0.2721398,  0.28185907, 0.29157835, 0.30129763,
-                                         0.31101692, 0.3207362,  0.33045548, 0.34017476, 0.24955511, 0.2564872,  0.26341927, 0.27035138,
-                                         0.27728346, 0.28421554, 0.29114762, 0.2980797,  0.3050118,  0.3119439,  0.31887597, 0.32580805},
-                          std::vector<int32_t>{2, 3},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_4D_axes_23_max"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0,        0.0152075, 0.030415, 0.0456224, 0.0608299, 0.0760374, 0.0912449, 0.106452, 0.12166,  0.136867,
-                                         0.152075, 0.167282,  0.18249,  0.197697,  0.212905,  0.228112,  0.24332,   0.258527, 0.273735, 0.288942,
-                                         0.30415,  0.319357,  0.334565, 0.349772,  0.135448,  0.141092,  0.146736,  0.15238,  0.158023, 0.163667,
-                                         0.169311, 0.174954,  0.180598, 0.186242,  0.191885,  0.197529,  0.203173,  0.208816, 0.21446,  0.220104,
-                                         0.225747, 0.231391,  0.237035, 0.242678,  0.248322,  0.253966,  0.25961,   0.265253},
-                          std::vector<int32_t>{1, 2, 3},
-                          op::EpsMode::ADD,
-                          1e-9,
-                          "normalize_l2_4D_axes_123_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.01520748, 0.03041495, 0.04562243, 0.06082991, 0.07603738, 0.09124486, 0.10645234,
-                                         0.12165982, 0.13686728, 0.15207477, 0.16728225, 0.18248972, 0.19769719, 0.21290468, 0.22811216,
-                                         0.24331963, 0.2585271,  0.27373457, 0.28894207, 0.30414954, 0.319357,   0.3345645,  0.34977198,
-                                         0.13544846, 0.14109215, 0.14673583, 0.15237951, 0.15802321, 0.16366689, 0.16931057, 0.17495427,
-                                         0.18059795, 0.18624163, 0.19188532, 0.197529,   0.20317268, 0.20881638, 0.21446006, 0.22010374,
-                                         0.22574744, 0.23139112, 0.2370348,  0.2426785,  0.24832217, 0.25396585, 0.25960955, 0.26525325},
-                          std::vector<int32_t>{1, 2, 3},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_4D_axes_123_max"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0,        0.0152066, 0.0304132, 0.0456198, 0.0608264, 0.076033, 0.0912396, 0.106446, 0.121653, 0.136859,
-                                         0.152066, 0.167273,  0.182479,  0.197686,  0.212892,  0.228099, 0.243306,  0.258512, 0.273719, 0.288925,
-                                         0.304132, 0.319339,  0.334545,  0.349752,  0.135447,  0.141091, 0.146735,  0.152378, 0.158022, 0.163666,
-                                         0.169309, 0.174953,  0.180597,  0.18624,   0.191884,  0.197527, 0.203171,  0.208815, 0.214458, 0.220102,
-                                         0.225746, 0.231389,  0.237033,  0.242677,  0.24832,   0.253964, 0.259607,  0.265251},
-                          std::vector<int32_t>{1, 2, 3},
-                          op::EpsMode::ADD,
-                          0.5,
-                          "normalize_l2_4D_axes_123_big_eps_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.01520748, 0.03041495, 0.04562243, 0.06082991, 0.07603738, 0.09124486, 0.10645234,
-                                         0.12165982, 0.13686728, 0.15207477, 0.16728225, 0.18248972, 0.19769719, 0.21290468, 0.22811216,
-                                         0.24331963, 0.2585271,  0.27373457, 0.28894207, 0.30414954, 0.319357,   0.3345645,  0.34977198,
-                                         0.13544846, 0.14109215, 0.14673583, 0.15237951, 0.15802321, 0.16366689, 0.16931057, 0.17495427,
-                                         0.18059795, 0.18624163, 0.19188532, 0.197529,   0.20317268, 0.20881638, 0.21446006, 0.22010374,
-                                         0.22574744, 0.23139112, 0.2370348,  0.2426785,  0.24832217, 0.25396585, 0.25960955, 0.26525325},
-                          std::vector<int32_t>{1, 2, 3},
-                          op::EpsMode::MAX,
-                          100,
-                          "normalize_l2_4D_axes_123_big_eps_max"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0,        0.0152075, 0.030415, 0.0456224, 0.0608299, 0.0760374, 0.0912449, 0.106452, 0.12166,  0.136867,
-                                         0.152075, 0.167282,  0.18249,  0.197697,  0.212905,  0.228112,  0.24332,   0.258527, 0.273735, 0.288942,
-                                         0.30415,  0.319357,  0.334565, 0.349772,  0.135448,  0.141092,  0.146736,  0.15238,  0.158023, 0.163667,
-                                         0.169311, 0.174954,  0.180598, 0.186242,  0.191885,  0.197529,  0.203173,  0.208816, 0.21446,  0.220104,
-                                         0.225747, 0.231391,  0.237035, 0.242678,  0.248322,  0.253966,  0.25961,   0.265253},
-                          std::vector<int32_t>{3, 1, 2},
-                          op::EpsMode::ADD,
-                          1e-9,
-                          "normalize_l2_4D_axes_unsorted_312_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.01520748, 0.03041495, 0.04562243, 0.06082991, 0.07603738, 0.09124486, 0.10645234,
-                                         0.12165982, 0.13686728, 0.15207477, 0.16728225, 0.18248972, 0.19769719, 0.21290468, 0.22811216,
-                                         0.24331963, 0.2585271,  0.27373457, 0.28894207, 0.30414954, 0.319357,   0.3345645,  0.34977198,
-                                         0.13544846, 0.14109215, 0.14673583, 0.15237951, 0.15802321, 0.16366689, 0.16931057, 0.17495427,
-                                         0.18059795, 0.18624163, 0.19188532, 0.197529,   0.20317268, 0.20881638, 0.21446006, 0.22010374,
-                                         0.22574744, 0.23139112, 0.2370348,  0.2426785,  0.24832217, 0.25396585, 0.25960955, 0.26525325},
-                          std::vector<int32_t>{3, 1, 2},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_4D_axes_unsorted_312_max"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.00529108, 0.01058216, 0.01587324, 0.02116432, 0.02645539, 0.03174648, 0.03703756,
-                                         0.04232863, 0.04761971, 0.05291079, 0.05820187, 0.06349295, 0.06878403, 0.07407511, 0.07936618,
-                                         0.08465727, 0.08994835, 0.09523942, 0.10053051, 0.10582158, 0.11111266, 0.11640374, 0.12169482,
-                                         0.12698591, 0.13227698, 0.13756806, 0.14285913, 0.14815022, 0.1534413,  0.15873237, 0.16402346,
-                                         0.16931453, 0.17460561, 0.1798967,  0.18518777, 0.19047885, 0.19576994, 0.20106101, 0.20635208,
-                                         0.21164316, 0.21693425, 0.22222532, 0.2275164,  0.23280749, 0.23809856, 0.24338964, 0.24868073},
-                          std::vector<int32_t>{0, 1, 2, 3},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_4D_axes_0123_add"),
-        NormalizeL2Params(Shape{2, 2, 3, 4},
-                          Shape{2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.00529108, 0.01058216, 0.01587324, 0.02116432, 0.02645539, 0.03174648, 0.03703756,
-                                         0.04232863, 0.04761971, 0.05291079, 0.05820187, 0.06349295, 0.06878403, 0.07407511, 0.07936618,
-                                         0.08465727, 0.08994835, 0.09523942, 0.10053051, 0.10582158, 0.11111266, 0.11640374, 0.12169482,
-                                         0.12698591, 0.13227698, 0.13756806, 0.14285913, 0.14815022, 0.1534413,  0.15873237, 0.16402346,
-                                         0.16931453, 0.17460561, 0.1798967,  0.18518777, 0.19047885, 0.19576994, 0.20106101, 0.20635208,
-                                         0.21164316, 0.21693425, 0.22222532, 0.2275164,  0.23280749, 0.23809856, 0.24338964, 0.24868073},
-                          std::vector<int32_t>{0, 1, 2, 3},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_4D_axes_0123_max"),
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,       0.0399648, 0.0766909, 0.110424, 0.141413, 0.169897, 0.196106, 0.22025,
+                           0.242524, 0.263106,  0.282155,  0.299815, 0.316217, 0.331475, 0.345695, 0.358969,
+                           0.371381, 0.383005,  0.39391,   0.404155, 0.413794, 0.422877, 0.431447, 0.439545,
+                           0.999913, 0.999121,  0.996981,  0.993816, 0.989888, 0.985403, 0.980528, 0.975393,
+                           0.970098, 0.964723,  0.959327,  0.953958, 0.94865,  0.94343,  0.938315, 0.933319,
+                           0.928452, 0.923719,  0.919123,  0.914666, 0.910347, 0.906165, 0.902117, 0.8982},
+            std::vector<int32_t>{0},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_4D_axes_0_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.03996804, 0.07669649, 0.11043153, 0.14142135, 0.1699069,  0.19611612,
+                           0.22026087, 0.2425356,  0.26311737, 0.2821663,  0.2998266,  0.31622776, 0.331486,
+                           0.34570533, 0.35897905, 0.37139067, 0.38301498, 0.3939193,  0.40416384, 0.41380292,
+                           0.42288542, 0.43145543, 0.43955287, 0.99999994, 0.9992009,  0.9970544,  0.9938838,
+                           0.98994946, 0.98546,    0.9805806,  0.97544104, 0.9701424,  0.96476364, 0.9593654,
+                           0.95399374, 0.9486833,  0.9434601,  0.93834305, 0.93334556, 0.9284767,  0.923742,
+                           0.919145,   0.91468656, 0.9103665,  0.90618306, 0.90213406, 0.8982167},
+            std::vector<int32_t>{0},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_4D_axes_0_max"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.07667395, 0.14138602, 0.19607423, 0.24249104, 0.28212142, 0.31618387,
+                           0.3456632,  0.37135068, 0.3938816,  0.41376755, 0.43142232, 0.9996529,  0.9967614,
+                           0.9897021,  0.9803712,  0.96996415, 0.9592128,  0.94855154, 0.93822867, 0.9283767,
+                           0.9190571,  0.9102886,  0.9020648,  0.5546854,  0.55984336, 0.56467056, 0.56919736,
+                           0.5734503,  0.57745326, 0.58122724, 0.5847912,  0.58816177, 0.59135413, 0.594382,
+                           0.59725744, 0.8320281,  0.8285682,  0.82528776, 0.82217395, 0.8192147,  0.8163994,
+                           0.8137182,  0.81116194, 0.8087224,  0.806392,   0.8041638,  0.8020314},
+            std::vector<int32_t>{1},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_4D_axes_1_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.07669649, 0.14142135, 0.19611612, 0.2425356,  0.2821663,  0.31622776,
+                           0.34570533, 0.37139067, 0.3939193,  0.41380292, 0.43145543, 0.99999994, 0.9970544,
+                           0.98994946, 0.9805806,  0.9701424,  0.9593654,  0.9486833,  0.93834305, 0.9284767,
+                           0.919145,   0.9103665,  0.90213406, 0.5547002,  0.55985737, 0.56468385, 0.5692099,
+                           0.57346237, 0.57746464, 0.58123815, 0.5848015,  0.58817166, 0.59136367, 0.59439105,
+                           0.5972662,  0.83205026, 0.82858896, 0.8253072,  0.8221921,  0.8192319,  0.81641555,
+                           0.8137334,  0.8111763,  0.808736,   0.80640495, 0.8041761,  0.8020432},
+            std::vector<int32_t>{1},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_4D_axes_1_max"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0,        0.0966285, 0.168971, 0.224168, 0.446934, 0.483143, 0.506912, 0.523058,
+                           0.893869, 0.869657,  0.844853, 0.821949, 0.424238, 0.43355,  0.441814, 0.449194,
+                           0.56565,  0.56695,   0.568047, 0.56898,  0.707063, 0.70035,  0.694279, 0.688765,
+                           0.491529, 0.494579,  0.497422, 0.500077, 0.57345,  0.573712, 0.573949, 0.574163,
+                           0.655372, 0.652845,  0.650475, 0.648248, 0.517886, 0.519373, 0.520787, 0.522135,
+                           0.575429, 0.575521,  0.575607, 0.575687, 0.632972, 0.63167,  0.630427, 0.629239},
+            std::vector<int32_t>{2},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_4D_axes_2_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.09667365, 0.16903085, 0.22423053, 0.4472136,  0.48336822, 0.50709254,
+                           0.52320457, 0.8944272,  0.8700628,  0.8451542,  0.8221786,  0.42426404, 0.4335743,
+                           0.4418361,  0.4492145,  0.5656854,  0.5669818,  0.56807494, 0.569005,   0.7071067,
+                           0.70038927, 0.6943139,  0.68879557, 0.49153918, 0.4945891,  0.49743116, 0.5000857,
+                           0.57346237, 0.5737234,  0.57395905, 0.5741725,  0.65538555, 0.6528576,  0.6504869,
+                           0.6482592,  0.51789176, 0.5193782,  0.52079225, 0.5221394,  0.5754353,  0.5755272,
+                           0.57561255, 0.5756921,  0.63297886, 0.6316762,  0.6304327,  0.62924486},
+            std::vector<int32_t>{2},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_4D_axes_2_max"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0,        0.266312, 0.532624, 0.798935, 0.356207, 0.445259, 0.534311, 0.623362,
+                           0.41811,  0.470373, 0.522637, 0.574901, 0.442898, 0.479806, 0.516714, 0.553622,
+                           0.456194, 0.484706, 0.513219, 0.541731, 0.464476, 0.4877,   0.510924, 0.534148,
+                           0.470128, 0.489716, 0.509305, 0.528893, 0.474229, 0.491166, 0.508102, 0.525039,
+                           0.477341, 0.492258, 0.507175, 0.522092, 0.479783, 0.49311,  0.506437, 0.519764,
+                           0.481749, 0.493793, 0.505837, 0.517881, 0.483368, 0.494353, 0.505339, 0.516325},
+            std::vector<int32_t>{3},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_4D_axes_3_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.26726124, 0.5345225,  0.8017837,  0.3563483,  0.44543537, 0.5345225,
+                           0.62360954, 0.41816667, 0.4704375,  0.52270836, 0.5749792,  0.44292808, 0.47983873,
+                           0.5167494,  0.5536601,  0.45621273, 0.484726,   0.5132393,  0.54175264, 0.4644887,
+                           0.4877131,  0.5109376,  0.534162,   0.47013652, 0.48972553, 0.50931454, 0.5289036,
+                           0.47423577, 0.49117276, 0.50810975, 0.5250467,  0.47734618, 0.49226326, 0.50718033,
+                           0.5220974,  0.4797868,  0.49311423, 0.50644165, 0.5197691,  0.48175293, 0.49379677,
+                           0.5058406,  0.51788443, 0.48337057, 0.49435627, 0.50534195, 0.5163277},
+            std::vector<int32_t>{3},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_4D_axes_3_max"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.04445103, 0.08890206, 0.1333531,  0.17780413, 0.22225516, 0.2667062,
+                           0.31115723, 0.35560825, 0.40005928, 0.4445103,  0.48896134, 0.19420375, 0.2103874,
+                           0.22657104, 0.24275468, 0.2589383,  0.275122,   0.29130563, 0.30748928, 0.32367292,
+                           0.33985656, 0.3560402,  0.37222385, 0.2332616,  0.24298084, 0.25270006, 0.2624193,
+                           0.27213854, 0.2818578,  0.291577,   0.30129623, 0.3110155,  0.3207347,  0.33045393,
+                           0.34017318, 0.2495545,  0.25648656, 0.26341864, 0.27035072, 0.27728277, 0.28421485,
+                           0.29114693, 0.29807898, 0.30501106, 0.3119431,  0.3188752,  0.32580727},
+            std::vector<int32_t>{2, 3},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_4D_axes_23_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.04445542, 0.08891085, 0.13336627, 0.1778217,  0.22227712, 0.26673254,
+                           0.31118798, 0.3556434,  0.4000988,  0.44455424, 0.48900968, 0.19420628, 0.21039014,
+                           0.226574,   0.24275786, 0.2589417,  0.27512556, 0.29130942, 0.30749327, 0.32367712,
+                           0.339861,   0.35604486, 0.3722287,  0.23326269, 0.24298197, 0.25270125, 0.26242054,
+                           0.2721398,  0.28185907, 0.29157835, 0.30129763, 0.31101692, 0.3207362,  0.33045548,
+                           0.34017476, 0.24955511, 0.2564872,  0.26341927, 0.27035138, 0.27728346, 0.28421554,
+                           0.29114762, 0.2980797,  0.3050118,  0.3119439,  0.31887597, 0.32580805},
+            std::vector<int32_t>{2, 3},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_4D_axes_23_max"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0,        0.0152075, 0.030415, 0.0456224, 0.0608299, 0.0760374, 0.0912449, 0.106452,
+                           0.12166,  0.136867,  0.152075, 0.167282,  0.18249,   0.197697,  0.212905,  0.228112,
+                           0.24332,  0.258527,  0.273735, 0.288942,  0.30415,   0.319357,  0.334565,  0.349772,
+                           0.135448, 0.141092,  0.146736, 0.15238,   0.158023,  0.163667,  0.169311,  0.174954,
+                           0.180598, 0.186242,  0.191885, 0.197529,  0.203173,  0.208816,  0.21446,   0.220104,
+                           0.225747, 0.231391,  0.237035, 0.242678,  0.248322,  0.253966,  0.25961,   0.265253},
+            std::vector<int32_t>{1, 2, 3},
+            op::EpsMode::ADD,
+            1e-9,
+            "normalize_l2_4D_axes_123_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.01520748, 0.03041495, 0.04562243, 0.06082991, 0.07603738, 0.09124486,
+                           0.10645234, 0.12165982, 0.13686728, 0.15207477, 0.16728225, 0.18248972, 0.19769719,
+                           0.21290468, 0.22811216, 0.24331963, 0.2585271,  0.27373457, 0.28894207, 0.30414954,
+                           0.319357,   0.3345645,  0.34977198, 0.13544846, 0.14109215, 0.14673583, 0.15237951,
+                           0.15802321, 0.16366689, 0.16931057, 0.17495427, 0.18059795, 0.18624163, 0.19188532,
+                           0.197529,   0.20317268, 0.20881638, 0.21446006, 0.22010374, 0.22574744, 0.23139112,
+                           0.2370348,  0.2426785,  0.24832217, 0.25396585, 0.25960955, 0.26525325},
+            std::vector<int32_t>{1, 2, 3},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_4D_axes_123_max"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0,        0.0152066, 0.0304132, 0.0456198, 0.0608264, 0.076033, 0.0912396, 0.106446,
+                           0.121653, 0.136859,  0.152066,  0.167273,  0.182479,  0.197686, 0.212892,  0.228099,
+                           0.243306, 0.258512,  0.273719,  0.288925,  0.304132,  0.319339, 0.334545,  0.349752,
+                           0.135447, 0.141091,  0.146735,  0.152378,  0.158022,  0.163666, 0.169309,  0.174953,
+                           0.180597, 0.18624,   0.191884,  0.197527,  0.203171,  0.208815, 0.214458,  0.220102,
+                           0.225746, 0.231389,  0.237033,  0.242677,  0.24832,   0.253964, 0.259607,  0.265251},
+            std::vector<int32_t>{1, 2, 3},
+            op::EpsMode::ADD,
+            0.5,
+            "normalize_l2_4D_axes_123_big_eps_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.01520748, 0.03041495, 0.04562243, 0.06082991, 0.07603738, 0.09124486,
+                           0.10645234, 0.12165982, 0.13686728, 0.15207477, 0.16728225, 0.18248972, 0.19769719,
+                           0.21290468, 0.22811216, 0.24331963, 0.2585271,  0.27373457, 0.28894207, 0.30414954,
+                           0.319357,   0.3345645,  0.34977198, 0.13544846, 0.14109215, 0.14673583, 0.15237951,
+                           0.15802321, 0.16366689, 0.16931057, 0.17495427, 0.18059795, 0.18624163, 0.19188532,
+                           0.197529,   0.20317268, 0.20881638, 0.21446006, 0.22010374, 0.22574744, 0.23139112,
+                           0.2370348,  0.2426785,  0.24832217, 0.25396585, 0.25960955, 0.26525325},
+            std::vector<int32_t>{1, 2, 3},
+            op::EpsMode::MAX,
+            100,
+            "normalize_l2_4D_axes_123_big_eps_max"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0,        0.0152075, 0.030415, 0.0456224, 0.0608299, 0.0760374, 0.0912449, 0.106452,
+                           0.12166,  0.136867,  0.152075, 0.167282,  0.18249,   0.197697,  0.212905,  0.228112,
+                           0.24332,  0.258527,  0.273735, 0.288942,  0.30415,   0.319357,  0.334565,  0.349772,
+                           0.135448, 0.141092,  0.146736, 0.15238,   0.158023,  0.163667,  0.169311,  0.174954,
+                           0.180598, 0.186242,  0.191885, 0.197529,  0.203173,  0.208816,  0.21446,   0.220104,
+                           0.225747, 0.231391,  0.237035, 0.242678,  0.248322,  0.253966,  0.25961,   0.265253},
+            std::vector<int32_t>{3, 1, 2},
+            op::EpsMode::ADD,
+            1e-9,
+            "normalize_l2_4D_axes_unsorted_312_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.01520748, 0.03041495, 0.04562243, 0.06082991, 0.07603738, 0.09124486,
+                           0.10645234, 0.12165982, 0.13686728, 0.15207477, 0.16728225, 0.18248972, 0.19769719,
+                           0.21290468, 0.22811216, 0.24331963, 0.2585271,  0.27373457, 0.28894207, 0.30414954,
+                           0.319357,   0.3345645,  0.34977198, 0.13544846, 0.14109215, 0.14673583, 0.15237951,
+                           0.15802321, 0.16366689, 0.16931057, 0.17495427, 0.18059795, 0.18624163, 0.19188532,
+                           0.197529,   0.20317268, 0.20881638, 0.21446006, 0.22010374, 0.22574744, 0.23139112,
+                           0.2370348,  0.2426785,  0.24832217, 0.25396585, 0.25960955, 0.26525325},
+            std::vector<int32_t>{3, 1, 2},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_4D_axes_unsorted_312_max"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.00529108, 0.01058216, 0.01587324, 0.02116432, 0.02645539, 0.03174648,
+                           0.03703756, 0.04232863, 0.04761971, 0.05291079, 0.05820187, 0.06349295, 0.06878403,
+                           0.07407511, 0.07936618, 0.08465727, 0.08994835, 0.09523942, 0.10053051, 0.10582158,
+                           0.11111266, 0.11640374, 0.12169482, 0.12698591, 0.13227698, 0.13756806, 0.14285913,
+                           0.14815022, 0.1534413,  0.15873237, 0.16402346, 0.16931453, 0.17460561, 0.1798967,
+                           0.18518777, 0.19047885, 0.19576994, 0.20106101, 0.20635208, 0.21164316, 0.21693425,
+                           0.22222532, 0.2275164,  0.23280749, 0.23809856, 0.24338964, 0.24868073},
+            std::vector<int32_t>{0, 1, 2, 3},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_4D_axes_0123_add"),
+        NormalizeL2Params(
+            Shape{2, 2, 3, 4},
+            Shape{2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.00529108, 0.01058216, 0.01587324, 0.02116432, 0.02645539, 0.03174648,
+                           0.03703756, 0.04232863, 0.04761971, 0.05291079, 0.05820187, 0.06349295, 0.06878403,
+                           0.07407511, 0.07936618, 0.08465727, 0.08994835, 0.09523942, 0.10053051, 0.10582158,
+                           0.11111266, 0.11640374, 0.12169482, 0.12698591, 0.13227698, 0.13756806, 0.14285913,
+                           0.14815022, 0.1534413,  0.15873237, 0.16402346, 0.16931453, 0.17460561, 0.1798967,
+                           0.18518777, 0.19047885, 0.19576994, 0.20106101, 0.20635208, 0.21164316, 0.21693425,
+                           0.22222532, 0.2275164,  0.23280749, 0.23809856, 0.24338964, 0.24868073},
+            std::vector<int32_t>{0, 1, 2, 3},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_4D_axes_0123_max"),
         NormalizeL2Params(Shape{1, 2, 2, 3, 4},
                           Shape{1, 2, 2, 3, 4},
                           ET,
@@ -593,186 +623,207 @@ std::vector<NormalizeL2Params> generateParamsForNormalizeL2() {
                           op::EpsMode::MAX,
                           0.1,
                           "normalize_l2_5D_axes_empty_max"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0,        0.0399648, 0.0766909, 0.110424, 0.141413, 0.169897, 0.196106, 0.22025,
-                                        0.242524, 0.263106,  0.282155,  0.299815, 0.316217, 0.331475, 0.345695, 0.358969,
-                                        0.371381, 0.383005,  0.39391,   0.404155, 0.413794, 0.422877, 0.431447, 0.439545,
-                                        0.999913, 0.999121,  0.996981,  0.993816, 0.989888, 0.985403, 0.980528, 0.975393,
-                                        0.970098, 0.964723,  0.959327,  0.953958, 0.94865,  0.94343,  0.938315, 0.933319,
-                                        0.928452, 0.923719,  0.919123,  0.914666, 0.910347, 0.906165, 0.902117, 0.8982},
-                          std::vector<int32_t>{1},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_5D_axes_1_add"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.03996804, 0.07669649, 0.11043153, 0.14142135, 0.1699069,  0.19611612, 0.22026087,
-                                         0.2425356,  0.26311737, 0.2821663,  0.2998266,  0.31622776, 0.331486,   0.34570533, 0.35897905,
-                                         0.37139067, 0.38301498, 0.3939193,  0.40416384, 0.41380292, 0.42288542, 0.43145543, 0.43955287,
-                                         0.99999994, 0.9992009,  0.9970544,  0.9938838,  0.98994946, 0.98546,    0.9805806,  0.97544104,
-                                         0.9701424,  0.96476364, 0.9593654,  0.95399374, 0.9486833,  0.9434601,  0.93834305, 0.93334556,
-                                         0.9284767,  0.923742,   0.919145,   0.91468656, 0.9103665,  0.90618306, 0.90213406, 0.8982167},
-                          std::vector<int32_t>{1},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_5D_axes_1_max"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.07667395, 0.14138602, 0.19607423, 0.24249104, 0.28212142, 0.31618387, 0.3456632,
-                                         0.37135068, 0.3938816,  0.41376755, 0.43142232, 0.9996529,  0.9967614,  0.9897021,  0.9803712,
-                                         0.96996415, 0.9592128,  0.94855154, 0.93822867, 0.9283767,  0.9190571,  0.9102886,  0.9020648,
-                                         0.5546854,  0.55984336, 0.56467056, 0.56919736, 0.5734503,  0.57745326, 0.58122724, 0.5847912,
-                                         0.58816177, 0.59135413, 0.594382,   0.59725744, 0.8320281,  0.8285682,  0.82528776, 0.82217395,
-                                         0.8192147,  0.8163994,  0.8137182,  0.81116194, 0.8087224,  0.806392,   0.8041638,  0.8020314},
-                          std::vector<int32_t>{2},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_5D_axes_2_add"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.07669649, 0.14142135, 0.19611612, 0.2425356,  0.2821663,  0.31622776, 0.34570533,
-                                         0.37139067, 0.3939193,  0.41380292, 0.43145543, 0.99999994, 0.9970544,  0.98994946, 0.9805806,
-                                         0.9701424,  0.9593654,  0.9486833,  0.93834305, 0.9284767,  0.919145,   0.9103665,  0.90213406,
-                                         0.5547002,  0.55985737, 0.56468385, 0.5692099,  0.57346237, 0.57746464, 0.58123815, 0.5848015,
-                                         0.58817166, 0.59136367, 0.59439105, 0.5972662,  0.83205026, 0.82858896, 0.8253072,  0.8221921,
-                                         0.8192319,  0.81641555, 0.8137334,  0.8111763,  0.808736,   0.80640495, 0.8041761,  0.8020432},
-                          std::vector<int32_t>{2},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_5D_axes_2_max"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0,        0.0966285, 0.168971, 0.224168, 0.446934, 0.483143, 0.506912, 0.523058,
-                                         0.893869, 0.869657,  0.844853, 0.821949, 0.424238, 0.43355,  0.441814, 0.449194,
-                                         0.56565,  0.56695,   0.568047, 0.56898,  0.707063, 0.70035,  0.694279, 0.688765,
-                                         0.491529, 0.494579,  0.497422, 0.500077, 0.57345,  0.573712, 0.573949, 0.574163,
-                                         0.655372, 0.652845,  0.650475, 0.648248, 0.517886, 0.519373, 0.520787, 0.522135,
-                                         0.575429, 0.575521,  0.575607, 0.575687, 0.632972, 0.63167,  0.630427, 0.629239},
-                          std::vector<int32_t>{3},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_5D_axes_3_add"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.09667365, 0.16903085, 0.22423053, 0.4472136,  0.48336822, 0.50709254, 0.52320457,
-                                         0.8944272,  0.8700628,  0.8451542,  0.8221786,  0.42426404, 0.4335743,  0.4418361,  0.4492145,
-                                         0.5656854,  0.5669818,  0.56807494, 0.569005,   0.7071067,  0.70038927, 0.6943139,  0.68879557,
-                                         0.49153918, 0.4945891,  0.49743116, 0.5000857,  0.57346237, 0.5737234,  0.57395905, 0.5741725,
-                                         0.65538555, 0.6528576,  0.6504869,  0.6482592,  0.51789176, 0.5193782,  0.52079225, 0.5221394,
-                                         0.5754353,  0.5755272,  0.57561255, 0.5756921,  0.63297886, 0.6316762,  0.6304327,  0.62924486},
-                          std::vector<int32_t>{3},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_5D_axes_3_max"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0,        0.266312, 0.532624, 0.798935, 0.356207, 0.445259, 0.534311, 0.623362,
-                                         0.41811,  0.470373, 0.522637, 0.574901, 0.442898, 0.479806, 0.516714, 0.553622,
-                                         0.456194, 0.484706, 0.513219, 0.541731, 0.464476, 0.4877,   0.510924, 0.534148,
-                                         0.470128, 0.489716, 0.509305, 0.528893, 0.474229, 0.491166, 0.508102, 0.525039,
-                                         0.477341, 0.492258, 0.507175, 0.522092, 0.479783, 0.49311,  0.506437, 0.519764,
-                                         0.481749, 0.493793, 0.505837, 0.517881, 0.483368, 0.494353, 0.505339, 0.516325},
-                          std::vector<int32_t>{4},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_5D_axes_4_add"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.26726124, 0.5345225,  0.8017837,  0.3563483,  0.44543537, 0.5345225,  0.62360954,
-                                         0.41816667, 0.4704375,  0.52270836, 0.5749792,  0.44292808, 0.47983873, 0.5167494,  0.5536601,
-                                         0.45621273, 0.484726,   0.5132393,  0.54175264, 0.4644887,  0.4877131,  0.5109376,  0.534162,
-                                         0.47013652, 0.48972553, 0.50931454, 0.5289036,  0.47423577, 0.49117276, 0.50810975, 0.5250467,
-                                         0.47734618, 0.49226326, 0.50718033, 0.5220974,  0.4797868,  0.49311423, 0.50644165, 0.5197691,
-                                         0.48175293, 0.49379677, 0.5058406,  0.51788443, 0.48337057, 0.49435627, 0.50534195, 0.5163277},
-                          std::vector<int32_t>{4},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_5D_axes_4_max"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.04445103, 0.08890206, 0.1333531,  0.17780413, 0.22225516, 0.2667062,  0.31115723,
-                                         0.35560825, 0.40005928, 0.4445103,  0.48896134, 0.19420375, 0.2103874,  0.22657104, 0.24275468,
-                                         0.2589383,  0.275122,   0.29130563, 0.30748928, 0.32367292, 0.33985656, 0.3560402,  0.37222385,
-                                         0.2332616,  0.24298084, 0.25270006, 0.2624193,  0.27213854, 0.2818578,  0.291577,   0.30129623,
-                                         0.3110155,  0.3207347,  0.33045393, 0.34017318, 0.2495545,  0.25648656, 0.26341864, 0.27035072,
-                                         0.27728277, 0.28421485, 0.29114693, 0.29807898, 0.30501106, 0.3119431,  0.3188752,  0.32580727},
-                          std::vector<int32_t>{3, 4},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_5D_axes_34_add"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.04445542, 0.08891085, 0.13336627, 0.1778217,  0.22227712, 0.26673254, 0.31118798,
-                                         0.3556434,  0.4000988,  0.44455424, 0.48900968, 0.19420628, 0.21039014, 0.226574,   0.24275786,
-                                         0.2589417,  0.27512556, 0.29130942, 0.30749327, 0.32367712, 0.339861,   0.35604486, 0.3722287,
-                                         0.23326269, 0.24298197, 0.25270125, 0.26242054, 0.2721398,  0.28185907, 0.29157835, 0.30129763,
-                                         0.31101692, 0.3207362,  0.33045548, 0.34017476, 0.24955511, 0.2564872,  0.26341927, 0.27035138,
-                                         0.27728346, 0.28421554, 0.29114762, 0.2980797,  0.3050118,  0.3119439,  0.31887597, 0.32580805},
-                          std::vector<int32_t>{3, 4},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_5D_axes_34_max"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.0152073,  0.0304146,  0.0456219,  0.0608292,  0.07603651, 0.0912438,  0.10645111,
-                                         0.12165841, 0.1368657,  0.15207301, 0.16728032, 0.1824876,  0.19769491, 0.21290222, 0.22810951,
-                                         0.24331681, 0.25852412, 0.2737314,  0.28893873, 0.30414602, 0.3193533,  0.33456063, 0.34976792,
-                                         0.13544825, 0.14109191, 0.1467356,  0.15237927, 0.15802296, 0.16366662, 0.1693103,  0.17495398,
-                                         0.18059766, 0.18624133, 0.19188501, 0.19752869, 0.20317237, 0.20881604, 0.21445972, 0.2201034,
-                                         0.22574706, 0.23139074, 0.23703443, 0.2426781,  0.24832177, 0.25396547, 0.25960913, 0.2652528},
-                          std::vector<int32_t>{2, 3, 4},
-                          op::EpsMode::ADD,
-                          0.1,
-                          "normalize_l2_5D_axes_234_add"),
-        NormalizeL2Params(Shape{1, 2, 2, 3, 4},
-                          Shape{1, 2, 2, 3, 4},
-                          ET,
-                          ET,
-                          static_cast<T>(0),
-                          std::vector<T>{0.,         0.01520748, 0.03041495, 0.04562243, 0.06082991, 0.07603738, 0.09124486, 0.10645234,
-                                         0.12165982, 0.13686728, 0.15207477, 0.16728225, 0.18248972, 0.19769719, 0.21290468, 0.22811216,
-                                         0.24331963, 0.2585271,  0.27373457, 0.28894207, 0.30414954, 0.319357,   0.3345645,  0.34977198,
-                                         0.13544846, 0.14109215, 0.14673583, 0.15237951, 0.15802321, 0.16366689, 0.16931057, 0.17495427,
-                                         0.18059795, 0.18624163, 0.19188532, 0.197529,   0.20317268, 0.20881638, 0.21446006, 0.22010374,
-                                         0.22574744, 0.23139112, 0.2370348,  0.2426785,  0.24832217, 0.25396585, 0.25960955, 0.26525325},
-                          std::vector<int32_t>{2, 3, 4},
-                          op::EpsMode::MAX,
-                          0.1,
-                          "normalize_l2_5D_axes_234_max"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0,        0.0399648, 0.0766909, 0.110424, 0.141413, 0.169897, 0.196106, 0.22025,
+                           0.242524, 0.263106,  0.282155,  0.299815, 0.316217, 0.331475, 0.345695, 0.358969,
+                           0.371381, 0.383005,  0.39391,   0.404155, 0.413794, 0.422877, 0.431447, 0.439545,
+                           0.999913, 0.999121,  0.996981,  0.993816, 0.989888, 0.985403, 0.980528, 0.975393,
+                           0.970098, 0.964723,  0.959327,  0.953958, 0.94865,  0.94343,  0.938315, 0.933319,
+                           0.928452, 0.923719,  0.919123,  0.914666, 0.910347, 0.906165, 0.902117, 0.8982},
+            std::vector<int32_t>{1},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_5D_axes_1_add"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.03996804, 0.07669649, 0.11043153, 0.14142135, 0.1699069,  0.19611612,
+                           0.22026087, 0.2425356,  0.26311737, 0.2821663,  0.2998266,  0.31622776, 0.331486,
+                           0.34570533, 0.35897905, 0.37139067, 0.38301498, 0.3939193,  0.40416384, 0.41380292,
+                           0.42288542, 0.43145543, 0.43955287, 0.99999994, 0.9992009,  0.9970544,  0.9938838,
+                           0.98994946, 0.98546,    0.9805806,  0.97544104, 0.9701424,  0.96476364, 0.9593654,
+                           0.95399374, 0.9486833,  0.9434601,  0.93834305, 0.93334556, 0.9284767,  0.923742,
+                           0.919145,   0.91468656, 0.9103665,  0.90618306, 0.90213406, 0.8982167},
+            std::vector<int32_t>{1},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_5D_axes_1_max"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.07667395, 0.14138602, 0.19607423, 0.24249104, 0.28212142, 0.31618387,
+                           0.3456632,  0.37135068, 0.3938816,  0.41376755, 0.43142232, 0.9996529,  0.9967614,
+                           0.9897021,  0.9803712,  0.96996415, 0.9592128,  0.94855154, 0.93822867, 0.9283767,
+                           0.9190571,  0.9102886,  0.9020648,  0.5546854,  0.55984336, 0.56467056, 0.56919736,
+                           0.5734503,  0.57745326, 0.58122724, 0.5847912,  0.58816177, 0.59135413, 0.594382,
+                           0.59725744, 0.8320281,  0.8285682,  0.82528776, 0.82217395, 0.8192147,  0.8163994,
+                           0.8137182,  0.81116194, 0.8087224,  0.806392,   0.8041638,  0.8020314},
+            std::vector<int32_t>{2},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_5D_axes_2_add"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.07669649, 0.14142135, 0.19611612, 0.2425356,  0.2821663,  0.31622776,
+                           0.34570533, 0.37139067, 0.3939193,  0.41380292, 0.43145543, 0.99999994, 0.9970544,
+                           0.98994946, 0.9805806,  0.9701424,  0.9593654,  0.9486833,  0.93834305, 0.9284767,
+                           0.919145,   0.9103665,  0.90213406, 0.5547002,  0.55985737, 0.56468385, 0.5692099,
+                           0.57346237, 0.57746464, 0.58123815, 0.5848015,  0.58817166, 0.59136367, 0.59439105,
+                           0.5972662,  0.83205026, 0.82858896, 0.8253072,  0.8221921,  0.8192319,  0.81641555,
+                           0.8137334,  0.8111763,  0.808736,   0.80640495, 0.8041761,  0.8020432},
+            std::vector<int32_t>{2},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_5D_axes_2_max"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0,        0.0966285, 0.168971, 0.224168, 0.446934, 0.483143, 0.506912, 0.523058,
+                           0.893869, 0.869657,  0.844853, 0.821949, 0.424238, 0.43355,  0.441814, 0.449194,
+                           0.56565,  0.56695,   0.568047, 0.56898,  0.707063, 0.70035,  0.694279, 0.688765,
+                           0.491529, 0.494579,  0.497422, 0.500077, 0.57345,  0.573712, 0.573949, 0.574163,
+                           0.655372, 0.652845,  0.650475, 0.648248, 0.517886, 0.519373, 0.520787, 0.522135,
+                           0.575429, 0.575521,  0.575607, 0.575687, 0.632972, 0.63167,  0.630427, 0.629239},
+            std::vector<int32_t>{3},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_5D_axes_3_add"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.09667365, 0.16903085, 0.22423053, 0.4472136,  0.48336822, 0.50709254,
+                           0.52320457, 0.8944272,  0.8700628,  0.8451542,  0.8221786,  0.42426404, 0.4335743,
+                           0.4418361,  0.4492145,  0.5656854,  0.5669818,  0.56807494, 0.569005,   0.7071067,
+                           0.70038927, 0.6943139,  0.68879557, 0.49153918, 0.4945891,  0.49743116, 0.5000857,
+                           0.57346237, 0.5737234,  0.57395905, 0.5741725,  0.65538555, 0.6528576,  0.6504869,
+                           0.6482592,  0.51789176, 0.5193782,  0.52079225, 0.5221394,  0.5754353,  0.5755272,
+                           0.57561255, 0.5756921,  0.63297886, 0.6316762,  0.6304327,  0.62924486},
+            std::vector<int32_t>{3},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_5D_axes_3_max"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0,        0.266312, 0.532624, 0.798935, 0.356207, 0.445259, 0.534311, 0.623362,
+                           0.41811,  0.470373, 0.522637, 0.574901, 0.442898, 0.479806, 0.516714, 0.553622,
+                           0.456194, 0.484706, 0.513219, 0.541731, 0.464476, 0.4877,   0.510924, 0.534148,
+                           0.470128, 0.489716, 0.509305, 0.528893, 0.474229, 0.491166, 0.508102, 0.525039,
+                           0.477341, 0.492258, 0.507175, 0.522092, 0.479783, 0.49311,  0.506437, 0.519764,
+                           0.481749, 0.493793, 0.505837, 0.517881, 0.483368, 0.494353, 0.505339, 0.516325},
+            std::vector<int32_t>{4},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_5D_axes_4_add"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.26726124, 0.5345225,  0.8017837,  0.3563483,  0.44543537, 0.5345225,
+                           0.62360954, 0.41816667, 0.4704375,  0.52270836, 0.5749792,  0.44292808, 0.47983873,
+                           0.5167494,  0.5536601,  0.45621273, 0.484726,   0.5132393,  0.54175264, 0.4644887,
+                           0.4877131,  0.5109376,  0.534162,   0.47013652, 0.48972553, 0.50931454, 0.5289036,
+                           0.47423577, 0.49117276, 0.50810975, 0.5250467,  0.47734618, 0.49226326, 0.50718033,
+                           0.5220974,  0.4797868,  0.49311423, 0.50644165, 0.5197691,  0.48175293, 0.49379677,
+                           0.5058406,  0.51788443, 0.48337057, 0.49435627, 0.50534195, 0.5163277},
+            std::vector<int32_t>{4},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_5D_axes_4_max"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.04445103, 0.08890206, 0.1333531,  0.17780413, 0.22225516, 0.2667062,
+                           0.31115723, 0.35560825, 0.40005928, 0.4445103,  0.48896134, 0.19420375, 0.2103874,
+                           0.22657104, 0.24275468, 0.2589383,  0.275122,   0.29130563, 0.30748928, 0.32367292,
+                           0.33985656, 0.3560402,  0.37222385, 0.2332616,  0.24298084, 0.25270006, 0.2624193,
+                           0.27213854, 0.2818578,  0.291577,   0.30129623, 0.3110155,  0.3207347,  0.33045393,
+                           0.34017318, 0.2495545,  0.25648656, 0.26341864, 0.27035072, 0.27728277, 0.28421485,
+                           0.29114693, 0.29807898, 0.30501106, 0.3119431,  0.3188752,  0.32580727},
+            std::vector<int32_t>{3, 4},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_5D_axes_34_add"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.04445542, 0.08891085, 0.13336627, 0.1778217,  0.22227712, 0.26673254,
+                           0.31118798, 0.3556434,  0.4000988,  0.44455424, 0.48900968, 0.19420628, 0.21039014,
+                           0.226574,   0.24275786, 0.2589417,  0.27512556, 0.29130942, 0.30749327, 0.32367712,
+                           0.339861,   0.35604486, 0.3722287,  0.23326269, 0.24298197, 0.25270125, 0.26242054,
+                           0.2721398,  0.28185907, 0.29157835, 0.30129763, 0.31101692, 0.3207362,  0.33045548,
+                           0.34017476, 0.24955511, 0.2564872,  0.26341927, 0.27035138, 0.27728346, 0.28421554,
+                           0.29114762, 0.2980797,  0.3050118,  0.3119439,  0.31887597, 0.32580805},
+            std::vector<int32_t>{3, 4},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_5D_axes_34_max"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.0152073,  0.0304146,  0.0456219,  0.0608292,  0.07603651, 0.0912438,
+                           0.10645111, 0.12165841, 0.1368657,  0.15207301, 0.16728032, 0.1824876,  0.19769491,
+                           0.21290222, 0.22810951, 0.24331681, 0.25852412, 0.2737314,  0.28893873, 0.30414602,
+                           0.3193533,  0.33456063, 0.34976792, 0.13544825, 0.14109191, 0.1467356,  0.15237927,
+                           0.15802296, 0.16366662, 0.1693103,  0.17495398, 0.18059766, 0.18624133, 0.19188501,
+                           0.19752869, 0.20317237, 0.20881604, 0.21445972, 0.2201034,  0.22574706, 0.23139074,
+                           0.23703443, 0.2426781,  0.24832177, 0.25396547, 0.25960913, 0.2652528},
+            std::vector<int32_t>{2, 3, 4},
+            op::EpsMode::ADD,
+            0.1,
+            "normalize_l2_5D_axes_234_add"),
+        NormalizeL2Params(
+            Shape{1, 2, 2, 3, 4},
+            Shape{1, 2, 2, 3, 4},
+            ET,
+            ET,
+            static_cast<T>(0),
+            std::vector<T>{0.,         0.01520748, 0.03041495, 0.04562243, 0.06082991, 0.07603738, 0.09124486,
+                           0.10645234, 0.12165982, 0.13686728, 0.15207477, 0.16728225, 0.18248972, 0.19769719,
+                           0.21290468, 0.22811216, 0.24331963, 0.2585271,  0.27373457, 0.28894207, 0.30414954,
+                           0.319357,   0.3345645,  0.34977198, 0.13544846, 0.14109215, 0.14673583, 0.15237951,
+                           0.15802321, 0.16366689, 0.16931057, 0.17495427, 0.18059795, 0.18624163, 0.19188532,
+                           0.197529,   0.20317268, 0.20881638, 0.21446006, 0.22010374, 0.22574744, 0.23139112,
+                           0.2370348,  0.2426785,  0.24832217, 0.25396585, 0.25960955, 0.26525325},
+            std::vector<int32_t>{2, 3, 4},
+            op::EpsMode::MAX,
+            0.1,
+            "normalize_l2_5D_axes_234_max"),
     };
 
     return params;
@@ -780,8 +831,7 @@ std::vector<NormalizeL2Params> generateParamsForNormalizeL2() {
 
 std::vector<NormalizeL2Params> generateCombinedParamsForNormalizeL2() {
     const std::vector<std::vector<NormalizeL2Params>> allTypeParams{
-        generateParamsForNormalizeL2<element::Type_t::f32>()
-    };
+        generateParamsForNormalizeL2<element::Type_t::f32>()};
 
     std::vector<NormalizeL2Params> combinedParams;
 
@@ -792,10 +842,9 @@ std::vector<NormalizeL2Params> generateCombinedParamsForNormalizeL2() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_NormalizeL2_With_Hardcoded_Refs,
-    ReferenceNormalizeL2LayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForNormalizeL2()),
-    ReferenceNormalizeL2LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_NormalizeL2_With_Hardcoded_Refs,
+                         ReferenceNormalizeL2LayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForNormalizeL2()),
+                         ReferenceNormalizeL2LayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/not_equal.cpp b/src/plugins/template/tests/functional/op_reference/not_equal.cpp
index c02c5ea537f779..cd871b25d1350e 100644
--- a/src/plugins/template/tests/functional/op_reference/not_equal.cpp
+++ b/src/plugins/template/tests/functional/op_reference/not_equal.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/not_equal.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/not_equal.hpp"
 #include "comparison.hpp"
 
 using namespace ov;
@@ -16,43 +17,43 @@ namespace {
 template <element::Type_t IN_ET>
 std::vector<RefComparisonParams> generateComparisonParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RefComparisonParams> compParams {
+    std::vector<RefComparisonParams> compParams{
         // 1D // 2D // 3D // 4D
-        Builder {}
+        Builder{}
+            .compType(ComparisonTypes::NOT_EQUAL)
+            .input1({{2, 2}, type, std::vector<T>{1, 0, 10, 255}})
+            .input2({{2, 2}, type, std::vector<T>{1, 0, 10, 255}})
+            .expected({{2, 2}, element::boolean, std::vector<char>{0, 0, 0, 0}}),
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{2, 2}, type, std::vector<T> {1, 0, 10, 255}})
-            .input2({{2, 2}, type, std::vector<T> {1, 0, 10, 255}})
-            .expected({{2, 2}, element::boolean, std::vector<char> {0, 0, 0, 0}}),
-        Builder {}
+            .input1({{2, 3}, type, std::vector<T>{0, 15, 45, 10, 5, 10}})
+            .input2({{2, 3}, type, std::vector<T>{1, 15, 5, 10, 50, 10}})
+            .expected({{2, 3}, element::boolean, std::vector<char>{1, 0, 1, 0, 1, 0}}),
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{2, 3}, type, std::vector<T> {0, 15, 45, 10, 5, 10}})
-            .input2({{2, 3}, type, std::vector<T> {1, 15, 5, 10, 50, 10}})
-            .expected({{2, 3}, element::boolean, std::vector<char> {1, 0, 1, 0, 1, 0}}),
-        Builder {}
+            .input1({{1}, type, std::vector<T>{20}})
+            .input2({{1}, type, std::vector<T>{10}})
+            .expected({{1}, element::boolean, std::vector<char>{1}}),
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{1}, type, std::vector<T> {20}})
-            .input2({{1}, type, std::vector<T> {10}})
-            .expected({{1}, element::boolean, std::vector<char> {1}}),
-        Builder {}
+            .input1({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 1, 5, 12, 8}})
+            .input2({{2, 4}, type, std::vector<T>{0, 12, 23, 0, 10, 5, 11, 8}})
+            .expected({{2, 4}, element::boolean, std::vector<char>{0, 0, 0, 0, 1, 0, 1, 0}}),
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 1, 5, 12, 8}})
-            .input2({{2, 4}, type, std::vector<T> {0, 12, 23, 0, 10, 5, 11, 8}})
-            .expected({{2, 4}, element::boolean, std::vector<char> {0, 0, 0, 0, 1, 0, 1, 0}}),
-        Builder {}
-                .compType(ComparisonTypes::NOT_EQUAL)
-                .input1({{3, 1, 2}, type, std::vector<T> {2, 7, 4, 7, 3, 7}})
-                .input2({{1, 2, 1}, type, std::vector<T> {7, 7}})
-                .expected({{3, 2, 2}, element::boolean, std::vector<char> {1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0}}),
-        Builder {}
+            .input1({{3, 1, 2}, type, std::vector<T>{2, 7, 4, 7, 3, 7}})
+            .input2({{1, 2, 1}, type, std::vector<T>{7, 7}})
+            .expected({{3, 2, 2}, element::boolean, std::vector<char>{1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0}}),
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{2, 1, 2, 1}, type, std::vector<T> {1, 2, 1, 4}})
-            .input2({{1, 2, 1}, type, std::vector<T> {1, 1}})
-            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char> {0, 1, 0, 1}})};
+            .input1({{2, 1, 2, 1}, type, std::vector<T>{1, 2, 1, 4}})
+            .input2({{1, 2, 1}, type, std::vector<T>{1, 1}})
+            .expected({{2, 1, 2, 1}, element::boolean, std::vector<char>{0, 1, 0, 1}})};
     return compParams;
 }
 
 std::vector<RefComparisonParams> generateComparisonCombinedParams() {
-    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams{
         generateComparisonParams<element::Type_t::f32>(element::f32),
         generateComparisonParams<element::Type_t::f16>(element::f16),
         generateComparisonParams<element::Type_t::i32>(element::i32),
@@ -66,39 +67,40 @@ std::vector<RefComparisonParams> generateComparisonCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs, ReferenceComparisonLayerTest,
+INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs,
+                         ReferenceComparisonLayerTest,
                          ::testing::ValuesIn(generateComparisonCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
 
 template <element::Type_t IN_ET>
 std::vector<RefComparisonParams> generateNumericParams(const element::Type& type) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RefComparisonParams> compParams {
-        Builder {}
+    std::vector<RefComparisonParams> compParams{
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{4}, type, std::vector<T> {-2.5f, 25.5f, 2.25f, NAN}})
-            .input2({{4}, type, std::vector<T> {10.0f, 5.0f, 2.25f, 10.0f}})
-            .expected({{4}, element::boolean, std::vector<char> {1, 1, 0, 1}}),
-        Builder {}
+            .input1({{4}, type, std::vector<T>{-2.5f, 25.5f, 2.25f, NAN}})
+            .input2({{4}, type, std::vector<T>{10.0f, 5.0f, 2.25f, 10.0f}})
+            .expected({{4}, element::boolean, std::vector<char>{1, 1, 0, 1}}),
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{2, 3}, type, std::vector<T> {0.0f, NAN, NAN, 1.0f, 21.0f, -INFINITY}})
-            .input2({{2, 3}, type, std::vector<T> {1.0f, NAN, 23.0f, 1.0f, 19.0f, 21.0f}})
-            .expected({{2, 3}, element::boolean, std::vector<char> {1, 1, 1, 0, 1, 1}}),
-        Builder {}
+            .input1({{2, 3}, type, std::vector<T>{0.0f, NAN, NAN, 1.0f, 21.0f, -INFINITY}})
+            .input2({{2, 3}, type, std::vector<T>{1.0f, NAN, 23.0f, 1.0f, 19.0f, 21.0f}})
+            .expected({{2, 3}, element::boolean, std::vector<char>{1, 1, 1, 0, 1, 1}}),
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{1}, type, std::vector<T> {INFINITY}})
-            .input2({{1}, type, std::vector<T> {INFINITY}})
-            .expected({{1}, element::boolean, std::vector<char> {0}}),
-        Builder {}
+            .input1({{1}, type, std::vector<T>{INFINITY}})
+            .input2({{1}, type, std::vector<T>{INFINITY}})
+            .expected({{1}, element::boolean, std::vector<char>{0}}),
+        Builder{}
             .compType(ComparisonTypes::NOT_EQUAL)
-            .input1({{5}, type, std::vector<T> {-2.5f, 25.5f, 2.25f, INFINITY, 6.0f}})
-            .input2({{5}, type, std::vector<T> {10.0f, 5.0f, 2.25f, 10.0f, -INFINITY}})
-            .expected({{5}, element::boolean, std::vector<char> {1, 1, 0, 1, 1}})};
+            .input1({{5}, type, std::vector<T>{-2.5f, 25.5f, 2.25f, INFINITY, 6.0f}})
+            .input2({{5}, type, std::vector<T>{10.0f, 5.0f, 2.25f, 10.0f, -INFINITY}})
+            .expected({{5}, element::boolean, std::vector<char>{1, 1, 0, 1, 1}})};
     return compParams;
 }
 
 std::vector<RefComparisonParams> generateNumericCombinedParams() {
-    const std::vector<std::vector<RefComparisonParams>> compTypeParams {
+    const std::vector<std::vector<RefComparisonParams>> compTypeParams{
         generateNumericParams<element::Type_t::f16>(element::f16),
         generateNumericParams<element::Type_t::f32>(element::f32)};
     std::vector<RefComparisonParams> combinedParams;
@@ -109,8 +111,10 @@ std::vector<RefComparisonParams> generateNumericCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Numeric_With_Hardcoded_Refs, ReferenceComparisonLayerTest, ::testing::ValuesIn(generateNumericCombinedParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_Numeric_With_Hardcoded_Refs,
+                         ReferenceComparisonLayerTest,
+                         ::testing::ValuesIn(generateNumericCombinedParams()),
                          ReferenceComparisonLayerTest::getTestCaseName);
-} // namespace
-} // namespace ComparisonOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace
+}  // namespace ComparisonOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/one_hot.cpp b/src/plugins/template/tests/functional/op_reference/one_hot.cpp
index b0f53a1e783052..0c6dc8c6937273 100644
--- a/src/plugins/template/tests/functional/op_reference/one_hot.cpp
+++ b/src/plugins/template/tests/functional/op_reference/one_hot.cpp
@@ -2,24 +2,32 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/one_hot.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/one_hot.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct OneHotParams {
-    OneHotParams(
-        const reference_tests::Tensor& dataTensor, const int32_t axis,
-        const reference_tests::Tensor& depthTensor, const reference_tests::Tensor& onValueTensor, const reference_tests::Tensor& offValueTensor,
-        const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), axis(axis),
-        depthTensor(depthTensor), onValueTensor(onValueTensor), offValueTensor(offValueTensor),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    OneHotParams(const reference_tests::Tensor& dataTensor,
+                 const int32_t axis,
+                 const reference_tests::Tensor& depthTensor,
+                 const reference_tests::Tensor& onValueTensor,
+                 const reference_tests::Tensor& offValueTensor,
+                 const reference_tests::Tensor& expectedTensor,
+                 const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          axis(axis),
+          depthTensor(depthTensor),
+          onValueTensor(onValueTensor),
+          offValueTensor(offValueTensor),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     int32_t axis;
@@ -65,12 +73,15 @@ class ReferenceOneHotTest : public testing::TestWithParam<OneHotParams>, public
     static std::shared_ptr<Model> CreateFunction(const OneHotParams& params) {
         std::shared_ptr<Model> function;
         const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, params.dataTensor.shape);
-        const auto depth = std::make_shared<op::v0::Constant>(params.depthTensor.type, params.depthTensor.shape,
+        const auto depth = std::make_shared<op::v0::Constant>(params.depthTensor.type,
+                                                              params.depthTensor.shape,
                                                               params.depthTensor.data.data());
-        const auto onValue = std::make_shared<op::v0::Constant>(params.onValueTensor.type, params.onValueTensor.shape,
-                                                              params.onValueTensor.data.data());
-        const auto offValue = std::make_shared<op::v0::Constant>(params.offValueTensor.type, params.offValueTensor.shape,
-                                                              params.offValueTensor.data.data());
+        const auto onValue = std::make_shared<op::v0::Constant>(params.onValueTensor.type,
+                                                                params.onValueTensor.shape,
+                                                                params.onValueTensor.data.data());
+        const auto offValue = std::make_shared<op::v0::Constant>(params.offValueTensor.type,
+                                                                 params.offValueTensor.shape,
+                                                                 params.offValueTensor.data.data());
         const auto oneHot = std::make_shared<op::v1::OneHot>(data, depth, onValue, offValue, params.axis);
         function = std::make_shared<ov::Model>(oneHot, ParameterVector{data});
         return function;
@@ -81,9 +92,9 @@ TEST_P(ReferenceOneHotTest, CompareWithRefs) {
     Exec();
 }
 
-template<typename T>
+template <typename T>
 std::vector<T> generateExpectedValues(const Shape& input_shape, std::vector<T> input, uint32_t category_count) {
-//    std::vector<T> input{0, 11, 101, 1001, 10001, static_cast<int32_t>(category_count - 1)};
+    //    std::vector<T> input{0, 11, 101, 1001, 10001, static_cast<int32_t>(category_count - 1)};
     std::vector<T> output(shape_size(input_shape), 0);
     for (size_t i = 0; i < input.size(); ++i) {
         output[i * category_count + input[i]] = 1;
@@ -95,80 +106,70 @@ template <element::Type_t ET1, element::Type_t ET2>
 std::vector<OneHotParams> generateParams() {
     using T1 = typename element_type_traits<ET1>::value_type;
     using T2 = typename element_type_traits<ET2>::value_type;
-    std::vector<OneHotParams> params {
-        OneHotParams(
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{2}),
-            0,
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
-            reference_tests::Tensor(ET2, {3}, std::vector<T2>{0, 0, 1}),
-            "one_hot_scalar_2_in_3"),
-        OneHotParams(
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{1}),
-            0,
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
-            reference_tests::Tensor(ET2, {3}, std::vector<T2>{0, 1, 0}),
-            "one_hot_scalar_1_in_3"),
-        OneHotParams(
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{0}),
-            0,
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
-            reference_tests::Tensor(ET2, {3}, std::vector<T2>{1, 0, 0}),
-            "one_hot_scalar_0_in_3"),
-        OneHotParams(
-            reference_tests::Tensor(ET1, {8}, std::vector<T1>{2, 1, 0, 0, 2, 2, 1, 0}),
-            0,
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
-            reference_tests::Tensor(ET2, {3, 8}, std::vector<T2>{0, 0, 1, 1, 0, 0, 0, 1,
-                                                0, 1, 0, 0, 0, 0, 1, 0,
-                                                1, 0, 0, 0, 1, 1, 0, 0}),
-            "one_hot_vector_0"),
-        OneHotParams(
-            reference_tests::Tensor(ET1, {8}, std::vector<T1>{2, 1, 0, 0, 2, 2, 1, 0}),
-            1,
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
-            reference_tests::Tensor(ET2, {8, 3}, std::vector<T2>{0, 0, 1, 0, 1, 0, 1, 0,
-                                                0, 1, 0, 0, 0, 0, 1, 0,
-                                                0, 1, 0, 1, 0, 1, 0, 0}),
-            "one_hot_vector_1"),
-        OneHotParams(
-            reference_tests::Tensor(ET1, {8}, std::vector<T1>{2, 1, 0, 0, 3, 2, 1, 0}),
-            1,
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
-            reference_tests::Tensor(ET2, {8, 3}, std::vector<T2>{0, 0, 1, 0, 1, 0, 1, 0,
-                                                0, 1, 0, 0, 0, 0, 0, 0,
-                                                0, 1, 0, 1, 0, 1, 0, 0}),
-            "one_hot_vector_1_barely_oob"),
-        OneHotParams(
-            reference_tests::Tensor(ET1, {3, 3}, std::vector<T1>{0, 1, 1, 2, 1, 0, 0, 2, 1}),
-            0,
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
-            reference_tests::Tensor(ET2, {3, 3, 3}, std::vector<T2>{1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1,
-                                                   0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0}),
-            "one_hot_matrix_0"),
-        OneHotParams(
-            reference_tests::Tensor(ET1, {6}, std::vector<T1>{0, 11, 101, 1001, 10001, 19999}),
-            1,
-            reference_tests::Tensor(ET1, {}, std::vector<T1>{20000}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
-            reference_tests::Tensor(ET2, {6, 20000}, generateExpectedValues({6, 20000},
-                                                           std::vector<T2>{0, 11, 101, 1001, 10001, 19999},
-                                                           20000)),
-            "one_hot_vector_many_categories"),
+    std::vector<OneHotParams> params{
+        OneHotParams(reference_tests::Tensor(ET1, {}, std::vector<T1>{2}),
+                     0,
+                     reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
+                     reference_tests::Tensor(ET2, {3}, std::vector<T2>{0, 0, 1}),
+                     "one_hot_scalar_2_in_3"),
+        OneHotParams(reference_tests::Tensor(ET1, {}, std::vector<T1>{1}),
+                     0,
+                     reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
+                     reference_tests::Tensor(ET2, {3}, std::vector<T2>{0, 1, 0}),
+                     "one_hot_scalar_1_in_3"),
+        OneHotParams(reference_tests::Tensor(ET1, {}, std::vector<T1>{0}),
+                     0,
+                     reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
+                     reference_tests::Tensor(ET2, {3}, std::vector<T2>{1, 0, 0}),
+                     "one_hot_scalar_0_in_3"),
+        OneHotParams(reference_tests::Tensor(ET1, {8}, std::vector<T1>{2, 1, 0, 0, 2, 2, 1, 0}),
+                     0,
+                     reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
+                     reference_tests::Tensor(ET2, {3, 8}, std::vector<T2>{0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0,
+                                                                          0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0}),
+                     "one_hot_vector_0"),
+        OneHotParams(reference_tests::Tensor(ET1, {8}, std::vector<T1>{2, 1, 0, 0, 2, 2, 1, 0}),
+                     1,
+                     reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
+                     reference_tests::Tensor(ET2, {8, 3}, std::vector<T2>{0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0,
+                                                                          0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0}),
+                     "one_hot_vector_1"),
+        OneHotParams(reference_tests::Tensor(ET1, {8}, std::vector<T1>{2, 1, 0, 0, 3, 2, 1, 0}),
+                     1,
+                     reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
+                     reference_tests::Tensor(ET2, {8, 3}, std::vector<T2>{0, 0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0,
+                                                                          0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0}),
+                     "one_hot_vector_1_barely_oob"),
+        OneHotParams(reference_tests::Tensor(ET1, {3, 3}, std::vector<T1>{0, 1, 1, 2, 1, 0, 0, 2, 1}),
+                     0,
+                     reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
+                     reference_tests::Tensor(ET2, {3, 3, 3}, std::vector<T2>{1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 0, 1,
+                                                                             0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0}),
+                     "one_hot_matrix_0"),
+        OneHotParams(reference_tests::Tensor(ET1, {6}, std::vector<T1>{0, 11, 101, 1001, 10001, 19999}),
+                     1,
+                     reference_tests::Tensor(ET1, {}, std::vector<T1>{20000}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                     reference_tests::Tensor(ET2, {}, std::vector<T2>{0}),
+                     reference_tests::Tensor(
+                         ET2,
+                         {6, 20000},
+                         generateExpectedValues({6, 20000}, std::vector<T2>{0, 11, 101, 1001, 10001, 19999}, 20000)),
+                     "one_hot_vector_many_categories"),
     };
     return params;
 }
@@ -177,23 +178,23 @@ template <element::Type_t ET1, element::Type_t ET2>
 std::vector<OneHotParams> generateParamsFloat() {
     using T1 = typename element_type_traits<ET1>::value_type;
     using T2 = typename element_type_traits<ET2>::value_type;
-    std::vector<OneHotParams> params {
+    std::vector<OneHotParams> params{
         OneHotParams(
             reference_tests::Tensor(ET1, {3, 3}, std::vector<T1>{0, 1, 1, 2, 1, 0, 0, 2, 1}),
             0,
             reference_tests::Tensor(ET1, {}, std::vector<T1>{3}),
             reference_tests::Tensor(ET2, {}, std::vector<T2>{2.5}),
             reference_tests::Tensor(ET2, {}, std::vector<T2>{0.5}),
-            reference_tests::Tensor(ET2, {3, 3, 3}, std::vector<T2>{
-                2.5, 0.5, 0.5, 0.5, 0.5, 2.5, 2.5, 0.5, 0.5, 0.5, 2.5, 2.5, 0.5, 2.5,
-                0.5, 0.5, 0.5, 2.5, 0.5, 0.5, 0.5, 2.5, 0.5, 0.5, 0.5, 2.5, 0.5}),
+            reference_tests::Tensor(ET2, {3, 3, 3}, std::vector<T2>{2.5, 0.5, 0.5, 0.5, 0.5, 2.5, 2.5, 0.5, 0.5,
+                                                                    0.5, 2.5, 2.5, 0.5, 2.5, 0.5, 0.5, 0.5, 2.5,
+                                                                    0.5, 0.5, 0.5, 2.5, 0.5, 0.5, 0.5, 2.5, 0.5}),
             "one_hot_on_off_float"),
     };
     return params;
 }
 
 std::vector<OneHotParams> generateCombinedParams() {
-    const std::vector<std::vector<OneHotParams>> generatedParams {
+    const std::vector<std::vector<OneHotParams>> generatedParams{
         generateParams<element::Type_t::i32, element::Type_t::i16>(),
         generateParams<element::Type_t::i32, element::Type_t::i32>(),
         generateParams<element::Type_t::i32, element::Type_t::i64>(),
@@ -221,6 +222,8 @@ std::vector<OneHotParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_OneHot_With_Hardcoded_Refs, ReferenceOneHotTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceOneHotTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_OneHot_With_Hardcoded_Refs,
+                         ReferenceOneHotTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceOneHotTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/pad.cpp b/src/plugins/template/tests/functional/op_reference/pad.cpp
index 1ca30e499d923a..eca5f7dbd074a7 100644
--- a/src/plugins/template/tests/functional/op_reference/pad.cpp
+++ b/src/plugins/template/tests/functional/op_reference/pad.cpp
@@ -2,34 +2,48 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/pad.hpp"
+
 #include <gtest/gtest.h>
+
 #include <functional_test_utils/skip_tests_config.hpp>
 
-#include "openvino/op/pad.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct PadParams {
-    PadParams(
-        const reference_tests::Tensor& inputData, const reference_tests::Tensor& padsBegin, const reference_tests::Tensor& padsEnd,
-        const reference_tests::Tensor& expectedOutput, op::PadMode padMode, const reference_tests::Tensor& constantValue,
-        const std::string& testcaseName = "") :
-        inputData(inputData), padsBegin(padsBegin), padsEnd(padsEnd),
-        expectedOutput(expectedOutput), padMode(padMode),
-        useConstValue{true}, constantValue(constantValue),
-        testcaseName(testcaseName) {}
-
-    PadParams(
-        const reference_tests::Tensor& inputData, const reference_tests::Tensor& padsBegin, const reference_tests::Tensor& padsEnd,
-        const reference_tests::Tensor& expectedOutput, op::PadMode padMode,
-        const std::string& testcaseName = "") :
-        inputData(inputData), padsBegin(padsBegin), padsEnd(padsEnd),
-        expectedOutput(expectedOutput), padMode(padMode),
-        testcaseName(testcaseName) {}
+    PadParams(const reference_tests::Tensor& inputData,
+              const reference_tests::Tensor& padsBegin,
+              const reference_tests::Tensor& padsEnd,
+              const reference_tests::Tensor& expectedOutput,
+              op::PadMode padMode,
+              const reference_tests::Tensor& constantValue,
+              const std::string& testcaseName = "")
+        : inputData(inputData),
+          padsBegin(padsBegin),
+          padsEnd(padsEnd),
+          expectedOutput(expectedOutput),
+          padMode(padMode),
+          useConstValue{true},
+          constantValue(constantValue),
+          testcaseName(testcaseName) {}
+
+    PadParams(const reference_tests::Tensor& inputData,
+              const reference_tests::Tensor& padsBegin,
+              const reference_tests::Tensor& padsEnd,
+              const reference_tests::Tensor& expectedOutput,
+              op::PadMode padMode,
+              const std::string& testcaseName = "")
+        : inputData(inputData),
+          padsBegin(padsBegin),
+          padsEnd(padsEnd),
+          expectedOutput(expectedOutput),
+          padMode(padMode),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor inputData;
     reference_tests::Tensor padsBegin;
@@ -124,7 +138,7 @@ class ReferencePadV1Test : public ReferencePadTest {
         function = CreateFunction(GetParam());
     }
 
-    public:
+public:
     static std::shared_ptr<Model> CreateFunction(const PadParams& params) {
         return commonConstPadsCreateFunction<op::v1::Pad>(params);
     }
@@ -142,7 +156,6 @@ class ReferencePadV12Test : public ReferencePadTest {
     }
 };
 
-
 TEST_P(ReferencePadV1Test, CompareWithRefs) {
     Exec();
 }
@@ -163,7 +176,6 @@ TEST_P(ReferencePadTestParamsOk, CompareWithRefs) {
     EXPECT_NO_THROW(Exec());
 }
 
-
 class ReferencePadV1TestNonConstPadsBeginPadsEndPadVal : public ReferencePadTest {
 public:
     void SetUp() override {
@@ -196,13 +208,15 @@ TEST_P(ReferencePadV12TestNonConstPadsBeginPadsEndPadVal, CompareWithRefs) {
     Exec();
 }
 
-class ReferencePadV1TestNonConstPadsBeginPadsEndPadValTooLarge : public ReferencePadV1TestNonConstPadsBeginPadsEndPadVal {};
+class ReferencePadV1TestNonConstPadsBeginPadsEndPadValTooLarge
+    : public ReferencePadV1TestNonConstPadsBeginPadsEndPadVal {};
 
 TEST_P(ReferencePadV1TestNonConstPadsBeginPadsEndPadValTooLarge, CompareWithRefs) {
     EXPECT_ANY_THROW(Exec());
 }
 
-class ReferencePadV1TestNonConstPadsBeginPadsEndPadValParamsOk : public ReferencePadV1TestNonConstPadsBeginPadsEndPadVal {};
+class ReferencePadV1TestNonConstPadsBeginPadsEndPadValParamsOk
+    : public ReferencePadV1TestNonConstPadsBeginPadsEndPadVal {};
 
 TEST_P(ReferencePadV1TestNonConstPadsBeginPadsEndPadValParamsOk, CompareWithRefs) {
     EXPECT_NO_THROW(Exec());
@@ -212,691 +226,1308 @@ template <element::Type_t ET, element::Type_t ET_INT>
 std::vector<PadParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
     using T_INT = typename element_type_traits<ET_INT>::value_type;
-    std::vector<PadParams> params {
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{5}),
-            reference_tests::Tensor(ET, {15}, std::vector<T>{
-                2112, 2112, 2112, 2112, 1, 2, 3, 4, 5, 6, 2112, 2112, 2112, 2112, 2112,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_1d_constant_const_value_provided_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET, {10}, std::vector<T>{
-                2112, 2112, 2112, 2112, 1, 2, 3, 4, 5, 6,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_1d_constant_const_value_provided_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {9}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 2112, 2112, 2112,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_1d_constant_const_value_provided_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{5}),
-            reference_tests::Tensor(ET, {15}, std::vector<T>{
-                0, 0, 0, 0, 1, 2, 3, 4, 5, 6, 0, 0, 0, 0, 0,
-            }),
-            op::PadMode::CONSTANT,
-            "pad_1d_constant_use_default_const_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET, {10}, std::vector<T>{
-                0, 0, 0, 0, 1, 2, 3, 4, 5, 6,
-            }),
-            op::PadMode::CONSTANT,
-            "pad_1d_constant_use_default_const_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {9}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 0, 0, 0,
-            }),
-            op::PadMode::CONSTANT,
-            "pad_1d_constant_use_default_const_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{3, 4}),
-            reference_tests::Tensor(ET, {6, 8}, std::vector<T>{
-                2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 1,    2,    2112, 2112, 2112, 2112,
-                2112, 2112, 3,    4,    2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_2d_constant_const_value_provided_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                2112, 2112, 2112, 2112,
-                2112, 2112, 1,    2,
-                2112, 2112, 3,    4,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_2d_constant_const_value_provided_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1,    2,    2112, 2112,
-                3,    4,    2112, 2112,
-                2112, 2112, 2112, 2112,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_2d_constant_const_value_provided_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{3, 4}),
-            reference_tests::Tensor(ET, {6, 8}, std::vector<T>{
-                0, 0, 0, 0, 0, 0, 0, 0,
-                0, 0, 1, 2, 0, 0, 0, 0,
-                0, 0, 3, 4, 0, 0, 0, 0,
-                0, 0, 0, 0, 0, 0, 0, 0,
-                0, 0, 0, 0, 0, 0, 0, 0,
-                0, 0, 0, 0, 0, 0, 0, 0,
-            }),
-            op::PadMode::CONSTANT,
-            "pad_2d_constant_use_default_const_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                0, 0, 0, 0,
-                0, 0, 1, 2,
-                0, 0, 3, 4,
-            }),
-            op::PadMode::CONSTANT,
-            "pad_2d_constant_use_default_const_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 0, 0,
-                3, 4, 0, 0,
-                0, 0, 0, 0,
-            }),
-            op::PadMode::CONSTANT,
-            "pad_2d_constant_use_default_const_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {11}, std::vector<T>{
-                1, 1, 1, 2, 3, 4, 5, 6, 6, 6, 6,
-            }),
-            op::PadMode::EDGE,
-            "pad_1d_edge_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{1}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET, {7}, std::vector<T>{
-                1, 1, 2, 3, 4, 5, 6,
-            }),
-            op::PadMode::EDGE,
-            "pad_1d_edge_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET, {8}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 6, 6,
-            }),
-            op::PadMode::EDGE,
-            "pad_1d_edge_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
-            reference_tests::Tensor(ET, {5, 5}, std::vector<T>{
-                1, 1, 1, 2, 2,
-                1, 1, 1, 2, 2,
-                3, 3, 3, 4, 4,
-                3, 3, 3, 4, 4,
-                3, 3, 3, 4, 4,
-            }),
-            op::PadMode::EDGE,
-            "pad_2d_edge_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 1, 1, 2,
-                1, 1, 1, 2,
-                3, 3, 3, 4,
-            }),
-            op::PadMode::EDGE,
-            "pad_2d_edge_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                1, 2, 2,
-                3, 4, 4,
-                3, 4, 4,
-                3, 4, 4,
-            }),
-            op::PadMode::EDGE,
-            "pad_2d_edge_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {11}, std::vector<T>{
-                3, 2, 1, 2, 3, 4, 5, 6, 5, 4, 3,
-            }),
-            op::PadMode::REFLECT,
-            "pad_1d_reflect_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{1}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET, {7}, std::vector<T>{
-                2, 1, 2, 3, 4, 5, 6,
-            }),
-            op::PadMode::REFLECT,
-            "pad_1d_reflect_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET, {8}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 5, 4,
-            }),
-            op::PadMode::REFLECT,
-            "pad_1d_reflect_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 7, 8, 9,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
-            reference_tests::Tensor(ET, {6, 6}, std::vector<T>{
-                6, 5, 4, 5, 6, 5,
-                3, 2, 1, 2, 3, 2,
-                6, 5, 4, 5, 6, 5,
-                9, 8, 7, 8, 9, 8,
-                6, 5, 4, 5, 6, 5,
-                3, 2, 1, 2, 3, 2,
-            }),
-            op::PadMode::REFLECT,
-            "pad_2d_reflect_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 7, 8, 9,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {4, 5}, std::vector<T>{
-                6, 5, 4, 5, 6,
-                3, 2, 1, 2, 3,
-                6, 5, 4, 5, 6,
-                9, 8, 7, 8, 9,
-            }),
-            op::PadMode::REFLECT,
-            "pad_2d_reflect_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 7, 8, 9,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
-            reference_tests::Tensor(ET, {5, 4}, std::vector<T>{
-                1, 2, 3, 2,
-                4, 5, 6, 5,
-                7, 8, 9, 8,
-                4, 5, 6, 5,
-                1, 2, 3, 2,
-            }),
-            op::PadMode::REFLECT,
-            "pad_2d_reflect_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {11}, std::vector<T>{
-                2, 1, 1, 2, 3, 4, 5, 6, 6, 5, 4,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_1d_symmetric_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{1}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET, {7}, std::vector<T>{
-                1, 1, 2, 3, 4, 5, 6,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_1d_symmetric_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET, {8}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 6, 5,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_1d_symmetric_2"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 7, 8, 9,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
-            reference_tests::Tensor(ET, {6, 6}, std::vector<T>{
-                2, 1, 1, 2, 3, 3,
-                2, 1, 1, 2, 3, 3,
-                5, 4, 4, 5, 6, 6,
-                8, 7, 7, 8, 9, 9,
-                8, 7, 7, 8, 9, 9,
-                5, 4, 4, 5, 6, 6,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_2d_symmetric_0"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 7, 8, 9,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {4, 5}, std::vector<T>{
-                2, 1, 1, 2, 3,
-                2, 1, 1, 2, 3,
-                5, 4, 4, 5, 6,
-                8, 7, 7, 8, 9,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_2d_symmetric_1"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 7, 8, 9,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
-            reference_tests::Tensor(ET, {5, 4}, std::vector<T>{
-                1, 2, 3, 3,
-                4, 5, 6, 6,
-                7, 8, 9, 9,
-                7, 8, 9, 9,
-                4, 5, 6, 6,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_2d_symmetric"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{5}),
-            reference_tests::Tensor(ET, {15}, std::vector<T>{
-                2112, 2112, 2112, 2112, 1, 2, 3, 4, 5, 6, 2112, 2112, 2112, 2112, 2112,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_exterior_1d"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-2}),
-            reference_tests::Tensor(ET, {8}, std::vector<T>{
-                2112, 2112, 2112, 2112, 1, 2, 3, 4,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_negative_exterior_1d"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
-            reference_tests::Tensor(ET, {3}, std::vector<T>{
-                2112, 2112, 2112,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_negative_exterior_1d_check_limits"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {11}, std::vector<T>{
-                1, 1, 1, 2, 3, 4, 5, 6, 6, 6, 6,
-            }),
-            op::PadMode::EDGE,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_edge_1d"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-3}),
-            reference_tests::Tensor(ET, {5}, std::vector<T>{
-                1, 1, 1, 2, 3,
-            }),
-            op::PadMode::EDGE,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_edge_1d_top_neg"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
-            reference_tests::Tensor(ET, {1}, std::vector<T>{
-                1,
-            }),
-            op::PadMode::EDGE,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_edge_1d_top_neg_bigger_than_tensor"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {7}, std::vector<T>{
-                3, 4, 5, 6, 6, 6, 6,
-            }),
-            op::PadMode::EDGE,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_edge_1d_bottom_neg"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {2}, std::vector<T>{
-                6, 6,
-            }),
-            op::PadMode::EDGE,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_edge_1d_bottom_neg_bigger_than_tensor"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET, {6, 9}, std::vector<T>{
-                1, 1, 1, 1, 2,  3,  4,  4,  4,
-                1, 1, 1, 1, 2,  3,  4,  4,  4,
-                1, 1, 1, 1, 2,  3,  4,  4,  4,
-                5, 5, 5, 5, 6,  7,  8,  8,  8,
-                9, 9, 9, 9, 10, 11, 12, 12, 12,
-                9, 9, 9, 9, 10, 11, 12, 12, 12,
-            }),
-            op::PadMode::EDGE,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_edge_2d"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET, {6, 5}, std::vector<T>{
-                2,  3,  4,  4,  4,
-                2,  3,  4,  4,  4,
-                2,  3,  4,  4,  4,
-                6,  7,  8,  8,  8,
-                10, 11, 12, 12, 12,
-                10, 11, 12, 12, 12,
-            }),
-            op::PadMode::EDGE,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_edge_2d_with_neg"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {11}, std::vector<T>{
-                3, 2, 1, 2, 3, 4, 5, 6, 5, 4, 3,
-            }),
-            op::PadMode::REFLECT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_reflect_1d"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-3}),
-            reference_tests::Tensor(ET, {5}, std::vector<T>{
-                3, 2, 1, 2, 3,
-            }),
-            op::PadMode::REFLECT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_reflect_1d_top_neg"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
-            reference_tests::Tensor(ET, {1}, std::vector<T>{
-                3,
-            }),
-            op::PadMode::REFLECT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_reflect_1d_top_neg_bigger_than_tensor"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-2}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {7}, std::vector<T>{
-                3, 4, 5, 6, 5, 4, 3,
-            }),
-            op::PadMode::REFLECT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_reflect_1d_bottom_neg"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
-            reference_tests::Tensor(ET, {2}, std::vector<T>{
-                4, 3,
-            }),
-            op::PadMode::REFLECT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_reflect_1d_bottom_neg_bigger_than_tensor"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2,  3,  4,
-                5, 6,  7,  8,
-                9, 10, 11, 12,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET, {6, 9}, std::vector<T>{
-                12, 11, 10, 9, 10, 11, 12, 11, 10,
-                8,  7,  6,  5, 6,  7,  8,  7,  6,
-                4,  3,  2,  1, 2,  3,  4,  3,  2,
-                8,  7,  6,  5, 6,  7,  8,  7,  6,
-                12, 11, 10, 9, 10, 11, 12, 11, 10,
-                8,  7,  6,  5, 6,  7,  8,  7,  6,
-            }),
-            op::PadMode::REFLECT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_reflect_2d"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2,  3,  4,
-                5, 6,  7,  8,
-                9, 10, 11, 12,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET, {6, 5}, std::vector<T>{
-                10, 11, 12, 11, 10,
-                6,  7,  8,  7,  6,
-                2,  3,  4,  3,  2,
-                6,  7,  8,  7,  6,
-                10, 11, 12, 11, 10,
-                6,  7,  8,  7,  6,
-            }),
-            op::PadMode::REFLECT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_reflect_2d_with_neg"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, -1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 0}),
-            reference_tests::Tensor(ET, {5, 2}, std::vector<T>{
-                9, 9,
-                2, 3,
-                5, 6,
-                9, 9,
-                9, 9,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{9}),
-            "pad_negative_exterior_2d"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-                7, 8, 9,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
-            reference_tests::Tensor(ET, {1, 1}, std::vector<T>{5}),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{9}),
-            "pad_negative_exterior_2d_all_negative"),
+    std::vector<PadParams> params{
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{5}),
+                  reference_tests::Tensor(ET,
+                                          {15},
+                                          std::vector<T>{
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_1d_constant_const_value_provided_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET,
+                                          {10},
+                                          std::vector<T>{
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_1d_constant_const_value_provided_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {9},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              2112,
+                                              2112,
+                                              2112,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_1d_constant_const_value_provided_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{5}),
+                  reference_tests::Tensor(ET,
+                                          {15},
+                                          std::vector<T>{
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  "pad_1d_constant_use_default_const_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET,
+                                          {10},
+                                          std::vector<T>{
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  "pad_1d_constant_use_default_const_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {9},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              0,
+                                              0,
+                                              0,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  "pad_1d_constant_use_default_const_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{3, 4}),
+                  reference_tests::Tensor(ET,
+                                          {6, 8},
+                                          std::vector<T>{
+                                              2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 1,    2,
+                                              2112, 2112, 2112, 2112, 2112, 2112, 3,    4,    2112, 2112, 2112, 2112,
+                                              2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
+                                              2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_2d_constant_const_value_provided_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              1,
+                                              2,
+                                              2112,
+                                              2112,
+                                              3,
+                                              4,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_2d_constant_const_value_provided_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              2112,
+                                              2112,
+                                              3,
+                                              4,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_2d_constant_const_value_provided_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{3, 4}),
+                  reference_tests::Tensor(ET,
+                                          {6, 8},
+                                          std::vector<T>{
+                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 0, 0,
+                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  "pad_2d_constant_use_default_const_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              1,
+                                              2,
+                                              0,
+                                              0,
+                                              3,
+                                              4,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  "pad_2d_constant_use_default_const_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              0,
+                                              0,
+                                              3,
+                                              4,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  "pad_2d_constant_use_default_const_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {11},
+                                          std::vector<T>{
+                                              1,
+                                              1,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              6,
+                                              6,
+                                              6,
+                                          }),
+                  op::PadMode::EDGE,
+                  "pad_1d_edge_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{1}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET,
+                                          {7},
+                                          std::vector<T>{
+                                              1,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  op::PadMode::EDGE,
+                  "pad_1d_edge_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET,
+                                          {8},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              6,
+                                              6,
+                                          }),
+                  op::PadMode::EDGE,
+                  "pad_1d_edge_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
+                  reference_tests::Tensor(ET,
+                                          {5, 5},
+                                          std::vector<T>{
+                                              1, 1, 1, 2, 2, 1, 1, 1, 2, 2, 3, 3, 3, 4, 4, 3, 3, 3, 4, 4, 3, 3, 3, 4, 4,
+                                          }),
+                  op::PadMode::EDGE,
+                  "pad_2d_edge_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              1,
+                                              1,
+                                              1,
+                                              2,
+                                              1,
+                                              1,
+                                              1,
+                                              2,
+                                              3,
+                                              3,
+                                              3,
+                                              4,
+                                          }),
+                  op::PadMode::EDGE,
+                  "pad_2d_edge_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
+                  reference_tests::Tensor(ET,
+                                          {4, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              2,
+                                              3,
+                                              4,
+                                              4,
+                                              3,
+                                              4,
+                                              4,
+                                              3,
+                                              4,
+                                              4,
+                                          }),
+                  op::PadMode::EDGE,
+                  "pad_2d_edge_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {11},
+                                          std::vector<T>{
+                                              3,
+                                              2,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              5,
+                                              4,
+                                              3,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_1d_reflect_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{1}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET,
+                                          {7},
+                                          std::vector<T>{
+                                              2,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_1d_reflect_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET,
+                                          {8},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              5,
+                                              4,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_1d_reflect_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
+                  reference_tests::Tensor(ET,
+                                          {6, 6},
+                                          std::vector<T>{
+                                              6, 5, 4, 5, 6, 5, 3, 2, 1, 2, 3, 2, 6, 5, 4, 5, 6, 5,
+                                              9, 8, 7, 8, 9, 8, 6, 5, 4, 5, 6, 5, 3, 2, 1, 2, 3, 2,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_2d_reflect_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {4, 5},
+                                          std::vector<T>{
+                                              6, 5, 4, 5, 6, 3, 2, 1, 2, 3, 6, 5, 4, 5, 6, 9, 8, 7, 8, 9,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_2d_reflect_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
+                  reference_tests::Tensor(ET,
+                                          {5, 4},
+                                          std::vector<T>{
+                                              1, 2, 3, 2, 4, 5, 6, 5, 7, 8, 9, 8, 4, 5, 6, 5, 1, 2, 3, 2,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_2d_reflect_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {11},
+                                          std::vector<T>{
+                                              2,
+                                              1,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              6,
+                                              5,
+                                              4,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_1d_symmetric_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{1}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET,
+                                          {7},
+                                          std::vector<T>{
+                                              1,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_1d_symmetric_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{0}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET,
+                                          {8},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              6,
+                                              5,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_1d_symmetric_2"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
+                  reference_tests::Tensor(ET,
+                                          {6, 6},
+                                          std::vector<T>{
+                                              2, 1, 1, 2, 3, 3, 2, 1, 1, 2, 3, 3, 5, 4, 4, 5, 6, 6,
+                                              8, 7, 7, 8, 9, 9, 8, 7, 7, 8, 9, 9, 5, 4, 4, 5, 6, 6,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_2d_symmetric_0"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {4, 5},
+                                          std::vector<T>{
+                                              2, 1, 1, 2, 3, 2, 1, 1, 2, 3, 5, 4, 4, 5, 6, 8, 7, 7, 8, 9,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_2d_symmetric_1"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
+                  reference_tests::Tensor(ET,
+                                          {5, 4},
+                                          std::vector<T>{
+                                              1, 2, 3, 3, 4, 5, 6, 6, 7, 8, 9, 9, 7, 8, 9, 9, 4, 5, 6, 6,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_2d_symmetric"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{5}),
+                  reference_tests::Tensor(ET,
+                                          {15},
+                                          std::vector<T>{
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_exterior_1d"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-2}),
+                  reference_tests::Tensor(ET,
+                                          {8},
+                                          std::vector<T>{
+                                              2112,
+                                              2112,
+                                              2112,
+                                              2112,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_negative_exterior_1d"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
+                  reference_tests::Tensor(ET,
+                                          {3},
+                                          std::vector<T>{
+                                              2112,
+                                              2112,
+                                              2112,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_negative_exterior_1d_check_limits"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {11},
+                                          std::vector<T>{
+                                              1,
+                                              1,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              6,
+                                              6,
+                                              6,
+                                          }),
+                  op::PadMode::EDGE,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_edge_1d"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-3}),
+                  reference_tests::Tensor(ET,
+                                          {5},
+                                          std::vector<T>{
+                                              1,
+                                              1,
+                                              1,
+                                              2,
+                                              3,
+                                          }),
+                  op::PadMode::EDGE,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_edge_1d_top_neg"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
+                  reference_tests::Tensor(ET,
+                                          {1},
+                                          std::vector<T>{
+                                              1,
+                                          }),
+                  op::PadMode::EDGE,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_edge_1d_top_neg_bigger_than_tensor"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {7},
+                                          std::vector<T>{
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              6,
+                                              6,
+                                              6,
+                                          }),
+                  op::PadMode::EDGE,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_edge_1d_bottom_neg"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {2},
+                                          std::vector<T>{
+                                              6,
+                                              6,
+                                          }),
+                  op::PadMode::EDGE,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_edge_1d_bottom_neg_bigger_than_tensor"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                              10,
+                                              11,
+                                              12,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(
+                      ET,
+                      {6, 9},
+                      std::vector<T>{
+                          1, 1, 1, 1, 2, 3, 4, 4, 4, 1, 1, 1, 1, 2,  3,  4,  4,  4,  1, 1, 1, 1, 2,  3,  4,  4,  4,
+                          5, 5, 5, 5, 6, 7, 8, 8, 8, 9, 9, 9, 9, 10, 11, 12, 12, 12, 9, 9, 9, 9, 10, 11, 12, 12, 12,
+                      }),
+                  op::PadMode::EDGE,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_edge_2d"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                              10,
+                                              11,
+                                              12,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET,
+                                          {6, 5},
+                                          std::vector<T>{
+                                              2, 3, 4, 4, 4, 2,  3,  4,  4,  4,  2,  3,  4,  4,  4,
+                                              6, 7, 8, 8, 8, 10, 11, 12, 12, 12, 10, 11, 12, 12, 12,
+                                          }),
+                  op::PadMode::EDGE,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_edge_2d_with_neg"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {11},
+                                          std::vector<T>{
+                                              3,
+                                              2,
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              5,
+                                              4,
+                                              3,
+                                          }),
+                  op::PadMode::REFLECT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_reflect_1d"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-3}),
+                  reference_tests::Tensor(ET,
+                                          {5},
+                                          std::vector<T>{
+                                              3,
+                                              2,
+                                              1,
+                                              2,
+                                              3,
+                                          }),
+                  op::PadMode::REFLECT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_reflect_1d_top_neg"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
+                  reference_tests::Tensor(ET,
+                                          {1},
+                                          std::vector<T>{
+                                              3,
+                                          }),
+                  op::PadMode::REFLECT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_reflect_1d_top_neg_bigger_than_tensor"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-2}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {7},
+                                          std::vector<T>{
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              5,
+                                              4,
+                                              3,
+                                          }),
+                  op::PadMode::REFLECT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_reflect_1d_bottom_neg"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {6},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{-7}),
+                  reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{3}),
+                  reference_tests::Tensor(ET,
+                                          {2},
+                                          std::vector<T>{
+                                              4,
+                                              3,
+                                          }),
+                  op::PadMode::REFLECT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_reflect_1d_bottom_neg_bigger_than_tensor"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                              10,
+                                              11,
+                                              12,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET,
+                                          {6, 9},
+                                          std::vector<T>{
+                                              12, 11, 10, 9, 10, 11, 12, 11, 10, 8, 7, 6, 5, 6, 7, 8, 7, 6,
+                                              4,  3,  2,  1, 2,  3,  4,  3,  2,  8, 7, 6, 5, 6, 7, 8, 7, 6,
+                                              12, 11, 10, 9, 10, 11, 12, 11, 10, 8, 7, 6, 5, 6, 7, 8, 7, 6,
+                                          }),
+                  op::PadMode::REFLECT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_reflect_2d"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                              10,
+                                              11,
+                                              12,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET,
+                                          {6, 5},
+                                          std::vector<T>{
+                                              10, 11, 12, 11, 10, 6,  7,  8,  7,  6,  2, 3, 4, 3, 2,
+                                              6,  7,  8,  7,  6,  10, 11, 12, 11, 10, 6, 7, 8, 7, 6,
+                                          }),
+                  op::PadMode::REFLECT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_reflect_2d_with_neg"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, -1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 0}),
+                  reference_tests::Tensor(ET,
+                                          {5, 2},
+                                          std::vector<T>{
+                                              9,
+                                              9,
+                                              2,
+                                              3,
+                                              5,
+                                              6,
+                                              9,
+                                              9,
+                                              9,
+                                              9,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{9}),
+                  "pad_negative_exterior_2d"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
+                  reference_tests::Tensor(ET, {1, 1}, std::vector<T>{5}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{9}),
+                  "pad_negative_exterior_2d_all_negative"),
 
         PadParams(
             reference_tests::Tensor(ET, {0, 0}, std::vector<T>{}),
             reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
             reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{3, 2}),
-            reference_tests::Tensor(ET, {5, 5}, std::vector<T>{
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-            }),
+            reference_tests::Tensor(ET,
+                                    {5, 5},
+                                    std::vector<T>{
+                                        2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
+                                        2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
+                                    }),
             op::PadMode::CONSTANT,
             reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
             "pad_exterior_2d_0x0"),
@@ -905,13 +1536,12 @@ std::vector<PadParams> generateParams() {
             reference_tests::Tensor(ET, {0, 3}, std::vector<T>{}),
             reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
             reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{3, 1}),
-            reference_tests::Tensor(ET, {5, 5}, std::vector<T>{
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-            }),
+            reference_tests::Tensor(ET,
+                                    {5, 5},
+                                    std::vector<T>{
+                                        2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
+                                        2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
+                                    }),
             op::PadMode::CONSTANT,
             reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
             "pad_exterior_2d_0x3"),
@@ -920,365 +1550,317 @@ std::vector<PadParams> generateParams() {
             reference_tests::Tensor(ET, {3, 0}, std::vector<T>{}),
             reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 3}),
             reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET, {5, 5}, std::vector<T>{
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-                2112, 2112, 2112, 2112, 2112,
-            }),
+            reference_tests::Tensor(ET,
+                                    {5, 5},
+                                    std::vector<T>{
+                                        2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
+                                        2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112, 2112,
+                                    }),
             op::PadMode::CONSTANT,
             reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
             "pad_exterior_2d_3x0"),
 
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2, 4, 4}, std::vector<T>{
-                0, 1, 0, 2,
-                0, 3, 2, 0,
-                2, 0, 0, 0,
-                0, 2, 1, 0,
-
-                0, 0, 0, 2,
-                0, 2, 3, 0,
-                2, 0, 1, 0,
-                2, 0, 0, 0,
-
-                0, 2, 1, 1,
-                0, 0, 2, 0,
-                0, 0, 1, 2,
-                0, 0, 0, 0,
-
-                2, 1, 0, 0,
-                0, 2, 0, 0,
-                1, 1, 2, 0,
-                1, 0, 0, 0,
-            }),
-            reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, 0, 0, 0}),
-            reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, 0, 2, 2}),
-            reference_tests::Tensor(ET, {2, 2, 6, 6}, std::vector<T>{
-                0,  1,  0,  2,  42, 42,
-                0,  3,  2,  0,  42, 42,
-                2,  0,  0,  0,  42, 42,
-                0,  2,  1,  0,  42, 42,
-                42, 42, 42, 42, 42, 42,
-                42, 42, 42, 42, 42, 42,
-
-                0,  0,  0,  2,  42, 42,
-                0,  2,  3,  0,  42, 42,
-                2,  0,  1,  0,  42, 42,
-                2,  0,  0,  0,  42, 42,
-                42, 42, 42, 42, 42, 42,
-                42, 42, 42, 42, 42, 42,
-
-                0,  2,  1,  1,  42, 42,
-                0,  0,  2,  0,  42, 42,
-                0,  0,  1,  2,  42, 42,
-                0,  0,  0,  0,  42, 42,
-                42, 42, 42, 42, 42, 42,
-                42, 42, 42, 42, 42, 42,
-
-                2,  1,  0,  0,  42, 42,
-                0,  2,  0,  0,  42, 42,
-                1,  1,  2,  0,  42, 42,
-                1,  0,  0,  0,  42, 42,
-                42, 42, 42, 42, 42, 42,
-                42, 42, 42, 42, 42, 42,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{42}),
-            "pad_2channel_2image_asym"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
-            reference_tests::Tensor(ET, {4, 7}, std::vector<T>{
-                2, 1, 1, 2, 3, 3, 2,
-                2, 1, 1, 2, 3, 3, 2,
-                5, 4, 4, 5, 6, 6, 5,
-                5, 4, 4, 5, 6, 6, 5,
-            }),
-            op::PadMode::SYMMETRIC,
-            reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
-            "pad_symmetric"),
-        PadParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-                7, 8, 9,
-                10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
-            reference_tests::Tensor(ET, {2, 1}, std::vector<T>{
-                5, 8
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_4x3_mode_const"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
-            reference_tests::Tensor(ET, {1, 2}, std::vector<T>{
-                6, 7
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_3x4_mode_const"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-
-                7, 8, 9,
-                10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, 0, 0}),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{-1, 0, 0}),
-            reference_tests::Tensor(ET, {1, 2, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_2x2x3_mode_const_remove_last"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-
-                7, 8, 9,
-                10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{-1, 0, 0}),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, 0, 0}),
-            reference_tests::Tensor(ET, {1, 2, 3}, std::vector<T>{
-                7, 8, 9,
-                10, 11, 12
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_2x2x3_mode_const_remove_first"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-
-                7, 8, 9,
-                10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, -1, 0}),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, 0, 0}),
-            reference_tests::Tensor(ET, {2, 1, 3}, std::vector<T>{
-                4, 5, 6,
-
-                10, 11, 12
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_2x2x3_mode_const_remove_middle_begin"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{
-                1, 2, 3,
-                4, 5, 6,
-
-                7, 8, 9,
-                10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, 0, 0}),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, -1, 0}),
-            reference_tests::Tensor(ET, {2, 1, 3}, std::vector<T>{
-                1, 2, 3,
-
-                7, 8, 9,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_2x2x3_mode_const_remove_middle_end"),
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2,
-                3, 4,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
-            reference_tests::Tensor(ET, {0, 2}, std::vector<T>{}),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{10}),
-            "pad_neg_2x2_reult_empty_mode_const"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-2, -2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -2}),
-            reference_tests::Tensor(ET, {0, 0}, std::vector<T>{}),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{10}),
-            "pad_neg_3x4_reult_empty_mode_const"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, -2}),
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                5, 6,
-                9, 10
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_mix_cross_3x4_mode_const"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
-            reference_tests::Tensor(ET, {4, 5}, std::vector<T>{
-                 7, 8, 0, 0, 0,
-                 11, 12, 0, 0, 0,
-                 0, 0, 0, 0, 0,
-                 0, 0, 0, 0, 0
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_begin_3x4_mode_const"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -2}),
-            reference_tests::Tensor(ET, {4, 5}, std::vector<T>{
-                0, 0, 0, 0, 0,
-                0, 0, 0, 0, 0,
-                0, 0, 0, 1, 2,
-                0, 0, 0, 5, 6,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{0}),
-            "pad_neg_end_3x4_mode_const"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2, 4, 4},
+                                          std::vector<T>{
+                                              0, 1, 0, 2, 0, 3, 2, 0, 2, 0, 0, 0, 0, 2, 1, 0,
+
+                                              0, 0, 0, 2, 0, 2, 3, 0, 2, 0, 1, 0, 2, 0, 0, 0,
+
+                                              0, 2, 1, 1, 0, 0, 2, 0, 0, 0, 1, 2, 0, 0, 0, 0,
+
+                                              2, 1, 0, 0, 0, 2, 0, 0, 1, 1, 2, 0, 1, 0, 0, 0,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, 0, 0, 0}),
+                  reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, 0, 2, 2}),
+                  reference_tests::Tensor(ET,
+                                          {2, 2, 6, 6},
+                                          std::vector<T>{
+                                              0, 1, 0, 2, 42, 42, 0,  3,  2,  0,  42, 42, 2,  0,  0,  0,  42, 42,
+                                              0, 2, 1, 0, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42,
+
+                                              0, 0, 0, 2, 42, 42, 0,  2,  3,  0,  42, 42, 2,  0,  1,  0,  42, 42,
+                                              2, 0, 0, 0, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42,
+
+                                              0, 2, 1, 1, 42, 42, 0,  0,  2,  0,  42, 42, 0,  0,  1,  2,  42, 42,
+                                              0, 0, 0, 0, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42,
+
+                                              2, 1, 0, 0, 42, 42, 0,  2,  0,  0,  42, 42, 1,  1,  2,  0,  42, 42,
+                                              1, 0, 0, 0, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42, 42,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{42}),
+                  "pad_2channel_2image_asym"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{1, 2}),
+                  reference_tests::Tensor(
+                      ET,
+                      {4, 7},
+                      std::vector<T>{
+                          2, 1, 1, 2, 3, 3, 2, 2, 1, 1, 2, 3, 3, 2, 5, 4, 4, 5, 6, 6, 5, 5, 4, 4, 5, 6, 6, 5,
+                      }),
+                  op::PadMode::SYMMETRIC,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{2112}),
+                  "pad_symmetric"),
+        PadParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
+                  reference_tests::Tensor(ET, {2, 1}, std::vector<T>{5, 8}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_4x3_mode_const"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -1}),
+                  reference_tests::Tensor(ET, {1, 2}, std::vector<T>{6, 7}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_3x4_mode_const"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2, 3},
+                                          std::vector<T>{1,
+                                                         2,
+                                                         3,
+                                                         4,
+                                                         5,
+                                                         6,
+
+                                                         7,
+                                                         8,
+                                                         9,
+                                                         10,
+                                                         11,
+                                                         12}),
+                  reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, 0, 0}),
+                  reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{-1, 0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {1, 2, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_2x2x3_mode_const_remove_last"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2, 3},
+                                          std::vector<T>{1,
+                                                         2,
+                                                         3,
+                                                         4,
+                                                         5,
+                                                         6,
+
+                                                         7,
+                                                         8,
+                                                         9,
+                                                         10,
+                                                         11,
+                                                         12}),
+                  reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{-1, 0, 0}),
+                  reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, 0, 0}),
+                  reference_tests::Tensor(ET, {1, 2, 3}, std::vector<T>{7, 8, 9, 10, 11, 12}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_2x2x3_mode_const_remove_first"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2, 3},
+                                          std::vector<T>{1,
+                                                         2,
+                                                         3,
+                                                         4,
+                                                         5,
+                                                         6,
+
+                                                         7,
+                                                         8,
+                                                         9,
+                                                         10,
+                                                         11,
+                                                         12}),
+                  reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, -1, 0}),
+                  reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, 0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {2, 1, 3},
+                                          std::vector<T>{4,
+                                                         5,
+                                                         6,
+
+                                                         10,
+                                                         11,
+                                                         12}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_2x2x3_mode_const_remove_middle_begin"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2, 3},
+                                          std::vector<T>{1,
+                                                         2,
+                                                         3,
+                                                         4,
+                                                         5,
+                                                         6,
+
+                                                         7,
+                                                         8,
+                                                         9,
+                                                         10,
+                                                         11,
+                                                         12}),
+                  reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, 0, 0}),
+                  reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{0, -1, 0}),
+                  reference_tests::Tensor(ET,
+                                          {2, 1, 3},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+
+                                              7,
+                                              8,
+                                              9,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_2x2x3_mode_const_remove_middle_end"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
+                  reference_tests::Tensor(ET, {0, 2}, std::vector<T>{}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{10}),
+                  "pad_neg_2x2_reult_empty_mode_const"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-2, -2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -2}),
+                  reference_tests::Tensor(ET, {0, 0}, std::vector<T>{}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{10}),
+                  "pad_neg_3x4_reult_empty_mode_const"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, -2}),
+                  reference_tests::Tensor(ET, {2, 2}, std::vector<T>{5, 6, 9, 10}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_mix_cross_3x4_mode_const"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
+                  reference_tests::Tensor(ET, {4, 5}, std::vector<T>{7, 8, 0, 0, 0, 11, 12, 0, 0, 0,
+                                                                     0, 0, 0, 0, 0, 0,  0,  0, 0, 0}),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_begin_3x4_mode_const"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 3}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, -2}),
+                  reference_tests::Tensor(ET,
+                                          {4, 5},
+                                          std::vector<T>{
+                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 5, 6,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{0}),
+                  "pad_neg_end_3x4_mode_const"),
+        PadParams(
+            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
             reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
             reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 3}),
-            reference_tests::Tensor(ET, {4, 6}, std::vector<T>{
-                10, 11, 12, 11, 10, 9,
-                6,   7,  8,  7,  6, 5,
-                2,   3,  4,  3,  2, 1,
-                6,   7,  8,  7,  6, 5,
-            }),
+            reference_tests::Tensor(ET,
+                                    {4, 6},
+                                    std::vector<T>{
+                                        10, 11, 12, 11, 10, 9, 6, 7, 8, 7, 6, 5, 2, 3, 4, 3, 2, 1, 6, 7, 8, 7, 6, 5,
+                                    }),
             op::PadMode::REFLECT,
             "pad_neg_ones_cross_3x4_mode_reflect"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12,
-
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-4, 3}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -5}),
-            reference_tests::Tensor(ET, {1, 2}, std::vector<T>{
-               4, 3,
-            }),
-            op::PadMode::REFLECT,
-            "pad_neg_mix_cross_3x4_mode_reflect"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 3}),
-            reference_tests::Tensor(ET, {4, 6}, std::vector<T>{
-                2, 3, 4, 4, 4, 4,
-                2, 3, 4, 4, 4, 4,
-                2, 3, 4, 4, 4, 4,
-                6, 7, 8, 8, 8, 8,
-            }),
-            op::PadMode::EDGE,
-            "pad_neg_ones_cross_3x4_mode_edge"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, -2}),
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                5, 6,
-                9, 10
-            }),
-            op::PadMode::EDGE,
-            "pad_neg_mix_cross_3x4_mode_edge"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, -2}),
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                5, 6,
-                9, 10
-            }),
-            op::PadMode::REFLECT,
-            "pad_neg_mix_cross_3x4_mode_reflect"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, -2}),
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                5, 6,
-                9, 10
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_neg_mix_cross_3x4_mode_symmetric"),
-        PadParams(
-            reference_tests::Tensor(ET, {3, 4}, std::vector<T>{
-                1, 2, 3, 4,
-                5, 6, 7, 8,
-                9, 10, 11, 12
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 3}),
-            reference_tests::Tensor(ET, {4, 6}, std::vector<T>{
-                6, 7, 8, 8, 7, 6,
-                2, 3, 4, 4, 3, 2,
-                2, 3, 4, 4, 3, 2,
-                6, 7, 8, 8, 7, 6,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_neg_ones_cross_3x4_mode_symmetric"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {3, 4},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              3,
+                                              4,
+                                              5,
+                                              6,
+                                              7,
+                                              8,
+                                              9,
+                                              10,
+                                              11,
+                                              12,
+
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-4, 3}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -5}),
+                  reference_tests::Tensor(ET,
+                                          {1, 2},
+                                          std::vector<T>{
+                                              4,
+                                              3,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_neg_mix_cross_3x4_mode_reflect"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 3}),
+                  reference_tests::Tensor(ET,
+                                          {4, 6},
+                                          std::vector<T>{
+                                              2, 3, 4, 4, 4, 4, 2, 3, 4, 4, 4, 4, 2, 3, 4, 4, 4, 4, 6, 7, 8, 8, 8, 8,
+                                          }),
+                  op::PadMode::EDGE,
+                  "pad_neg_ones_cross_3x4_mode_edge"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, -2}),
+                  reference_tests::Tensor(ET, {2, 2}, std::vector<T>{5, 6, 9, 10}),
+                  op::PadMode::EDGE,
+                  "pad_neg_mix_cross_3x4_mode_edge"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, -2}),
+                  reference_tests::Tensor(ET, {2, 2}, std::vector<T>{5, 6, 9, 10}),
+                  op::PadMode::REFLECT,
+                  "pad_neg_mix_cross_3x4_mode_reflect"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 0}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, -2}),
+                  reference_tests::Tensor(ET, {2, 2}, std::vector<T>{5, 6, 9, 10}),
+                  op::PadMode::SYMMETRIC,
+                  "pad_neg_mix_cross_3x4_mode_symmetric"),
+        PadParams(reference_tests::Tensor(ET, {3, 4}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, -1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{-1, 3}),
+                  reference_tests::Tensor(ET,
+                                          {4, 6},
+                                          std::vector<T>{
+                                              6, 7, 8, 8, 7, 6, 2, 3, 4, 4, 3, 2, 2, 3, 4, 4, 3, 2, 6, 7, 8, 8, 7, 6,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_neg_ones_cross_3x4_mode_symmetric"),
     };
     return params;
 }
@@ -1287,56 +1869,80 @@ template <element::Type_t ET, element::Type_t ET_INT>
 std::vector<PadParams> generateParamsFloatValue() {
     using T = typename element_type_traits<ET>::value_type;
     using T_INT = typename element_type_traits<ET_INT>::value_type;
-    std::vector<PadParams> params {
-        PadParams(
-            reference_tests::Tensor(ET, {1, 2, 2, 2}, std::vector<T>{
-                0.0f, 0.0f,
-                0.0f, 0.0f,
-                0.0f, 0.0f,
-                0.0f, 0.0f,
-            }),
+    std::vector<PadParams> params{
+        PadParams(
+            reference_tests::Tensor(ET,
+                                    {1, 2, 2, 2},
+                                    std::vector<T>{
+                                        0.0f,
+                                        0.0f,
+                                        0.0f,
+                                        0.0f,
+                                        0.0f,
+                                        0.0f,
+                                        0.0f,
+                                        0.0f,
+                                    }),
             reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, 0, 1, 1}),
             reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, 0, 1, 1}),
-            reference_tests::Tensor(ET, {1, 2, 4, 4}, std::vector<T>{
-                42.0f, 42.0f, 42.0f, 42.0f,
-                42.0f, 0.0f, 0.0f, 42.0f,
-                42.0f, 0.0f, 0.0f, 42.0f,
-                42.0f, 42.0f, 42.0f, 42.0f,
-                42.0f, 42.0f, 42.0f, 42.0f,
-                42.0f, 0.0f, 0.0f, 42.0f,
-                42.0f, 0.0f, 0.0f, 42.0f,
-                42.0f, 42.0f, 42.0f, 42.0f,
-            }),
+            reference_tests::Tensor(ET,
+                                    {1, 2, 4, 4},
+                                    std::vector<T>{
+                                        42.0f, 42.0f, 42.0f, 42.0f, 42.0f, 0.0f,  0.0f,  42.0f, 42.0f, 0.0f,  0.0f,
+                                        42.0f, 42.0f, 42.0f, 42.0f, 42.0f, 42.0f, 42.0f, 42.0f, 42.0f, 42.0f, 0.0f,
+                                        0.0f,  42.0f, 42.0f, 0.0f,  0.0f,  42.0f, 42.0f, 42.0f, 42.0f, 42.0f,
+                                    }),
             op::PadMode::CONSTANT,
             reference_tests::Tensor(ET, {}, std::vector<T>{42}),
             "pad_exterior_4d_1x2x2x2"),
 
-        PadParams(
-            reference_tests::Tensor(ET, {1, 3, 2, 2}, std::vector<T>{
-                0.0f, 0.0f,
-                0.0f, 0.0f,
-                1.0f, 1.0f,
-                1.0f, 1.0f,
-                2.0f, 2.0f,
-                2.0f, 2.0f,
-            }),
-            reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, -1, 1, 1}),
-            reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, -1, 1, 1}),
-            reference_tests::Tensor(ET, {1, 1, 4, 4}, std::vector<T>{
-                42.0f, 42.0f, 42.0f, 42.0f,
-                42.0f, 1.0f,  1.0f,  42.0f,
-                42.0f, 1.0f,  1.0f,  42.0f,
-                42.0f, 42.0f, 42.0f, 42.0f,
-            }),
-            op::PadMode::CONSTANT,
-            reference_tests::Tensor(ET, {}, std::vector<T>{42}),
-            "pad_negative_exterior_4d"),
+        PadParams(reference_tests::Tensor(ET,
+                                          {1, 3, 2, 2},
+                                          std::vector<T>{
+                                              0.0f,
+                                              0.0f,
+                                              0.0f,
+                                              0.0f,
+                                              1.0f,
+                                              1.0f,
+                                              1.0f,
+                                              1.0f,
+                                              2.0f,
+                                              2.0f,
+                                              2.0f,
+                                              2.0f,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, -1, 1, 1}),
+                  reference_tests::Tensor(ET_INT, {4}, std::vector<T_INT>{0, -1, 1, 1}),
+                  reference_tests::Tensor(ET,
+                                          {1, 1, 4, 4},
+                                          std::vector<T>{
+                                              42.0f,
+                                              42.0f,
+                                              42.0f,
+                                              42.0f,
+                                              42.0f,
+                                              1.0f,
+                                              1.0f,
+                                              42.0f,
+                                              42.0f,
+                                              1.0f,
+                                              1.0f,
+                                              42.0f,
+                                              42.0f,
+                                              42.0f,
+                                              42.0f,
+                                              42.0f,
+                                          }),
+                  op::PadMode::CONSTANT,
+                  reference_tests::Tensor(ET, {}, std::vector<T>{42}),
+                  "pad_negative_exterior_4d"),
     };
     return params;
 }
 
 std::vector<PadParams> generateCombinedParams() {
-    const std::vector<std::vector<PadParams>> generatedParams {
+    const std::vector<std::vector<PadParams>> generatedParams{
         generateParams<element::Type_t::i16, element::Type_t::i32>(),
         generateParams<element::Type_t::i32, element::Type_t::i32>(),
         generateParams<element::Type_t::i64, element::Type_t::i32>(),
@@ -1370,53 +1976,88 @@ std::vector<PadParams> generateCombinedParams() {
     return combinedParams;
 }
 
+INSTANTIATE_TEST_SUITE_P(smoke_PadV1_With_Hardcoded_Refs,
+                         ReferencePadV1Test,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferencePadTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_PadV1_With_Hardcoded_Refs, ReferencePadV1Test,
-    testing::ValuesIn(generateCombinedParams()), ReferencePadTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_PadV1_With_Hardcoded_Refs, ReferencePadV1TestNonConstPadsBeginPadsEndPadVal,
-    testing::ValuesIn(generateCombinedParams()), ReferencePadTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_PadV1_With_Hardcoded_Refs,
+                         ReferencePadV1TestNonConstPadsBeginPadsEndPadVal,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferencePadTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_PadV12_With_Hardcoded_Refs, ReferencePadV12Test,
-    testing::ValuesIn(generateCombinedParams()), ReferencePadTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_PadV12_With_Hardcoded_Refs,
+                         ReferencePadV12Test,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferencePadTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_PadV12_With_Hardcoded_Refs, ReferencePadV12TestNonConstPadsBeginPadsEndPadVal,
-    testing::ValuesIn(generateCombinedParams()), ReferencePadTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_PadV12_With_Hardcoded_Refs,
+                         ReferencePadV12TestNonConstPadsBeginPadsEndPadVal,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferencePadTest::getTestCaseName);
 
 template <element::Type_t ET, element::Type_t ET_INT>
 std::vector<PadParams> generateParamsTooLarge() {
     using T = typename element_type_traits<ET>::value_type;
     using T_INT = typename element_type_traits<ET_INT>::value_type;
-    std::vector<PadParams> params {
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 4, 5,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 3}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {2, 5}, std::vector<T>{
-                0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_to_large_symmetric_padding"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 4, 5,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{
-                0, 0, 0, 0, 0, 0, 0, 0,
-            }),
-            op::PadMode::REFLECT,
-            "pad_to_large_reflect_padding"),
+    std::vector<PadParams> params{
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              4,
+                                              5,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 3}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {2, 5},
+                                          std::vector<T>{
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_to_large_symmetric_padding"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              4,
+                                              5,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {2, 4},
+                                          std::vector<T>{
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                              0,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_to_large_reflect_padding"),
     };
     return params;
 }
 
 std::vector<PadParams> generateCombinedParamsTooLarge() {
-    const std::vector<std::vector<PadParams>> generatedParams {
+    const std::vector<std::vector<PadParams>> generatedParams{
         generateParamsTooLarge<element::Type_t::f32, element::Type_t::i64>(),
     };
     std::vector<PadParams> combinedParams;
@@ -1427,46 +2068,74 @@ std::vector<PadParams> generateCombinedParamsTooLarge() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Pad_With_Hardcoded_Refs, ReferencePadTestParamsTooLarge,
-    testing::ValuesIn(generateCombinedParamsTooLarge()), ReferencePadTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Pad_With_Hardcoded_Refs,
+                         ReferencePadTestParamsTooLarge,
+                         testing::ValuesIn(generateCombinedParamsTooLarge()),
+                         ReferencePadTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Pad_With_Hardcoded_Refs, ReferencePadV1TestNonConstPadsBeginPadsEndPadValTooLarge,
-    testing::ValuesIn(generateCombinedParamsTooLarge()), ReferencePadTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Pad_With_Hardcoded_Refs,
+                         ReferencePadV1TestNonConstPadsBeginPadsEndPadValTooLarge,
+                         testing::ValuesIn(generateCombinedParamsTooLarge()),
+                         ReferencePadTest::getTestCaseName);
 
 template <element::Type_t ET, element::Type_t ET_INT>
 std::vector<PadParams> generateParamsOk() {
     using T = typename element_type_traits<ET>::value_type;
     using T_INT = typename element_type_traits<ET_INT>::value_type;
-    std::vector<PadParams> params {
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 4, 5,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 2}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{
-                2, 1, 1, 2, 5, 4, 4, 5,
-            }),
-            op::PadMode::SYMMETRIC,
-            "pad_ok_symmetric_padding"),
-
-        PadParams(
-            reference_tests::Tensor(ET, {2, 2}, std::vector<T>{
-                1, 2, 4, 5,
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 1}),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                2, 1, 2, 5, 4, 5,
-            }),
-            op::PadMode::REFLECT,
-            "pad_ok_reflect_padding"),
+    std::vector<PadParams> params{
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              4,
+                                              5,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 2}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {2, 4},
+                                          std::vector<T>{
+                                              2,
+                                              1,
+                                              1,
+                                              2,
+                                              5,
+                                              4,
+                                              4,
+                                              5,
+                                          }),
+                  op::PadMode::SYMMETRIC,
+                  "pad_ok_symmetric_padding"),
+
+        PadParams(reference_tests::Tensor(ET,
+                                          {2, 2},
+                                          std::vector<T>{
+                                              1,
+                                              2,
+                                              4,
+                                              5,
+                                          }),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 1}),
+                  reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{0, 0}),
+                  reference_tests::Tensor(ET,
+                                          {2, 3},
+                                          std::vector<T>{
+                                              2,
+                                              1,
+                                              2,
+                                              5,
+                                              4,
+                                              5,
+                                          }),
+                  op::PadMode::REFLECT,
+                  "pad_ok_reflect_padding"),
     };
     return params;
 }
 
 std::vector<PadParams> generateCombinedParamsOk() {
-    const std::vector<std::vector<PadParams>> generatedParams {
+    const std::vector<std::vector<PadParams>> generatedParams{
         generateParamsOk<element::Type_t::f32, element::Type_t::i64>(),
     };
     std::vector<PadParams> combinedParams;
@@ -1477,9 +2146,13 @@ std::vector<PadParams> generateCombinedParamsOk() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Pad_With_Hardcoded_Refs, ReferencePadTestParamsOk,
-    testing::ValuesIn(generateCombinedParamsOk()), ReferencePadTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Pad_With_Hardcoded_Refs,
+                         ReferencePadTestParamsOk,
+                         testing::ValuesIn(generateCombinedParamsOk()),
+                         ReferencePadTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Pad_With_Hardcoded_Refs, ReferencePadV1TestNonConstPadsBeginPadsEndPadValParamsOk,
-    testing::ValuesIn(generateCombinedParamsOk()), ReferencePadTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Pad_With_Hardcoded_Refs,
+                         ReferencePadV1TestNonConstPadsBeginPadsEndPadValParamsOk,
+                         testing::ValuesIn(generateCombinedParamsOk()),
+                         ReferencePadTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/parameter_as_output.cpp b/src/plugins/template/tests/functional/op_reference/parameter_as_output.cpp
index 607e93e38498b3..6b44fdc17734af 100644
--- a/src/plugins/template/tests/functional/op_reference/parameter_as_output.cpp
+++ b/src/plugins/template/tests/functional/op_reference/parameter_as_output.cpp
@@ -72,14 +72,12 @@ template <element::Type_t ET>
 std::vector<ParameterParams> generateParamsForParameter() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<ParameterParams> params{
-        ParameterParams(Shape{3, 4},
-                        Shape{3, 4},
-                        ET,
-                        ET,
-                        std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11},
-                        std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11})
-    };
+    std::vector<ParameterParams> params{ParameterParams(Shape{3, 4},
+                                                        Shape{3, 4},
+                                                        ET,
+                                                        ET,
+                                                        std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11},
+                                                        std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11})};
 
     return params;
 }
@@ -97,8 +95,7 @@ std::vector<ParameterParams> generateCombinedParamsForParameter() {
         generateParamsForParameter<element::Type_t::u64>(),
         generateParamsForParameter<element::Type_t::u32>(),
         generateParamsForParameter<element::Type_t::u16>(),
-        generateParamsForParameter<element::Type_t::u8>()
-    };
+        generateParamsForParameter<element::Type_t::u8>()};
 
     std::vector<ParameterParams> combinedParams;
 
@@ -109,10 +106,9 @@ std::vector<ParameterParams> generateCombinedParamsForParameter() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Parameter_With_Hardcoded_Refs,
-    ReferenceParameterLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForParameter()),
-    ReferenceParameterLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Parameter_With_Hardcoded_Refs,
+                         ReferenceParameterLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForParameter()),
+                         ReferenceParameterLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/power.cpp b/src/plugins/template/tests/functional/op_reference/power.cpp
index 53b04579041a0c..4ca0615397731d 100644
--- a/src/plugins/template/tests/functional/op_reference/power.cpp
+++ b/src/plugins/template/tests/functional/op_reference/power.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/power.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/power.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,11 +16,11 @@ namespace {
 struct PowerParams {
     template <class IT>
     PowerParams(const PartialShape& iShape1,
-              const PartialShape& iShape2,
-              const element::Type& iType,
-              const std::vector<IT>& iValues1,
-              const std::vector<IT>& iValues2,
-              const std::vector<IT>& oValues)
+                const PartialShape& iShape2,
+                const element::Type& iType,
+                const std::vector<IT>& iValues1,
+                const std::vector<IT>& iValues2,
+                const std::vector<IT>& oValues)
         : pshape1(iShape1),
           pshape2(iShape2),
           inType(iType),
@@ -57,9 +59,9 @@ class ReferencePowerLayerTest : public testing::TestWithParam<PowerParams>, publ
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto power = std::make_shared<op::v1::Power>(in1, in2);
@@ -78,43 +80,40 @@ std::vector<PowerParams> generateParamsForPower() {
 
     std::vector<PowerParams> params{
         PowerParams(ov::PartialShape{2, 2},
-                       ov::PartialShape{2, 2},
-                       IN_ET,
-                       std::vector<T>{1, 2, 3, 5},
-                       std::vector<T>{2, 0, 6, 3},
-                       std::vector<T>{1, 1, 729, 125}),
+                    ov::PartialShape{2, 2},
+                    IN_ET,
+                    std::vector<T>{1, 2, 3, 5},
+                    std::vector<T>{2, 0, 6, 3},
+                    std::vector<T>{1, 1, 729, 125}),
         PowerParams(ov::PartialShape{2, 1, 5},
-                       ov::PartialShape{2, 1},
-                       IN_ET,
-                       std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
-                       std::vector<T>{1, 2},
-                       std::vector<T>{1, 2, 3, 4, 5, 1, 4, 9, 16, 25, 6, 7, 8, 9, 10, 36, 49, 64, 81, 100}),
+                    ov::PartialShape{2, 1},
+                    IN_ET,
+                    std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
+                    std::vector<T>{1, 2},
+                    std::vector<T>{1, 2, 3, 4, 5, 1, 4, 9, 16, 25, 6, 7, 8, 9, 10, 36, 49, 64, 81, 100}),
         PowerParams(ov::PartialShape{1},
-                       ov::PartialShape{1},
-                       IN_ET,
-                       std::vector<T>{2},
-                       std::vector<T>{3},
-                       std::vector<T>{8}),
+                    ov::PartialShape{1},
+                    IN_ET,
+                    std::vector<T>{2},
+                    std::vector<T>{3},
+                    std::vector<T>{8}),
         PowerParams(ov::PartialShape{2, 2},
                     ov::PartialShape{1},
                     IN_ET,
                     std::vector<T>{2, 3, 4, 5},
                     std::vector<T>{2},
-                    std::vector<T>{4, 9, 16, 25})
-    };
+                    std::vector<T>{4, 9, 16, 25})};
     return params;
 }
 
 std::vector<PowerParams> generateCombinedParamsForPower() {
-    const std::vector<std::vector<PowerParams>> allTypeParams{
-        generateParamsForPower<element::Type_t::f32>(),
-        generateParamsForPower<element::Type_t::f16>(),
-        generateParamsForPower<element::Type_t::bf16>(),
-        generateParamsForPower<element::Type_t::i64>(),
-        generateParamsForPower<element::Type_t::i32>(),
-        generateParamsForPower<element::Type_t::u64>(),
-        generateParamsForPower<element::Type_t::u32>()
-    };
+    const std::vector<std::vector<PowerParams>> allTypeParams{generateParamsForPower<element::Type_t::f32>(),
+                                                              generateParamsForPower<element::Type_t::f16>(),
+                                                              generateParamsForPower<element::Type_t::bf16>(),
+                                                              generateParamsForPower<element::Type_t::i64>(),
+                                                              generateParamsForPower<element::Type_t::i32>(),
+                                                              generateParamsForPower<element::Type_t::u64>(),
+                                                              generateParamsForPower<element::Type_t::u32>()};
 
     std::vector<PowerParams> combinedParams;
 
@@ -125,10 +124,9 @@ std::vector<PowerParams> generateCombinedParamsForPower() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Power_With_Hardcoded_Refs,
-    ReferencePowerLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForPower()),
-    ReferencePowerLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Power_With_Hardcoded_Refs,
+                         ReferencePowerLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForPower()),
+                         ReferencePowerLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/prelu.cpp b/src/plugins/template/tests/functional/op_reference/prelu.cpp
index bfc9c949decb68..98ab7d02f83e79 100644
--- a/src/plugins/template/tests/functional/op_reference/prelu.cpp
+++ b/src/plugins/template/tests/functional/op_reference/prelu.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/prelu.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/prelu.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,8 +14,13 @@ using namespace ov;
 namespace {
 struct PreluParams {
     template <class IT>
-    PreluParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
-                const ov::Shape& slopeShape, const std::vector<IT>& negativeSlopeValues, const std::string& test_name = "")
+    PreluParams(const ov::PartialShape& shape,
+                const ov::element::Type& iType,
+                const std::vector<IT>& iValues,
+                const std::vector<IT>& oValues,
+                const ov::Shape& slopeShape,
+                const std::vector<IT>& negativeSlopeValues,
+                const std::string& test_name = "")
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -59,11 +65,13 @@ class ReferencePreluLayerTest : public testing::TestWithParam<PreluParams>, publ
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const Shape& slope_shape, const element::Type& input_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const Shape& slope_shape,
+                                                 const element::Type& input_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto SLOPE = std::make_shared<op::v0::Parameter>(input_type, slope_shape);
         const auto Prelu = std::make_shared<op::v0::PRelu>(in, SLOPE);
-        return std::make_shared<ov::Model>(NodeVector {Prelu}, ParameterVector {in, SLOPE});
+        return std::make_shared<ov::Model>(NodeVector{Prelu}, ParameterVector{in, SLOPE});
     }
 };
 
@@ -75,179 +83,186 @@ template <element::Type_t IN_ET>
 std::vector<PreluParams> generatePreluFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<PreluParams> preluParams {
-        PreluParams(ov::PartialShape {6},
+    std::vector<PreluParams> preluParams{
+        PreluParams(ov::PartialShape{6},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 5, 6},
                     std::vector<T>{1, 2, -6, -8, 5, 6},
-                    ov::Shape {1},
+                    ov::Shape{1},
                     std::vector<T>{2}),
-        PreluParams(ov::PartialShape {6},
+        PreluParams(ov::PartialShape{6},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 5, 6},
                     std::vector<T>{1, 2, -12, -20, 5, 6},
-                    ov::Shape {6},
+                    ov::Shape{6},
                     std::vector<T>{2, 3, 4, 5, 6, 7}),
-        PreluParams(ov::PartialShape {3, 2},
+        PreluParams(ov::PartialShape{3, 2},
                     IN_ET,
                     std::vector<T>{-2, 3, -2, 1, -1, 0},
                     std::vector<T>{0, 3, 0, 1, 0, 0},
-                    ov::Shape {2},
+                    ov::Shape{2},
                     std::vector<T>{0, 1}),
-        PreluParams(ov::PartialShape {2, 6},
+        PreluParams(ov::PartialShape{2, 6},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 5, 6, 7, 8, -9, -10, 11, 12},
                     std::vector<T>{1, 2, -9, -16, 5, 6, 7, 8, -27, -40, 11, 12},
-                    ov::Shape {6},
+                    ov::Shape{6},
                     std::vector<T>{1, 2, 3, 4, 5, 6}),
-        PreluParams(ov::PartialShape {3, 2},
+        PreluParams(ov::PartialShape{3, 2},
                     IN_ET,
                     std::vector<T>{-1, -1, -1, -1, -1, -1},
                     std::vector<T>{-2, -0.5, -2, -0.5, -2, -0.5},
-                    ov::Shape {2},
+                    ov::Shape{2},
                     std::vector<T>{2, 0.5},
                     "C_2_const"),
-        PreluParams(ov::PartialShape {2, 2, 2},
+        PreluParams(ov::PartialShape{2, 2, 2},
                     IN_ET,
                     std::vector<T>{-0.5, -2, -3, -4, -5, -6, -7, -8},
                     std::vector<T>{0.25, 1, 6, 8, 2.5, 3, 14, 16},
-                    ov::Shape {2},
+                    ov::Shape{2},
                     std::vector<T>{-0.5, -2}),
-        PreluParams(ov::PartialShape {3, 2},
+        PreluParams(ov::PartialShape{3, 2},
                     IN_ET,
                     std::vector<T>{-2, 3, -2, 1, -1, 0},
                     std::vector<T>{1, 3, 1, 1, 0.5, 0},
-                    ov::Shape {2},
+                    ov::Shape{2},
                     std::vector<T>{-0.5, -1},
                     "negative_slope"),
-        PreluParams(ov::PartialShape {2, 6},
+        PreluParams(ov::PartialShape{2, 6},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 5, 6, 1, 2, -3, -4, 5, 6},
                     std::vector<T>{1, 2, -6, -8, 5, 6, 1, 2, -12, -8, 5, 6},
-                    ov::Shape {2, 6},
+                    ov::Shape{2, 6},
                     std::vector<T>{2, 2, 2, 2, 2, 2, 1, 1, 4, 2, 1, 1}),
-        PreluParams(ov::PartialShape {2, 2, 2, 2},
+        PreluParams(ov::PartialShape{2, 2, 2, 2},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 1, 2, -3, -4, 1, 2, -3, -4, 1, 2, -3, -4},
                     std::vector<T>{1, 2, -3, -8, 1, 2, -9, -16, 1, 2, -3, -8, 1, 2, -9, -16},
-                    ov::Shape {2, 1, 2},
+                    ov::Shape{2, 1, 2},
                     std::vector<T>{1, 2, 3, 4}),
-        PreluParams(ov::PartialShape {2, 2, 2, 2},
+        PreluParams(ov::PartialShape{2, 2, 2, 2},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 1, 2, -3, -4, 1, 2, -3, -4, 1, 2, -3, -4},
                     std::vector<T>{1, 2, -3, -8, 1, 2, -9, -16, 1, 2, -3, -8, 1, 2, -9, -16},
-                    ov::Shape {1, 2, 1, 2},
+                    ov::Shape{1, 2, 1, 2},
                     std::vector<T>{1, 2, 3, 4}),
-        PreluParams(ov::PartialShape {2, 2, 6},
-                    IN_ET,
-                    std::vector<T>{1, 2, -3, -4, -5, 6, -1, -2, -3, -4, -5, -6, 1, 2, -3, -4, 5, 6, -2, 4, -6, -8, 10, 12},
-                    std::vector<T>{1, 2, -9, -16, -5, 6, -2, -2, -9, -16, -5, -42, 1, 2, -9, -16, 5, 6, -2, 4, -18, -32, 10, 12},
-                    ov::Shape {2, 1, 6},
-                    std::vector<T>{2, 1, 3, 4, 1, 7, 1, 2, 3, 4, 5, 6}),
-        PreluParams(ov::PartialShape {2, 3, 2},
+        PreluParams(
+            ov::PartialShape{2, 2, 6},
+            IN_ET,
+            std::vector<T>{1, 2, -3, -4, -5, 6, -1, -2, -3, -4, -5, -6, 1, 2, -3, -4, 5, 6, -2, 4, -6, -8, 10, 12},
+            std::vector<T>{1, 2, -9, -16, -5, 6, -2, -2, -9,  -16, -5, -42,
+                           1, 2, -9, -16, 5,  6, -2, 4,  -18, -32, 10, 12},
+            ov::Shape{2, 1, 6},
+            std::vector<T>{2, 1, 3, 4, 1, 7, 1, 2, 3, 4, 5, 6}),
+        PreluParams(ov::PartialShape{2, 3, 2},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, -5, 6, -1, -2, -3, -4, -5, -6},
                     std::vector<T>{1, 2, -9, -16, -5, 6, -1, -4, -9, -16, -25, -36},
-                    ov::Shape {2, 3, 2},
+                    ov::Shape{2, 3, 2},
                     std::vector<T>{2, 1, 3, 4, 1, 7, 1, 2, 3, 4, 5, 6}),
-        PreluParams(ov::PartialShape {2, 1, 2},
+        PreluParams(ov::PartialShape{2, 1, 2},
                     IN_ET,
                     std::vector<T>{-10, -10, -10, -10},
                     std::vector<T>{-1, -100, -1, -100},
-                    ov::Shape {2},
+                    ov::Shape{2},
                     std::vector<T>{0.1, 10}),
-        PreluParams(ov::PartialShape {1, 2, 1, 2},
+        PreluParams(ov::PartialShape{1, 2, 1, 2},
                     IN_ET,
                     std::vector<T>{-10, -10, -10, -10},
                     std::vector<T>{-1, -1, -100, -100},
-                    ov::Shape {2},
+                    ov::Shape{2},
                     std::vector<T>{0.1, 10}),
-        PreluParams(ov::PartialShape {1, 5, 1, 1},
+        PreluParams(ov::PartialShape{1, 5, 1, 1},
                     IN_ET,
                     std::vector<T>{-1, 0, -1, -1, -1},
                     std::vector<T>{-1, 0, -3, -4, -5},
-                    ov::Shape {5},
+                    ov::Shape{5},
                     std::vector<T>{1, 2, 3, 4, 5}),
-        PreluParams(ov::PartialShape {2, 3, 4, 5},
-                    IN_ET,
-                    std::vector<T>{-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.},
-                    std::vector<T>{-0.,   -1.,   -2.,   -3.,   -4.,   -5.,   -6.,   -7.,   -8.,   -9.,   -10.,  -11.,  -12.,  -13.,  -14.,
-                                   -15.,  -16.,  -17.,  -18.,  -19.,  -20.,  -21.,  -22.,  -23.,  -24.,  -25.,  -26.,  -27.,  -28.,  -29.,
-                                   -30.,  -31.,  -32.,  -33.,  -34.,  -35.,  -36.,  -37.,  -38.,  -39.,  -40.,  -41.,  -42.,  -43.,  -44.,
-                                   -45.,  -46.,  -47.,  -48.,  -49.,  -50.,  -51.,  -52.,  -53.,  -54.,  -55.,  -56.,  -57.,  -58.,  -59.,
-                                   -60.,  -61.,  -62.,  -63.,  -64.,  -65.,  -66.,  -67.,  -68.,  -69.,  -70.,  -71.,  -72.,  -73.,  -74.,
-                                   -75.,  -76.,  -77.,  -78.,  -79.,  -80.,  -81.,  -82.,  -83.,  -84.,  -85.,  -86.,  -87.,  -88.,  -89.,
-                                   -90.,  -91.,  -92.,  -93.,  -94.,  -95.,  -96.,  -97.,  -98.,  -99.,  -100., -101., -102., -103., -104.,
-                                   -105., -106., -107., -108., -109., -110., -111., -112., -113., -114., -115., -116., -117., -118., -119.},
-                    ov::Shape {2, 3, 4, 5},
-                    std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
-                                   18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
-                                   36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
-                                   54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
-                                   72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
-                                   90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107,
-                                   108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}),
-        PreluParams(ov::PartialShape {2, 3, 4, 5},
-                    IN_ET,
-                    std::vector<T>{-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.},
-                    std::vector<T>{-0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2.,
-                                   -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0.,
-                                   -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3.,
-                                   -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1.,
-                                   -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4.,
-                                   -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2.,
-                                   -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4.},
-                    ov::Shape {5},
-                    std::vector<T>{0, 1, 2, 3, 4}),
-        PreluParams(ov::PartialShape {2, 3, 4, 5},
-                    IN_ET,
-                    std::vector<T>{-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.},
-                    std::vector<T>{-0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0.,
-                                   -0., -0., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2.,
-                                   -2., -2., -2., -2., -2., -2., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0.,
-                                   -0., -0., -0., -0., -0., -0., -0., -0., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -2., -2., -2., -2., -2., -2., -2., -2.,
-                                   -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2.},
-                    ov::Shape {3},
-                    std::vector<T>{0, 1, 2}),
-        PreluParams(ov::PartialShape {2, 3, 4, 5},
-                    IN_ET,
-                    std::vector<T>{-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.},
-                    std::vector<T>{-0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0.,
-                                   -0., -0., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2.,
-                                   -2., -2., -2., -2., -2., -2., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0.,
-                                   -0., -0., -0., -0., -0., -0., -0., -0., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
-                                   -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -2., -2., -2., -2., -2., -2., -2., -2.,
-                                   -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2.},
-                    ov::Shape {3, 1, 1},
-                    std::vector<T>{0, 1, 2})
-    };
+        PreluParams(
+            ov::PartialShape{2, 3, 4, 5},
+            IN_ET,
+            std::vector<T>{-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.},
+            std::vector<T>{-0.,   -1.,   -2.,   -3.,   -4.,   -5.,   -6.,   -7.,   -8.,   -9.,   -10.,  -11.,
+                           -12.,  -13.,  -14.,  -15.,  -16.,  -17.,  -18.,  -19.,  -20.,  -21.,  -22.,  -23.,
+                           -24.,  -25.,  -26.,  -27.,  -28.,  -29.,  -30.,  -31.,  -32.,  -33.,  -34.,  -35.,
+                           -36.,  -37.,  -38.,  -39.,  -40.,  -41.,  -42.,  -43.,  -44.,  -45.,  -46.,  -47.,
+                           -48.,  -49.,  -50.,  -51.,  -52.,  -53.,  -54.,  -55.,  -56.,  -57.,  -58.,  -59.,
+                           -60.,  -61.,  -62.,  -63.,  -64.,  -65.,  -66.,  -67.,  -68.,  -69.,  -70.,  -71.,
+                           -72.,  -73.,  -74.,  -75.,  -76.,  -77.,  -78.,  -79.,  -80.,  -81.,  -82.,  -83.,
+                           -84.,  -85.,  -86.,  -87.,  -88.,  -89.,  -90.,  -91.,  -92.,  -93.,  -94.,  -95.,
+                           -96.,  -97.,  -98.,  -99.,  -100., -101., -102., -103., -104., -105., -106., -107.,
+                           -108., -109., -110., -111., -112., -113., -114., -115., -116., -117., -118., -119.},
+            ov::Shape{2, 3, 4, 5},
+            std::vector<T>{0,   1,   2,   3,   4,   5,   6,   7,   8,   9,   10,  11,  12,  13,  14,  15,  16,  17,
+                           18,  19,  20,  21,  22,  23,  24,  25,  26,  27,  28,  29,  30,  31,  32,  33,  34,  35,
+                           36,  37,  38,  39,  40,  41,  42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,
+                           54,  55,  56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,  70,  71,
+                           72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,  84,  85,  86,  87,  88,  89,
+                           90,  91,  92,  93,  94,  95,  96,  97,  98,  99,  100, 101, 102, 103, 104, 105, 106, 107,
+                           108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}),
+        PreluParams(
+            ov::PartialShape{2, 3, 4, 5},
+            IN_ET,
+            std::vector<T>{-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.},
+            std::vector<T>{-0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2.,
+                           -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0.,
+                           -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3.,
+                           -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1.,
+                           -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4.,
+                           -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4., -0., -1., -2.,
+                           -3., -4., -0., -1., -2., -3., -4., -0., -1., -2., -3., -4.},
+            ov::Shape{5},
+            std::vector<T>{0, 1, 2, 3, 4}),
+        PreluParams(
+            ov::PartialShape{2, 3, 4, 5},
+            IN_ET,
+            std::vector<T>{-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.},
+            std::vector<T>{-0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0.,
+                           -0., -0., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2.,
+                           -2., -2., -2., -2., -2., -2., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0.,
+                           -0., -0., -0., -0., -0., -0., -0., -0., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -2., -2., -2., -2., -2., -2., -2., -2.,
+                           -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2.},
+            ov::Shape{3},
+            std::vector<T>{0, 1, 2}),
+        PreluParams(
+            ov::PartialShape{2, 3, 4, 5},
+            IN_ET,
+            std::vector<T>{-1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.},
+            std::vector<T>{-0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0.,
+                           -0., -0., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2.,
+                           -2., -2., -2., -2., -2., -2., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0., -0.,
+                           -0., -0., -0., -0., -0., -0., -0., -0., -1., -1., -1., -1., -1., -1., -1., -1., -1., -1.,
+                           -1., -1., -1., -1., -1., -1., -1., -1., -1., -1., -2., -2., -2., -2., -2., -2., -2., -2.,
+                           -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2., -2.},
+            ov::Shape{3, 1, 1},
+            std::vector<T>{0, 1, 2})};
     return preluParams;
 }
 
@@ -255,157 +270,150 @@ template <element::Type_t IN_ET>
 std::vector<PreluParams> generatePreluI8Params() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<PreluParams> preluParams {
-        PreluParams(ov::PartialShape {6},
+    std::vector<PreluParams> preluParams{
+        PreluParams(ov::PartialShape{6},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 5, 6},
                     std::vector<T>{1, 2, -6, -8, 5, 6},
-                    ov::Shape {1},
+                    ov::Shape{1},
                     std::vector<T>{2}),
-        PreluParams(ov::PartialShape {6},
+        PreluParams(ov::PartialShape{6},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 5, 6},
                     std::vector<T>{1, 2, -12, -20, 5, 6},
-                    ov::Shape {6},
+                    ov::Shape{6},
                     std::vector<T>{2, 3, 4, 5, 6, 7}),
-        PreluParams(ov::PartialShape {3, 2},
+        PreluParams(ov::PartialShape{3, 2},
                     IN_ET,
                     std::vector<T>{-2, 3, -2, 1, -1, 0},
                     std::vector<T>{0, 3, 0, 1, 0, 0},
-                    ov::Shape {2},
+                    ov::Shape{2},
                     std::vector<T>{0, 1}),
-        PreluParams(ov::PartialShape {2, 6},
+        PreluParams(ov::PartialShape{2, 6},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 5, 6, 7, 8, -9, -10, 11, 12},
                     std::vector<T>{1, 2, -9, -16, 5, 6, 7, 8, -27, -40, 11, 12},
-                    ov::Shape {6},
+                    ov::Shape{6},
                     std::vector<T>{1, 2, 3, 4, 5, 6}),
-        PreluParams(ov::PartialShape {2, 6},
+        PreluParams(ov::PartialShape{2, 6},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 5, 6, 1, 2, -3, -4, 5, 6},
                     std::vector<T>{1, 2, -6, -8, 5, 6, 1, 2, -12, -8, 5, 6},
-                    ov::Shape {2, 6},
+                    ov::Shape{2, 6},
                     std::vector<T>{2, 2, 2, 2, 2, 2, 1, 1, 4, 2, 1, 1}),
-        PreluParams(ov::PartialShape {2, 2, 2, 2},
+        PreluParams(ov::PartialShape{2, 2, 2, 2},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 1, 2, -3, -4, 1, 2, -3, -4, 1, 2, -3, -4},
                     std::vector<T>{1, 2, -3, -8, 1, 2, -9, -16, 1, 2, -3, -8, 1, 2, -9, -16},
-                    ov::Shape {2, 1, 2},
+                    ov::Shape{2, 1, 2},
                     std::vector<T>{1, 2, 3, 4}),
-        PreluParams(ov::PartialShape {2, 2, 2, 2},
+        PreluParams(ov::PartialShape{2, 2, 2, 2},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, 1, 2, -3, -4, 1, 2, -3, -4, 1, 2, -3, -4},
                     std::vector<T>{1, 2, -3, -8, 1, 2, -9, -16, 1, 2, -3, -8, 1, 2, -9, -16},
-                    ov::Shape {1, 2, 1, 2},
+                    ov::Shape{1, 2, 1, 2},
                     std::vector<T>{1, 2, 3, 4}),
-        PreluParams(ov::PartialShape {2, 2, 6},
-                    IN_ET,
-                    std::vector<T>{1, 2, -3, -4, -5, 6, -1, -2, -3, -4, -5, -6, 1, 2, -3, -4, 5, 6, -2, 4, -6, -8, 10, 12},
-                    std::vector<T>{1, 2, -9, -16, -5, 6, -2, -2, -9, -16, -5, -42, 1, 2, -9, -16, 5, 6, -2, 4, -18, -32, 10, 12},
-                    ov::Shape {2, 1, 6},
-                    std::vector<T>{2, 1, 3, 4, 1, 7, 1, 2, 3, 4, 5, 6}),
-        PreluParams(ov::PartialShape {2, 3, 2},
+        PreluParams(
+            ov::PartialShape{2, 2, 6},
+            IN_ET,
+            std::vector<T>{1, 2, -3, -4, -5, 6, -1, -2, -3, -4, -5, -6, 1, 2, -3, -4, 5, 6, -2, 4, -6, -8, 10, 12},
+            std::vector<T>{1, 2, -9, -16, -5, 6, -2, -2, -9,  -16, -5, -42,
+                           1, 2, -9, -16, 5,  6, -2, 4,  -18, -32, 10, 12},
+            ov::Shape{2, 1, 6},
+            std::vector<T>{2, 1, 3, 4, 1, 7, 1, 2, 3, 4, 5, 6}),
+        PreluParams(ov::PartialShape{2, 3, 2},
                     IN_ET,
                     std::vector<T>{1, 2, -3, -4, -5, 6, -1, -2, -3, -4, -5, -6},
                     std::vector<T>{1, 2, -9, -16, -5, 6, -1, -4, -9, -16, -25, -36},
-                    ov::Shape {2, 3, 2},
+                    ov::Shape{2, 3, 2},
                     std::vector<T>{2, 1, 3, 4, 1, 7, 1, 2, 3, 4, 5, 6}),
-        PreluParams(ov::PartialShape {1, 5, 1, 1},
+        PreluParams(ov::PartialShape{1, 5, 1, 1},
                     IN_ET,
                     std::vector<T>{-1, 0, -1, -1, -1},
                     std::vector<T>{-1, 0, -3, -4, -5},
-                    ov::Shape {5},
+                    ov::Shape{5},
                     std::vector<T>{1, 2, 3, 4, 5}),
-        PreluParams(ov::PartialShape {2, 3, 4, 5},
-                    IN_ET,
-                    std::vector<T>{-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
-                    std::vector<T>{-0,   -1,   -2,   -3,   -4,   -5,   -6,   -7,   -8,   -9,   -10,  -11,  -12,  -13,  -14,
-                                   -15,  -16,  -17,  -18,  -19,  -20,  -21,  -22,  -23,  -24,  -25,  -26,  -27,  -28,  -29,
-                                   -30,  -31,  -32,  -33,  -34,  -35,  -36,  -37,  -38,  -39,  -40,  -41,  -42,  -43,  -44,
-                                   -45,  -46,  -47,  -48,  -49,  -50,  -51,  -52,  -53,  -54,  -55,  -56,  -57,  -58,  -59,
-                                   -60,  -61,  -62,  -63,  -64,  -65,  -66,  -67,  -68,  -69,  -70,  -71,  -72,  -73,  -74,
-                                   -75,  -76,  -77,  -78,  -79,  -80,  -81,  -82,  -83,  -84,  -85,  -86,  -87,  -88,  -89,
-                                   -90,  -91,  -92,  -93,  -94,  -95,  -96,  -97,  -98,  -99,  -100, -101, -102, -103, -104,
-                                   -105, -106, -107, -108, -109, -110, -111, -112, -113, -114, -115, -116, -117, -118, -119},
-                    ov::Shape {2, 3, 4, 5},
-                    std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
-                                   18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
-                                   36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,
-                                   54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,
-                                   72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,
-                                   90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107,
-                                   108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}),
-        PreluParams(ov::PartialShape {2, 3, 4, 5},
-                    IN_ET,
-                    std::vector<T>{-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
-                    std::vector<T>{-0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2,
-                                   -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0,
-                                   -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3,
-                                   -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1,
-                                   -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4,
-                                   -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2,
-                                   -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4},
-                    ov::Shape {5},
+        PreluParams(
+            ov::PartialShape{2, 3, 4, 5},
+            IN_ET,
+            std::vector<T>{-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                           -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                           -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                           -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                           -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                           -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
+            std::vector<T>{-0,   -1,   -2,   -3,   -4,   -5,   -6,   -7,   -8,   -9,   -10,  -11,  -12,  -13,  -14,
+                           -15,  -16,  -17,  -18,  -19,  -20,  -21,  -22,  -23,  -24,  -25,  -26,  -27,  -28,  -29,
+                           -30,  -31,  -32,  -33,  -34,  -35,  -36,  -37,  -38,  -39,  -40,  -41,  -42,  -43,  -44,
+                           -45,  -46,  -47,  -48,  -49,  -50,  -51,  -52,  -53,  -54,  -55,  -56,  -57,  -58,  -59,
+                           -60,  -61,  -62,  -63,  -64,  -65,  -66,  -67,  -68,  -69,  -70,  -71,  -72,  -73,  -74,
+                           -75,  -76,  -77,  -78,  -79,  -80,  -81,  -82,  -83,  -84,  -85,  -86,  -87,  -88,  -89,
+                           -90,  -91,  -92,  -93,  -94,  -95,  -96,  -97,  -98,  -99,  -100, -101, -102, -103, -104,
+                           -105, -106, -107, -108, -109, -110, -111, -112, -113, -114, -115, -116, -117, -118, -119},
+            ov::Shape{2, 3, 4, 5},
+            std::vector<T>{0,   1,   2,   3,   4,   5,   6,   7,   8,   9,   10,  11,  12,  13,  14,  15,  16,  17,
+                           18,  19,  20,  21,  22,  23,  24,  25,  26,  27,  28,  29,  30,  31,  32,  33,  34,  35,
+                           36,  37,  38,  39,  40,  41,  42,  43,  44,  45,  46,  47,  48,  49,  50,  51,  52,  53,
+                           54,  55,  56,  57,  58,  59,  60,  61,  62,  63,  64,  65,  66,  67,  68,  69,  70,  71,
+                           72,  73,  74,  75,  76,  77,  78,  79,  80,  81,  82,  83,  84,  85,  86,  87,  88,  89,
+                           90,  91,  92,  93,  94,  95,  96,  97,  98,  99,  100, 101, 102, 103, 104, 105, 106, 107,
+                           108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119}),
+        PreluParams(ov::PartialShape{2, 3, 4, 5},
+                    IN_ET,
+                    std::vector<T>{-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
+                    std::vector<T>{-0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4,
+                                   -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4,
+                                   -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4,
+                                   -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4,
+                                   -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4,
+                                   -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4, -0, -1, -2, -3, -4},
+                    ov::Shape{5},
                     std::vector<T>{0, 1, 2, 3, 4}),
-        PreluParams(ov::PartialShape {2, 3, 4, 5},
-                    IN_ET,
-                    std::vector<T>{-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
-                    std::vector<T>{-0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0,
-                                   -0, -0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2,
-                                   -2, -2, -2, -2, -2, -2, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0,
-                                   -0, -0, -0, -0, -0, -0, -0, -0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -2, -2, -2, -2, -2, -2, -2, -2,
-                                   -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2},
-                    ov::Shape {3},
+        PreluParams(ov::PartialShape{2, 3, 4, 5},
+                    IN_ET,
+                    std::vector<T>{-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
+                    std::vector<T>{-0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2,
+                                   -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2},
+                    ov::Shape{3},
                     std::vector<T>{0, 1, 2}),
-        PreluParams(ov::PartialShape {2, 3, 4, 5},
-                    IN_ET,
-                    std::vector<T>{-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
-                    std::vector<T>{-0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0,
-                                   -0, -0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2,
-                                   -2, -2, -2, -2, -2, -2, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0,
-                                   -0, -0, -0, -0, -0, -0, -0, -0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
-                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -2, -2, -2, -2, -2, -2, -2, -2,
-                                   -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2},
-                    ov::Shape {3, 1, 1},
-                    std::vector<T>{0, 1, 2})
-    };
+        PreluParams(ov::PartialShape{2, 3, 4, 5},
+                    IN_ET,
+                    std::vector<T>{-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1},
+                    std::vector<T>{-0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2,
+                                   -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0, -0,
+                                   -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1,
+                                   -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2, -2},
+                    ov::Shape{3, 1, 1},
+                    std::vector<T>{0, 1, 2})};
     return preluParams;
 }
 
 std::vector<PreluParams> generatePreluCombinedParams() {
-    const std::vector<std::vector<PreluParams>> preluTypeParams {
-        generatePreluFloatParams<element::Type_t::f32>(),
-        generatePreluFloatParams<element::Type_t::f16>(),
-        generatePreluFloatParams<element::Type_t::bf16>(),
-        generatePreluI8Params<element::Type_t::i8>()
-        };
+    const std::vector<std::vector<PreluParams>> preluTypeParams{generatePreluFloatParams<element::Type_t::f32>(),
+                                                                generatePreluFloatParams<element::Type_t::f16>(),
+                                                                generatePreluFloatParams<element::Type_t::bf16>(),
+                                                                generatePreluI8Params<element::Type_t::i8>()};
     std::vector<PreluParams> combinedParams;
 
     for (const auto& params : preluTypeParams) {
@@ -414,7 +422,9 @@ std::vector<PreluParams> generatePreluCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Prelu_With_Hardcoded_Refs, ReferencePreluLayerTest,
-    testing::ValuesIn(generatePreluCombinedParams()), ReferencePreluLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Prelu_With_Hardcoded_Refs,
+                         ReferencePreluLayerTest,
+                         testing::ValuesIn(generatePreluCombinedParams()),
+                         ReferencePreluLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/prior_box_clustered.cpp b/src/plugins/template/tests/functional/op_reference/prior_box_clustered.cpp
index cecf1055276cfc..9097c3a2019f8b 100644
--- a/src/plugins/template/tests/functional/op_reference/prior_box_clustered.cpp
+++ b/src/plugins/template/tests/functional/op_reference/prior_box_clustered.cpp
@@ -4,8 +4,8 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/op/prior_box.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/prior_box.hpp"
 #include "openvino/opsets/opset1.hpp"
 
 using namespace reference_tests;
@@ -17,9 +17,11 @@ struct PriorBoxClusteredParams {
     PriorBoxClusteredParams(const std::vector<float>& widths,
                             const std::vector<float>& heights,
                             const bool clip,
-                            const ov::Shape& layerShapeShape, const ov::Shape& imageShapeShape,
+                            const ov::Shape& layerShapeShape,
+                            const ov::Shape& imageShapeShape,
                             const ov::element::Type& iType,
-                            const std::vector<IT>& layerShapeValues, const std::vector<IT>& imageShapeValues,
+                            const std::vector<IT>& layerShapeValues,
+                            const std::vector<IT>& imageShapeValues,
                             const std::vector<float>& oValues,
                             const std::vector<float>& variances = {},
                             const std::string& testcaseName = "")
@@ -31,12 +33,12 @@ struct PriorBoxClusteredParams {
           imageShapeData(CreateTensor(iType, imageShapeValues)),
           refData(CreateTensor(outType, oValues)),
           testcaseName(testcaseName) {
-              attrs.widths = widths;
-              attrs.heights = heights;
-              attrs.clip = clip;
-              if ( variances.size() != 0)
-                attrs.variances = variances;
-          }
+        attrs.widths = widths;
+        attrs.heights = heights;
+        attrs.clip = clip;
+        if (variances.size() != 0)
+            attrs.variances = variances;
+    }
 
     ov::op::v0::PriorBoxClustered::Attributes attrs;
     ov::Shape layerShapeShape;
@@ -49,7 +51,8 @@ struct PriorBoxClusteredParams {
     std::string testcaseName;
 };
 
-class ReferencePriorBoxClusteredLayerTest : public testing::TestWithParam<PriorBoxClusteredParams>, public CommonReferenceTest {
+class ReferencePriorBoxClusteredLayerTest : public testing::TestWithParam<PriorBoxClusteredParams>,
+                                            public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -72,10 +75,12 @@ class ReferencePriorBoxClusteredLayerTest : public testing::TestWithParam<PriorB
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PriorBoxClusteredParams& params) {
-        auto LS = std::make_shared<opset1::Constant>(params.inType, params.layerShapeShape, params.layerShapeData.data());
-        auto IS = std::make_shared<opset1::Constant>(params.inType, params.imageShapeShape, params.imageShapeData.data());
+        auto LS =
+            std::make_shared<opset1::Constant>(params.inType, params.layerShapeShape, params.layerShapeData.data());
+        auto IS =
+            std::make_shared<opset1::Constant>(params.inType, params.imageShapeShape, params.imageShapeData.data());
         const auto PriorBoxClustered = std::make_shared<op::v0::PriorBoxClustered>(LS, IS, params.attrs);
-        return std::make_shared<ov::Model>(NodeVector {PriorBoxClustered}, ParameterVector {});
+        return std::make_shared<ov::Model>(NodeVector{PriorBoxClustered}, ParameterVector{});
     }
 };
 
@@ -87,30 +92,40 @@ template <element::Type_t IN_ET>
 std::vector<PriorBoxClusteredParams> generatePriorBoxClusteredFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<PriorBoxClusteredParams> priorBoxClusteredParams {
-        PriorBoxClusteredParams({3.0f}, {3.0f}, true,
-                       {2}, {2},
-                       IN_ET,
-                       std::vector<T>{2, 2},
-                       std::vector<T>{10, 10},
-                       std::vector<float>{0,        0,        0.15f,    0.15f,    0.34999f, 0,    0.64999f, 0.15f, 0,    0.34999f, 0.15f,
-                                          0.64999f, 0.34999f, 0.34999f, 0.64999f, 0.64999f, 0.1f, 0.1f,     0.1f,  0.1f, 0.1f,     0.1f,
-                                          0.1f,     0.1f,     0.1f,     0.1f,     0.1f,     0.1f, 0.1f,     0.1f,  0.1f, 0.1f}),
-        PriorBoxClusteredParams({3.0f}, {3.0f}, true,
-                       {2}, {2},
-                       IN_ET,
-                       std::vector<T>{2, 2},
-                       std::vector<T>{10, 10},
-                       std::vector<float>{0,        0,        0.15f,    0.15f,    0.34999f, 0,    0.64999f, 0.15f, 0,    0.34999f, 0.15f,
-                                          0.64999f, 0.34999f, 0.34999f, 0.64999f, 0.64999f, 0.1f, 0.2f,     0.3f,  0.4f, 0.1f,     0.2f,
-                                          0.3f,     0.4f,     0.1f,     0.2f,     0.3f,     0.4f, 0.1f,     0.2f,  0.3f, 0.4f},
-                       {0.1f, 0.2f, 0.3f, 0.4f}),
+    std::vector<PriorBoxClusteredParams> priorBoxClusteredParams{
+        PriorBoxClusteredParams(
+            {3.0f},
+            {3.0f},
+            true,
+            {2},
+            {2},
+            IN_ET,
+            std::vector<T>{2, 2},
+            std::vector<T>{10, 10},
+            std::vector<float>{0,    0,        0.15f, 0.15f,    0.34999f, 0,        0.64999f, 0.15f,
+                               0,    0.34999f, 0.15f, 0.64999f, 0.34999f, 0.34999f, 0.64999f, 0.64999f,
+                               0.1f, 0.1f,     0.1f,  0.1f,     0.1f,     0.1f,     0.1f,     0.1f,
+                               0.1f, 0.1f,     0.1f,  0.1f,     0.1f,     0.1f,     0.1f,     0.1f}),
+        PriorBoxClusteredParams(
+            {3.0f},
+            {3.0f},
+            true,
+            {2},
+            {2},
+            IN_ET,
+            std::vector<T>{2, 2},
+            std::vector<T>{10, 10},
+            std::vector<float>{0,    0,        0.15f, 0.15f,    0.34999f, 0,        0.64999f, 0.15f,
+                               0,    0.34999f, 0.15f, 0.64999f, 0.34999f, 0.34999f, 0.64999f, 0.64999f,
+                               0.1f, 0.2f,     0.3f,  0.4f,     0.1f,     0.2f,     0.3f,     0.4f,
+                               0.1f, 0.2f,     0.3f,  0.4f,     0.1f,     0.2f,     0.3f,     0.4f},
+            {0.1f, 0.2f, 0.3f, 0.4f}),
     };
     return priorBoxClusteredParams;
 }
 
 std::vector<PriorBoxClusteredParams> generatePriorBoxClusteredCombinedParams() {
-    const std::vector<std::vector<PriorBoxClusteredParams>> priorBoxClusteredTypeParams {
+    const std::vector<std::vector<PriorBoxClusteredParams>> priorBoxClusteredTypeParams{
         generatePriorBoxClusteredFloatParams<element::Type_t::i64>(),
         generatePriorBoxClusteredFloatParams<element::Type_t::i32>(),
         generatePriorBoxClusteredFloatParams<element::Type_t::i16>(),
@@ -119,7 +134,7 @@ std::vector<PriorBoxClusteredParams> generatePriorBoxClusteredCombinedParams() {
         generatePriorBoxClusteredFloatParams<element::Type_t::u32>(),
         generatePriorBoxClusteredFloatParams<element::Type_t::u16>(),
         generatePriorBoxClusteredFloatParams<element::Type_t::u8>(),
-        };
+    };
     std::vector<PriorBoxClusteredParams> combinedParams;
 
     for (const auto& params : priorBoxClusteredTypeParams) {
@@ -128,7 +143,9 @@ std::vector<PriorBoxClusteredParams> generatePriorBoxClusteredCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_PriorBoxClustered_With_Hardcoded_Refs, ReferencePriorBoxClusteredLayerTest,
-    testing::ValuesIn(generatePriorBoxClusteredCombinedParams()), ReferencePriorBoxClusteredLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_PriorBoxClustered_With_Hardcoded_Refs,
+                         ReferencePriorBoxClusteredLayerTest,
+                         testing::ValuesIn(generatePriorBoxClusteredCombinedParams()),
+                         ReferencePriorBoxClusteredLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/proposal.cpp b/src/plugins/template/tests/functional/op_reference/proposal.cpp
index 119d29b03e5b8a..431ded8ca1a5a7 100644
--- a/src/plugins/template/tests/functional/op_reference/proposal.cpp
+++ b/src/plugins/template/tests/functional/op_reference/proposal.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/proposal.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/proposal.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -14,58 +15,58 @@ namespace {
 struct ProposalV1Params {
     template <class IT>
     ProposalV1Params(const float iou_threshold,
-               const int min_bbox_size,
-               const int feature_stride,
-               const int pre_nms_topn,
-               const int post_nms_topn,
-               const size_t image_shape_num,
-               const size_t image_h,
-               const size_t image_w,
-               const size_t image_z,
-               const std::vector<float>& ratios,
-               const std::vector<float>& scales,
-               const size_t batch_size,
-               const size_t anchor_num,
-               const size_t feat_map_height,
-               const size_t feat_map_width,
-               const ov::element::Type& iType,
-               const std::vector<IT>& clsScoreValues,
-               const std::vector<IT>& bboxPredValues,
-               const std::vector<IT>& proposalValues,
-               const std::string& test_name = "")
+                     const int min_bbox_size,
+                     const int feature_stride,
+                     const int pre_nms_topn,
+                     const int post_nms_topn,
+                     const size_t image_shape_num,
+                     const size_t image_h,
+                     const size_t image_w,
+                     const size_t image_z,
+                     const std::vector<float>& ratios,
+                     const std::vector<float>& scales,
+                     const size_t batch_size,
+                     const size_t anchor_num,
+                     const size_t feat_map_height,
+                     const size_t feat_map_width,
+                     const ov::element::Type& iType,
+                     const std::vector<IT>& clsScoreValues,
+                     const std::vector<IT>& bboxPredValues,
+                     const std::vector<IT>& proposalValues,
+                     const std::string& test_name = "")
         : inType(iType),
           outType(iType),
           clsScoreData(CreateTensor(iType, clsScoreValues)),
           bboxPredData(CreateTensor(iType, bboxPredValues)),
           refProposalData(CreateTensor(iType, proposalValues)),
           testcaseName(test_name) {
-              clsScoreShape = Shape{batch_size, anchor_num * 2, feat_map_height, feat_map_width};
-              bboxPredShape = Shape{batch_size, anchor_num * 4, feat_map_height, feat_map_width};
-              imageShapeShape = Shape{image_shape_num};
+        clsScoreShape = Shape{batch_size, anchor_num * 2, feat_map_height, feat_map_width};
+        bboxPredShape = Shape{batch_size, anchor_num * 4, feat_map_height, feat_map_width};
+        imageShapeShape = Shape{image_shape_num};
 
-              attrs.base_size = min_bbox_size;
-              attrs.min_size = min_bbox_size;
-              attrs.pre_nms_topn = pre_nms_topn;
-              attrs.post_nms_topn = post_nms_topn;
-              attrs.nms_thresh = iou_threshold;
-              attrs.feat_stride = feature_stride;
-              attrs.min_size = min_bbox_size;
-              attrs.ratio = ratios;
-              attrs.scale = scales;
-              attrs.clip_before_nms = true;
-              attrs.clip_after_nms = false;
-              attrs.normalize = false;
-              attrs.box_size_scale = 1.0f;
-              attrs.box_coordinate_scale = 1.0f;
-              attrs.framework = "";
-              attrs.infer_probs = false;
+        attrs.base_size = min_bbox_size;
+        attrs.min_size = min_bbox_size;
+        attrs.pre_nms_topn = pre_nms_topn;
+        attrs.post_nms_topn = post_nms_topn;
+        attrs.nms_thresh = iou_threshold;
+        attrs.feat_stride = feature_stride;
+        attrs.min_size = min_bbox_size;
+        attrs.ratio = ratios;
+        attrs.scale = scales;
+        attrs.clip_before_nms = true;
+        attrs.clip_after_nms = false;
+        attrs.normalize = false;
+        attrs.box_size_scale = 1.0f;
+        attrs.box_coordinate_scale = 1.0f;
+        attrs.framework = "";
+        attrs.infer_probs = false;
 
-              std::vector<IT> inputShapeValues;
-              inputShapeValues.push_back(static_cast<IT>(image_h));
-              inputShapeValues.push_back(static_cast<IT>(image_w));
-              inputShapeValues.push_back(static_cast<IT>(image_z));
-              imageShapeData = CreateTensor(iType, inputShapeValues);
-          }
+        std::vector<IT> inputShapeValues;
+        inputShapeValues.push_back(static_cast<IT>(image_h));
+        inputShapeValues.push_back(static_cast<IT>(image_w));
+        inputShapeValues.push_back(static_cast<IT>(image_z));
+        imageShapeData = CreateTensor(iType, inputShapeValues);
+    }
 
     ov::op::v0::Proposal::Attributes attrs;
     ov::PartialShape clsScoreShape;
@@ -83,26 +84,26 @@ struct ProposalV1Params {
 struct ProposalV4Params {
     template <class IT>
     ProposalV4Params(const float iou_threshold,
-               const int min_bbox_size,
-               const int feature_stride,
-               const int pre_nms_topn,
-               const int post_nms_topn,
-               const size_t image_shape_num,
-               const size_t image_h,
-               const size_t image_w,
-               const size_t image_z,
-               const std::vector<float>& ratios,
-               const std::vector<float>& scales,
-               const size_t batch_size,
-               const size_t anchor_num,
-               const size_t feat_map_height,
-               const size_t feat_map_width,
-               const ov::element::Type& iType,
-               const std::vector<IT>& clsScoreValues,
-               const std::vector<IT>& bboxPredValues,
-               const std::vector<IT>& proposalValues,
-               const std::vector<IT>& probsValues,
-               const std::string& test_name = "")
+                     const int min_bbox_size,
+                     const int feature_stride,
+                     const int pre_nms_topn,
+                     const int post_nms_topn,
+                     const size_t image_shape_num,
+                     const size_t image_h,
+                     const size_t image_w,
+                     const size_t image_z,
+                     const std::vector<float>& ratios,
+                     const std::vector<float>& scales,
+                     const size_t batch_size,
+                     const size_t anchor_num,
+                     const size_t feat_map_height,
+                     const size_t feat_map_width,
+                     const ov::element::Type& iType,
+                     const std::vector<IT>& clsScoreValues,
+                     const std::vector<IT>& bboxPredValues,
+                     const std::vector<IT>& proposalValues,
+                     const std::vector<IT>& probsValues,
+                     const std::string& test_name = "")
         : inType(iType),
           outType(iType),
           clsScoreData(CreateTensor(iType, clsScoreValues)),
@@ -110,33 +111,33 @@ struct ProposalV4Params {
           refProposalData(CreateTensor(iType, proposalValues)),
           refProbsData(CreateTensor(iType, probsValues)),
           testcaseName(test_name) {
-              clsScoreShape = Shape{batch_size, anchor_num * 2, feat_map_height, feat_map_width};
-              bboxPredShape = Shape{batch_size, anchor_num * 4, feat_map_height, feat_map_width};
-              imageShapeShape = Shape{image_shape_num};
+        clsScoreShape = Shape{batch_size, anchor_num * 2, feat_map_height, feat_map_width};
+        bboxPredShape = Shape{batch_size, anchor_num * 4, feat_map_height, feat_map_width};
+        imageShapeShape = Shape{image_shape_num};
 
-              attrs.base_size = min_bbox_size;
-              attrs.min_size = min_bbox_size;
-              attrs.pre_nms_topn = pre_nms_topn;
-              attrs.post_nms_topn = post_nms_topn;
-              attrs.nms_thresh = iou_threshold;
-              attrs.feat_stride = feature_stride;
-              attrs.min_size = min_bbox_size;
-              attrs.ratio = ratios;
-              attrs.scale = scales;
-              attrs.clip_before_nms = true;
-              attrs.clip_after_nms = false;
-              attrs.normalize = false;
-              attrs.box_size_scale = 1.0f;
-              attrs.box_coordinate_scale = 1.0f;
-              attrs.framework = "";
-              attrs.infer_probs = true;
+        attrs.base_size = min_bbox_size;
+        attrs.min_size = min_bbox_size;
+        attrs.pre_nms_topn = pre_nms_topn;
+        attrs.post_nms_topn = post_nms_topn;
+        attrs.nms_thresh = iou_threshold;
+        attrs.feat_stride = feature_stride;
+        attrs.min_size = min_bbox_size;
+        attrs.ratio = ratios;
+        attrs.scale = scales;
+        attrs.clip_before_nms = true;
+        attrs.clip_after_nms = false;
+        attrs.normalize = false;
+        attrs.box_size_scale = 1.0f;
+        attrs.box_coordinate_scale = 1.0f;
+        attrs.framework = "";
+        attrs.infer_probs = true;
 
-              std::vector<IT> inputShapeValues;
-              inputShapeValues.push_back(static_cast<IT>(image_h));
-              inputShapeValues.push_back(static_cast<IT>(image_w));
-              inputShapeValues.push_back(static_cast<IT>(image_z));
-              imageShapeData = CreateTensor(iType, inputShapeValues);
-          }
+        std::vector<IT> inputShapeValues;
+        inputShapeValues.push_back(static_cast<IT>(image_h));
+        inputShapeValues.push_back(static_cast<IT>(image_w));
+        inputShapeValues.push_back(static_cast<IT>(image_z));
+        imageShapeData = CreateTensor(iType, inputShapeValues);
+    }
 
     ov::op::v4::Proposal::Attributes attrs;
     ov::PartialShape clsScoreShape;
@@ -182,8 +183,10 @@ class ReferenceProposalV1LayerTest : public testing::TestWithParam<ProposalV1Par
         const auto class_probs_param = std::make_shared<op::v0::Parameter>(params.inType, params.clsScoreShape);
         const auto bbox_deltas_param = std::make_shared<op::v0::Parameter>(params.inType, params.bboxPredShape);
         const auto image_shape_param = std::make_shared<op::v0::Parameter>(params.inType, params.imageShapeShape);
-        const auto Proposal = std::make_shared<op::v0::Proposal>(class_probs_param, bbox_deltas_param, image_shape_param, params.attrs);
-        return std::make_shared<ov::Model>(NodeVector {Proposal}, ParameterVector {class_probs_param, bbox_deltas_param, image_shape_param});
+        const auto Proposal =
+            std::make_shared<op::v0::Proposal>(class_probs_param, bbox_deltas_param, image_shape_param, params.attrs);
+        return std::make_shared<ov::Model>(NodeVector{Proposal},
+                                           ParameterVector{class_probs_param, bbox_deltas_param, image_shape_param});
     }
 };
 
@@ -217,8 +220,10 @@ class ReferenceProposalV4LayerTest : public testing::TestWithParam<ProposalV4Par
         const auto class_probs_param = std::make_shared<op::v0::Parameter>(params.inType, params.clsScoreShape);
         const auto bbox_deltas_param = std::make_shared<op::v0::Parameter>(params.inType, params.bboxPredShape);
         const auto image_shape_param = std::make_shared<op::v0::Parameter>(params.inType, params.imageShapeShape);
-        const auto Proposal = std::make_shared<op::v4::Proposal>(class_probs_param, bbox_deltas_param, image_shape_param, params.attrs);
-        return std::make_shared<ov::Model>(Proposal->outputs(), ParameterVector {class_probs_param, bbox_deltas_param, image_shape_param});
+        const auto Proposal =
+            std::make_shared<op::v4::Proposal>(class_probs_param, bbox_deltas_param, image_shape_param, params.attrs);
+        return std::make_shared<ov::Model>(Proposal->outputs(),
+                                           ParameterVector{class_probs_param, bbox_deltas_param, image_shape_param});
     }
 };
 
@@ -234,99 +239,115 @@ template <element::Type_t IN_ET>
 std::vector<ProposalV1Params> generateProposalV1Params() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ProposalV1Params> proposalV1Params {
-        ProposalV1Params(0.7f, 16, 16, 6000, 10, // iou_threshold, min_nnox_size, feature_stride,pre_nms_topn, post_nms_topn
-                       3, 210, 350, 1, // image_shape_num, image_h, image_w, image_z
-                       {0.5f}, // ratios
-                       {32.0f}, //scales
-                       1, 1, 10, 10, // batch_size, anchor_num, feat_map_height, feat_map_width
-                       IN_ET,
-                    std::vector<T>{
-                                0.000240f, 0.003802f, 0.111432f, 0.000503f, 0.007887f, 0.144701f, 0.399074f, 0.004680f,  // 0
-                                0.139741f, 0.002386f, 0.030003f, 0.276552f, 0.000267f, 0.022971f, 0.287953f, 0.050235f,  // 8
-                                0.002580f, 0.206311f, 0.000146f, 0.009656f, 0.175462f, 0.000147f, 0.014718f, 0.272348f,  // 16
-                                0.065199f, 0.003286f, 0.185335f, 0.003720f, 0.025932f, 0.251401f, 0.001465f, 0.090447f,  // 24
-                                0.488469f, 0.092259f, 0.019306f, 0.379091f, 0.005311f, 0.010369f, 0.087615f, 0.042003f,  // 32
-                                0.073871f, 0.416763f, 0.044282f, 0.069776f, 0.313032f, 0.000457f, 0.017346f, 0.089762f,  // 40
-                                0.000820f, 0.103986f, 0.367993f, 0.026315f, 0.035701f, 0.299252f, 0.000135f, 0.017825f,  // 48
-                                0.150119f, 0.000076f, 0.050511f, 0.269601f, 0.026680f, 0.003541f, 0.189765f, 0.000051f,  // 56
-                                0.004315f, 0.193150f, 0.000032f, 0.007254f, 0.185557f, 0.051526f, 0.000657f, 0.117579f,  // 64
-                                0.000115f, 0.010179f, 0.293187f, 0.000025f, 0.006505f, 0.175345f, 0.032587f, 0.000469f,  // 72
-                                0.098443f, 0.000121f, 0.009600f, 0.322782f, 0.000032f, 0.004543f, 0.166860f, 0.044911f,  // 80
-                                0.000187f, 0.102691f, 0.000242f, 0.005502f, 0.107865f, 0.000191f, 0.005336f, 0.086893f,  // 88
-                                0.078422f, 0.000345f, 0.079096f, 0.000281f, 0.016388f, 0.214072f, 0.000107f, 0.012027f,  // 96
-                                0.192754f, 0.049531f, 0.000386f, 0.149893f, 0.000374f, 0.016965f, 0.204781f, 0.000163f,  // 104
-                                0.016272f, 0.215277f, 0.032298f, 0.000857f, 0.133426f, 0.000614f, 0.020215f, 0.165789f,  // 112
-                                0.000225f, 0.036951f, 0.262195f, 0.087675f, 0.004596f, 0.147764f, 0.000219f, 0.010502f,  // 120
-                                0.163394f, 0.000152f, 0.023116f, 0.241702f, 0.081800f, 0.002197f, 0.146637f, 0.000193f,  // 128
-                                0.012017f, 0.133497f, 0.000375f, 0.028605f, 0.309179f, 0.065962f, 0.005508f, 0.155530f,  // 136
-                                0.000186f, 0.004540f, 0.079319f, 0.000799f, 0.031003f, 0.303045f, 0.051473f, 0.017770f,  // 144
-                                0.206188f, 0.000202f, 0.004291f, 0.061095f, 0.001109f, 0.018094f, 0.156639f, 0.026062f,  // 152
-                                0.005270f, 0.148651f, 0.000026f, 0.007300f, 0.096013f, 0.000383f, 0.022134f, 0.129511f,  // 160
-                                0.080882f, 0.003416f, 0.129922f, 0.000037f, 0.010040f, 0.130007f, 0.000116f, 0.014904f,  // 168
-                                0.171423f, 0.082893f, 0.000921f, 0.154976f, 0.000142f, 0.016552f, 0.209696f, 0.000227f,  // 176
-                                0.022418f, 0.228501f, 0.111712f, 0.001987f, 0.158164f, 0.001200f, 0.027049f, 0.308222f,  // 184
-                                0.001366f, 0.038146f, 0.287945f, 0.072526f, 0.016064f, 0.257895f, 0.000595f, 0.016962f,  // 192
-                                },
-                    std::vector<T>{
-                                0.006756f,  -0.055635f, 0.030843f,  0.007482f,  0.009056f,  -0.041824f, 0.119722f,  0.168988f,  0.002822f,
-                                0.039733f,  0.109005f,  0.245152f,  -0.013196f, -0.018222f, -0.170122f, -0.374904f, -0.005455f, -0.034059f,
-                                -0.006787f, 0.072005f,  -0.017933f, -0.007358f, 0.034149f,  0.123846f,  0.128319f,  0.016107f,  -0.615487f,
-                                -1.235094f, -0.024253f, -0.019406f, 0.134142f,  0.157853f,  -0.021119f, 0.007383f,  0.089365f,  0.092854f,
-                                0.062491f,  0.002366f,  0.122464f,  -0.003326f, 0.015468f,  -0.034088f, 0.079009f,  0.075483f,  0.011972f,
-                                0.042427f,  0.106865f,  0.158754f,  0.071211f,  -0.034009f, 0.007985f,  -0.441477f, 0.009046f,  -0.028515f,
-                                0.095372f,  0.119598f,  -0.007553f, -0.0072f,   0.105072f,  0.084314f,  0.23268f,   -0.02906f,  -0.408454f,
-                                -1.13439f,  0.016202f,  -0.037859f, 0.130873f,  0.129652f,  0.002064f,  -0.011969f, 0.171623f,  0.050218f,
-                                0.113831f,  0.028922f,  0.017785f,  0.059708f,  0.037658f,  -0.011245f, 0.097197f,  0.137491f,  0.024218f,
-                                0.04739f,   0.091978f,  0.217333f,  0.088418f,  -0.004662f, -0.095168f, -0.397928f, 0.02639f,   -0.008501f,
-                                0.068487f,  0.108465f,  0.020069f,  0.018829f,  0.040206f,  0.068473f,  0.226458f,  -0.072871f, -0.672384f,
-                                -1.447558f, 0.039598f,  0.017471f,  0.187288f,  0.08409f,   0.017152f,  -0.00516f,  0.183419f,  0.068469f,
-                                0.063944f,  0.160725f,  -0.022493f, -0.132291f, 0.010542f,  0.036318f,  0.074042f,  -0.013323f, 0.00808f,
-                                0.060365f,  0.120566f,  0.21866f,   0.046324f,  0.088741f,  0.029469f,  -0.517183f, 0.00917f,   0.011915f,
-                                0.053674f,  0.140168f,  0.0033f,    0.022759f,  -0.006196f, 0.063839f,  0.083726f,  -0.088385f, -0.57208f,
-                                -1.454211f, 0.020655f,  0.010788f,  0.134951f,  0.109709f,  0.015445f,  -0.015363f, 0.109153f,  0.051209f,
-                                0.024297f,  0.139126f,  -0.12358f,  -0.127979f, 0.004587f,  0.004751f,  0.047292f,  0.027066f,  0.011003f,
-                                0.069887f,  0.117052f,  0.267419f,  0.039306f,  0.077584f,  0.02579f,   -0.496149f, -0.005569f, 0.015494f,
-                                -0.011662f, 0.105549f,  -0.007015f, 0.031984f,  -0.075742f, 0.0852f,    0.023886f,  -0.053107f, -0.325533f,
-                                -1.329066f, 0.004688f,  0.034501f,  0.089317f,  0.042463f,  0.004212f,  -0.015128f, 0.00892f,   0.028266f,
-                                0.009997f,  0.157822f,  0.020116f,  -0.142337f, 0.008199f,  0.046564f,  0.083014f,  0.046307f,  0.006771f,
-                                0.084997f,  0.141935f,  0.228339f,  -0.020308f, 0.077745f,  -0.018319f, -0.522311f, 0.010432f,  0.024641f,
-                                0.020571f,  0.097148f,  0.002064f,  0.035053f,  -0.121995f, 0.012222f,  -0.030779f, 0.100481f,  -0.331737f,
-                                -1.257669f, -0.013079f, 0.021227f,  0.159949f,  0.120097f,  0.005765f,  -0.012335f, -0.005268f, 0.042067f,
-                                -0.043972f, 0.102556f,  0.180494f,  -0.084721f, -0.011962f, 0.031302f,  0.112511f,  0.027557f,  -0.002085f,
-                                0.082978f,  0.149409f,  0.195091f,  -0.033731f, 0.019861f,  -0.064047f, -0.471328f, -0.004093f, 0.016803f,
-                                0.044635f,  0.058912f,  -0.018735f, 0.035536f,  -0.050373f, -0.002794f, -0.086705f, 0.038435f,  -0.301466f,
-                                -1.071246f, -0.028247f, 0.018984f,  0.254702f,  0.141142f,  -0.017522f, 0.014843f,  0.079391f,  0.079662f,
-                                -0.051204f, 0.048419f,  0.235604f,  -0.185797f, -0.019569f, 0.02678f,   0.162507f,  0.046435f,  -0.004606f,
-                                0.08806f,   0.18634f,   0.193957f,  -0.024333f, -0.01298f,  -0.17977f,  -0.65881f,  -0.003778f, 0.007418f,
-                                0.065439f,  0.104549f,  -0.027706f, 0.03301f,   0.057492f,  0.032019f,  -0.135337f, 0.000269f,  -0.250203f,
-                                -1.181688f, -0.027022f, -0.006755f, 0.206848f,  0.129268f,  -0.003529f, 0.013445f,  0.181484f,  0.139955f,
-                                -0.036587f, 0.065824f,  0.288751f,  -0.110813f, -0.015578f, 0.044818f,  0.17756f,   0.006914f,  0.002329f,
-                                0.068982f,  0.189079f,  0.184253f,  0.00301f,   -0.039168f, -0.010855f, -0.393254f, 0.000028f,  0.001906f,
-                                0.07217f,   0.063305f,  -0.026144f, 0.028842f,  0.139149f,  0.023377f,  0.023362f,  0.023559f,  -0.145386f,
-                                -0.863572f, -0.015749f, -0.021364f, 0.172571f,  0.078393f,  -0.037253f, 0.014978f,  0.221502f,  0.189111f,
-                                -0.048956f, 0.085409f,  0.325399f,  -0.058294f, -0.028495f, 0.021663f,  0.19392f,   0.02706f,   0.006908f,
-                                0.065751f,  0.176395f,  0.138375f,  0.012418f,  -0.031228f, -0.008762f, -0.427345f, -0.013677f, -0.002429f,
-                                0.069655f,  0.019505f,  -0.036763f, 0.022528f,  0.201062f,  0.022205f,  0.024528f,  0.06241f,   -0.076237f,
-                                -0.840695f, -0.007268f, -0.027865f, 0.211056f,  0.074744f,  -0.053563f, 0.006863f,  0.301432f,  0.192879f,
-                                -0.021944f, 0.100535f,  0.19031f,   -0.133746f, -0.006151f, 0.023944f,  0.13561f,   -0.03259f,  0.000618f,
-                                0.063736f,  0.180904f,  0.12393f,   0.001275f,  -0.0306f,   -0.032822f, -0.496515f, 0.009757f,  0.014602f,
-                                0.004532f,  -0.039969f, -0.015984f, 0.047726f,  0.099865f,  0.003163f,  0.026623f,  0.117951f,  -0.076234f,
-                                -0.811997f, 0.01301f,   0.020042f,  0.173756f,  -0.036191f, -0.068887f, 0.0229f,    0.245465f,  0.214282f,
-                                -0.011054f, 0.132813f,  0.241014f,  -0.148763f,
-                                },
-                    std::vector<T>{
-                                0.000000f, 0.000000f,   0.000000f,  349.000000f, 209.000000f,  // 0
-                                0.000000f, 0.000000f,   0.000000f,  237.625443f, 209.000000f,  // 5
-                                0.000000f, 140.305511f, 0.000000f,  349.000000f, 209.000000f,  // 10
-                                0.000000f, 0.000000f,   0.000000f,  349.000000f, 65.359818f,   // 15
-                                0.000000f, 0.000000f,   0.000000f,  349.000000f, 130.324097f,  // 20
-                                0.000000f, 0.000000f,   15.562508f, 97.587891f,  181.224182f,  // 25
-                                0.000000f, 0.000000f,   68.539543f, 250.406708f, 209.000000f,  // 30
-                                0.000000f, 0.000000f,   0.000000f,  195.881531f, 99.841385f,   // 35
-                                0.000000f, 0.000000f,   0.000000f,  78.303986f,  209.000000f,  // 40
-                                0.000000f, 0.000000f,   0.000000f,  0.000000f,   209.000000f,  // 45
-                                }),
+    std::vector<ProposalV1Params> proposalV1Params{
+        ProposalV1Params(
+            0.7f,
+            16,
+            16,
+            6000,
+            10,  // iou_threshold, min_nnox_size, feature_stride,pre_nms_topn, post_nms_topn
+            3,
+            210,
+            350,
+            1,        // image_shape_num, image_h, image_w, image_z
+            {0.5f},   // ratios
+            {32.0f},  // scales
+            1,
+            1,
+            10,
+            10,  // batch_size, anchor_num, feat_map_height, feat_map_width
+            IN_ET,
+            std::vector<T>{
+                0.000240f, 0.003802f, 0.111432f, 0.000503f, 0.007887f, 0.144701f, 0.399074f, 0.004680f,  // 0
+                0.139741f, 0.002386f, 0.030003f, 0.276552f, 0.000267f, 0.022971f, 0.287953f, 0.050235f,  // 8
+                0.002580f, 0.206311f, 0.000146f, 0.009656f, 0.175462f, 0.000147f, 0.014718f, 0.272348f,  // 16
+                0.065199f, 0.003286f, 0.185335f, 0.003720f, 0.025932f, 0.251401f, 0.001465f, 0.090447f,  // 24
+                0.488469f, 0.092259f, 0.019306f, 0.379091f, 0.005311f, 0.010369f, 0.087615f, 0.042003f,  // 32
+                0.073871f, 0.416763f, 0.044282f, 0.069776f, 0.313032f, 0.000457f, 0.017346f, 0.089762f,  // 40
+                0.000820f, 0.103986f, 0.367993f, 0.026315f, 0.035701f, 0.299252f, 0.000135f, 0.017825f,  // 48
+                0.150119f, 0.000076f, 0.050511f, 0.269601f, 0.026680f, 0.003541f, 0.189765f, 0.000051f,  // 56
+                0.004315f, 0.193150f, 0.000032f, 0.007254f, 0.185557f, 0.051526f, 0.000657f, 0.117579f,  // 64
+                0.000115f, 0.010179f, 0.293187f, 0.000025f, 0.006505f, 0.175345f, 0.032587f, 0.000469f,  // 72
+                0.098443f, 0.000121f, 0.009600f, 0.322782f, 0.000032f, 0.004543f, 0.166860f, 0.044911f,  // 80
+                0.000187f, 0.102691f, 0.000242f, 0.005502f, 0.107865f, 0.000191f, 0.005336f, 0.086893f,  // 88
+                0.078422f, 0.000345f, 0.079096f, 0.000281f, 0.016388f, 0.214072f, 0.000107f, 0.012027f,  // 96
+                0.192754f, 0.049531f, 0.000386f, 0.149893f, 0.000374f, 0.016965f, 0.204781f, 0.000163f,  // 104
+                0.016272f, 0.215277f, 0.032298f, 0.000857f, 0.133426f, 0.000614f, 0.020215f, 0.165789f,  // 112
+                0.000225f, 0.036951f, 0.262195f, 0.087675f, 0.004596f, 0.147764f, 0.000219f, 0.010502f,  // 120
+                0.163394f, 0.000152f, 0.023116f, 0.241702f, 0.081800f, 0.002197f, 0.146637f, 0.000193f,  // 128
+                0.012017f, 0.133497f, 0.000375f, 0.028605f, 0.309179f, 0.065962f, 0.005508f, 0.155530f,  // 136
+                0.000186f, 0.004540f, 0.079319f, 0.000799f, 0.031003f, 0.303045f, 0.051473f, 0.017770f,  // 144
+                0.206188f, 0.000202f, 0.004291f, 0.061095f, 0.001109f, 0.018094f, 0.156639f, 0.026062f,  // 152
+                0.005270f, 0.148651f, 0.000026f, 0.007300f, 0.096013f, 0.000383f, 0.022134f, 0.129511f,  // 160
+                0.080882f, 0.003416f, 0.129922f, 0.000037f, 0.010040f, 0.130007f, 0.000116f, 0.014904f,  // 168
+                0.171423f, 0.082893f, 0.000921f, 0.154976f, 0.000142f, 0.016552f, 0.209696f, 0.000227f,  // 176
+                0.022418f, 0.228501f, 0.111712f, 0.001987f, 0.158164f, 0.001200f, 0.027049f, 0.308222f,  // 184
+                0.001366f, 0.038146f, 0.287945f, 0.072526f, 0.016064f, 0.257895f, 0.000595f, 0.016962f,  // 192
+            },
+            std::vector<T>{
+                0.006756f,  -0.055635f, 0.030843f,  0.007482f,  0.009056f,  -0.041824f, 0.119722f,  0.168988f,
+                0.002822f,  0.039733f,  0.109005f,  0.245152f,  -0.013196f, -0.018222f, -0.170122f, -0.374904f,
+                -0.005455f, -0.034059f, -0.006787f, 0.072005f,  -0.017933f, -0.007358f, 0.034149f,  0.123846f,
+                0.128319f,  0.016107f,  -0.615487f, -1.235094f, -0.024253f, -0.019406f, 0.134142f,  0.157853f,
+                -0.021119f, 0.007383f,  0.089365f,  0.092854f,  0.062491f,  0.002366f,  0.122464f,  -0.003326f,
+                0.015468f,  -0.034088f, 0.079009f,  0.075483f,  0.011972f,  0.042427f,  0.106865f,  0.158754f,
+                0.071211f,  -0.034009f, 0.007985f,  -0.441477f, 0.009046f,  -0.028515f, 0.095372f,  0.119598f,
+                -0.007553f, -0.0072f,   0.105072f,  0.084314f,  0.23268f,   -0.02906f,  -0.408454f, -1.13439f,
+                0.016202f,  -0.037859f, 0.130873f,  0.129652f,  0.002064f,  -0.011969f, 0.171623f,  0.050218f,
+                0.113831f,  0.028922f,  0.017785f,  0.059708f,  0.037658f,  -0.011245f, 0.097197f,  0.137491f,
+                0.024218f,  0.04739f,   0.091978f,  0.217333f,  0.088418f,  -0.004662f, -0.095168f, -0.397928f,
+                0.02639f,   -0.008501f, 0.068487f,  0.108465f,  0.020069f,  0.018829f,  0.040206f,  0.068473f,
+                0.226458f,  -0.072871f, -0.672384f, -1.447558f, 0.039598f,  0.017471f,  0.187288f,  0.08409f,
+                0.017152f,  -0.00516f,  0.183419f,  0.068469f,  0.063944f,  0.160725f,  -0.022493f, -0.132291f,
+                0.010542f,  0.036318f,  0.074042f,  -0.013323f, 0.00808f,   0.060365f,  0.120566f,  0.21866f,
+                0.046324f,  0.088741f,  0.029469f,  -0.517183f, 0.00917f,   0.011915f,  0.053674f,  0.140168f,
+                0.0033f,    0.022759f,  -0.006196f, 0.063839f,  0.083726f,  -0.088385f, -0.57208f,  -1.454211f,
+                0.020655f,  0.010788f,  0.134951f,  0.109709f,  0.015445f,  -0.015363f, 0.109153f,  0.051209f,
+                0.024297f,  0.139126f,  -0.12358f,  -0.127979f, 0.004587f,  0.004751f,  0.047292f,  0.027066f,
+                0.011003f,  0.069887f,  0.117052f,  0.267419f,  0.039306f,  0.077584f,  0.02579f,   -0.496149f,
+                -0.005569f, 0.015494f,  -0.011662f, 0.105549f,  -0.007015f, 0.031984f,  -0.075742f, 0.0852f,
+                0.023886f,  -0.053107f, -0.325533f, -1.329066f, 0.004688f,  0.034501f,  0.089317f,  0.042463f,
+                0.004212f,  -0.015128f, 0.00892f,   0.028266f,  0.009997f,  0.157822f,  0.020116f,  -0.142337f,
+                0.008199f,  0.046564f,  0.083014f,  0.046307f,  0.006771f,  0.084997f,  0.141935f,  0.228339f,
+                -0.020308f, 0.077745f,  -0.018319f, -0.522311f, 0.010432f,  0.024641f,  0.020571f,  0.097148f,
+                0.002064f,  0.035053f,  -0.121995f, 0.012222f,  -0.030779f, 0.100481f,  -0.331737f, -1.257669f,
+                -0.013079f, 0.021227f,  0.159949f,  0.120097f,  0.005765f,  -0.012335f, -0.005268f, 0.042067f,
+                -0.043972f, 0.102556f,  0.180494f,  -0.084721f, -0.011962f, 0.031302f,  0.112511f,  0.027557f,
+                -0.002085f, 0.082978f,  0.149409f,  0.195091f,  -0.033731f, 0.019861f,  -0.064047f, -0.471328f,
+                -0.004093f, 0.016803f,  0.044635f,  0.058912f,  -0.018735f, 0.035536f,  -0.050373f, -0.002794f,
+                -0.086705f, 0.038435f,  -0.301466f, -1.071246f, -0.028247f, 0.018984f,  0.254702f,  0.141142f,
+                -0.017522f, 0.014843f,  0.079391f,  0.079662f,  -0.051204f, 0.048419f,  0.235604f,  -0.185797f,
+                -0.019569f, 0.02678f,   0.162507f,  0.046435f,  -0.004606f, 0.08806f,   0.18634f,   0.193957f,
+                -0.024333f, -0.01298f,  -0.17977f,  -0.65881f,  -0.003778f, 0.007418f,  0.065439f,  0.104549f,
+                -0.027706f, 0.03301f,   0.057492f,  0.032019f,  -0.135337f, 0.000269f,  -0.250203f, -1.181688f,
+                -0.027022f, -0.006755f, 0.206848f,  0.129268f,  -0.003529f, 0.013445f,  0.181484f,  0.139955f,
+                -0.036587f, 0.065824f,  0.288751f,  -0.110813f, -0.015578f, 0.044818f,  0.17756f,   0.006914f,
+                0.002329f,  0.068982f,  0.189079f,  0.184253f,  0.00301f,   -0.039168f, -0.010855f, -0.393254f,
+                0.000028f,  0.001906f,  0.07217f,   0.063305f,  -0.026144f, 0.028842f,  0.139149f,  0.023377f,
+                0.023362f,  0.023559f,  -0.145386f, -0.863572f, -0.015749f, -0.021364f, 0.172571f,  0.078393f,
+                -0.037253f, 0.014978f,  0.221502f,  0.189111f,  -0.048956f, 0.085409f,  0.325399f,  -0.058294f,
+                -0.028495f, 0.021663f,  0.19392f,   0.02706f,   0.006908f,  0.065751f,  0.176395f,  0.138375f,
+                0.012418f,  -0.031228f, -0.008762f, -0.427345f, -0.013677f, -0.002429f, 0.069655f,  0.019505f,
+                -0.036763f, 0.022528f,  0.201062f,  0.022205f,  0.024528f,  0.06241f,   -0.076237f, -0.840695f,
+                -0.007268f, -0.027865f, 0.211056f,  0.074744f,  -0.053563f, 0.006863f,  0.301432f,  0.192879f,
+                -0.021944f, 0.100535f,  0.19031f,   -0.133746f, -0.006151f, 0.023944f,  0.13561f,   -0.03259f,
+                0.000618f,  0.063736f,  0.180904f,  0.12393f,   0.001275f,  -0.0306f,   -0.032822f, -0.496515f,
+                0.009757f,  0.014602f,  0.004532f,  -0.039969f, -0.015984f, 0.047726f,  0.099865f,  0.003163f,
+                0.026623f,  0.117951f,  -0.076234f, -0.811997f, 0.01301f,   0.020042f,  0.173756f,  -0.036191f,
+                -0.068887f, 0.0229f,    0.245465f,  0.214282f,  -0.011054f, 0.132813f,  0.241014f,  -0.148763f,
+            },
+            std::vector<T>{
+                0.000000f, 0.000000f,   0.000000f,  349.000000f, 209.000000f,  // 0
+                0.000000f, 0.000000f,   0.000000f,  237.625443f, 209.000000f,  // 5
+                0.000000f, 140.305511f, 0.000000f,  349.000000f, 209.000000f,  // 10
+                0.000000f, 0.000000f,   0.000000f,  349.000000f, 65.359818f,   // 15
+                0.000000f, 0.000000f,   0.000000f,  349.000000f, 130.324097f,  // 20
+                0.000000f, 0.000000f,   15.562508f, 97.587891f,  181.224182f,  // 25
+                0.000000f, 0.000000f,   68.539543f, 250.406708f, 209.000000f,  // 30
+                0.000000f, 0.000000f,   0.000000f,  195.881531f, 99.841385f,   // 35
+                0.000000f, 0.000000f,   0.000000f,  78.303986f,  209.000000f,  // 40
+                0.000000f, 0.000000f,   0.000000f,  0.000000f,   209.000000f,  // 45
+            }),
     };
     return proposalV1Params;
 }
@@ -335,122 +356,137 @@ template <element::Type_t IN_ET>
 std::vector<ProposalV4Params> generateProposalV4Params() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ProposalV4Params> proposalV4Params {
-        ProposalV4Params(0.7f, 16, 16, 6000, 10, // iou_threshold, min_nnox_size, feature_stride,pre_nms_topn, post_nms_topn
-                       3, 210, 350, 1, // image_shape_num, image_h, image_w, image_z
-                       {0.5f}, // ratios
-                       {32.0f}, //scales
-                       1, 1, 10, 10, // batch_size, anchor_num, feat_map_height, feat_map_width
-                       IN_ET,
-                    std::vector<T>{
-                                0.000240f, 0.003802f, 0.111432f, 0.000503f, 0.007887f, 0.144701f, 0.399074f, 0.004680f,  // 0
-                                0.139741f, 0.002386f, 0.030003f, 0.276552f, 0.000267f, 0.022971f, 0.287953f, 0.050235f,  // 8
-                                0.002580f, 0.206311f, 0.000146f, 0.009656f, 0.175462f, 0.000147f, 0.014718f, 0.272348f,  // 16
-                                0.065199f, 0.003286f, 0.185335f, 0.003720f, 0.025932f, 0.251401f, 0.001465f, 0.090447f,  // 24
-                                0.488469f, 0.092259f, 0.019306f, 0.379091f, 0.005311f, 0.010369f, 0.087615f, 0.042003f,  // 32
-                                0.073871f, 0.416763f, 0.044282f, 0.069776f, 0.313032f, 0.000457f, 0.017346f, 0.089762f,  // 40
-                                0.000820f, 0.103986f, 0.367993f, 0.026315f, 0.035701f, 0.299252f, 0.000135f, 0.017825f,  // 48
-                                0.150119f, 0.000076f, 0.050511f, 0.269601f, 0.026680f, 0.003541f, 0.189765f, 0.000051f,  // 56
-                                0.004315f, 0.193150f, 0.000032f, 0.007254f, 0.185557f, 0.051526f, 0.000657f, 0.117579f,  // 64
-                                0.000115f, 0.010179f, 0.293187f, 0.000025f, 0.006505f, 0.175345f, 0.032587f, 0.000469f,  // 72
-                                0.098443f, 0.000121f, 0.009600f, 0.322782f, 0.000032f, 0.004543f, 0.166860f, 0.044911f,  // 80
-                                0.000187f, 0.102691f, 0.000242f, 0.005502f, 0.107865f, 0.000191f, 0.005336f, 0.086893f,  // 88
-                                0.078422f, 0.000345f, 0.079096f, 0.000281f, 0.016388f, 0.214072f, 0.000107f, 0.012027f,  // 96
-                                0.192754f, 0.049531f, 0.000386f, 0.149893f, 0.000374f, 0.016965f, 0.204781f, 0.000163f,  // 104
-                                0.016272f, 0.215277f, 0.032298f, 0.000857f, 0.133426f, 0.000614f, 0.020215f, 0.165789f,  // 112
-                                0.000225f, 0.036951f, 0.262195f, 0.087675f, 0.004596f, 0.147764f, 0.000219f, 0.010502f,  // 120
-                                0.163394f, 0.000152f, 0.023116f, 0.241702f, 0.081800f, 0.002197f, 0.146637f, 0.000193f,  // 128
-                                0.012017f, 0.133497f, 0.000375f, 0.028605f, 0.309179f, 0.065962f, 0.005508f, 0.155530f,  // 136
-                                0.000186f, 0.004540f, 0.079319f, 0.000799f, 0.031003f, 0.303045f, 0.051473f, 0.017770f,  // 144
-                                0.206188f, 0.000202f, 0.004291f, 0.061095f, 0.001109f, 0.018094f, 0.156639f, 0.026062f,  // 152
-                                0.005270f, 0.148651f, 0.000026f, 0.007300f, 0.096013f, 0.000383f, 0.022134f, 0.129511f,  // 160
-                                0.080882f, 0.003416f, 0.129922f, 0.000037f, 0.010040f, 0.130007f, 0.000116f, 0.014904f,  // 168
-                                0.171423f, 0.082893f, 0.000921f, 0.154976f, 0.000142f, 0.016552f, 0.209696f, 0.000227f,  // 176
-                                0.022418f, 0.228501f, 0.111712f, 0.001987f, 0.158164f, 0.001200f, 0.027049f, 0.308222f,  // 184
-                                0.001366f, 0.038146f, 0.287945f, 0.072526f, 0.016064f, 0.257895f, 0.000595f, 0.016962f,  // 192
-                                },
-                    std::vector<T>{
-                                0.006756f,  -0.055635f, 0.030843f,  0.007482f,  0.009056f,  -0.041824f, 0.119722f,  0.168988f,  0.002822f,
-                                0.039733f,  0.109005f,  0.245152f,  -0.013196f, -0.018222f, -0.170122f, -0.374904f, -0.005455f, -0.034059f,
-                                -0.006787f, 0.072005f,  -0.017933f, -0.007358f, 0.034149f,  0.123846f,  0.128319f,  0.016107f,  -0.615487f,
-                                -1.235094f, -0.024253f, -0.019406f, 0.134142f,  0.157853f,  -0.021119f, 0.007383f,  0.089365f,  0.092854f,
-                                0.062491f,  0.002366f,  0.122464f,  -0.003326f, 0.015468f,  -0.034088f, 0.079009f,  0.075483f,  0.011972f,
-                                0.042427f,  0.106865f,  0.158754f,  0.071211f,  -0.034009f, 0.007985f,  -0.441477f, 0.009046f,  -0.028515f,
-                                0.095372f,  0.119598f,  -0.007553f, -0.0072f,   0.105072f,  0.084314f,  0.23268f,   -0.02906f,  -0.408454f,
-                                -1.13439f,  0.016202f,  -0.037859f, 0.130873f,  0.129652f,  0.002064f,  -0.011969f, 0.171623f,  0.050218f,
-                                0.113831f,  0.028922f,  0.017785f,  0.059708f,  0.037658f,  -0.011245f, 0.097197f,  0.137491f,  0.024218f,
-                                0.04739f,   0.091978f,  0.217333f,  0.088418f,  -0.004662f, -0.095168f, -0.397928f, 0.02639f,   -0.008501f,
-                                0.068487f,  0.108465f,  0.020069f,  0.018829f,  0.040206f,  0.068473f,  0.226458f,  -0.072871f, -0.672384f,
-                                -1.447558f, 0.039598f,  0.017471f,  0.187288f,  0.08409f,   0.017152f,  -0.00516f,  0.183419f,  0.068469f,
-                                0.063944f,  0.160725f,  -0.022493f, -0.132291f, 0.010542f,  0.036318f,  0.074042f,  -0.013323f, 0.00808f,
-                                0.060365f,  0.120566f,  0.21866f,   0.046324f,  0.088741f,  0.029469f,  -0.517183f, 0.00917f,   0.011915f,
-                                0.053674f,  0.140168f,  0.0033f,    0.022759f,  -0.006196f, 0.063839f,  0.083726f,  -0.088385f, -0.57208f,
-                                -1.454211f, 0.020655f,  0.010788f,  0.134951f,  0.109709f,  0.015445f,  -0.015363f, 0.109153f,  0.051209f,
-                                0.024297f,  0.139126f,  -0.12358f,  -0.127979f, 0.004587f,  0.004751f,  0.047292f,  0.027066f,  0.011003f,
-                                0.069887f,  0.117052f,  0.267419f,  0.039306f,  0.077584f,  0.02579f,   -0.496149f, -0.005569f, 0.015494f,
-                                -0.011662f, 0.105549f,  -0.007015f, 0.031984f,  -0.075742f, 0.0852f,    0.023886f,  -0.053107f, -0.325533f,
-                                -1.329066f, 0.004688f,  0.034501f,  0.089317f,  0.042463f,  0.004212f,  -0.015128f, 0.00892f,   0.028266f,
-                                0.009997f,  0.157822f,  0.020116f,  -0.142337f, 0.008199f,  0.046564f,  0.083014f,  0.046307f,  0.006771f,
-                                0.084997f,  0.141935f,  0.228339f,  -0.020308f, 0.077745f,  -0.018319f, -0.522311f, 0.010432f,  0.024641f,
-                                0.020571f,  0.097148f,  0.002064f,  0.035053f,  -0.121995f, 0.012222f,  -0.030779f, 0.100481f,  -0.331737f,
-                                -1.257669f, -0.013079f, 0.021227f,  0.159949f,  0.120097f,  0.005765f,  -0.012335f, -0.005268f, 0.042067f,
-                                -0.043972f, 0.102556f,  0.180494f,  -0.084721f, -0.011962f, 0.031302f,  0.112511f,  0.027557f,  -0.002085f,
-                                0.082978f,  0.149409f,  0.195091f,  -0.033731f, 0.019861f,  -0.064047f, -0.471328f, -0.004093f, 0.016803f,
-                                0.044635f,  0.058912f,  -0.018735f, 0.035536f,  -0.050373f, -0.002794f, -0.086705f, 0.038435f,  -0.301466f,
-                                -1.071246f, -0.028247f, 0.018984f,  0.254702f,  0.141142f,  -0.017522f, 0.014843f,  0.079391f,  0.079662f,
-                                -0.051204f, 0.048419f,  0.235604f,  -0.185797f, -0.019569f, 0.02678f,   0.162507f,  0.046435f,  -0.004606f,
-                                0.08806f,   0.18634f,   0.193957f,  -0.024333f, -0.01298f,  -0.17977f,  -0.65881f,  -0.003778f, 0.007418f,
-                                0.065439f,  0.104549f,  -0.027706f, 0.03301f,   0.057492f,  0.032019f,  -0.135337f, 0.000269f,  -0.250203f,
-                                -1.181688f, -0.027022f, -0.006755f, 0.206848f,  0.129268f,  -0.003529f, 0.013445f,  0.181484f,  0.139955f,
-                                -0.036587f, 0.065824f,  0.288751f,  -0.110813f, -0.015578f, 0.044818f,  0.17756f,   0.006914f,  0.002329f,
-                                0.068982f,  0.189079f,  0.184253f,  0.00301f,   -0.039168f, -0.010855f, -0.393254f, 0.000028f,  0.001906f,
-                                0.07217f,   0.063305f,  -0.026144f, 0.028842f,  0.139149f,  0.023377f,  0.023362f,  0.023559f,  -0.145386f,
-                                -0.863572f, -0.015749f, -0.021364f, 0.172571f,  0.078393f,  -0.037253f, 0.014978f,  0.221502f,  0.189111f,
-                                -0.048956f, 0.085409f,  0.325399f,  -0.058294f, -0.028495f, 0.021663f,  0.19392f,   0.02706f,   0.006908f,
-                                0.065751f,  0.176395f,  0.138375f,  0.012418f,  -0.031228f, -0.008762f, -0.427345f, -0.013677f, -0.002429f,
-                                0.069655f,  0.019505f,  -0.036763f, 0.022528f,  0.201062f,  0.022205f,  0.024528f,  0.06241f,   -0.076237f,
-                                -0.840695f, -0.007268f, -0.027865f, 0.211056f,  0.074744f,  -0.053563f, 0.006863f,  0.301432f,  0.192879f,
-                                -0.021944f, 0.100535f,  0.19031f,   -0.133746f, -0.006151f, 0.023944f,  0.13561f,   -0.03259f,  0.000618f,
-                                0.063736f,  0.180904f,  0.12393f,   0.001275f,  -0.0306f,   -0.032822f, -0.496515f, 0.009757f,  0.014602f,
-                                0.004532f,  -0.039969f, -0.015984f, 0.047726f,  0.099865f,  0.003163f,  0.026623f,  0.117951f,  -0.076234f,
-                                -0.811997f, 0.01301f,   0.020042f,  0.173756f,  -0.036191f, -0.068887f, 0.0229f,    0.245465f,  0.214282f,
-                                -0.011054f, 0.132813f,  0.241014f,  -0.148763f,
-                                },
-                    std::vector<T>{
-                                0.000000f, 0.000000f,   0.000000f,  349.000000f, 209.000000f,  // 0
-                                0.000000f, 0.000000f,   0.000000f,  237.625443f, 209.000000f,  // 5
-                                0.000000f, 140.305511f, 0.000000f,  349.000000f, 209.000000f,  // 10
-                                0.000000f, 0.000000f,   0.000000f,  349.000000f, 65.359818f,   // 15
-                                0.000000f, 0.000000f,   0.000000f,  349.000000f, 130.324097f,  // 20
-                                0.000000f, 0.000000f,   15.562508f, 97.587891f,  181.224182f,  // 25
-                                0.000000f, 0.000000f,   68.539543f, 250.406708f, 209.000000f,  // 30
-                                0.000000f, 0.000000f,   0.000000f,  195.881531f, 99.841385f,   // 35
-                                0.000000f, 0.000000f,   0.000000f,  78.303986f,  209.000000f,  // 40
-                                0.000000f, 0.000000f,   0.000000f,  0.000000f,   209.000000f,  // 45
-                                },
-                    std::vector<T>{
-                                0.3091790f,
-                                0.1555300f,
-                                0.1549760f,
-                                0.1466370f,
-                                0.0260620f,
-                                0.0177700f,
-                                0.0019870f,
-                                0.0008570f,
-                                0.0002190f,
-                                0.0000000f,
-                                }),
+    std::vector<ProposalV4Params> proposalV4Params{
+        ProposalV4Params(
+            0.7f,
+            16,
+            16,
+            6000,
+            10,  // iou_threshold, min_nnox_size, feature_stride,pre_nms_topn, post_nms_topn
+            3,
+            210,
+            350,
+            1,        // image_shape_num, image_h, image_w, image_z
+            {0.5f},   // ratios
+            {32.0f},  // scales
+            1,
+            1,
+            10,
+            10,  // batch_size, anchor_num, feat_map_height, feat_map_width
+            IN_ET,
+            std::vector<T>{
+                0.000240f, 0.003802f, 0.111432f, 0.000503f, 0.007887f, 0.144701f, 0.399074f, 0.004680f,  // 0
+                0.139741f, 0.002386f, 0.030003f, 0.276552f, 0.000267f, 0.022971f, 0.287953f, 0.050235f,  // 8
+                0.002580f, 0.206311f, 0.000146f, 0.009656f, 0.175462f, 0.000147f, 0.014718f, 0.272348f,  // 16
+                0.065199f, 0.003286f, 0.185335f, 0.003720f, 0.025932f, 0.251401f, 0.001465f, 0.090447f,  // 24
+                0.488469f, 0.092259f, 0.019306f, 0.379091f, 0.005311f, 0.010369f, 0.087615f, 0.042003f,  // 32
+                0.073871f, 0.416763f, 0.044282f, 0.069776f, 0.313032f, 0.000457f, 0.017346f, 0.089762f,  // 40
+                0.000820f, 0.103986f, 0.367993f, 0.026315f, 0.035701f, 0.299252f, 0.000135f, 0.017825f,  // 48
+                0.150119f, 0.000076f, 0.050511f, 0.269601f, 0.026680f, 0.003541f, 0.189765f, 0.000051f,  // 56
+                0.004315f, 0.193150f, 0.000032f, 0.007254f, 0.185557f, 0.051526f, 0.000657f, 0.117579f,  // 64
+                0.000115f, 0.010179f, 0.293187f, 0.000025f, 0.006505f, 0.175345f, 0.032587f, 0.000469f,  // 72
+                0.098443f, 0.000121f, 0.009600f, 0.322782f, 0.000032f, 0.004543f, 0.166860f, 0.044911f,  // 80
+                0.000187f, 0.102691f, 0.000242f, 0.005502f, 0.107865f, 0.000191f, 0.005336f, 0.086893f,  // 88
+                0.078422f, 0.000345f, 0.079096f, 0.000281f, 0.016388f, 0.214072f, 0.000107f, 0.012027f,  // 96
+                0.192754f, 0.049531f, 0.000386f, 0.149893f, 0.000374f, 0.016965f, 0.204781f, 0.000163f,  // 104
+                0.016272f, 0.215277f, 0.032298f, 0.000857f, 0.133426f, 0.000614f, 0.020215f, 0.165789f,  // 112
+                0.000225f, 0.036951f, 0.262195f, 0.087675f, 0.004596f, 0.147764f, 0.000219f, 0.010502f,  // 120
+                0.163394f, 0.000152f, 0.023116f, 0.241702f, 0.081800f, 0.002197f, 0.146637f, 0.000193f,  // 128
+                0.012017f, 0.133497f, 0.000375f, 0.028605f, 0.309179f, 0.065962f, 0.005508f, 0.155530f,  // 136
+                0.000186f, 0.004540f, 0.079319f, 0.000799f, 0.031003f, 0.303045f, 0.051473f, 0.017770f,  // 144
+                0.206188f, 0.000202f, 0.004291f, 0.061095f, 0.001109f, 0.018094f, 0.156639f, 0.026062f,  // 152
+                0.005270f, 0.148651f, 0.000026f, 0.007300f, 0.096013f, 0.000383f, 0.022134f, 0.129511f,  // 160
+                0.080882f, 0.003416f, 0.129922f, 0.000037f, 0.010040f, 0.130007f, 0.000116f, 0.014904f,  // 168
+                0.171423f, 0.082893f, 0.000921f, 0.154976f, 0.000142f, 0.016552f, 0.209696f, 0.000227f,  // 176
+                0.022418f, 0.228501f, 0.111712f, 0.001987f, 0.158164f, 0.001200f, 0.027049f, 0.308222f,  // 184
+                0.001366f, 0.038146f, 0.287945f, 0.072526f, 0.016064f, 0.257895f, 0.000595f, 0.016962f,  // 192
+            },
+            std::vector<T>{
+                0.006756f,  -0.055635f, 0.030843f,  0.007482f,  0.009056f,  -0.041824f, 0.119722f,  0.168988f,
+                0.002822f,  0.039733f,  0.109005f,  0.245152f,  -0.013196f, -0.018222f, -0.170122f, -0.374904f,
+                -0.005455f, -0.034059f, -0.006787f, 0.072005f,  -0.017933f, -0.007358f, 0.034149f,  0.123846f,
+                0.128319f,  0.016107f,  -0.615487f, -1.235094f, -0.024253f, -0.019406f, 0.134142f,  0.157853f,
+                -0.021119f, 0.007383f,  0.089365f,  0.092854f,  0.062491f,  0.002366f,  0.122464f,  -0.003326f,
+                0.015468f,  -0.034088f, 0.079009f,  0.075483f,  0.011972f,  0.042427f,  0.106865f,  0.158754f,
+                0.071211f,  -0.034009f, 0.007985f,  -0.441477f, 0.009046f,  -0.028515f, 0.095372f,  0.119598f,
+                -0.007553f, -0.0072f,   0.105072f,  0.084314f,  0.23268f,   -0.02906f,  -0.408454f, -1.13439f,
+                0.016202f,  -0.037859f, 0.130873f,  0.129652f,  0.002064f,  -0.011969f, 0.171623f,  0.050218f,
+                0.113831f,  0.028922f,  0.017785f,  0.059708f,  0.037658f,  -0.011245f, 0.097197f,  0.137491f,
+                0.024218f,  0.04739f,   0.091978f,  0.217333f,  0.088418f,  -0.004662f, -0.095168f, -0.397928f,
+                0.02639f,   -0.008501f, 0.068487f,  0.108465f,  0.020069f,  0.018829f,  0.040206f,  0.068473f,
+                0.226458f,  -0.072871f, -0.672384f, -1.447558f, 0.039598f,  0.017471f,  0.187288f,  0.08409f,
+                0.017152f,  -0.00516f,  0.183419f,  0.068469f,  0.063944f,  0.160725f,  -0.022493f, -0.132291f,
+                0.010542f,  0.036318f,  0.074042f,  -0.013323f, 0.00808f,   0.060365f,  0.120566f,  0.21866f,
+                0.046324f,  0.088741f,  0.029469f,  -0.517183f, 0.00917f,   0.011915f,  0.053674f,  0.140168f,
+                0.0033f,    0.022759f,  -0.006196f, 0.063839f,  0.083726f,  -0.088385f, -0.57208f,  -1.454211f,
+                0.020655f,  0.010788f,  0.134951f,  0.109709f,  0.015445f,  -0.015363f, 0.109153f,  0.051209f,
+                0.024297f,  0.139126f,  -0.12358f,  -0.127979f, 0.004587f,  0.004751f,  0.047292f,  0.027066f,
+                0.011003f,  0.069887f,  0.117052f,  0.267419f,  0.039306f,  0.077584f,  0.02579f,   -0.496149f,
+                -0.005569f, 0.015494f,  -0.011662f, 0.105549f,  -0.007015f, 0.031984f,  -0.075742f, 0.0852f,
+                0.023886f,  -0.053107f, -0.325533f, -1.329066f, 0.004688f,  0.034501f,  0.089317f,  0.042463f,
+                0.004212f,  -0.015128f, 0.00892f,   0.028266f,  0.009997f,  0.157822f,  0.020116f,  -0.142337f,
+                0.008199f,  0.046564f,  0.083014f,  0.046307f,  0.006771f,  0.084997f,  0.141935f,  0.228339f,
+                -0.020308f, 0.077745f,  -0.018319f, -0.522311f, 0.010432f,  0.024641f,  0.020571f,  0.097148f,
+                0.002064f,  0.035053f,  -0.121995f, 0.012222f,  -0.030779f, 0.100481f,  -0.331737f, -1.257669f,
+                -0.013079f, 0.021227f,  0.159949f,  0.120097f,  0.005765f,  -0.012335f, -0.005268f, 0.042067f,
+                -0.043972f, 0.102556f,  0.180494f,  -0.084721f, -0.011962f, 0.031302f,  0.112511f,  0.027557f,
+                -0.002085f, 0.082978f,  0.149409f,  0.195091f,  -0.033731f, 0.019861f,  -0.064047f, -0.471328f,
+                -0.004093f, 0.016803f,  0.044635f,  0.058912f,  -0.018735f, 0.035536f,  -0.050373f, -0.002794f,
+                -0.086705f, 0.038435f,  -0.301466f, -1.071246f, -0.028247f, 0.018984f,  0.254702f,  0.141142f,
+                -0.017522f, 0.014843f,  0.079391f,  0.079662f,  -0.051204f, 0.048419f,  0.235604f,  -0.185797f,
+                -0.019569f, 0.02678f,   0.162507f,  0.046435f,  -0.004606f, 0.08806f,   0.18634f,   0.193957f,
+                -0.024333f, -0.01298f,  -0.17977f,  -0.65881f,  -0.003778f, 0.007418f,  0.065439f,  0.104549f,
+                -0.027706f, 0.03301f,   0.057492f,  0.032019f,  -0.135337f, 0.000269f,  -0.250203f, -1.181688f,
+                -0.027022f, -0.006755f, 0.206848f,  0.129268f,  -0.003529f, 0.013445f,  0.181484f,  0.139955f,
+                -0.036587f, 0.065824f,  0.288751f,  -0.110813f, -0.015578f, 0.044818f,  0.17756f,   0.006914f,
+                0.002329f,  0.068982f,  0.189079f,  0.184253f,  0.00301f,   -0.039168f, -0.010855f, -0.393254f,
+                0.000028f,  0.001906f,  0.07217f,   0.063305f,  -0.026144f, 0.028842f,  0.139149f,  0.023377f,
+                0.023362f,  0.023559f,  -0.145386f, -0.863572f, -0.015749f, -0.021364f, 0.172571f,  0.078393f,
+                -0.037253f, 0.014978f,  0.221502f,  0.189111f,  -0.048956f, 0.085409f,  0.325399f,  -0.058294f,
+                -0.028495f, 0.021663f,  0.19392f,   0.02706f,   0.006908f,  0.065751f,  0.176395f,  0.138375f,
+                0.012418f,  -0.031228f, -0.008762f, -0.427345f, -0.013677f, -0.002429f, 0.069655f,  0.019505f,
+                -0.036763f, 0.022528f,  0.201062f,  0.022205f,  0.024528f,  0.06241f,   -0.076237f, -0.840695f,
+                -0.007268f, -0.027865f, 0.211056f,  0.074744f,  -0.053563f, 0.006863f,  0.301432f,  0.192879f,
+                -0.021944f, 0.100535f,  0.19031f,   -0.133746f, -0.006151f, 0.023944f,  0.13561f,   -0.03259f,
+                0.000618f,  0.063736f,  0.180904f,  0.12393f,   0.001275f,  -0.0306f,   -0.032822f, -0.496515f,
+                0.009757f,  0.014602f,  0.004532f,  -0.039969f, -0.015984f, 0.047726f,  0.099865f,  0.003163f,
+                0.026623f,  0.117951f,  -0.076234f, -0.811997f, 0.01301f,   0.020042f,  0.173756f,  -0.036191f,
+                -0.068887f, 0.0229f,    0.245465f,  0.214282f,  -0.011054f, 0.132813f,  0.241014f,  -0.148763f,
+            },
+            std::vector<T>{
+                0.000000f, 0.000000f,   0.000000f,  349.000000f, 209.000000f,  // 0
+                0.000000f, 0.000000f,   0.000000f,  237.625443f, 209.000000f,  // 5
+                0.000000f, 140.305511f, 0.000000f,  349.000000f, 209.000000f,  // 10
+                0.000000f, 0.000000f,   0.000000f,  349.000000f, 65.359818f,   // 15
+                0.000000f, 0.000000f,   0.000000f,  349.000000f, 130.324097f,  // 20
+                0.000000f, 0.000000f,   15.562508f, 97.587891f,  181.224182f,  // 25
+                0.000000f, 0.000000f,   68.539543f, 250.406708f, 209.000000f,  // 30
+                0.000000f, 0.000000f,   0.000000f,  195.881531f, 99.841385f,   // 35
+                0.000000f, 0.000000f,   0.000000f,  78.303986f,  209.000000f,  // 40
+                0.000000f, 0.000000f,   0.000000f,  0.000000f,   209.000000f,  // 45
+            },
+            std::vector<T>{
+                0.3091790f,
+                0.1555300f,
+                0.1549760f,
+                0.1466370f,
+                0.0260620f,
+                0.0177700f,
+                0.0019870f,
+                0.0008570f,
+                0.0002190f,
+                0.0000000f,
+            }),
     };
     return proposalV4Params;
 }
 
 std::vector<ProposalV1Params> generateProposalV1CombinedParams() {
-    const std::vector<std::vector<ProposalV1Params>> proposalTypeParams {
+    const std::vector<std::vector<ProposalV1Params>> proposalTypeParams{
         generateProposalV1Params<element::Type_t::f64>(),
         generateProposalV1Params<element::Type_t::f32>(),
         generateProposalV1Params<element::Type_t::f16>(),
-        generateProposalV1Params<element::Type_t::bf16>()
-        };
+        generateProposalV1Params<element::Type_t::bf16>()};
     std::vector<ProposalV1Params> combinedParams;
 
     for (const auto& params : proposalTypeParams) {
@@ -460,12 +496,11 @@ std::vector<ProposalV1Params> generateProposalV1CombinedParams() {
 }
 
 std::vector<ProposalV4Params> generateProposalV4CombinedParams() {
-    const std::vector<std::vector<ProposalV4Params>> proposalTypeParams {
+    const std::vector<std::vector<ProposalV4Params>> proposalTypeParams{
         generateProposalV4Params<element::Type_t::f64>(),
         generateProposalV4Params<element::Type_t::f32>(),
         generateProposalV4Params<element::Type_t::f16>(),
-        generateProposalV4Params<element::Type_t::bf16>()
-        };
+        generateProposalV4Params<element::Type_t::bf16>()};
     std::vector<ProposalV4Params> combinedParams;
 
     for (const auto& params : proposalTypeParams) {
@@ -474,10 +509,14 @@ std::vector<ProposalV4Params> generateProposalV4CombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Proposal_With_Hardcoded_Refs, ReferenceProposalV1LayerTest,
-    testing::ValuesIn(generateProposalV1CombinedParams()), ReferenceProposalV1LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Proposal_With_Hardcoded_Refs,
+                         ReferenceProposalV1LayerTest,
+                         testing::ValuesIn(generateProposalV1CombinedParams()),
+                         ReferenceProposalV1LayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Proposal_With_Hardcoded_Refs, ReferenceProposalV4LayerTest,
-    testing::ValuesIn(generateProposalV4CombinedParams()), ReferenceProposalV4LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Proposal_With_Hardcoded_Refs,
+                         ReferenceProposalV4LayerTest,
+                         testing::ValuesIn(generateProposalV4CombinedParams()),
+                         ReferenceProposalV4LayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/psroi_pooling.cpp b/src/plugins/template/tests/functional/op_reference/psroi_pooling.cpp
index f6e7596219bc13..0d7207b5ddc885 100644
--- a/src/plugins/template/tests/functional/op_reference/psroi_pooling.cpp
+++ b/src/plugins/template/tests/functional/op_reference/psroi_pooling.cpp
@@ -2,10 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/psroi_pooling.hpp"
+
 #include <gtest/gtest.h>
 
 #include <random>
-#include "openvino/op/psroi_pooling.hpp"
+
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -14,11 +16,16 @@ using namespace ov;
 namespace {
 struct PSROIPoolingParams {
     template <class IT>
-    PSROIPoolingParams(const size_t num_channels, const size_t group_size,
-                       const size_t spatial_bins_x, const size_t spatial_bins_y,
-                       const size_t num_boxes, const float spatial_scale, const std::string& mode,
+    PSROIPoolingParams(const size_t num_channels,
+                       const size_t group_size,
+                       const size_t spatial_bins_x,
+                       const size_t spatial_bins_y,
+                       const size_t num_boxes,
+                       const float spatial_scale,
+                       const std::string& mode,
                        const ov::element::Type& iType,
-                       const std::vector<IT>& coordsValues, const std::vector<IT>& oValues,
+                       const std::vector<IT>& coordsValues,
+                       const std::vector<IT>& oValues,
                        const std::string& test_name = "")
         : groupSize(group_size),
           spatialBinsX(spatial_bins_x),
@@ -31,19 +38,19 @@ struct PSROIPoolingParams {
           coordsData(CreateTensor(iType, coordsValues)),
           refData(CreateTensor(iType, oValues)),
           testcaseName(test_name) {
-              if (mode == "bilinear")
-                  outputDim = num_channels / (spatial_bins_x * spatial_bins_y);
-              else
-                  outputDim = num_channels / (group_size * group_size);
-              imageShape = Shape{2, num_channels, 20, 20};
-              coordsShape = Shape{num_boxes, 5};
-              std::vector<IT> imageValues(shape_size(imageShape.get_shape()));
-              float val = 0;
-              std::generate(imageValues.begin(), imageValues.end(), [val]() mutable -> float {
-                  return val += 0.1;
-              });
-              imageData = CreateTensor(iType, imageValues);
-          }
+        if (mode == "bilinear")
+            outputDim = num_channels / (spatial_bins_x * spatial_bins_y);
+        else
+            outputDim = num_channels / (group_size * group_size);
+        imageShape = Shape{2, num_channels, 20, 20};
+        coordsShape = Shape{num_boxes, 5};
+        std::vector<IT> imageValues(shape_size(imageShape.get_shape()));
+        float val = 0;
+        std::generate(imageValues.begin(), imageValues.end(), [val]() mutable -> float {
+            return val += 0.1;
+        });
+        imageData = CreateTensor(iType, imageValues);
+    }
 
     size_t groupSize;
     size_t spatialBinsX;
@@ -98,7 +105,7 @@ class ReferencePSROIPoolingLayerTest : public testing::TestWithParam<PSROIPoolin
                                                                          static_cast<int>(params.spatialBinsX),
                                                                          static_cast<int>(params.spatialBinsY),
                                                                          params.mode);
-        return std::make_shared<ov::Model>(NodeVector {PSROIPooling}, ParameterVector {image, coords});
+        return std::make_shared<ov::Model>(NodeVector{PSROIPooling}, ParameterVector{image, coords});
     }
 };
 
@@ -110,103 +117,118 @@ template <element::Type_t IN_ET>
 std::vector<PSROIPoolingParams> generatePSROIPoolingFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<PSROIPoolingParams> pSROIPoolingParams {
-        PSROIPoolingParams(8,
-                           2,
-                           1,
+    std::vector<PSROIPoolingParams> pSROIPoolingParams{
+        PSROIPoolingParams(
+            8,
+            2,
+            1,
+            1,
+            3,
+            1,
+            "average",
+            IN_ET,
+            std::vector<T>{// batch_id, x1, y1, x2, y2
+                           0,
                            1,
-                           3,
-                           1,
-                           "average",
-                           IN_ET,
-                           std::vector<T>{
-                                        // batch_id, x1, y1, x2, y2
-                                        0, 1, 2, 4, 6, 1, 0, 3, 10, 4, 0, 10, 7, 11, 13},
-                           std::vector<T>{
-                                        6.2499962, 46.44986,  90.249184, 130.44876, 166.25095, 206.45341, 250.25606, 290.45853,
-                                        326.36069, 366.86316, 408.36572, 448.86816, 486.37045, 526.86841, 568.35828, 608.84839,
-                                        18.100033, 58.199684, 104.09898, 144.1996,  178.10167, 218.20412, 264.1069,  304.20935}),
-        PSROIPoolingParams(8,
                            2,
-                           1,
-                           1,
                            4,
-                           0.2,
-                           "average",
-                           IN_ET,
-                           std::vector<T>{
-                                        // batch_id, x1, y1, x2, y2
-                                        0, 5, 10, 20, 30, 0, 0, 15, 50, 20, 1, 50, 35, 55, 65, 1, 0, 60, 5, 70},
-                           std::vector<T>{
-                                        6.24999619, 46.399868,  90.2491837, 130.398758, 166.250946, 206.403397, 250.256058, 290.408508,
-                                        6.34999657, 46.8498573, 87.3492432, 127.848656, 166.350952, 206.853409, 247.355896, 287.858368,
-                                        338.11142,  378.163879, 424.116669, 464.169128, 498.121185, 538.165649, 584.104431, 624.144653,
-                                        345.111847, 385.164307, 427.116852, 467.169312, 505.121613, 545.16394,  587.103699, 627.143921}),
-        PSROIPoolingParams(12,
-                           3,
-                           2,
-                           3,
-                           5,
+                           6,
                            1,
-                           "bilinear",
-                           IN_ET,
-                           std::vector<T>{
-                                        0,   0.1, 0.2, 0.7,  0.4, 1,    0.4,  0.1, 0.9, 0.3, 0,   0.5, 0.7,
-                                        0.7, 0.9, 1,   0.15, 0.3, 0.65, 0.35, 0,   0.0, 0.2, 0.7, 0.8},
-                           std::vector<T>{
-                                        210.71394, 210.99896, 211.28398, 211.98065, 212.26567, 212.55066, 213.24738, 213.53239, 213.8174,  250.71545,
-                                        251.00047, 251.28548, 251.98218, 252.2672,  252.5522,  253.2489,  253.53392, 253.81892, 687.40869, 687.64606,
-                                        687.88354, 688.67511, 688.91254, 689.14996, 689.94147, 690.17896, 690.41644, 727.40021, 727.6377,  727.87518,
-                                        728.66669, 728.90405, 729.14154, 729.93292, 730.17041, 730.4079,  230.28471, 230.3797,  230.47472, 231.55144,
-                                        231.64642, 231.74141, 232.81813, 232.91313, 233.00813, 270.28638, 270.38141, 270.47641, 271.5531,  271.64813,
-                                        271.74313, 272.81985, 272.91486, 273.00986, 692.63281, 692.87018, 693.1076,  692.94928, 693.18683, 693.42426,
-                                        693.26593, 693.50342, 693.74078, 732.62402, 732.86139, 733.09888, 732.94049, 733.17804, 733.41547, 733.25714,
-                                        733.49463, 733.73199, 215.63843, 215.97093, 216.30345, 219.43855, 219.77106, 220.10358, 223.23871, 223.57123,
-                                        223.90375, 255.63994, 255.97246, 256.30496, 259.44009, 259.77261, 260.10513, 263.2403,  263.57281, 263.9053}),
-        PSROIPoolingParams(12,
-                           4,
-                           2,
+                           0,
                            3,
-                           6,
-                           0.5,
-                           "bilinear",
-                           IN_ET,
-                           std::vector<T>{
-                                        // batch_id, x1, y1, x2, y2
-                                        0, 0.1, 0.2, 0.7, 0.4,  0, 0.5, 0.7, 1.2, 1.3, 0, 1.0,  1.3, 1.2,  1.8,
-                                        1, 0.5, 1.1, 0.7, 1.44, 1, 0.2, 1.1, 0.5, 1.2, 1, 0.34, 1.3, 1.15, 1.35},
-                           std::vector<T>{
-                                        205.40955, 205.50456, 205.59955, 205.69453, 205.83179, 205.9268,  206.0218,  206.11681, 206.25403, 206.34901,
-                                        206.44403, 206.53905, 206.67627, 206.77126, 206.86627, 206.96129, 245.41107, 245.50606, 245.60106, 245.69604,
-                                        245.8333,  245.9283,  246.02327, 246.1183,  246.25554, 246.35052, 246.44556, 246.54054, 246.67778, 246.77277,
-                                        246.86775, 246.96278, 217.84717, 217.95801, 218.06885, 218.17969, 219.11389, 219.22473, 219.33557, 219.44641,
-                                        220.3806,  220.49144, 220.60228, 220.71312, 221.64732, 221.75816, 221.86897, 221.97981, 257.84872, 257.95956,
-                                        258.0704,  258.18124, 259.11545, 259.22629, 259.33713, 259.44797, 260.38217, 260.49301, 260.60385, 260.71469,
-                                        261.6489,  261.75974, 261.87057, 261.98141, 228.9705,  229.00215, 229.03383, 229.06549, 230.02608, 230.05774,
-                                        230.08943, 230.12109, 231.08168, 231.11334, 231.14502, 231.1767,  232.13728, 232.16895, 232.20062, 232.23228,
-                                        268.97217, 269.00385, 269.03549, 269.06717, 270.02777, 270.05945, 270.09109, 270.12277, 271.08337, 271.11502,
-                                        271.1467,  271.17838, 272.13901, 272.17065, 272.2023,  272.23398, 703.65057, 703.68219, 703.71387, 703.74554,
-                                        704.36816, 704.39984, 704.43146, 704.4632,  705.08575, 705.11749, 705.14911, 705.18085, 705.80347, 705.83514,
-                                        705.86676, 705.89844, 743.64136, 743.67291, 743.70459, 743.73633, 744.35889, 744.39056, 744.42218, 744.45392,
-                                        745.07648, 745.10815, 745.13983, 745.17157, 745.79413, 745.82574, 745.85742, 745.8891,  701.86963, 701.91724,
-                                        701.9646,  702.01221, 702.08081, 702.12823, 702.17578, 702.22321, 702.29181, 702.33936, 702.38678, 702.43433,
-                                        702.50293, 702.55035, 702.5979,  702.64545, 741.86041, 741.90796, 741.95538, 742.00293, 742.07153, 742.11896,
-                                        742.1665,  742.21405, 742.28253, 742.33008, 742.3775,  742.42505, 742.49365, 742.54108, 742.58862, 742.63617,
-                                        705.60645, 705.73468, 705.86298, 705.99115, 705.71198, 705.84027, 705.96844, 706.09668, 705.81757, 705.94574,
-                                        706.07397, 706.20215, 705.9231,  706.05127, 706.1795,  706.3078,  745.59698, 745.72534, 745.85352, 745.98169,
-                                        745.70264, 745.83081, 745.95898, 746.08722, 745.80811, 745.93628, 746.06451, 746.19269, 745.91364, 746.04181,
-                                        746.1701,  746.29834}),
+                           10,
+                           4,
+                           0,
+                           10,
+                           7,
+                           11,
+                           13},
+            std::vector<T>{6.2499962, 46.44986,  90.249184, 130.44876, 166.25095, 206.45341, 250.25606, 290.45853,
+                           326.36069, 366.86316, 408.36572, 448.86816, 486.37045, 526.86841, 568.35828, 608.84839,
+                           18.100033, 58.199684, 104.09898, 144.1996,  178.10167, 218.20412, 264.1069,  304.20935}),
+        PSROIPoolingParams(
+            8,
+            2,
+            1,
+            1,
+            4,
+            0.2,
+            "average",
+            IN_ET,
+            std::vector<T>{// batch_id, x1, y1, x2, y2
+                           0, 5, 10, 20, 30, 0, 0, 15, 50, 20, 1, 50, 35, 55, 65, 1, 0, 60, 5, 70},
+            std::vector<T>{6.24999619, 46.399868,  90.2491837, 130.398758, 166.250946, 206.403397, 250.256058,
+                           290.408508, 6.34999657, 46.8498573, 87.3492432, 127.848656, 166.350952, 206.853409,
+                           247.355896, 287.858368, 338.11142,  378.163879, 424.116669, 464.169128, 498.121185,
+                           538.165649, 584.104431, 624.144653, 345.111847, 385.164307, 427.116852, 467.169312,
+                           505.121613, 545.16394,  587.103699, 627.143921}),
+        PSROIPoolingParams(
+            12,
+            3,
+            2,
+            3,
+            5,
+            1,
+            "bilinear",
+            IN_ET,
+            std::vector<T>{0,   0.1, 0.2, 0.7,  0.4, 1,    0.4,  0.1, 0.9, 0.3, 0,   0.5, 0.7,
+                           0.7, 0.9, 1,   0.15, 0.3, 0.65, 0.35, 0,   0.0, 0.2, 0.7, 0.8},
+            std::vector<T>{
+                210.71394, 210.99896, 211.28398, 211.98065, 212.26567, 212.55066, 213.24738, 213.53239, 213.8174,
+                250.71545, 251.00047, 251.28548, 251.98218, 252.2672,  252.5522,  253.2489,  253.53392, 253.81892,
+                687.40869, 687.64606, 687.88354, 688.67511, 688.91254, 689.14996, 689.94147, 690.17896, 690.41644,
+                727.40021, 727.6377,  727.87518, 728.66669, 728.90405, 729.14154, 729.93292, 730.17041, 730.4079,
+                230.28471, 230.3797,  230.47472, 231.55144, 231.64642, 231.74141, 232.81813, 232.91313, 233.00813,
+                270.28638, 270.38141, 270.47641, 271.5531,  271.64813, 271.74313, 272.81985, 272.91486, 273.00986,
+                692.63281, 692.87018, 693.1076,  692.94928, 693.18683, 693.42426, 693.26593, 693.50342, 693.74078,
+                732.62402, 732.86139, 733.09888, 732.94049, 733.17804, 733.41547, 733.25714, 733.49463, 733.73199,
+                215.63843, 215.97093, 216.30345, 219.43855, 219.77106, 220.10358, 223.23871, 223.57123, 223.90375,
+                255.63994, 255.97246, 256.30496, 259.44009, 259.77261, 260.10513, 263.2403,  263.57281, 263.9053}),
+        PSROIPoolingParams(
+            12,
+            4,
+            2,
+            3,
+            6,
+            0.5,
+            "bilinear",
+            IN_ET,
+            std::vector<T>{// batch_id, x1, y1, x2, y2
+                           0, 0.1, 0.2, 0.7, 0.4,  0, 0.5, 0.7, 1.2, 1.3, 0, 1.0,  1.3, 1.2,  1.8,
+                           1, 0.5, 1.1, 0.7, 1.44, 1, 0.2, 1.1, 0.5, 1.2, 1, 0.34, 1.3, 1.15, 1.35},
+            std::vector<T>{
+                205.40955, 205.50456, 205.59955, 205.69453, 205.83179, 205.9268,  206.0218,  206.11681, 206.25403,
+                206.34901, 206.44403, 206.53905, 206.67627, 206.77126, 206.86627, 206.96129, 245.41107, 245.50606,
+                245.60106, 245.69604, 245.8333,  245.9283,  246.02327, 246.1183,  246.25554, 246.35052, 246.44556,
+                246.54054, 246.67778, 246.77277, 246.86775, 246.96278, 217.84717, 217.95801, 218.06885, 218.17969,
+                219.11389, 219.22473, 219.33557, 219.44641, 220.3806,  220.49144, 220.60228, 220.71312, 221.64732,
+                221.75816, 221.86897, 221.97981, 257.84872, 257.95956, 258.0704,  258.18124, 259.11545, 259.22629,
+                259.33713, 259.44797, 260.38217, 260.49301, 260.60385, 260.71469, 261.6489,  261.75974, 261.87057,
+                261.98141, 228.9705,  229.00215, 229.03383, 229.06549, 230.02608, 230.05774, 230.08943, 230.12109,
+                231.08168, 231.11334, 231.14502, 231.1767,  232.13728, 232.16895, 232.20062, 232.23228, 268.97217,
+                269.00385, 269.03549, 269.06717, 270.02777, 270.05945, 270.09109, 270.12277, 271.08337, 271.11502,
+                271.1467,  271.17838, 272.13901, 272.17065, 272.2023,  272.23398, 703.65057, 703.68219, 703.71387,
+                703.74554, 704.36816, 704.39984, 704.43146, 704.4632,  705.08575, 705.11749, 705.14911, 705.18085,
+                705.80347, 705.83514, 705.86676, 705.89844, 743.64136, 743.67291, 743.70459, 743.73633, 744.35889,
+                744.39056, 744.42218, 744.45392, 745.07648, 745.10815, 745.13983, 745.17157, 745.79413, 745.82574,
+                745.85742, 745.8891,  701.86963, 701.91724, 701.9646,  702.01221, 702.08081, 702.12823, 702.17578,
+                702.22321, 702.29181, 702.33936, 702.38678, 702.43433, 702.50293, 702.55035, 702.5979,  702.64545,
+                741.86041, 741.90796, 741.95538, 742.00293, 742.07153, 742.11896, 742.1665,  742.21405, 742.28253,
+                742.33008, 742.3775,  742.42505, 742.49365, 742.54108, 742.58862, 742.63617, 705.60645, 705.73468,
+                705.86298, 705.99115, 705.71198, 705.84027, 705.96844, 706.09668, 705.81757, 705.94574, 706.07397,
+                706.20215, 705.9231,  706.05127, 706.1795,  706.3078,  745.59698, 745.72534, 745.85352, 745.98169,
+                745.70264, 745.83081, 745.95898, 746.08722, 745.80811, 745.93628, 746.06451, 746.19269, 745.91364,
+                746.04181, 746.1701,  746.29834}),
     };
     return pSROIPoolingParams;
 }
 
 std::vector<PSROIPoolingParams> generatePSROIPoolingCombinedParams() {
-    const std::vector<std::vector<PSROIPoolingParams>> pSROIPoolingTypeParams {
+    const std::vector<std::vector<PSROIPoolingParams>> pSROIPoolingTypeParams{
         generatePSROIPoolingFloatParams<element::Type_t::f64>(),
         generatePSROIPoolingFloatParams<element::Type_t::f32>(),
         generatePSROIPoolingFloatParams<element::Type_t::f16>(),
-        generatePSROIPoolingFloatParams<element::Type_t::bf16>()
-        };
+        generatePSROIPoolingFloatParams<element::Type_t::bf16>()};
     std::vector<PSROIPoolingParams> combinedParams;
 
     for (const auto& params : pSROIPoolingTypeParams) {
@@ -215,7 +237,9 @@ std::vector<PSROIPoolingParams> generatePSROIPoolingCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_PSROIPooling_With_Hardcoded_Refs, ReferencePSROIPoolingLayerTest,
-    testing::ValuesIn(generatePSROIPoolingCombinedParams()), ReferencePSROIPoolingLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_PSROIPooling_With_Hardcoded_Refs,
+                         ReferencePSROIPoolingLayerTest,
+                         testing::ValuesIn(generatePSROIPoolingCombinedParams()),
+                         ReferencePSROIPoolingLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/random_uniform.cpp b/src/plugins/template/tests/functional/op_reference/random_uniform.cpp
index 2ffc8c351e2b0d..9da97ef7c0b426 100644
--- a/src/plugins/template/tests/functional/op_reference/random_uniform.cpp
+++ b/src/plugins/template/tests/functional/op_reference/random_uniform.cpp
@@ -59,22 +59,22 @@ class ReferenceRandomUniformLayerTest : public testing::TestWithParam<RandomUnif
 
 private:
     static std::shared_ptr<Model> CreateFunction(const std::vector<int64_t>& out_shape,
-                                                    const reference_tests::Tensor& min_val,
-                                                    const reference_tests::Tensor& max_val,
-                                                    const ov::element::Type& out_type,
-                                                    int64_t global_seed,
-                                                    int64_t op_seed) {
+                                                 const reference_tests::Tensor& min_val,
+                                                 const reference_tests::Tensor& max_val,
+                                                 const ov::element::Type& out_type,
+                                                 int64_t global_seed,
+                                                 int64_t op_seed) {
         const auto min_val_param = std::make_shared<opset8::Parameter>(min_val.type, min_val.shape);
         const auto max_val_param = std::make_shared<opset8::Parameter>(max_val.type, max_val.shape);
         auto out_shape_ = std::make_shared<opset8::Constant>(element::i64, Shape{out_shape.size()}, out_shape);
 
         return std::make_shared<ov::Model>(NodeVector{std::make_shared<opset8::RandomUniform>(out_shape_,
-                                                                                             min_val_param,
-                                                                                             max_val_param,
-                                                                                             out_type,
-                                                                                             global_seed,
-                                                                                             op_seed)},
-                                          ParameterVector{min_val_param, max_val_param});
+                                                                                              min_val_param,
+                                                                                              max_val_param,
+                                                                                              out_type,
+                                                                                              global_seed,
+                                                                                              op_seed)},
+                                           ParameterVector{min_val_param, max_val_param});
     }
 };
 
@@ -95,13 +95,14 @@ INSTANTIATE_TEST_SUITE_P(
                             element::Type_t::f32,
                             150,
                             10,
-                            reference_tests::Tensor{{3, 2, 4},
-                                   element::f32,
-                                   std::vector<float>{0.70112360, 0.30539632, 0.93931055, 0.94560349, 0.11694777,
-                                                      0.50770056, 0.51971972, 0.22727466, 0.99137402, 0.35519040,
-                                                      0.82692313, 0.59864855, 0.31364107, 0.57481313, 0.41399086,
-                                                      0.96308255, 0.37140799, 0.85253167, 0.09358585, 0.08200955,
-                                                      0.23655081, 0.81056309, 0.74226606, 0.76106691}},
+                            reference_tests::Tensor{
+                                {3, 2, 4},
+                                element::f32,
+                                std::vector<float>{0.70112360, 0.30539632, 0.93931055, 0.94560349, 0.11694777,
+                                                   0.50770056, 0.51971972, 0.22727466, 0.99137402, 0.35519040,
+                                                   0.82692313, 0.59864855, 0.31364107, 0.57481313, 0.41399086,
+                                                   0.96308255, 0.37140799, 0.85253167, 0.09358585, 0.08200955,
+                                                   0.23655081, 0.81056309, 0.74226606, 0.76106691}},
                             "float32_default_min_max"),
         RandomUniformParams(std::vector<int64_t>{3, 2, 4},
                             reference_tests::Tensor{{1}, element::f16, std::vector<float16>{0}},
@@ -109,13 +110,14 @@ INSTANTIATE_TEST_SUITE_P(
                             element::Type_t::f16,
                             150,
                             10,
-                            reference_tests::Tensor{{3, 2, 4},
-                                   element::f16,
-                                   std::vector<float16>{0.60449219, 0.80664062, 0.83203125, 0.38378906, 0.03613281,
-                                                        0.08300781, 0.54394531, 0.83398438, 0.33593750, 0.71972656,
-                                                        0.15429688, 0.12890625, 0.34765625, 0.86914062, 0.41308594,
-                                                        0.57226562, 0.57421875, 0.93945312, 0.65527344, 0.82226562,
-                                                        0.82421875, 0.13281250, 0.64355469, 0.66015625}},
+                            reference_tests::Tensor{
+                                {3, 2, 4},
+                                element::f16,
+                                std::vector<float16>{0.60449219, 0.80664062, 0.83203125, 0.38378906, 0.03613281,
+                                                     0.08300781, 0.54394531, 0.83398438, 0.33593750, 0.71972656,
+                                                     0.15429688, 0.12890625, 0.34765625, 0.86914062, 0.41308594,
+                                                     0.57226562, 0.57421875, 0.93945312, 0.65527344, 0.82226562,
+                                                     0.82421875, 0.13281250, 0.64355469, 0.66015625}},
                             "float16_default_min_max"),
         RandomUniformParams(std::vector<int64_t>{3, 2, 4},
                             reference_tests::Tensor{{1}, element::f32, std::vector<float>{-650}},
@@ -123,14 +125,15 @@ INSTANTIATE_TEST_SUITE_P(
                             element::Type_t::f32,
                             150,
                             10,
-                            reference_tests::Tensor{{3, 2, 4},
-                                   element::f32,
-                                   std::vector<float>{121.23596191,  -314.06405640, 383.24157715,  390.16381836,
-                                                      -521.35742188, -91.52935791,  -78.30828857,  -399.99786377,
-                                                      440.51147461,  -259.29055786, 259.61541748,  8.51342773,
-                                                      -304.99481201, -17.70556641,  -194.61004639, 409.39074707,
-                                                      -241.45120239, 287.78485107,  -547.05554199, -559.78948975,
-                                                      -389.79409790, 241.61938477,  166.49267578,  187.17358398}},
+                            reference_tests::Tensor{
+                                {3, 2, 4},
+                                element::f32,
+                                std::vector<float>{121.23596191,  -314.06405640, 383.24157715,  390.16381836,
+                                                   -521.35742188, -91.52935791,  -78.30828857,  -399.99786377,
+                                                   440.51147461,  -259.29055786, 259.61541748,  8.51342773,
+                                                   -304.99481201, -17.70556641,  -194.61004639, 409.39074707,
+                                                   -241.45120239, 287.78485107,  -547.05554199, -559.78948975,
+                                                   -389.79409790, 241.61938477,  166.49267578,  187.17358398}},
                             "float32_non_default_min_max"),
         RandomUniformParams(std::vector<int64_t>{3, 2, 4},
                             reference_tests::Tensor{{1}, element::f16, std::vector<float16>{-1.5}},
@@ -138,13 +141,14 @@ INSTANTIATE_TEST_SUITE_P(
                             element::Type_t::f16,
                             150,
                             10,
-                            reference_tests::Tensor{{3, 2, 4},
-                                   element::f16,
-                                   std::vector<float16>{-1.19726562, -1.09667969, -1.08398438, -1.30859375, -1.48242188,
-                                                        -1.45898438, -1.22851562, -1.08300781, -1.33203125, -1.14062500,
-                                                        -1.42285156, -1.43554688, -1.32617188, -1.06542969, -1.29296875,
-                                                        -1.21386719, -1.21289062, -1.03027344, -1.17187500, -1.08886719,
-                                                        -1.08789062, -1.43359375, -1.17773438, -1.16992188}},
+                            reference_tests::Tensor{
+                                {3, 2, 4},
+                                element::f16,
+                                std::vector<float16>{-1.19726562, -1.09667969, -1.08398438, -1.30859375, -1.48242188,
+                                                     -1.45898438, -1.22851562, -1.08300781, -1.33203125, -1.14062500,
+                                                     -1.42285156, -1.43554688, -1.32617188, -1.06542969, -1.29296875,
+                                                     -1.21386719, -1.21289062, -1.03027344, -1.17187500, -1.08886719,
+                                                     -1.08789062, -1.43359375, -1.17773438, -1.16992188}},
                             "float16_non_default_min_max"),
         RandomUniformParams(std::vector<int64_t>{2, 3, 4},
                             reference_tests::Tensor{{1}, element::i32, std::vector<int32_t>{-100}},
@@ -153,11 +157,11 @@ INSTANTIATE_TEST_SUITE_P(
                             100,
                             350,
                             reference_tests::Tensor{{2, 3, 4},
-                                   element::i32,
-                                   std::vector<int32_t>{
-                                       22, -56, -33, -89, -98, -33, -3,  -48, -82, 5,  -66, 21,
-                                       29, -42, -73, -37, 3,   36,  -35, 20,  -11, -8, -78, 47,
-                                   }},
+                                                    element::i32,
+                                                    std::vector<int32_t>{
+                                                        22, -56, -33, -89, -98, -33, -3,  -48, -82, 5,  -66, 21,
+                                                        29, -42, -73, -37, 3,   36,  -35, 20,  -11, -8, -78, 47,
+                                                    }},
                             "int32"),
         RandomUniformParams(std::vector<int64_t>{5, 4, 3},
                             reference_tests::Tensor{{1}, element::i64, std::vector<int64_t>{-2600}},
@@ -165,14 +169,15 @@ INSTANTIATE_TEST_SUITE_P(
                             element::Type_t::i64,
                             755,
                             951,
-                            reference_tests::Tensor{{5, 4, 3},
-                                   element::i64,
-                                   std::vector<int64_t>{
-                                       2116, -1581, 2559,  -339,  -1660, 519,   90,   2027,  -210, 3330, 1831,  -1737,
-                                       2683, 2661,  3473,  1220,  3534,  -2384, 2199, 1935,  499,  2861, 2743,  3223,
-                                       -531, -836,  -65,   3435,  632,   1765,  2613, 1891,  1698, 3069, 169,   -792,
-                                       -32,  2976,  -1552, -2588, 3327,  -1756, 2637, -1084, 3567, -778, -1465, 2967,
-                                       1242, 2672,  -1585, -2271, 3536,  -1502, 400,  2241,  3126, 908,  1073,  -2110}},
+                            reference_tests::Tensor{
+                                {5, 4, 3},
+                                element::i64,
+                                std::vector<int64_t>{
+                                    2116, -1581, 2559,  -339,  -1660, 519,   90,   2027,  -210, 3330, 1831,  -1737,
+                                    2683, 2661,  3473,  1220,  3534,  -2384, 2199, 1935,  499,  2861, 2743,  3223,
+                                    -531, -836,  -65,   3435,  632,   1765,  2613, 1891,  1698, 3069, 169,   -792,
+                                    -32,  2976,  -1552, -2588, 3327,  -1756, 2637, -1084, 3567, -778, -1465, 2967,
+                                    1242, 2672,  -1585, -2271, 3536,  -1502, 400,  2241,  3126, 908,  1073,  -2110}},
                             "int64"),
         RandomUniformParams(std::vector<int64_t>{7, 3},
                             reference_tests::Tensor{{1}, element::bf16, std::vector<bfloat16>{0}},
@@ -180,12 +185,13 @@ INSTANTIATE_TEST_SUITE_P(
                             element::Type_t::bf16,
                             4978,
                             5164,
-                            reference_tests::Tensor{{7, 3},
-                                   element::bf16,
-                                   std::vector<bfloat16>{0.8984375, 0.84375,   0.1640625, 0.1875,   0.46875,  0.6875,
-                                                         0.5234375, 0.3046875, 0.9140625, 0.453125, 0.953125, 0.328125,
-                                                         0.359375,  0.1875,    0.9453125, 0.390625, 0.21875,  0.9921875,
-                                                         0.8203125, 0.453125,  0.875}},
+                            reference_tests::Tensor{
+                                {7, 3},
+                                element::bf16,
+                                std::vector<bfloat16>{0.8984375, 0.84375,   0.1640625, 0.1875,   0.46875,  0.6875,
+                                                      0.5234375, 0.3046875, 0.9140625, 0.453125, 0.953125, 0.328125,
+                                                      0.359375,  0.1875,    0.9453125, 0.390625, 0.21875,  0.9921875,
+                                                      0.8203125, 0.453125,  0.875}},
                             "bfloat16_default_min_max"),
         RandomUniformParams(std::vector<int64_t>{7, 3},
                             reference_tests::Tensor{{1}, element::bf16, std::vector<bfloat16>{-150}},
@@ -193,10 +199,11 @@ INSTANTIATE_TEST_SUITE_P(
                             element::Type_t::bf16,
                             4978,
                             5164,
-                            reference_tests::Tensor{{7, 3},
-                                   element::bf16,
-                                   std::vector<bfloat16>{164, 146, -92.5, -84.5, 14,  90,    33,  -43.5, 170, 8,  182,
-                                                         -35, -24, -84.5, 180,   -14, -73.5, 198, 138,   8,   156}},
+                            reference_tests::Tensor{
+                                {7, 3},
+                                element::bf16,
+                                std::vector<bfloat16>{164, 146, -92.5, -84.5, 14,  90,    33,  -43.5, 170, 8,  182,
+                                                      -35, -24, -84.5, 180,   -14, -73.5, 198, 138,   8,   156}},
                             "bfloat16_non_default_min_max")),
     ReferenceRandomUniformLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/range.cpp b/src/plugins/template/tests/functional/op_reference/range.cpp
index 392d015480640c..1948fcb0919c6b 100644
--- a/src/plugins/template/tests/functional/op_reference/range.cpp
+++ b/src/plugins/template/tests/functional/op_reference/range.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/range.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/range.hpp"
 #include "openvino/op/constant.hpp"
 
 using namespace ov;
@@ -104,13 +106,13 @@ class ReferenceRangeV0LayerTest : public testing::TestWithParam<RangeParams>, pu
 
 private:
     static std::shared_ptr<Model> CreateFunction(Shape& ishape,
-                                                    Shape& oshape,
-                                                    element::Type& itype,
-                                                    element::Type& otype,
-                                                    element::Type& ntype,
-                                                    float fstart,
-                                                    float fstop,
-                                                    float fstep) {
+                                                 Shape& oshape,
+                                                 element::Type& itype,
+                                                 element::Type& otype,
+                                                 element::Type& ntype,
+                                                 float fstart,
+                                                 float fstop,
+                                                 float fstep) {
         auto start = CreateConstant(ishape, ntype, fstart);
         auto stop = CreateConstant(ishape, ntype, fstop);
         auto step = CreateConstant(ishape, ntype, fstep);
@@ -147,13 +149,13 @@ class ReferenceRangeV4LayerTest : public testing::TestWithParam<RangeParams>, pu
 
 private:
     static std::shared_ptr<Model> CreateFunction(Shape& ishape,
-                                                    Shape& oshape,
-                                                    element::Type& itype,
-                                                    element::Type& otype,
-                                                    element::Type& ntype,
-                                                    float fstart,
-                                                    float fstop,
-                                                    float fstep) {
+                                                 Shape& oshape,
+                                                 element::Type& itype,
+                                                 element::Type& otype,
+                                                 element::Type& ntype,
+                                                 float fstart,
+                                                 float fstop,
+                                                 float fstep) {
         auto start = CreateConstant(ishape, ntype, fstart);
         auto stop = CreateConstant(ishape, ntype, fstop);
         auto step = CreateConstant(ishape, ntype, fstep);
@@ -175,26 +177,8 @@ std::vector<RangeParams> generateParamsForRangeV0Int() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     std::vector<RangeParams> params{
-        RangeParams(
-            ov::Shape{},
-            ov::Shape{4},
-            IN_ET,
-            IN_ET,
-            IN_ET,
-            std::vector<T>{-5, -2, 1, 4},
-            -5,
-            6,
-            3),
-        RangeParams(
-            ov::Shape{},
-            ov::Shape{2},
-            IN_ET,
-            IN_ET,
-            IN_ET,
-            std::vector<T>{10, 7},
-            10,
-            5,
-            -3)};
+        RangeParams(ov::Shape{}, ov::Shape{4}, IN_ET, IN_ET, IN_ET, std::vector<T>{-5, -2, 1, 4}, -5, 6, 3),
+        RangeParams(ov::Shape{}, ov::Shape{2}, IN_ET, IN_ET, IN_ET, std::vector<T>{10, 7}, 10, 5, -3)};
     return params;
 }
 
@@ -202,18 +186,15 @@ template <element::Type_t IN_ET>
 std::vector<RangeParams> generateParamsForRangeV0UnsignedInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<RangeParams> params{
-        RangeParams(
-            ov::Shape{},
-            ov::Shape{10},
-            IN_ET,
-            IN_ET,
-            IN_ET,
-            std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9},
-            0,
-            10,
-            1)
-    };
+    std::vector<RangeParams> params{RangeParams(ov::Shape{},
+                                                ov::Shape{10},
+                                                IN_ET,
+                                                IN_ET,
+                                                IN_ET,
+                                                std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9},
+                                                0,
+                                                10,
+                                                1)};
     return params;
 }
 
@@ -231,15 +212,7 @@ std::vector<RangeParams> generateParamsForRangeV0Float() {
                     0.0f,
                     1.0f,
                     0.25f),
-        RangeParams(ov::Shape{},
-                    ov::Shape{},
-                    IN_ET,
-                    IN_ET,
-                    IN_ET,
-                    std::vector<T>{1.0f, 4.f, 7.f},
-                    1.0f,
-                    10.0f,
-                    3.0f),
+        RangeParams(ov::Shape{}, ov::Shape{}, IN_ET, IN_ET, IN_ET, std::vector<T>{1.0f, 4.f, 7.f}, 1.0f, 10.0f, 3.0f),
         RangeParams(ov::Shape{},
                     ov::Shape{10},
                     IN_ET,
@@ -266,27 +239,8 @@ std::vector<RangeParams> generateParamsForRangeV4Int() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     std::vector<RangeParams> params{
-        RangeParams(
-            ov::Shape{},
-            ov::Shape{4},
-            IN_ET,
-            IN_ET,
-            IN_ET,
-            std::vector<T>{-5, -2, 1, 4},
-            -5,
-            6,
-            3),
-        RangeParams(
-            ov::Shape{},
-            ov::Shape{2},
-            IN_ET,
-            IN_ET,
-            IN_ET,
-            std::vector<T>{10, 7},
-            10,
-            5,
-            -3)
-    };
+        RangeParams(ov::Shape{}, ov::Shape{4}, IN_ET, IN_ET, IN_ET, std::vector<T>{-5, -2, 1, 4}, -5, 6, 3),
+        RangeParams(ov::Shape{}, ov::Shape{2}, IN_ET, IN_ET, IN_ET, std::vector<T>{10, 7}, 10, 5, -3)};
 
     return params;
 }
@@ -295,28 +249,24 @@ template <element::Type_t IN_ET>
 std::vector<RangeParams> generateParamsForRangeV4UnsignedInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<RangeParams> params{
-        RangeParams(
-            ov::Shape{},
-            ov::Shape{10},
-            IN_ET,
-            IN_ET,
-            element::Type_t::f32,
-            std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
-            1.2f,
-            11.3f,
-            1.6f),
-        RangeParams(
-            ov::Shape{},
-            ov::Shape{10},
-            IN_ET,
-            IN_ET,
-            IN_ET,
-            std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9},
-            0,
-            10,
-            1)
-    };
+    std::vector<RangeParams> params{RangeParams(ov::Shape{},
+                                                ov::Shape{10},
+                                                IN_ET,
+                                                IN_ET,
+                                                element::Type_t::f32,
+                                                std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10},
+                                                1.2f,
+                                                11.3f,
+                                                1.6f),
+                                    RangeParams(ov::Shape{},
+                                                ov::Shape{10},
+                                                IN_ET,
+                                                IN_ET,
+                                                IN_ET,
+                                                std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9},
+                                                0,
+                                                10,
+                                                1)};
 
     return params;
 }
@@ -352,8 +302,7 @@ std::vector<RangeParams> generateParamsForRangeV4Float() {
                     std::vector<T>{2.0f, 1.75f, 1.5f, 1.25f, 1.0f, 0.75f, 0.5f, 0.25f},
                     2,
                     0,
-                    -0.25)
-    };
+                    -0.25)};
 
     return params;
 }
@@ -404,16 +353,14 @@ std::vector<RangeParams> generateCombinedParamsForRangeV4() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Range_V0_With_Hardcoded_Refs,
-    ReferenceRangeV0LayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForRangeV0()),
-    ReferenceRangeV0LayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Range_V4_With_Hardcoded_Refs,
-    ReferenceRangeV4LayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForRangeV4()),
-    ReferenceRangeV4LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Range_V0_With_Hardcoded_Refs,
+                         ReferenceRangeV0LayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForRangeV0()),
+                         ReferenceRangeV0LayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Range_V4_With_Hardcoded_Refs,
+                         ReferenceRangeV4LayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForRangeV4()),
+                         ReferenceRangeV4LayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/rdft.cpp b/src/plugins/template/tests/functional/op_reference/rdft.cpp
index 91e247b28918ee..41bfc9d0645ac8 100644
--- a/src/plugins/template/tests/functional/op_reference/rdft.cpp
+++ b/src/plugins/template/tests/functional/op_reference/rdft.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/rdft.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/rdft.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -90,306 +91,262 @@ TEST_P(ReferenceRDFTLayerTest, CompareWithHardcodedRefs) {
 }
 
 static const std::vector<float> input_data = {
-    0.10606491,  0.7454715,   0.57231355,  0.4582412,   0.3847059,   0.27398932, 0.66796243, 0.395475,
-    0.2815729,   0.7799197,   0.59909415,  0.12294636,  0.38957402,  0.97498834, 0.46759892, 0.14017141,
-    0.04206858,  0.7279963,   0.61560553,  0.9027321,   0.6226334,   0.2601217,  0.5555177,  0.40498647,
-    0.14175586,  0.57774633,  0.52652127,  0.9385691,   0.9588788,   0.9844318,  0.23095612, 0.09707925,
-    0.24574867,  0.6907577,   0.1974319,   0.8295272,   0.34612727,  0.51401484, 0.66115797, 0.9336245,
-    0.06690067,  0.7468897,   0.39028263,  0.53575844,  0.060429193, 0.8913558,  0.77787375, 0.6701197,
-    0.7350527,   0.6636995,   0.18176624,  0.8629976,   0.45142895,  0.6497297,  0.159372,   0.40598175,
-    0.7988516,   0.7291543,   0.07090418,  0.7697132,   0.4972157,   0.7669217,  0.67975855, 0.13026066,
-    0.6587437,   0.24532892,  0.24545169,  0.83795583,  0.105490535, 0.7264323,  0.94568557, 0.7216649,
-    0.14389831,  0.7930531,   0.70895344,  0.9724701,   0.9775157,   0.49999878, 0.65569246, 0.26876843,
-    0.63248956,  0.85201293,  0.5689624,   0.023386303, 0.5546464,   0.36860028, 0.9603114,  0.39123482,
-    0.0380728,   0.89212376,  0.14387614,  0.63858676,  0.10003748,  0.8906635,  0.06681054, 0.7458642,
-    0.45452347,  0.54724604,  0.6496482,   0.7818356,   0.6608355,   0.77711326, 0.24588613, 0.013456763,
-    0.355845,    0.80388206,  0.027993264, 0.73677206,  0.52755004,  0.9052324,  0.54311025, 0.5367805,
-    0.4131242,   0.7752338,   0.109669454, 0.13664648,  0.7828739,   0.9083969,  0.5247593,  0.7493595,
-    0.19275227,  0.007190853, 0.6087981,   0.344136,    0.46909887,  0.41924855, 0.7072913,  0.19932869,
-    0.5303847,   0.651384,    0.06686331,  0.9717932,   0.65702224,  0.11786682, 0.3154073,  0.88923013,
-    0.5564087,   0.91047823,  0.28466642,  0.0934668,   0.88953066,  0.9919338,  0.18322521, 0.8185455,
-    0.566391,    0.014207997, 0.29673064,  0.6347744,   0.6801958,   0.39601147, 0.34374171, 0.7216888,
-    0.6152569,   0.76679546,  0.5860851,   0.4276813,   0.79339284,  0.13130653, 0.68764234, 0.053128112,
-    0.02611321,  0.2982243,   0.7618372,   0.3331729,   0.5468192,   0.15707079, 0.28592056, 0.15286565,
-    0.9368963,   0.350671,    0.4336494,   0.08934934,  0.41172776,  0.5850259,  0.70730376, 0.8598349,
-    0.088788144, 0.26711187,  0.8002491,   0.19422275,  0.8312039,   0.5198718,  0.40111357, 0.98375803,
-    0.77703434,  0.037818834, 0.704231,    0.689808,    0.17102319,  0.42153922, 0.7278252,  0.8030207,
-    0.9101717,   0.0199644,   0.13768466,  0.55669,     0.17991355,  0.6720098,  0.7733328,  0.20881335};
+    0.10606491, 0.7454715,   0.57231355,  0.4582412,  0.3847059,   0.27398932,  0.66796243,  0.395475,    0.2815729,
+    0.7799197,  0.59909415,  0.12294636,  0.38957402, 0.97498834,  0.46759892,  0.14017141,  0.04206858,  0.7279963,
+    0.61560553, 0.9027321,   0.6226334,   0.2601217,  0.5555177,   0.40498647,  0.14175586,  0.57774633,  0.52652127,
+    0.9385691,  0.9588788,   0.9844318,   0.23095612, 0.09707925,  0.24574867,  0.6907577,   0.1974319,   0.8295272,
+    0.34612727, 0.51401484,  0.66115797,  0.9336245,  0.06690067,  0.7468897,   0.39028263,  0.53575844,  0.060429193,
+    0.8913558,  0.77787375,  0.6701197,   0.7350527,  0.6636995,   0.18176624,  0.8629976,   0.45142895,  0.6497297,
+    0.159372,   0.40598175,  0.7988516,   0.7291543,  0.07090418,  0.7697132,   0.4972157,   0.7669217,   0.67975855,
+    0.13026066, 0.6587437,   0.24532892,  0.24545169, 0.83795583,  0.105490535, 0.7264323,   0.94568557,  0.7216649,
+    0.14389831, 0.7930531,   0.70895344,  0.9724701,  0.9775157,   0.49999878,  0.65569246,  0.26876843,  0.63248956,
+    0.85201293, 0.5689624,   0.023386303, 0.5546464,  0.36860028,  0.9603114,   0.39123482,  0.0380728,   0.89212376,
+    0.14387614, 0.63858676,  0.10003748,  0.8906635,  0.06681054,  0.7458642,   0.45452347,  0.54724604,  0.6496482,
+    0.7818356,  0.6608355,   0.77711326,  0.24588613, 0.013456763, 0.355845,    0.80388206,  0.027993264, 0.73677206,
+    0.52755004, 0.9052324,   0.54311025,  0.5367805,  0.4131242,   0.7752338,   0.109669454, 0.13664648,  0.7828739,
+    0.9083969,  0.5247593,   0.7493595,   0.19275227, 0.007190853, 0.6087981,   0.344136,    0.46909887,  0.41924855,
+    0.7072913,  0.19932869,  0.5303847,   0.651384,   0.06686331,  0.9717932,   0.65702224,  0.11786682,  0.3154073,
+    0.88923013, 0.5564087,   0.91047823,  0.28466642, 0.0934668,   0.88953066,  0.9919338,   0.18322521,  0.8185455,
+    0.566391,   0.014207997, 0.29673064,  0.6347744,  0.6801958,   0.39601147,  0.34374171,  0.7216888,   0.6152569,
+    0.76679546, 0.5860851,   0.4276813,   0.79339284, 0.13130653,  0.68764234,  0.053128112, 0.02611321,  0.2982243,
+    0.7618372,  0.3331729,   0.5468192,   0.15707079, 0.28592056,  0.15286565,  0.9368963,   0.350671,    0.4336494,
+    0.08934934, 0.41172776,  0.5850259,   0.70730376, 0.8598349,   0.088788144, 0.26711187,  0.8002491,   0.19422275,
+    0.8312039,  0.5198718,   0.40111357,  0.98375803, 0.77703434,  0.037818834, 0.704231,    0.689808,    0.17102319,
+    0.42153922, 0.7278252,   0.8030207,   0.9101717,  0.0199644,   0.13768466,  0.55669,     0.17991355,  0.6720098,
+    0.7733328,  0.20881335};
 
 static const std::vector<float> expected_rdft1d_results_1 = {
-    4.6657147,   -1.1622906e-06, 0.21456887,    -0.14946258, -0.20476034,  -0.37063062,
-    -0.31414136, 0.5099413,      -1.1779613,    0.07057127,  -0.64047664,  -1.0058284e-07,
-    4.982774,    -1.1771917e-06, 0.6607505,     0.18829148,  -0.9772357,   1.4243596,
-    0.8640026,   0.34923682,     0.33401352,    0.25859502,  -0.7548928,   8.940697e-08,
-    5.9711604,   -1.4901161e-06, 0.5638976,     1.5429841,   -0.52065414,  0.24638398,
-    -0.27140495, 0.5040715,      0.5360231,     0.3234269,   -0.36054826,  1.7508864e-07,
-    4.7464237,   -1.2218952e-06, -0.29650804,   0.80609477,  -0.161426,    1.0022418,
-    -0.50812817, 0.7967348,      0.4394225,     -0.1588624,  -1.3835809,   -7.4505806e-08,
-    5.53836,     -1.7136335e-06, -0.38635445,   0.8284859,   -0.23278837,  -0.63777345,
-    -0.93614054, 0.3215857,      -0.14075133,   -0.67071164, -1.4772836,   2.0861626e-07,
-    5.0798974,   -1.5944242e-06, 0.056767445,   0.03468219,  -0.1497254,   -0.9672509,
-    0.2603209,   0.69644475,     -0.9208536,    0.006730467, -1.7552528,   2.682209e-07,
-    4.893558,    -1.6242266e-06, 0.6719861,     -0.13982919, 0.064845346,  -0.39896214,
-    0.21785057,  -0.5099982,     -0.65526295,   1.4383471,   -0.52023906,  2.5331974e-07,
-    6.687699,    -1.5497208e-06, -0.7423769,    0.09968524,  1.052381,     -0.21306956,
-    0.5875206,   -0.3038844,     0.3991575,     -1.1895186,  0.17579001,   3.874302e-07,
-    5.2818384,   -1.1026859e-06, 0.5087582,     0.106959194, 1.1816688,    -0.87592727,
-    0.03740315,  0.5197907,      -1.3198637,    0.6398836,   0.22712436,   2.2351742e-08,
-    5.0190897,   -1.5646219e-06, -0.087282926,  0.50819266,  -0.28002462,  0.29240948,
-    -0.32303664, 0.38377762,     -0.0051696897, -0.99301195, -2.189299,    2.0861626e-07,
-    5.0545654,   -1.5795231e-06, 0.9146397,     0.83839166,  0.870533,     0.17405808,
-    -0.56308234, -0.7806684,     0.26397777,    0.6880482,   -1.4183462,   2.682209e-07,
-    5.479953,    -1.2665987e-06, 0.49444157,    0.7534672,   -0.76784146,  -0.4507342,
-    0.88815784,  0.6985409,      -0.2727425,    -0.25027415, -0.7328796,   2.682209e-07,
-    4.1296124,   -5.662441e-07,  -0.46133032,   0.30635798,  -0.18225375,  0.42515472,
-    -0.5484285,  0.9704039,      -0.35255045,   0.17549685,  0.8870368,    -3.1292439e-07,
-    4.8632016,   -1.8924475e-06, -0.6926452,    0.025076404, -0.039108217, -1.7492937,
-    -0.8120377,  -0.85315156,    -0.0022608787, 0.45002514,  -1.1024668,   3.501773e-07,
-    5.4715447,   -1.4901161e-06, 1.1176248,     -0.2109062,  -0.27492502,  0.08983741,
-    1.1903813,   -1.007312,      -0.20150042,   -0.83919466, -0.23939973,  4.917383e-07,
-    5.1267176,   -9.983778e-07,  -0.44803134,   -0.8066604,  -0.3435102,   -0.41692197,
-    -0.22457689, -0.1076939,     -0.29129186,   -1.1880502,  0.9255183,    -1.6391277e-07,
-    3.8495903,   -5.5134296e-07, 0.09505272,    -0.12751618, -1.1264827,   0.5068884,
-    -1.055237,   -0.19516481,    -0.34035242,   -0.15379356, 1.2655814,    -2.6077032e-07,
-    4.4372616,   -9.23872e-07,   -0.72962606,   -0.23475963, -0.04278487,  1.1032158,
-    -0.558924,   -0.5300043,     1.0578637,     -0.2466627,  0.44617313,   -7.8231096e-08,
-    5.5374002,   -1.4156103e-06, 0.016273111,   -0.5989829,  -0.19913958,  0.013256833,
-    1.8512837,   0.14526272,     -0.39700353,   -0.07573915, 0.23181,      2.9429793e-07,
-    4.989425,    -1.4901161e-06, 1.0391837,     0.16554561,  -0.22647032,  -1.0689808,
-    -0.84556,    -0.82779336,    0.9430445,     0.37618563,  0.4684292,    -9.685755e-08};
-
-static const std::vector<float> expected_rdft1d_results_2 = {
-    2.266797,  -8.195639e-08,  -0.37842733,  -0.41015846,  -0.48980892,  -0.10356337,
-    2.5542018, -2.2351742e-08, -0.3223713,   0.671882,     0.54300576,   -0.35418037,
-    1.985015,  -2.2351742e-08, -0.030243821, -0.20105253,  0.59431964,   0.07358998,
-    1.4619737, -7.450581e-09,  -0.4356845,   0.35701087,   0.28208786,   -0.36424285,
-    1.8002605, -1.1920929e-07, -0.43280697,  -0.56735414,  -0.30007166,  -0.541847,
-    2.3052943, -1.2293458e-07, -0.39316025,  -0.5526293,   -0.30507135,  -0.6021758,
-    2.7329001, -6.7055225e-08, 0.28245124,   -0.42586988,  -0.40586215,  0.4590181,
-    3.3132548, -5.9604645e-08, 0.6297612,    0.3694744,    0.077824846,  -0.6248544,
-    2.6314974, -2.9802322e-08, 0.58795106,   -0.60349375,  -0.3224758,   0.34408605,
-    1.8399743, -9.685755e-08,  -0.43963802,  -0.079073176, -0.120658875, -1.0880115,
-    2.0531366, -4.4703484e-08, 0.80112594,   -0.53726834,  -0.17560546,  -0.026561722,
-    2.3779182, -9.685755e-08,  -0.21852754,  -0.19336401,  0.38734403,   -0.5954362,
-    1.6219761, 7.450581e-09,   -0.43100592,  0.28373614,   0.101898566,  0.52321124,
-    2.128953,  -1.4901161e-07, -0.1622684,   -0.94116735,  -0.7350497,   0.12695336,
-    3.449626,  -8.940697e-08,  0.56062996,   -0.031283244, -0.06161648,  -0.8543532,
-    3.033568,  -8.195639e-08,  -0.37023768,  -0.03989461,  -0.28719214,  -0.22382751,
-    1.9661667, -1.4901161e-08, -0.59863573,  -0.015534669, -0.31916466,  0.55380434,
-    2.227056,  -5.2154064e-08, -0.12656188,  0.6895717,    0.097157195,  0.19840825,
-    3.5129817, -2.1234155e-07, 0.11158541,   0.5870459,    0.20993343,   -0.40297145,
-    2.5986667, 0.0,            0.26602313,   -1.1560227,   0.2542065,    0.45556274};
+    4.6657147,      -1.1622906e-06, 0.21456887,     -0.14946258,    -0.20476034,    -0.37063062,    -0.31414136,
+    0.5099413,      -1.1779613,     0.07057127,     -0.64047664,    -1.0058284e-07, 4.982774,       -1.1771917e-06,
+    0.6607505,      0.18829148,     -0.9772357,     1.4243596,      0.8640026,      0.34923682,     0.33401352,
+    0.25859502,     -0.7548928,     8.940697e-08,   5.9711604,      -1.4901161e-06, 0.5638976,      1.5429841,
+    -0.52065414,    0.24638398,     -0.27140495,    0.5040715,      0.5360231,      0.3234269,      -0.36054826,
+    1.7508864e-07,  4.7464237,      -1.2218952e-06, -0.29650804,    0.80609477,     -0.161426,      1.0022418,
+    -0.50812817,    0.7967348,      0.4394225,      -0.1588624,     -1.3835809,     -7.4505806e-08, 5.53836,
+    -1.7136335e-06, -0.38635445,    0.8284859,      -0.23278837,    -0.63777345,    -0.93614054,    0.3215857,
+    -0.14075133,    -0.67071164,    -1.4772836,     2.0861626e-07,  5.0798974,      -1.5944242e-06, 0.056767445,
+    0.03468219,     -0.1497254,     -0.9672509,     0.2603209,      0.69644475,     -0.9208536,     0.006730467,
+    -1.7552528,     2.682209e-07,   4.893558,       -1.6242266e-06, 0.6719861,      -0.13982919,    0.064845346,
+    -0.39896214,    0.21785057,     -0.5099982,     -0.65526295,    1.4383471,      -0.52023906,    2.5331974e-07,
+    6.687699,       -1.5497208e-06, -0.7423769,     0.09968524,     1.052381,       -0.21306956,    0.5875206,
+    -0.3038844,     0.3991575,      -1.1895186,     0.17579001,     3.874302e-07,   5.2818384,      -1.1026859e-06,
+    0.5087582,      0.106959194,    1.1816688,      -0.87592727,    0.03740315,     0.5197907,      -1.3198637,
+    0.6398836,      0.22712436,     2.2351742e-08,  5.0190897,      -1.5646219e-06, -0.087282926,   0.50819266,
+    -0.28002462,    0.29240948,     -0.32303664,    0.38377762,     -0.0051696897,  -0.99301195,    -2.189299,
+    2.0861626e-07,  5.0545654,      -1.5795231e-06, 0.9146397,      0.83839166,     0.870533,       0.17405808,
+    -0.56308234,    -0.7806684,     0.26397777,     0.6880482,      -1.4183462,     2.682209e-07,   5.479953,
+    -1.2665987e-06, 0.49444157,     0.7534672,      -0.76784146,    -0.4507342,     0.88815784,     0.6985409,
+    -0.2727425,     -0.25027415,    -0.7328796,     2.682209e-07,   4.1296124,      -5.662441e-07,  -0.46133032,
+    0.30635798,     -0.18225375,    0.42515472,     -0.5484285,     0.9704039,      -0.35255045,    0.17549685,
+    0.8870368,      -3.1292439e-07, 4.8632016,      -1.8924475e-06, -0.6926452,     0.025076404,    -0.039108217,
+    -1.7492937,     -0.8120377,     -0.85315156,    -0.0022608787,  0.45002514,     -1.1024668,     3.501773e-07,
+    5.4715447,      -1.4901161e-06, 1.1176248,      -0.2109062,     -0.27492502,    0.08983741,     1.1903813,
+    -1.007312,      -0.20150042,    -0.83919466,    -0.23939973,    4.917383e-07,   5.1267176,      -9.983778e-07,
+    -0.44803134,    -0.8066604,     -0.3435102,     -0.41692197,    -0.22457689,    -0.1076939,     -0.29129186,
+    -1.1880502,     0.9255183,      -1.6391277e-07, 3.8495903,      -5.5134296e-07, 0.09505272,     -0.12751618,
+    -1.1264827,     0.5068884,      -1.055237,      -0.19516481,    -0.34035242,    -0.15379356,    1.2655814,
+    -2.6077032e-07, 4.4372616,      -9.23872e-07,   -0.72962606,    -0.23475963,    -0.04278487,    1.1032158,
+    -0.558924,      -0.5300043,     1.0578637,      -0.2466627,     0.44617313,     -7.8231096e-08, 5.5374002,
+    -1.4156103e-06, 0.016273111,    -0.5989829,     -0.19913958,    0.013256833,    1.8512837,      0.14526272,
+    -0.39700353,    -0.07573915,    0.23181,        2.9429793e-07,  4.989425,       -1.4901161e-06, 1.0391837,
+    0.16554561,     -0.22647032,    -1.0689808,     -0.84556,       -0.82779336,    0.9430445,      0.37618563,
+    0.4684292,      -9.685755e-08};
+
+static const std::vector<float> expected_rdft1d_results_2 = {2.266797,    -8.195639e-08,  -0.37842733,  -0.41015846,
+                                                             -0.48980892, -0.10356337,    2.5542018,    -2.2351742e-08,
+                                                             -0.3223713,  0.671882,       0.54300576,   -0.35418037,
+                                                             1.985015,    -2.2351742e-08, -0.030243821, -0.20105253,
+                                                             0.59431964,  0.07358998,     1.4619737,    -7.450581e-09,
+                                                             -0.4356845,  0.35701087,     0.28208786,   -0.36424285,
+                                                             1.8002605,   -1.1920929e-07, -0.43280697,  -0.56735414,
+                                                             -0.30007166, -0.541847,      2.3052943,    -1.2293458e-07,
+                                                             -0.39316025, -0.5526293,     -0.30507135,  -0.6021758,
+                                                             2.7329001,   -6.7055225e-08, 0.28245124,   -0.42586988,
+                                                             -0.40586215, 0.4590181,      3.3132548,    -5.9604645e-08,
+                                                             0.6297612,   0.3694744,      0.077824846,  -0.6248544,
+                                                             2.6314974,   -2.9802322e-08, 0.58795106,   -0.60349375,
+                                                             -0.3224758,  0.34408605,     1.8399743,    -9.685755e-08,
+                                                             -0.43963802, -0.079073176,   -0.120658875, -1.0880115,
+                                                             2.0531366,   -4.4703484e-08, 0.80112594,   -0.53726834,
+                                                             -0.17560546, -0.026561722,   2.3779182,    -9.685755e-08,
+                                                             -0.21852754, -0.19336401,    0.38734403,   -0.5954362,
+                                                             1.6219761,   7.450581e-09,   -0.43100592,  0.28373614,
+                                                             0.101898566, 0.52321124,     2.128953,     -1.4901161e-07,
+                                                             -0.1622684,  -0.94116735,    -0.7350497,   0.12695336,
+                                                             3.449626,    -8.940697e-08,  0.56062996,   -0.031283244,
+                                                             -0.06161648, -0.8543532,     3.033568,     -8.195639e-08,
+                                                             -0.37023768, -0.03989461,    -0.28719214,  -0.22382751,
+                                                             1.9661667,   -1.4901161e-08, -0.59863573,  -0.015534669,
+                                                             -0.31916466, 0.55380434,     2.227056,     -5.2154064e-08,
+                                                             -0.12656188, 0.6895717,      0.097157195,  0.19840825,
+                                                             3.5129817,   -2.1234155e-07, 0.11158541,   0.5870459,
+                                                             0.20993343,  -0.40297145,    2.5986667,    0.0,
+                                                             0.26602313,  -1.1560227,     0.2542065,    0.45556274};
 
 static const std::vector<float> expected_rdft1d_results_3 = {
-    4.665715,    -1.6093254e-06, -0.5430559,   -0.5752678,     -0.37596112,  -1.1571281,
-    -0.46793216, -0.94566363,    0.6854232,    -0.3444838,     -0.674704,    0.5946392,
-    -0.64047587, 1.3560057e-06,  4.9827743,    -1.7434359e-06, -0.43517,     -0.049020194,
-    -1.4773891,  -1.0811031,     1.2506557,    0.5371344,      1.2869358,    -0.14998645,
-    0.8555907,   0.3693859,      -0.7548918,   1.5944242e-06,  5.971161,     -1.5199184e-06,
-    -1.2643411,  0.85635287,     -0.1801207,   -1.7264944,     0.6412285,    -0.4787441,
-    0.82227707,  0.65098876,     0.9114491,    0.40323836,     -0.36054718,  1.2852252e-06,
-    4.7464237,   -1.66893e-06,   -1.5010594,   0.2253451,      -0.87915635,  -0.4252541,
-    0.4976693,   -0.6554581,     0.928985,     0.8035921,      0.6578763,    -0.15220329,
-    -1.3835799,  1.0430813e-06,  5.5383606,    -1.4901161e-06, -1.619024,    -0.10987502,
-    0.20661727,  -1.3774645,     -0.3057741,   -1.0960662,     0.2971667,    0.46700704,
-    -0.20812088, -0.602368,      -1.4772825,   9.3877316e-07,  5.0798974,    -1.758337e-06,
-    -0.7421876,  -0.61749315,    0.21938956,   -1.3415859,     -0.838238,    -0.6598083,
-    1.0601404,   -0.7129184,     -0.27083004,  0.31763482,     -1.7552516,   1.4677644e-06,
-    4.893558,    -1.4975667e-06, -0.06445231,  -0.55879503,    0.08908144,   -1.2869594,
-    0.33623943,  -0.7704663,     -0.047739983, -1.0678453,     0.48350462,   1.5768427,
-    -0.52023804, 1.1697412e-06,  6.687699,     -1.3113022e-06, -1.292419,    -1.2920969,
-    1.2041754,   -0.2943018,     1.1889167,    -0.66985166,    1.1336832,    -0.13731277,
-    0.008011267, -0.9506076,     0.1757915,    1.1026859e-06,  5.2818394,    -1.4305115e-06,
-    -0.25987166, -0.48605326,    0.90237427,   -0.8028362,     -0.3040653,   -1.6981151,
-    1.1215456,   -0.7120959,     -0.4195284,   1.3941492,      0.22712523,   8.046627e-07,
-    5.01909,     -1.7881393e-06, -1.1856917,   -0.10931289,    -0.5164983,   -0.9724103,
-    0.30577338,  -0.72837675,    0.89680094,   0.21036407,     -0.052024096, -0.9455472,
-    -2.1892984,  1.4305115e-06,  5.054565,     -1.5050173e-06, -0.3471575,   0.40542153,
-    0.36438322,  -0.9765247,     1.2703501,    -1.7359983,     -0.1160066,   -0.25323528,
-    0.9753329,   0.5339062,      -1.418345,    9.834766e-07,   5.4799523,    -1.7285347e-06,
-    -0.7905842,  0.093313254,    0.068526804,  -1.8504739,     -0.01845923,  0.26084417,
-    1.5358877,   -0.4159652,     0.089752786,  0.089908056,    -0.7328786,   1.4007092e-06,
-    4.129612,    -9.536743e-07,  -1.2393575,   -0.28046644,    -0.58673245,  -0.39608067,
-    -0.12385368, -0.53435826,    0.77853805,   0.7645384,      -0.18040559,  0.6678516,
-    0.88703763,  8.046627e-07,   4.8632016,    -1.0430813e-06, -1.1780663,   -1.0952923,
-    1.1691413,   -1.4023741,     -0.546494,    -0.92614484,    -1.1796933,   -0.31762218,
-    0.25592417,  0.0959474,      -1.1024656,   1.013279e-06,   5.471545,     -1.6987324e-06,
-    0.35812324,  -0.66833705,    0.07725692,   -1.6537004,     1.6561611,    0.051166296,
-    0.865453,    -1.1392289,     -0.23588535,  -0.5480979,     -0.2393986,   1.3411045e-06,
-    5.126718,    -9.23872e-07,   -0.6379836,   -1.6675751,     0.013057679,  -0.9891113,
-    0.20881936,  -0.30439606,    0.37222707,   0.25244698,     -0.9197892,   -0.77782196,
-    0.9255192,   1.1101365e-06,  3.8495903,    -7.4505806e-07, -0.63088936,  -0.4556699,
-    -1.1905057,  -1.2522144,     0.46207082,   -0.31992733,    -0.4309795,   0.74295896,
-    -0.6106033,  0.18823686,     1.2655822,    7.748604e-07,   4.4372616,    -7.0780516e-07,
-    -1.1016369,  -1.0079124,     -0.6083025,   -0.0011255145,  1.4406854,    -0.2912693,
-    -0.26610214, 0.87299407,     0.69553405,   -0.45576566,    0.44617438,   7.4505806e-07,
-    5.5374007,   -1.5944242e-06, -0.32642078,  -1.3683549,     0.079301864,  -0.83741367,
-    0.67391664,  0.69433576,     1.6423957,    -1.1923066,     0.0334223,    0.37603495,
-    0.23181117,  1.4156103e-06,  4.9894247,    -7.748604e-07,  0.1788401,    -0.39274544,
-    0.78422666,  -2.1340246,     0.5487572,    -0.8765497,     -0.7899384,   0.5434137,
-    0.91613716,  0.08274247,     0.46843058,   8.34465e-07
-};
+    4.665715,    -1.6093254e-06, -0.5430559,  -0.5752678,   -0.37596112, -1.1571281,    -0.46793216,
+    -0.94566363, 0.6854232,      -0.3444838,  -0.674704,    0.5946392,   -0.64047587,   1.3560057e-06,
+    4.9827743,   -1.7434359e-06, -0.43517,    -0.049020194, -1.4773891,  -1.0811031,    1.2506557,
+    0.5371344,   1.2869358,      -0.14998645, 0.8555907,    0.3693859,   -0.7548918,    1.5944242e-06,
+    5.971161,    -1.5199184e-06, -1.2643411,  0.85635287,   -0.1801207,  -1.7264944,    0.6412285,
+    -0.4787441,  0.82227707,     0.65098876,  0.9114491,    0.40323836,  -0.36054718,   1.2852252e-06,
+    4.7464237,   -1.66893e-06,   -1.5010594,  0.2253451,    -0.87915635, -0.4252541,    0.4976693,
+    -0.6554581,  0.928985,       0.8035921,   0.6578763,    -0.15220329, -1.3835799,    1.0430813e-06,
+    5.5383606,   -1.4901161e-06, -1.619024,   -0.10987502,  0.20661727,  -1.3774645,    -0.3057741,
+    -1.0960662,  0.2971667,      0.46700704,  -0.20812088,  -0.602368,   -1.4772825,    9.3877316e-07,
+    5.0798974,   -1.758337e-06,  -0.7421876,  -0.61749315,  0.21938956,  -1.3415859,    -0.838238,
+    -0.6598083,  1.0601404,      -0.7129184,  -0.27083004,  0.31763482,  -1.7552516,    1.4677644e-06,
+    4.893558,    -1.4975667e-06, -0.06445231, -0.55879503,  0.08908144,  -1.2869594,    0.33623943,
+    -0.7704663,  -0.047739983,   -1.0678453,  0.48350462,   1.5768427,   -0.52023804,   1.1697412e-06,
+    6.687699,    -1.3113022e-06, -1.292419,   -1.2920969,   1.2041754,   -0.2943018,    1.1889167,
+    -0.66985166, 1.1336832,      -0.13731277, 0.008011267,  -0.9506076,  0.1757915,     1.1026859e-06,
+    5.2818394,   -1.4305115e-06, -0.25987166, -0.48605326,  0.90237427,  -0.8028362,    -0.3040653,
+    -1.6981151,  1.1215456,      -0.7120959,  -0.4195284,   1.3941492,   0.22712523,    8.046627e-07,
+    5.01909,     -1.7881393e-06, -1.1856917,  -0.10931289,  -0.5164983,  -0.9724103,    0.30577338,
+    -0.72837675, 0.89680094,     0.21036407,  -0.052024096, -0.9455472,  -2.1892984,    1.4305115e-06,
+    5.054565,    -1.5050173e-06, -0.3471575,  0.40542153,   0.36438322,  -0.9765247,    1.2703501,
+    -1.7359983,  -0.1160066,     -0.25323528, 0.9753329,    0.5339062,   -1.418345,     9.834766e-07,
+    5.4799523,   -1.7285347e-06, -0.7905842,  0.093313254,  0.068526804, -1.8504739,    -0.01845923,
+    0.26084417,  1.5358877,      -0.4159652,  0.089752786,  0.089908056, -0.7328786,    1.4007092e-06,
+    4.129612,    -9.536743e-07,  -1.2393575,  -0.28046644,  -0.58673245, -0.39608067,   -0.12385368,
+    -0.53435826, 0.77853805,     0.7645384,   -0.18040559,  0.6678516,   0.88703763,    8.046627e-07,
+    4.8632016,   -1.0430813e-06, -1.1780663,  -1.0952923,   1.1691413,   -1.4023741,    -0.546494,
+    -0.92614484, -1.1796933,     -0.31762218, 0.25592417,   0.0959474,   -1.1024656,    1.013279e-06,
+    5.471545,    -1.6987324e-06, 0.35812324,  -0.66833705,  0.07725692,  -1.6537004,    1.6561611,
+    0.051166296, 0.865453,       -1.1392289,  -0.23588535,  -0.5480979,  -0.2393986,    1.3411045e-06,
+    5.126718,    -9.23872e-07,   -0.6379836,  -1.6675751,   0.013057679, -0.9891113,    0.20881936,
+    -0.30439606, 0.37222707,     0.25244698,  -0.9197892,   -0.77782196, 0.9255192,     1.1101365e-06,
+    3.8495903,   -7.4505806e-07, -0.63088936, -0.4556699,   -1.1905057,  -1.2522144,    0.46207082,
+    -0.31992733, -0.4309795,     0.74295896,  -0.6106033,   0.18823686,  1.2655822,     7.748604e-07,
+    4.4372616,   -7.0780516e-07, -1.1016369,  -1.0079124,   -0.6083025,  -0.0011255145, 1.4406854,
+    -0.2912693,  -0.26610214,    0.87299407,  0.69553405,   -0.45576566, 0.44617438,    7.4505806e-07,
+    5.5374007,   -1.5944242e-06, -0.32642078, -1.3683549,   0.079301864, -0.83741367,   0.67391664,
+    0.69433576,  1.6423957,      -1.1923066,  0.0334223,    0.37603495,  0.23181117,    1.4156103e-06,
+    4.9894247,   -7.748604e-07,  0.1788401,   -0.39274544,  0.78422666,  -2.1340246,    0.5487572,
+    -0.8765497,  -0.7899384,     0.5434137,   0.91613716,   0.08274247,  0.46843058,    8.34465e-07};
 
 const std::vector<float> expected_rdft2d_results = {
-    52.8665,     -2.9623508e-05, 1.1642078,    3.826082,    -0.22771922,  -0.49822173,
-    -0.3857528,  3.2676966,      -2.5112464,   -0.27454787, -8.678656,    3.7550926e-06,
-    -0.818072,   0.8330209,      3.4618711,    -0.2419473,  1.7408192,    5.744002,
-    1.8477443,   2.039329,       0.3268112,    -2.7421296,  0.6809025,    1.7613728,
-    -2.294264,   -0.8984407,     -0.2868184,   -3.2426705,  -0.801461,    -0.58971727,
-    -1.463435,   -2.5413132,     0.116907075,  -0.5013529,  -2.8377397,   -2.8455539,
-    -0.13475686, -1.3145845,     -2.2820292,   -0.199,      -0.056986623, 0.12560216,
-    -0.589707,   -1.7577857,     -0.5274223,   -1.0395792,  0.53813136,   -1.7159984,
-    0.22503978,  2.902198,       -1.8643543,   -1.8789856,  2.1722724,    -2.068454,
-    0.59446484,  0.6067899,      1.5525781,    1.7612485,   1.1877432,    -0.48152098,
-    -0.16525066, 1.5497208e-06,  1.9815066,    0.55218977,  0.80434155,   -3.575598,
-    -2.1471107,  -0.57691807,    -3.004384,    3.8775828,   3.1358109,    -6.2584877e-07,
-    0.22504184,  -2.9021916,     1.0378464,    0.9877456,   0.38395065,   -1.6089694,
-    -0.5107449,  1.8621777,      -4.960479,    -1.8983803,  1.187743,     0.48151842,
-    -0.1347583,  1.3145843,      -0.9968031,   -1.3782079,  0.9922035,    1.6614089,
-    -0.83039653, -0.043888614,   1.9431384,    -1.6448143,  0.5381324,    1.7159982,
-    -2.2942696,  0.8984335,      1.3057998,    -0.26607463, -3.2994738,   -1.9240448,
-    1.4963659,   2.8365738,      -4.691832,    1.2995429,   -2.8377357,   2.8455553,
-    -0.8180722,  -0.8330165,     -1.3755352,   0.34623986,  -3.7555497,   -0.9723124,
-    -1.1528367,  -0.593254,      -0.023679793, 1.8681414,   0.6809023,    -1.7613728,
-    48.939255,   -2.4735928e-05, 1.3455832,    0.11001387,  -2.3319814,   -1.3735183,
-    -0.6780232,  -2.4875786,     0.40718403,   -1.0639579,  0.7314569,    -1.2665987e-07,
-    0.97006464,  -0.30789328,    3.3290033,    2.7749023,   -0.7520597,   -0.98800826,
-    1.3100916,   1.1514524,      1.1085359,    4.348257,    -2.839456,    2.4404035,
-    0.9518837,   2.1538901,      3.8438358,    2.410589,    3.0649068,    0.95690995,
-    2.2213395,   0.66509914,     -0.4409917,   -0.37408838, -0.6316552,   -1.5842111,
-    -0.72352415, -2.5862057,     0.2678757,    0.610149,    2.9564474,    0.08470708,
-    -2.0889034,  -8.370071,      -0.16373271,  2.0413866,   -3.3811545,   2.0487003,
-    0.0316903,   -1.078939,      -2.5515578,   -0.16135174, -0.17406325,  1.2709827,
-    -0.67006403, -1.6342779,     0.42163712,   2.1418998,   -0.96614444,  1.9175051,
-    -0.8538456,  2.8014183e-06,  2.0189362,    0.30467552,  0.5074463,    3.7919073,
-    2.427857,    0.7526233,      -2.4620402,   0.65359443,  0.7219074,    -2.3841858e-07,
-    0.03169757,  1.0789458,      -2.1129081,   -1.0250417,  4.8181386,    -0.39162922,
-    -1.2349386,  1.8470186,      -0.49495277,  -1.5516026,  -0.96614635,  -1.9175065,
-    -0.7235237,  2.5862021,      0.677946,     2.0370173,   -0.29536027,  0.6505451,
-    -2.8572361,  2.3176546,      3.4459226,    1.1869265,   -3.3811545,   -2.048697,
-    0.95187366,  -2.1538982,     1.808088,     -1.1755496,  -2.7418838,   -1.6770658,
-    -3.5766084,  -2.8320727,     -0.02944839,  -1.6522555,  -0.63165283,  1.5842092,
-    0.9700667,   0.30789307,     0.5195943,    2.4985125,   3.6537378,    -0.5842519,
-    -0.4843334,  0.78346854,     0.84766304,   1.1503224,   -2.839459,    -2.440402};
+    52.8665,      -2.9623508e-05, 1.1642078,   3.826082,       -0.22771922,  -0.49822173,   -0.3857528,  3.2676966,
+    -2.5112464,   -0.27454787,    -8.678656,   3.7550926e-06,  -0.818072,    0.8330209,     3.4618711,   -0.2419473,
+    1.7408192,    5.744002,       1.8477443,   2.039329,       0.3268112,    -2.7421296,    0.6809025,   1.7613728,
+    -2.294264,    -0.8984407,     -0.2868184,  -3.2426705,     -0.801461,    -0.58971727,   -1.463435,   -2.5413132,
+    0.116907075,  -0.5013529,     -2.8377397,  -2.8455539,     -0.13475686,  -1.3145845,    -2.2820292,  -0.199,
+    -0.056986623, 0.12560216,     -0.589707,   -1.7577857,     -0.5274223,   -1.0395792,    0.53813136,  -1.7159984,
+    0.22503978,   2.902198,       -1.8643543,  -1.8789856,     2.1722724,    -2.068454,     0.59446484,  0.6067899,
+    1.5525781,    1.7612485,      1.1877432,   -0.48152098,    -0.16525066,  1.5497208e-06, 1.9815066,   0.55218977,
+    0.80434155,   -3.575598,      -2.1471107,  -0.57691807,    -3.004384,    3.8775828,     3.1358109,   -6.2584877e-07,
+    0.22504184,   -2.9021916,     1.0378464,   0.9877456,      0.38395065,   -1.6089694,    -0.5107449,  1.8621777,
+    -4.960479,    -1.8983803,     1.187743,    0.48151842,     -0.1347583,   1.3145843,     -0.9968031,  -1.3782079,
+    0.9922035,    1.6614089,      -0.83039653, -0.043888614,   1.9431384,    -1.6448143,    0.5381324,   1.7159982,
+    -2.2942696,   0.8984335,      1.3057998,   -0.26607463,    -3.2994738,   -1.9240448,    1.4963659,   2.8365738,
+    -4.691832,    1.2995429,      -2.8377357,  2.8455553,      -0.8180722,   -0.8330165,    -1.3755352,  0.34623986,
+    -3.7555497,   -0.9723124,     -1.1528367,  -0.593254,      -0.023679793, 1.8681414,     0.6809023,   -1.7613728,
+    48.939255,    -2.4735928e-05, 1.3455832,   0.11001387,     -2.3319814,   -1.3735183,    -0.6780232,  -2.4875786,
+    0.40718403,   -1.0639579,     0.7314569,   -1.2665987e-07, 0.97006464,   -0.30789328,   3.3290033,   2.7749023,
+    -0.7520597,   -0.98800826,    1.3100916,   1.1514524,      1.1085359,    4.348257,      -2.839456,   2.4404035,
+    0.9518837,    2.1538901,      3.8438358,   2.410589,       3.0649068,    0.95690995,    2.2213395,   0.66509914,
+    -0.4409917,   -0.37408838,    -0.6316552,  -1.5842111,     -0.72352415,  -2.5862057,    0.2678757,   0.610149,
+    2.9564474,    0.08470708,     -2.0889034,  -8.370071,      -0.16373271,  2.0413866,     -3.3811545,  2.0487003,
+    0.0316903,    -1.078939,      -2.5515578,  -0.16135174,    -0.17406325,  1.2709827,     -0.67006403, -1.6342779,
+    0.42163712,   2.1418998,      -0.96614444, 1.9175051,      -0.8538456,   2.8014183e-06, 2.0189362,   0.30467552,
+    0.5074463,    3.7919073,      2.427857,    0.7526233,      -2.4620402,   0.65359443,    0.7219074,   -2.3841858e-07,
+    0.03169757,   1.0789458,      -2.1129081,  -1.0250417,     4.8181386,    -0.39162922,   -1.2349386,  1.8470186,
+    -0.49495277,  -1.5516026,     -0.96614635, -1.9175065,     -0.7235237,   2.5862021,     0.677946,    2.0370173,
+    -0.29536027,  0.6505451,      -2.8572361,  2.3176546,      3.4459226,    1.1869265,     -3.3811545,  -2.048697,
+    0.95187366,   -2.1538982,     1.808088,    -1.1755496,     -2.7418838,   -1.6770658,    -3.5766084,  -2.8320727,
+    -0.02944839,  -1.6522555,     -0.63165283, 1.5842092,      0.9700667,    0.30789307,    0.5195943,   2.4985125,
+    3.6537378,    -0.5842519,     -0.4843334,  0.78346854,     0.84766304,   1.1503224,     -2.839459,   -2.440402};
 
 const std::vector<float> expected_rdft2d_results_2 = {
-    25.904434,   -8.46386e-06,  -5.3626504,  0.3475349,   -2.7060094,   -5.767444,
-    1.615847,    -2.6387978,    4.020789,    1.4271183,   1.5420923,    0.6126925,
-    -4.6167765,  5.5730343e-06, -0.753784,   -0.19148755, 1.4881928,    -2.7645326,
-    -0.39467168, 1.014636,      0.5598,      -1.7654291,  -0.91835654,  -2.3019042,
-    -0.49356225, -0.8411435,    0.080773115, -1.2883577,  -0.5341466,   1.4913602,
-    -0.30008763, -0.5831754,    1.7365295,   1.821624,    -0.08851206,  -1.622279,
-    -0.27249795, -0.834725,     -0.6706438,  0.4766277,   0.62642634,   0.5483514,
-    -0.5341469,  -1.4913592,    0.8286207,   0.35826343,  -1.0869694,   -1.4876881,
-    -1.6723244,  -0.06565219,   0.16255295,  0.5317876,   -0.75649667,  1.2447717,
-    0.6264261,   -0.5483517,    -0.7537827,  0.19148779,  0.6306459,    -0.23442982,
-    0.57131517,  -1.366768,     -2.7544713,  1.3638397,   0.43463084,   -0.5446956,
-    -2.9949086,  1.4802479,     0.080771565, 1.2883584,   24.998875,    -7.390976e-06,
-    -3.1970425,  -1.5453612,    1.0925753,   -6.279154,   2.237704,     -2.8844912,
-    1.8841789,   -1.3615136,    0.90471864,  0.8395144,   -2.6060505,   4.976988e-06,
-    1.1634235,   0.42319643,    2.678257,    2.4692535,   0.34259582,   0.43598562,
-    2.748452,    0.88622695,    2.2745323,   -2.8840196,  1.8120161,    -0.27884078,
-    -1.5445104,  -0.7000726,    -1.0264511,  -0.7026249,  -1.071573,    1.062395,
-    -0.64628685, -0.36214483,   -0.5110928,  -1.0534683,  -2.786768,    2.6113648,
-    0.94799054,  0.53423727,    -0.69832724, 2.1821892,   -1.0264513,   0.70262754,
-    -0.41705567, -0.17140968,   1.4991179,   2.9674625,   -0.012362838, -3.8260121,
-    -1.5786235,  -0.32526863,   1.2857957,   1.7469958,   -0.6983267,   -2.1821907,
-    1.1634252,   -0.42319855,   0.2716269,   0.21222934,  -0.46608746,  -1.6447732,
-    1.8890494,   -1.8022469,    -0.37335354, 0.69326025,  -0.07385725,  -0.1723765,
-    -1.5445105,  0.7000739};
+    25.904434,   -8.46386e-06, -5.3626504,  0.3475349,    -2.7060094,  -5.767444,     1.615847,     -2.6387978,
+    4.020789,    1.4271183,    1.5420923,   0.6126925,    -4.6167765,  5.5730343e-06, -0.753784,    -0.19148755,
+    1.4881928,   -2.7645326,   -0.39467168, 1.014636,     0.5598,      -1.7654291,    -0.91835654,  -2.3019042,
+    -0.49356225, -0.8411435,   0.080773115, -1.2883577,   -0.5341466,  1.4913602,     -0.30008763,  -0.5831754,
+    1.7365295,   1.821624,     -0.08851206, -1.622279,    -0.27249795, -0.834725,     -0.6706438,   0.4766277,
+    0.62642634,  0.5483514,    -0.5341469,  -1.4913592,   0.8286207,   0.35826343,    -1.0869694,   -1.4876881,
+    -1.6723244,  -0.06565219,  0.16255295,  0.5317876,    -0.75649667, 1.2447717,     0.6264261,    -0.5483517,
+    -0.7537827,  0.19148779,   0.6306459,   -0.23442982,  0.57131517,  -1.366768,     -2.7544713,   1.3638397,
+    0.43463084,  -0.5446956,   -2.9949086,  1.4802479,    0.080771565, 1.2883584,     24.998875,    -7.390976e-06,
+    -3.1970425,  -1.5453612,   1.0925753,   -6.279154,    2.237704,    -2.8844912,    1.8841789,    -1.3615136,
+    0.90471864,  0.8395144,    -2.6060505,  4.976988e-06, 1.1634235,   0.42319643,    2.678257,     2.4692535,
+    0.34259582,  0.43598562,   2.748452,    0.88622695,   2.2745323,   -2.8840196,    1.8120161,    -0.27884078,
+    -1.5445104,  -0.7000726,   -1.0264511,  -0.7026249,   -1.071573,   1.062395,      -0.64628685,  -0.36214483,
+    -0.5110928,  -1.0534683,   -2.786768,   2.6113648,    0.94799054,  0.53423727,    -0.69832724,  2.1821892,
+    -1.0264513,  0.70262754,   -0.41705567, -0.17140968,  1.4991179,   2.9674625,     -0.012362838, -3.8260121,
+    -1.5786235,  -0.32526863,  1.2857957,   1.7469958,    -0.6983267,  -2.1821907,    1.1634252,    -0.42319855,
+    0.2716269,   0.21222934,   -0.46608746, -1.6447732,   1.8890494,   -1.8022469,    -0.37335354,  0.69326025,
+    -0.07385725, -0.1723765,   -1.5445105,  0.7000739};
 
 const std::vector<float> expected_rdft3d_results = {
-    101.805756,  -5.2273273e-05, 2.5097876,    3.936094,     -2.5597036,  -1.8717405,
-    -1.0637736,  0.7801182,      -2.1040666,   -1.3385094,   -7.9471993,  2.026558e-06,
-    0.15199316,  0.52512753,     6.7908745,    2.5329556,    0.98875976,  4.755993,
-    3.157838,    3.190782,       1.4353466,    1.6061276,    -2.158554,   4.201776,
-    -1.3423799,  1.2554499,      3.5570183,    -0.8320818,   2.263445,    0.36719292,
-    0.7579028,   -1.8762131,     -0.32408538,  -0.87544185,  -3.4693956,  -4.429764,
-    -0.85828185, -3.9007902,     -2.0141544,   0.4111499,    2.8994608,   0.21030927,
-    -2.6786098,  -10.127857,     -0.6911557,   1.0018079,    -2.8430226,  0.33270124,
-    0.25672907,  1.8232578,      -4.4159126,   -2.040338,    1.9982092,   -0.7974717,
-    -0.07559925, -1.0274884,     1.9742157,    3.9031482,    0.22159882,  1.4359848,
-    -1.0190966,  3.2186508e-06,  4.0004425,    0.8568655,    1.3117876,   0.2163087,
-    0.28074512,  0.17570588,     -5.466423,    4.531178,     3.857718,    -1.2516975e-06,
-    0.2567385,   -1.823246,      -1.0750613,   -0.037295938, 5.20209,     -2.0005994,
-    -1.7456844,  3.7091968,      -5.45543,     -3.4499822,   0.22159535,  -1.4359887,
-    -0.8582816,  3.9007854,      -0.31885874,  0.65880924,   0.6968423,   2.3119528,
-    -3.6876333,  2.273767,       5.38906,      -0.45788872,  -2.8430223,  -0.33269957,
-    -1.3423961,  -1.2554631,     3.1138885,    -1.4416232,   -6.0413575,  -3.6011095,
-    -2.080242,   0.0045015216,   -4.7212796,   -0.3527125,   -3.4693892,  4.429763,
-    0.15199506,  -0.52512354,    -0.85594195,  2.8447511,    -0.10181111, -1.5565643,
-    -1.6371696,  0.19021615,     0.8239815,    3.018465,     -2.158556,   -4.2017746,
-    3.9272437,   -3.9339066e-06, -0.18137527,  3.7160687,    2.1042633,   0.8752967,
-    0.29226887,  5.755277,       -2.9184306,   0.78941,      -9.410112,   3.0100346e-06,
-    -1.7881365,  1.140914,       0.13286811,   -3.01685,     2.4928799,   6.7320104,
-    0.5376528,   0.88787735,     -0.78172505,  -7.0903873,   3.5203578,   -0.6790314,
-    -3.246148,   -3.0523329,     -4.1306543,   -5.653259,    -3.866367,   -1.5466263,
-    -3.6847744,  -3.2064118,     0.5578996,    -0.12726665,  -2.2060838,  -1.2613428,
-    0.588767,    1.2716217,      -2.5499039,   -0.8091496,   -3.0134337,  0.0408957,
-    1.4991964,   6.6122847,      -0.36368948,  -3.0809648,   3.9192853,   -3.764699,
-    0.19334978,  3.9811373,      0.68720365,   -1.717634,    2.346336,    -3.3394372,
-    1.2645291,   2.241068,       1.1309403,    -0.3806507,   2.1538877,   -2.3990266,
-    0.6885946,   -1.4901161e-06, -0.037429705, 0.24751475,   0.2968948,   -7.367506,
-    -4.574969,   -1.329541,      -0.5423446,   3.2239883,    2.4139037,   2.9802322e-07,
-    0.19334424,  -3.9811373,     3.1507545,    2.0127864,    -4.4341884,  -1.2173393,
-    0.72419256,  0.015158802,    -4.4655256,   -0.34677732,  2.1538897,   2.3990245,
-    0.5887663,   -1.2716188,     -1.6747494,   -3.415226,    1.2875631,   1.0108626,
-    2.0268395,   -2.3615427,     -1.502785,    -2.8317401,   3.919288,    3.764695,
-    -3.2461433,  3.0523314,      -0.5022881,   0.9094755,    -0.55759126, -0.24697942,
-    5.0729737,   5.668646,       -4.662384,    2.9517999,    -2.2060819,  1.2613468,
-    -1.7881389,  -1.1409098,     -1.8951292,   -2.1522717,   -7.4092865,  -0.38806117,
-    -0.6685039,  -1.3767233,     -0.8713439,   0.71781945,   3.5203605,   0.6790297};
+    101.805756,  -5.2273273e-05, 2.5097876,   3.936094,      -2.5597036,  -1.8717405,     -1.0637736,   0.7801182,
+    -2.1040666,  -1.3385094,     -7.9471993,  2.026558e-06,  0.15199316,  0.52512753,     6.7908745,    2.5329556,
+    0.98875976,  4.755993,       3.157838,    3.190782,      1.4353466,   1.6061276,      -2.158554,    4.201776,
+    -1.3423799,  1.2554499,      3.5570183,   -0.8320818,    2.263445,    0.36719292,     0.7579028,    -1.8762131,
+    -0.32408538, -0.87544185,    -3.4693956,  -4.429764,     -0.85828185, -3.9007902,     -2.0141544,   0.4111499,
+    2.8994608,   0.21030927,     -2.6786098,  -10.127857,    -0.6911557,  1.0018079,      -2.8430226,   0.33270124,
+    0.25672907,  1.8232578,      -4.4159126,  -2.040338,     1.9982092,   -0.7974717,     -0.07559925,  -1.0274884,
+    1.9742157,   3.9031482,      0.22159882,  1.4359848,     -1.0190966,  3.2186508e-06,  4.0004425,    0.8568655,
+    1.3117876,   0.2163087,      0.28074512,  0.17570588,    -5.466423,   4.531178,       3.857718,     -1.2516975e-06,
+    0.2567385,   -1.823246,      -1.0750613,  -0.037295938,  5.20209,     -2.0005994,     -1.7456844,   3.7091968,
+    -5.45543,    -3.4499822,     0.22159535,  -1.4359887,    -0.8582816,  3.9007854,      -0.31885874,  0.65880924,
+    0.6968423,   2.3119528,      -3.6876333,  2.273767,      5.38906,     -0.45788872,    -2.8430223,   -0.33269957,
+    -1.3423961,  -1.2554631,     3.1138885,   -1.4416232,    -6.0413575,  -3.6011095,     -2.080242,    0.0045015216,
+    -4.7212796,  -0.3527125,     -3.4693892,  4.429763,      0.15199506,  -0.52512354,    -0.85594195,  2.8447511,
+    -0.10181111, -1.5565643,     -1.6371696,  0.19021615,    0.8239815,   3.018465,       -2.158556,    -4.2017746,
+    3.9272437,   -3.9339066e-06, -0.18137527, 3.7160687,     2.1042633,   0.8752967,      0.29226887,   5.755277,
+    -2.9184306,  0.78941,        -9.410112,   3.0100346e-06, -1.7881365,  1.140914,       0.13286811,   -3.01685,
+    2.4928799,   6.7320104,      0.5376528,   0.88787735,    -0.78172505, -7.0903873,     3.5203578,    -0.6790314,
+    -3.246148,   -3.0523329,     -4.1306543,  -5.653259,     -3.866367,   -1.5466263,     -3.6847744,   -3.2064118,
+    0.5578996,   -0.12726665,    -2.2060838,  -1.2613428,    0.588767,    1.2716217,      -2.5499039,   -0.8091496,
+    -3.0134337,  0.0408957,      1.4991964,   6.6122847,     -0.36368948, -3.0809648,     3.9192853,    -3.764699,
+    0.19334978,  3.9811373,      0.68720365,  -1.717634,     2.346336,    -3.3394372,     1.2645291,    2.241068,
+    1.1309403,   -0.3806507,     2.1538877,   -2.3990266,    0.6885946,   -1.4901161e-06, -0.037429705, 0.24751475,
+    0.2968948,   -7.367506,      -4.574969,   -1.329541,     -0.5423446,  3.2239883,      2.4139037,    2.9802322e-07,
+    0.19334424,  -3.9811373,     3.1507545,   2.0127864,     -4.4341884,  -1.2173393,     0.72419256,   0.015158802,
+    -4.4655256,  -0.34677732,    2.1538897,   2.3990245,     0.5887663,   -1.2716188,     -1.6747494,   -3.415226,
+    1.2875631,   1.0108626,      2.0268395,   -2.3615427,    -1.502785,   -2.8317401,     3.919288,     3.764695,
+    -3.2461433,  3.0523314,      -0.5022881,  0.9094755,     -0.55759126, -0.24697942,    5.0729737,    5.668646,
+    -4.662384,   2.9517999,      -2.2060819,  1.2613468,     -1.7881389,  -1.1409098,     -1.8951292,   -2.1522717,
+    -7.4092865,  -0.38806117,    -0.6685039,  -1.3767233,    -0.8713439,  0.71781945,     3.5203605,    0.6790297};
 
 const std::vector<float> expected_rdft3d_results_2 = {
-    50.90331,     -1.4543533e-05, -8.559692,   -1.1978266,     -1.6134334,  -12.046599,
-    3.8535514,    -5.5232873,     5.9049683,   0.065603495,    2.4468107,   1.4522064,
-    -7.222825,    1.2278557e-05,  0.40963984,  0.231709,       4.16645,     -0.29528028,
-    -0.052075505, 1.450621,       3.3082519,   -0.8792013,     1.356175,    -5.1859245,
-    1.3184534,    -1.1199851,     -1.4637363,  -1.9884299,     -1.5605974,  0.7887349,
-    -1.3716602,   0.47921878,     1.0902424,   1.4594792,      -0.59960556, -2.6757474,
-    -3.0592656,   1.7766399,      0.27734682,  1.0108652,      -0.07190053, 2.7305403,
-    -1.5605986,   -0.78873086,    0.41156515,  0.18685403,     0.4121489,   1.4797752,
-    -1.6846865,   -3.8916636,     -1.4160703,  0.20651829,     0.52929974,  2.9917672,
-    -0.07190076,  -2.7305427,     0.4096415,   -0.23171037,    0.9022726,   -0.022200808,
-    0.10522783,   -3.0115416,     -0.8654218,  -0.4384073,     0.061277367, 0.14856634,
-    -3.0687659,   1.3078697,      -1.4637384,  1.9884316,      25.904425,   -24.998884,
-    -6.9080105,   3.5445771,      -8.985163,   -6.860018,      -1.2686447,  -4.8765025,
-    2.6592734,    -0.45706248,    2.3816066,   -0.29202732,    -4.6167727,  2.6060565,
-    -0.33058774,  -1.3549114,     3.9574459,   -5.44279,       0.041313916, 0.67204094,
-    1.446027,     -4.5138807,     -3.8023772,  -4.576436,      -0.7724026,  -2.6531591,
-    -0.6192993,   0.25615194,     -1.2367722,  2.5178113,      0.7623075,   0.48839718,
-    1.3743844,    2.4679115,      -1.1419809,  -1.1111865,     2.3388672,   1.9520425,
-    -0.13640736,  -0.47136223,    2.8086162,   1.2466785,      0.16848034,  -0.46490768,
-    0.6572111,    0.7753189,      1.8804929,   -2.9868064,     -5.498336,   -0.053289652,
-    -0.16271627,  2.1104114,      0.9904991,   -0.041024223,   -1.5557647,  0.14997506,
-    -1.1769819,   -0.9719368,     0.8428756,   -0.5060569,     -1.0734584,  -0.9006812,
-    -4.556718,    -0.5252099,     1.1278908,   -0.17134166,    -3.1672862,  1.5541049,
-    0.78084624,   2.8328683,      0.90555733,  -1.3709068e-06, -2.1656086,  1.8928962,
-    -3.7985847,   0.511709,       -0.62185717, 0.24569236,     2.1366088,   2.7886305,
-    0.6373716,    -0.2268233,     -2.0107267,  5.662441e-07,   -1.9172084,  -0.6146841,
-    -1.1900643,   -5.233785,      -0.73726743, 0.5786506,      -2.188651,   -2.6516552,
-    -3.1928902,   0.58211625,     -2.305578,   -0.5623034,     1.6252834,   -0.58828497,
-    0.49230486,   2.1939852,      0.7714851,   -1.6455705,     2.382816,    2.1837692,
-    0.4225806,    -0.56881106,    2.514269,    -3.4460905,     -1.618634,   -0.057608932,
-    1.3247533,    -1.6338379,     0.49230492,  -2.1939862,     1.2456759,   0.5296728,
-    -2.5860875,   -4.45515,       -1.659962,   3.7603593,      1.7411764,   0.8570565,
-    -2.0422916,   -0.50222373,    1.3247528,   1.633839,       -1.9172082,  0.6146865,
-    0.35901868,   -0.44665974,    1.0374024,   0.27800465,     -4.6435204,  3.1660864,
-    0.8079842,    -1.2379556,     -2.921052,   1.6526239,      1.6252828,   0.588284,
-    25.90444,     24.998867,      -3.817289,   -2.8495073,     3.573144,    -4.6748676,
-    4.500339,     -0.40109348,    5.382302,    3.3112957,      0.7025763,   1.5174108,
-    -4.616783,    -2.6060438,     -1.1769816,  0.97193646,     -0.9810596,  -0.086276084,
-    -0.83065766,  1.3572321,      -0.3264265,  0.9830234,      1.9656628,   -0.027371943,
-    -0.2147214,   0.9708719,      0.7808455,   -2.8328671,     0.16847888,  0.46490908,
-    -1.3624828,   -1.6547482,     2.0986745,   1.1753378,      0.9649557,   -2.1333718,
-    -2.8838634,   -3.6214924,     -1.2048804,  1.4246187,      -1.5557631,  -0.14997569,
-    -1.2367743,   -2.5178103,     1.0000296,   -0.05879204,    -4.0544314,  0.01142931,
-    2.153687,     -0.078014135,   0.4878212,   -1.0468364,     -2.503492,   2.5305676,
-    2.808617,     -1.2466786,     -0.33058444, 1.3549128,      0.41841656,  0.03719666,
-    2.216088,     -1.8328552,     -0.95222485, 3.2528882,      -0.25863037, -0.91804826,
-    -2.822532,    1.4063904,      -0.6193025,  -0.25615215};
-
-template<class T>
+    50.90331,    -1.4543533e-05, -8.559692,    -1.1978266,   -1.6134334,  -12.046599,     3.8535514,   -5.5232873,
+    5.9049683,   0.065603495,    2.4468107,    1.4522064,    -7.222825,   1.2278557e-05,  0.40963984,  0.231709,
+    4.16645,     -0.29528028,    -0.052075505, 1.450621,     3.3082519,   -0.8792013,     1.356175,    -5.1859245,
+    1.3184534,   -1.1199851,     -1.4637363,   -1.9884299,   -1.5605974,  0.7887349,      -1.3716602,  0.47921878,
+    1.0902424,   1.4594792,      -0.59960556,  -2.6757474,   -3.0592656,  1.7766399,      0.27734682,  1.0108652,
+    -0.07190053, 2.7305403,      -1.5605986,   -0.78873086,  0.41156515,  0.18685403,     0.4121489,   1.4797752,
+    -1.6846865,  -3.8916636,     -1.4160703,   0.20651829,   0.52929974,  2.9917672,      -0.07190076, -2.7305427,
+    0.4096415,   -0.23171037,    0.9022726,    -0.022200808, 0.10522783,  -3.0115416,     -0.8654218,  -0.4384073,
+    0.061277367, 0.14856634,     -3.0687659,   1.3078697,    -1.4637384,  1.9884316,      25.904425,   -24.998884,
+    -6.9080105,  3.5445771,      -8.985163,    -6.860018,    -1.2686447,  -4.8765025,     2.6592734,   -0.45706248,
+    2.3816066,   -0.29202732,    -4.6167727,   2.6060565,    -0.33058774, -1.3549114,     3.9574459,   -5.44279,
+    0.041313916, 0.67204094,     1.446027,     -4.5138807,   -3.8023772,  -4.576436,      -0.7724026,  -2.6531591,
+    -0.6192993,  0.25615194,     -1.2367722,   2.5178113,    0.7623075,   0.48839718,     1.3743844,   2.4679115,
+    -1.1419809,  -1.1111865,     2.3388672,    1.9520425,    -0.13640736, -0.47136223,    2.8086162,   1.2466785,
+    0.16848034,  -0.46490768,    0.6572111,    0.7753189,    1.8804929,   -2.9868064,     -5.498336,   -0.053289652,
+    -0.16271627, 2.1104114,      0.9904991,    -0.041024223, -1.5557647,  0.14997506,     -1.1769819,  -0.9719368,
+    0.8428756,   -0.5060569,     -1.0734584,   -0.9006812,   -4.556718,   -0.5252099,     1.1278908,   -0.17134166,
+    -3.1672862,  1.5541049,      0.78084624,   2.8328683,    0.90555733,  -1.3709068e-06, -2.1656086,  1.8928962,
+    -3.7985847,  0.511709,       -0.62185717,  0.24569236,   2.1366088,   2.7886305,      0.6373716,   -0.2268233,
+    -2.0107267,  5.662441e-07,   -1.9172084,   -0.6146841,   -1.1900643,  -5.233785,      -0.73726743, 0.5786506,
+    -2.188651,   -2.6516552,     -3.1928902,   0.58211625,   -2.305578,   -0.5623034,     1.6252834,   -0.58828497,
+    0.49230486,  2.1939852,      0.7714851,    -1.6455705,   2.382816,    2.1837692,      0.4225806,   -0.56881106,
+    2.514269,    -3.4460905,     -1.618634,    -0.057608932, 1.3247533,   -1.6338379,     0.49230492,  -2.1939862,
+    1.2456759,   0.5296728,      -2.5860875,   -4.45515,     -1.659962,   3.7603593,      1.7411764,   0.8570565,
+    -2.0422916,  -0.50222373,    1.3247528,    1.633839,     -1.9172082,  0.6146865,      0.35901868,  -0.44665974,
+    1.0374024,   0.27800465,     -4.6435204,   3.1660864,    0.8079842,   -1.2379556,     -2.921052,   1.6526239,
+    1.6252828,   0.588284,       25.90444,     24.998867,    -3.817289,   -2.8495073,     3.573144,    -4.6748676,
+    4.500339,    -0.40109348,    5.382302,     3.3112957,    0.7025763,   1.5174108,      -4.616783,   -2.6060438,
+    -1.1769816,  0.97193646,     -0.9810596,   -0.086276084, -0.83065766, 1.3572321,      -0.3264265,  0.9830234,
+    1.9656628,   -0.027371943,   -0.2147214,   0.9708719,    0.7808455,   -2.8328671,     0.16847888,  0.46490908,
+    -1.3624828,  -1.6547482,     2.0986745,    1.1753378,    0.9649557,   -2.1333718,     -2.8838634,  -3.6214924,
+    -1.2048804,  1.4246187,      -1.5557631,   -0.14997569,  -1.2367743,  -2.5178103,     1.0000296,   -0.05879204,
+    -4.0544314,  0.01142931,     2.153687,     -0.078014135, 0.4878212,   -1.0468364,     -2.503492,   2.5305676,
+    2.808617,    -1.2466786,     -0.33058444,  1.3549128,    0.41841656,  0.03719666,     2.216088,    -1.8328552,
+    -0.95222485, 3.2528882,      -0.25863037,  -0.91804826,  -2.822532,   1.4063904,      -0.6193025,  -0.25615215};
+
+template <class T>
 static std::vector<T> convert(const std::vector<float>& v) {
     if (v.empty()) {
         return std::vector<T>();
@@ -683,9 +640,7 @@ std::vector<RDFTParams> generateParamsForRDFT() {
 }
 
 std::vector<RDFTParams> generateCombinedParamsForRDFT() {
-    const std::vector<std::vector<RDFTParams>> allTypeParams{
-        generateParamsForRDFT<element::Type_t::f32>()
-    };
+    const std::vector<std::vector<RDFTParams>> allTypeParams{generateParamsForRDFT<element::Type_t::f32>()};
 
     std::vector<RDFTParams> combinedParams;
 
@@ -696,9 +651,8 @@ std::vector<RDFTParams> generateCombinedParamsForRDFT() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_RDFT_With_Hardcoded_Refs,
-    ReferenceRDFTLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForRDFT()),
-    ReferenceRDFTLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_RDFT_With_Hardcoded_Refs,
+                         ReferenceRDFTLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForRDFT()),
+                         ReferenceRDFTLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/reduce_l1.cpp b/src/plugins/template/tests/functional/op_reference/reduce_l1.cpp
index 63802601ad000a..679074176e4a20 100644
--- a/src/plugins/template/tests/functional/op_reference/reduce_l1.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reduce_l1.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reduce_l1.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reduce_l1.hpp"
 #include "reduction.hpp"
 
 using namespace ov;
@@ -16,17 +17,19 @@ namespace {
 template <element::Type_t IN_ET>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::L1, keep_dims, std::vector<int64_t>{2},
-                        reference_tests::Tensor({3, 2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
-                        reference_tests::Tensor(reduce(Shape{3, 2, 2}, AxisSet{2}, keep_dims),
-                                element::Type(IN_ET), std::vector<T>{3, 7, 11, 15, 19, 23}))
-    };
+    std::vector<ReductionParams> params = {ReductionParams(
+        ReductionType::L1,
+        keep_dims,
+        std::vector<int64_t>{2},
+        reference_tests::Tensor({3, 2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+        reference_tests::Tensor(reduce(Shape{3, 2, 2}, AxisSet{2}, keep_dims),
+                                element::Type(IN_ET),
+                                std::vector<T>{3, 7, 11, 15, 19, 23}))};
     return params;
 }
 
 std::vector<ReductionParams> generateReductionCombinedParams() {
-    const std::vector<std::vector<ReductionParams>> reductionTypeParams {
+    const std::vector<std::vector<ReductionParams>> reductionTypeParams{
         generateReductionParams<element::Type_t::f32>(true),
         generateReductionParams<element::Type_t::f32>(false),
         generateReductionParams<element::Type_t::f16>(true),
@@ -36,16 +39,17 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
         generateReductionParams<element::Type_t::u32>(true),
         generateReductionParams<element::Type_t::u32>(false),
         generateReductionParams<element::Type_t::u64>(true),
-        generateReductionParams<element::Type_t::u64>(false)
-    };
+        generateReductionParams<element::Type_t::u64>(false)};
     std::vector<ReductionParams> combinedParams;
     std::for_each(reductionTypeParams.begin(), reductionTypeParams.end(), [&](std::vector<ReductionParams> params) {
         combinedParams.insert(combinedParams.end(), params.begin(), params.end());
     });
     return combinedParams;
 }
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs, ReferenceReductionLayerTest, ::testing::ValuesIn(generateReductionCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs,
+                         ReferenceReductionLayerTest,
+                         ::testing::ValuesIn(generateReductionCombinedParams()),
                          ReferenceReductionLayerTest::getTestCaseName);
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/reduce_l2.cpp b/src/plugins/template/tests/functional/op_reference/reduce_l2.cpp
index a0e7439c661e9d..8649400d97572e 100644
--- a/src/plugins/template/tests/functional/op_reference/reduce_l2.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reduce_l2.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reduce_l2.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reduce_l2.hpp"
 #include "reduction.hpp"
 
 using namespace ov;
@@ -14,32 +15,41 @@ namespace ReductionOpsRefTestDefinitions {
 namespace {
 
 template <element::Type_t IN_ET,
-          typename std::enable_if<!std::is_integral<typename element_type_traits<IN_ET>::value_type>::value, bool>::type = true>
+          typename std::enable_if<!std::is_integral<typename element_type_traits<IN_ET>::value_type>::value,
+                                  bool>::type = true>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::L2, keep_dims, std::vector<int64_t>{2},
-                        reference_tests::Tensor({3, 2, 2}, element::Type(IN_ET), std::vector<T>{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0}),
-                        reference_tests::Tensor(reduce(Shape{3, 2, 2}, AxisSet{2}, keep_dims),
-                                element::Type(IN_ET), std::vector<T>{2.23606798, 5.0, 7.81024968, 10.63014581, 13.45362405, 16.2788206}))
-    };
+    std::vector<ReductionParams> params = {ReductionParams(
+        ReductionType::L2,
+        keep_dims,
+        std::vector<int64_t>{2},
+        reference_tests::Tensor({3, 2, 2},
+                                element::Type(IN_ET),
+                                std::vector<T>{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0}),
+        reference_tests::Tensor(reduce(Shape{3, 2, 2}, AxisSet{2}, keep_dims),
+                                element::Type(IN_ET),
+                                std::vector<T>{2.23606798, 5.0, 7.81024968, 10.63014581, 13.45362405, 16.2788206}))};
     return params;
 }
 
 template <element::Type_t IN_ET,
-          typename std::enable_if<std::is_integral<typename element_type_traits<IN_ET>::value_type>::value, bool>::type = true>
+          typename std::enable_if<std::is_integral<typename element_type_traits<IN_ET>::value_type>::value,
+                                  bool>::type = true>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::L2, keep_dims, std::vector<int64_t>{2},
-                        reference_tests::Tensor({3, 2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
-                        reference_tests::Tensor(reduce(Shape{3, 2, 2}, AxisSet{2}, keep_dims), element::Type(IN_ET), std::vector<T>{2, 5, 8, 11, 13, 16}))
-    };
+    std::vector<ReductionParams> params = {ReductionParams(
+        ReductionType::L2,
+        keep_dims,
+        std::vector<int64_t>{2},
+        reference_tests::Tensor({3, 2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+        reference_tests::Tensor(reduce(Shape{3, 2, 2}, AxisSet{2}, keep_dims),
+                                element::Type(IN_ET),
+                                std::vector<T>{2, 5, 8, 11, 13, 16}))};
     return params;
 }
 
 std::vector<ReductionParams> generateReductionCombinedParams() {
-    const std::vector<std::vector<ReductionParams>> reductionTypeParams {
+    const std::vector<std::vector<ReductionParams>> reductionTypeParams{
         generateReductionParams<element::Type_t::f32>(true),
         generateReductionParams<element::Type_t::f32>(false),
         generateReductionParams<element::Type_t::f16>(true),
@@ -49,8 +59,7 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
         generateReductionParams<element::Type_t::u32>(true),
         generateReductionParams<element::Type_t::u32>(false),
         generateReductionParams<element::Type_t::u64>(true),
-        generateReductionParams<element::Type_t::u64>(false)
-    };
+        generateReductionParams<element::Type_t::u64>(false)};
     std::vector<ReductionParams> combinedParams;
     std::for_each(reductionTypeParams.begin(), reductionTypeParams.end(), [&](std::vector<ReductionParams> params) {
         combinedParams.insert(combinedParams.end(), params.begin(), params.end());
@@ -58,8 +67,10 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
     return combinedParams;
 }
 
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs, ReferenceReductionLayerTest, ::testing::ValuesIn(generateReductionCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs,
+                         ReferenceReductionLayerTest,
+                         ::testing::ValuesIn(generateReductionCombinedParams()),
                          ReferenceReductionLayerTest::getTestCaseName);
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/reduce_max.cpp b/src/plugins/template/tests/functional/op_reference/reduce_max.cpp
index 97233a73e9e654..4d2011f10833f7 100644
--- a/src/plugins/template/tests/functional/op_reference/reduce_max.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reduce_max.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reduce_max.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reduce_max.hpp"
 #include "reduction.hpp"
 
 using namespace ov;
@@ -17,38 +18,72 @@ template <element::Type_t IN_ET>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
     std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::Max, keep_dims, std::vector<int64_t>{0, 1},
+        ReductionParams(ReductionType::Max,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
                         reference_tests::Tensor({2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4}),
-                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims), element::Type(IN_ET), std::vector<T>{4})),
-        ReductionParams(ReductionType::Max, keep_dims, std::vector<int64_t>{0},
+                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{4})),
+        ReductionParams(ReductionType::Max,
+                        keep_dims,
+                        std::vector<int64_t>{0},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{5, 6})),
-        ReductionParams(ReductionType::Max, keep_dims, std::vector<int64_t>{1},
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{5, 6})),
+        ReductionParams(ReductionType::Max,
+                        keep_dims,
+                        std::vector<int64_t>{1},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims), element::Type(IN_ET), std::vector<T>{2, 4, 6})),
-        ReductionParams(ReductionType::Max, keep_dims, std::vector<int64_t>{0},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{2, 4, 6})),
+        ReductionParams(ReductionType::Max,
+                        keep_dims,
+                        std::vector<int64_t>{0},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
                         reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0}, keep_dims),
-                              element::Type(IN_ET), std::vector<T>{19, 20, 21, 22, 23, 24, 25, 26, 27})),
-        ReductionParams(ReductionType::Max, keep_dims, std::vector<int64_t>{2},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{2}, keep_dims), element::Type(IN_ET), std::vector<T>{3, 6, 9, 12, 15, 18, 21, 24, 27})),
-        ReductionParams(ReductionType::Max, keep_dims, std::vector<int64_t>{0, 1},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1}, keep_dims), element::Type(IN_ET), std::vector<T>{25, 26, 27})),
-        ReductionParams(ReductionType::Max, keep_dims, std::vector<int64_t>{0, 1, 2},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1, 2}, keep_dims), element::Type(IN_ET), std::vector<T>{27}))
-    };
+                                                element::Type(IN_ET),
+                                                std::vector<T>{19, 20, 21, 22, 23, 24, 25, 26, 27})),
+        ReductionParams(ReductionType::Max,
+                        keep_dims,
+                        std::vector<int64_t>{2},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{2}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{3, 6, 9, 12, 15, 18, 21, 24, 27})),
+        ReductionParams(ReductionType::Max,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{25, 26, 27})),
+        ReductionParams(ReductionType::Max,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1, 2},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1, 2}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{27}))};
     return params;
 }
 
 std::vector<ReductionParams> generateReductionCombinedParams() {
-    const std::vector<std::vector<ReductionParams>> reductionTypeParams {
+    const std::vector<std::vector<ReductionParams>> reductionTypeParams{
         generateReductionParams<element::Type_t::f32>(true),
         generateReductionParams<element::Type_t::f32>(false),
         generateReductionParams<element::Type_t::f16>(true),
@@ -58,8 +93,7 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
         generateReductionParams<element::Type_t::u32>(true),
         generateReductionParams<element::Type_t::u32>(false),
         generateReductionParams<element::Type_t::u64>(true),
-        generateReductionParams<element::Type_t::u64>(false)
-    };
+        generateReductionParams<element::Type_t::u64>(false)};
     std::vector<ReductionParams> combinedParams;
     std::for_each(reductionTypeParams.begin(), reductionTypeParams.end(), [&](std::vector<ReductionParams> params) {
         combinedParams.insert(combinedParams.end(), params.begin(), params.end());
@@ -67,8 +101,10 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs, ReferenceReductionLayerTest, ::testing::ValuesIn(generateReductionCombinedParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs,
+                         ReferenceReductionLayerTest,
+                         ::testing::ValuesIn(generateReductionCombinedParams()),
                          ReferenceReductionLayerTest::getTestCaseName);
-} // namespace
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/reduce_mean.cpp b/src/plugins/template/tests/functional/op_reference/reduce_mean.cpp
index 2baf98e48a8a0d..0a15efca570507 100644
--- a/src/plugins/template/tests/functional/op_reference/reduce_mean.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reduce_mean.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reduce_mean.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reduce_mean.hpp"
 #include "reduction.hpp"
 
 using namespace ov;
@@ -14,43 +15,67 @@ namespace ReductionOpsRefTestDefinitions {
 namespace {
 
 template <element::Type_t IN_ET,
-          typename std::enable_if<!std::is_integral<typename element_type_traits<IN_ET>::value_type>::value, bool>::type = true>
+          typename std::enable_if<!std::is_integral<typename element_type_traits<IN_ET>::value_type>::value,
+                                  bool>::type = true>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
     std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::Mean, keep_dims, std::vector<int64_t>{0, 1},
+        ReductionParams(ReductionType::Mean,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
                         reference_tests::Tensor({2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4}),
-                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims), element::Type(IN_ET), std::vector<T>{2.5})),
-        ReductionParams(ReductionType::Mean, keep_dims, std::vector<int64_t>{0},
+                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{2.5})),
+        ReductionParams(ReductionType::Mean,
+                        keep_dims,
+                        std::vector<int64_t>{0},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{3, 4})),
-        ReductionParams(ReductionType::Mean, keep_dims, std::vector<int64_t>{1},
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{3, 4})),
+        ReductionParams(ReductionType::Mean,
+                        keep_dims,
+                        std::vector<int64_t>{1},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims), element::Type(IN_ET), std::vector<T>{1.5, 3.5, 5.5}))
-    };
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1.5, 3.5, 5.5}))};
     return params;
 }
 
 template <element::Type_t IN_ET,
-          typename std::enable_if<std::is_integral<typename element_type_traits<IN_ET>::value_type>::value, bool>::type = true>
+          typename std::enable_if<std::is_integral<typename element_type_traits<IN_ET>::value_type>::value,
+                                  bool>::type = true>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
     std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::Mean, keep_dims, std::vector<int64_t>{0, 1},
+        ReductionParams(ReductionType::Mean,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
                         reference_tests::Tensor({2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4}),
-                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims), element::Type(IN_ET), std::vector<T>{2})),
-        ReductionParams(ReductionType::Mean, keep_dims, std::vector<int64_t>{0},
+                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{2})),
+        ReductionParams(ReductionType::Mean,
+                        keep_dims,
+                        std::vector<int64_t>{0},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{3, 4})),
-        ReductionParams(ReductionType::Mean, keep_dims, std::vector<int64_t>{1},
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{3, 4})),
+        ReductionParams(ReductionType::Mean,
+                        keep_dims,
+                        std::vector<int64_t>{1},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims), element::Type(IN_ET), std::vector<T>{1, 3, 5}))
-    };
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1, 3, 5}))};
     return params;
 }
 
 std::vector<ReductionParams> generateReductionCombinedParams() {
-    const std::vector<std::vector<ReductionParams>> reductionTypeParams {
+    const std::vector<std::vector<ReductionParams>> reductionTypeParams{
         generateReductionParams<element::Type_t::f32>(true),
         generateReductionParams<element::Type_t::f32>(false),
         generateReductionParams<element::Type_t::f16>(true),
@@ -60,16 +85,17 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
         generateReductionParams<element::Type_t::u32>(true),
         generateReductionParams<element::Type_t::u32>(false),
         generateReductionParams<element::Type_t::u64>(true),
-        generateReductionParams<element::Type_t::u64>(false)
-    };
+        generateReductionParams<element::Type_t::u64>(false)};
     std::vector<ReductionParams> combinedParams;
     std::for_each(reductionTypeParams.begin(), reductionTypeParams.end(), [&](std::vector<ReductionParams> params) {
         combinedParams.insert(combinedParams.end(), params.begin(), params.end());
     });
     return combinedParams;
 }
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs, ReferenceReductionLayerTest, ::testing::ValuesIn(generateReductionCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs,
+                         ReferenceReductionLayerTest,
+                         ::testing::ValuesIn(generateReductionCombinedParams()),
                          ReferenceReductionLayerTest::getTestCaseName);
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/reduce_min.cpp b/src/plugins/template/tests/functional/op_reference/reduce_min.cpp
index ea0f583055da32..0b9fb15f75c35f 100644
--- a/src/plugins/template/tests/functional/op_reference/reduce_min.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reduce_min.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reduce_min.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reduce_min.hpp"
 #include "reduction.hpp"
 
 using namespace ov;
@@ -17,37 +18,72 @@ template <element::Type_t IN_ET>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
     std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::Min, keep_dims, std::vector<int64_t>{0, 1},
+        ReductionParams(ReductionType::Min,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
                         reference_tests::Tensor({2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4}),
-                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims), element::Type(IN_ET), std::vector<T>{1})),
-        ReductionParams(ReductionType::Min, keep_dims, std::vector<int64_t>{0},
+                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1})),
+        ReductionParams(ReductionType::Min,
+                        keep_dims,
+                        std::vector<int64_t>{0},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{1, 2})),
-        ReductionParams(ReductionType::Min, keep_dims, std::vector<int64_t>{1},
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1, 2})),
+        ReductionParams(ReductionType::Min,
+                        keep_dims,
+                        std::vector<int64_t>{1},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims), element::Type(IN_ET), std::vector<T>{1, 3, 5})),
-        ReductionParams(ReductionType::Min, keep_dims, std::vector<int64_t>{0},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9})),
-        ReductionParams(ReductionType::Min, keep_dims, std::vector<int64_t>{2},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{2}, keep_dims), element::Type(IN_ET), std::vector<T>{1, 4, 7, 10, 13, 16, 19, 22, 25})),
-        ReductionParams(ReductionType::Min, keep_dims, std::vector<int64_t>{0, 1},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1}, keep_dims), element::Type(IN_ET), std::vector<T>{1, 2, 3})),
-        ReductionParams(ReductionType::Min, keep_dims, std::vector<int64_t>{0, 1, 2},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1, 2}, keep_dims), element::Type(IN_ET), std::vector<T>{1}))
-    };
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1, 3, 5})),
+        ReductionParams(ReductionType::Min,
+                        keep_dims,
+                        std::vector<int64_t>{0},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9})),
+        ReductionParams(ReductionType::Min,
+                        keep_dims,
+                        std::vector<int64_t>{2},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{2}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1, 4, 7, 10, 13, 16, 19, 22, 25})),
+        ReductionParams(ReductionType::Min,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1, 2, 3})),
+        ReductionParams(ReductionType::Min,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1, 2},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1, 2}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1}))};
     return params;
 }
 
 std::vector<ReductionParams> generateReductionCombinedParams() {
-    const std::vector<std::vector<ReductionParams>> reductionTypeParams {
+    const std::vector<std::vector<ReductionParams>> reductionTypeParams{
         generateReductionParams<element::Type_t::f32>(true),
         generateReductionParams<element::Type_t::f32>(false),
         generateReductionParams<element::Type_t::f16>(true),
@@ -57,16 +93,17 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
         generateReductionParams<element::Type_t::u32>(true),
         generateReductionParams<element::Type_t::u32>(false),
         generateReductionParams<element::Type_t::u64>(true),
-        generateReductionParams<element::Type_t::u64>(false)
-    };
+        generateReductionParams<element::Type_t::u64>(false)};
     std::vector<ReductionParams> combinedParams;
     std::for_each(reductionTypeParams.begin(), reductionTypeParams.end(), [&](std::vector<ReductionParams> params) {
         combinedParams.insert(combinedParams.end(), params.begin(), params.end());
     });
     return combinedParams;
 }
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs, ReferenceReductionLayerTest, ::testing::ValuesIn(generateReductionCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs,
+                         ReferenceReductionLayerTest,
+                         ::testing::ValuesIn(generateReductionCombinedParams()),
                          ReferenceReductionLayerTest::getTestCaseName);
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/reduce_prod.cpp b/src/plugins/template/tests/functional/op_reference/reduce_prod.cpp
index b37801458384ff..96cf56bd5faa6f 100644
--- a/src/plugins/template/tests/functional/op_reference/reduce_prod.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reduce_prod.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reduce_prod.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reduce_prod.hpp"
 #include "reduction.hpp"
 
 using namespace ov;
@@ -16,45 +17,68 @@ template <element::Type_t IN_ET>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
     std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::Prod, keep_dims, std::vector<int64_t>{0, 1},
+        ReductionParams(ReductionType::Prod,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
                         reference_tests::Tensor({2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4}),
-                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims), element::Type(IN_ET), std::vector<T>{24})),
-        ReductionParams(ReductionType::Prod, keep_dims, std::vector<int64_t>{0},
+                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{24})),
+        ReductionParams(ReductionType::Prod,
+                        keep_dims,
+                        std::vector<int64_t>{0},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{15, 48})),
-        ReductionParams(ReductionType::Prod, keep_dims, std::vector<int64_t>{1},
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{15, 48})),
+        ReductionParams(ReductionType::Prod,
+                        keep_dims,
+                        std::vector<int64_t>{1},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims), element::Type(IN_ET), std::vector<T>{2, 12, 30})),
-        ReductionParams(ReductionType::Prod, keep_dims, std::vector<int64_t>{0},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{1 * 10 * 19,
-                                                                                                                   2 * 11 * 20,
-                                                                                                                   3 * 12 * 21,
-                                                                                                                   4 * 13 * 22,
-                                                                                                                   5 * 14 * 23,
-                                                                                                                   6 * 15 * 24,
-                                                                                                                   7 * 16 * 25,
-                                                                                                                   8 * 17 * 26,
-                                                                                                                   9 * 18 * 27})),
-        ReductionParams(ReductionType::Prod, keep_dims, std::vector<int64_t>{2},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{2}, keep_dims), element::Type(IN_ET), std::vector<T>{1 * 2 * 3,
-                                                                                                                   4 * 5 * 6,
-                                                                                                                   7 * 8 * 9,
-                                                                                                                   10 * 11 * 12,
-                                                                                                                   13 * 14 * 15,
-                                                                                                                   16 * 17 * 18,
-                                                                                                                   19 * 20 * 21,
-                                                                                                                   22 * 23 * 24,
-                                                                                                                   25 * 26 * 27}))
-    };
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{2, 12, 30})),
+        ReductionParams(ReductionType::Prod,
+                        keep_dims,
+                        std::vector<int64_t>{0},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1 * 10 * 19,
+                                                               2 * 11 * 20,
+                                                               3 * 12 * 21,
+                                                               4 * 13 * 22,
+                                                               5 * 14 * 23,
+                                                               6 * 15 * 24,
+                                                               7 * 16 * 25,
+                                                               8 * 17 * 26,
+                                                               9 * 18 * 27})),
+        ReductionParams(ReductionType::Prod,
+                        keep_dims,
+                        std::vector<int64_t>{2},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{2}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1 * 2 * 3,
+                                                               4 * 5 * 6,
+                                                               7 * 8 * 9,
+                                                               10 * 11 * 12,
+                                                               13 * 14 * 15,
+                                                               16 * 17 * 18,
+                                                               19 * 20 * 21,
+                                                               22 * 23 * 24,
+                                                               25 * 26 * 27}))};
     return params;
 }
 
 std::vector<ReductionParams> generateReductionCombinedParams() {
-    const std::vector<std::vector<ReductionParams>> reductionTypeParams {
+    const std::vector<std::vector<ReductionParams>> reductionTypeParams{
         generateReductionParams<element::Type_t::f32>(true),
         generateReductionParams<element::Type_t::f32>(false),
         generateReductionParams<element::Type_t::f16>(true),
@@ -64,33 +88,45 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
         generateReductionParams<element::Type_t::u32>(true),
         generateReductionParams<element::Type_t::u32>(false),
         generateReductionParams<element::Type_t::u64>(true),
-        generateReductionParams<element::Type_t::u64>(false)
-    };
+        generateReductionParams<element::Type_t::u64>(false)};
     std::vector<ReductionParams> combinedParams;
     std::for_each(reductionTypeParams.begin(), reductionTypeParams.end(), [&](std::vector<ReductionParams> params) {
         combinedParams.insert(combinedParams.end(), params.begin(), params.end());
     });
 
-    combinedParams.push_back(
-        ReductionParams(ReductionType::Prod, true, std::vector<int64_t>{0, 1},
-            reference_tests::Tensor({3, 3, 3}, element::Type_t::f32, std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-            reference_tests::Tensor({1, 1, 3}, element::Type_t::f32, std::vector<float>{1.0f * 10.0f * 19.0f * 4.0f * 13.0f * 22.0f * 7.0f * 16.0f * 25.0f,
-                                                                       2.0f * 11.0f * 20.0f * 5.0f * 14.0f * 23.0f * 8.0f * 17.0f * 26.0f,
-                                                                       3.0f * 12.0f * 21.0f * 6.0f * 15.0f * 24.0f * 9.0f * 18.0f * 27.0f})));
-    combinedParams.push_back(
-        ReductionParams(ReductionType::Prod, true, std::vector<int64_t>{0, 1, 2},
-            reference_tests::Tensor({3, 3, 3}, element::Type_t::f32, std::vector<float>{1,  2,  3,  4,  5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
-                                                                       13, 12, 11, 10, 9, 8, 7, 6, 5, 4,  3,  2,  1}),
-            reference_tests::Tensor({1, 1, 1}, element::Type_t::f32, std::vector<float>{1.0f * 10.0f * 9.0f * 4.0f * 13.0f * 6.0f * 7.0f *
-                                                                       12.0f * 3.0f * 2.0f * 11.0f * 8.0f * 5.0f * 14.0f *
-                                                                       5.0f * 8.0f * 11.0f * 2.0f * 3.0f * 12.0f * 7.0f *
-                                                                       6.0f * 13.0f * 4.0f * 9.0f * 10.0f * 1.0f})));
+    combinedParams.push_back(ReductionParams(
+        ReductionType::Prod,
+        true,
+        std::vector<int64_t>{0, 1},
+        reference_tests::Tensor({3, 3, 3},
+                                element::Type_t::f32,
+                                std::vector<float>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                   15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+        reference_tests::Tensor(
+            {1, 1, 3},
+            element::Type_t::f32,
+            std::vector<float>{1.0f * 10.0f * 19.0f * 4.0f * 13.0f * 22.0f * 7.0f * 16.0f * 25.0f,
+                               2.0f * 11.0f * 20.0f * 5.0f * 14.0f * 23.0f * 8.0f * 17.0f * 26.0f,
+                               3.0f * 12.0f * 21.0f * 6.0f * 15.0f * 24.0f * 9.0f * 18.0f * 27.0f})));
+    combinedParams.push_back(ReductionParams(
+        ReductionType::Prod,
+        true,
+        std::vector<int64_t>{0, 1, 2},
+        reference_tests::Tensor({3, 3, 3}, element::Type_t::f32, std::vector<float>{1,  2,  3,  4,  5,  6,  7,  8,  9,
+                                                                                    10, 11, 12, 13, 14, 13, 12, 11, 10,
+                                                                                    9,  8,  7,  6,  5,  4,  3,  2,  1}),
+        reference_tests::Tensor({1, 1, 1},
+                                element::Type_t::f32,
+                                std::vector<float>{1.0f * 10.0f * 9.0f * 4.0f * 13.0f * 6.0f * 7.0f * 12.0f * 3.0f *
+                                                   2.0f * 11.0f * 8.0f * 5.0f * 14.0f * 5.0f * 8.0f * 11.0f * 2.0f *
+                                                   3.0f * 12.0f * 7.0f * 6.0f * 13.0f * 4.0f * 9.0f * 10.0f * 1.0f})));
 
     return combinedParams;
 }
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs, ReferenceReductionLayerTest, ::testing::ValuesIn(generateReductionCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs,
+                         ReferenceReductionLayerTest,
+                         ::testing::ValuesIn(generateReductionCombinedParams()),
                          ReferenceReductionLayerTest::getTestCaseName);
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/reduce_sum.cpp b/src/plugins/template/tests/functional/op_reference/reduce_sum.cpp
index 850cd269a6c1dc..82c3e305026894 100644
--- a/src/plugins/template/tests/functional/op_reference/reduce_sum.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reduce_sum.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reduce_sum.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reduce_sum.hpp"
 #include "reduction.hpp"
 
 using namespace ov;
@@ -28,56 +29,96 @@ template <element::Type_t IN_ET>
 std::vector<ReductionParams> generateReductionParams(const bool keep_dims) {
     using T = typename element_type_traits<IN_ET>::value_type;
     std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{0, 1},
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
                         reference_tests::Tensor({2, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4}),
-                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims), element::Type(IN_ET), std::vector<T>{10})),
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{0},
+                        reference_tests::Tensor(reduce(Shape{2, 2}, AxisSet{0, 1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{10})),
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{0},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{9, 12})),
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{1},
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{9, 12})),
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{1},
                         reference_tests::Tensor({3, 2}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6}),
-                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims), element::Type(IN_ET), std::vector<T>{3, 7, 11})),
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{0},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0}, keep_dims), element::Type(IN_ET), std::vector<T>{1 + 10 + 19,
-                                                                                                                   2 + 11 + 20,
-                                                                                                                   3 + 12 + 21,
-                                                                                                                   4 + 13 + 22,
-                                                                                                                   5 + 14 + 23,
-                                                                                                                   6 + 15 + 24,
-                                                                                                                   7 + 16 + 25,
-                                                                                                                   8 + 17 + 26,
-                                                                                                                   9 + 18 + 27})),
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{2},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{2}, keep_dims), element::Type(IN_ET), std::vector<T>{1 + 2 + 3,
-                                                                                                                   4 + 5 + 6,
-                                                                                                                   7 + 8 + 9,
-                                                                                                                   10 + 11 + 12,
-                                                                                                                   13 + 14 + 15,
-                                                                                                                   16 + 17 + 18,
-                                                                                                                   19 + 20 + 21,
-                                                                                                                   22 + 23 + 24,
-                                                                                                                   25 + 26 + 27})),
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{0, 1},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 2}, AxisSet{1}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{3, 7, 11})),
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{0},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1 + 10 + 19,
+                                                               2 + 11 + 20,
+                                                               3 + 12 + 21,
+                                                               4 + 13 + 22,
+                                                               5 + 14 + 23,
+                                                               6 + 15 + 24,
+                                                               7 + 16 + 25,
+                                                               8 + 17 + 26,
+                                                               9 + 18 + 27})),
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{2},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{2}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1 + 2 + 3,
+                                                               4 + 5 + 6,
+                                                               7 + 8 + 9,
+                                                               10 + 11 + 12,
+                                                               13 + 14 + 15,
+                                                               16 + 17 + 18,
+                                                               19 + 20 + 21,
+                                                               22 + 23 + 24,
+                                                               25 + 26 + 27})),
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1},
+                        reference_tests::Tensor({3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                               15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
                         reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1}, keep_dims),
-                               element::Type(IN_ET), std::vector<T>{1 + 10 + 19 + 4 + 13 + 22 + 7 + 16 + 25,
-                                                                               2 + 11 + 20 + 5 + 14 + 23 + 8 + 17 + 26,
-                                                                               3 + 12 + 21 + 6 + 15 + 24 + 9 + 18 + 27})),
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{0, 1, 2},
-                        reference_tests::Tensor({3, 3, 3}, element::Type(IN_ET), std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1, 2}, keep_dims), element::Type(IN_ET),
-                            std::vector<T>{1 + 10 + 19 + 4 + 13 + 22 + 7 + 16 + 25 + 2 + 11 + 20 + 5 + 14 + 23 + 8 +
-                                           17 + 26 + 3 + 12 + 21 + 6 + 15 + 24 + 9 + 18 + 27})),
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{0, 1, 2, 3, 4},
-                        reference_tests::Tensor({3, 3, 3, 3, 3}, element::Type(IN_ET), std::vector<T>(static_cast<uint64_t>(std::pow(3, 5)), 1)),
-                        reference_tests::Tensor(reduce(Shape{3, 3, 3, 3, 3}, AxisSet{0, 1, 2, 3, 4}, keep_dims), element::Type(IN_ET), std::vector<T>{243}))
-    };
+                                                element::Type(IN_ET),
+                                                std::vector<T>{1 + 10 + 19 + 4 + 13 + 22 + 7 + 16 + 25,
+                                                               2 + 11 + 20 + 5 + 14 + 23 + 8 + 17 + 26,
+                                                               3 + 12 + 21 + 6 + 15 + 24 + 9 + 18 + 27})),
+        ReductionParams(
+            ReductionType::Sum,
+            keep_dims,
+            std::vector<int64_t>{0, 1, 2},
+            reference_tests::Tensor({3, 3, 3},
+                                    element::Type(IN_ET),
+                                    std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14,
+                                                   15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27}),
+            reference_tests::Tensor(reduce(Shape{3, 3, 3}, AxisSet{0, 1, 2}, keep_dims),
+                                    element::Type(IN_ET),
+                                    std::vector<T>{1 + 10 + 19 + 4 + 13 + 22 + 7 + 16 + 25 + 2 + 11 + 20 + 5 + 14 + 23 +
+                                                   8 + 17 + 26 + 3 + 12 + 21 + 6 + 15 + 24 + 9 + 18 + 27})),
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{0, 1, 2, 3, 4},
+                        reference_tests::Tensor({3, 3, 3, 3, 3},
+                                                element::Type(IN_ET),
+                                                std::vector<T>(static_cast<uint64_t>(std::pow(3, 5)), 1)),
+                        reference_tests::Tensor(reduce(Shape{3, 3, 3, 3, 3}, AxisSet{0, 1, 2, 3, 4}, keep_dims),
+                                                element::Type(IN_ET),
+                                                std::vector<T>{243}))};
     return params;
 }
 
@@ -85,20 +126,29 @@ std::vector<ReductionParams> generateReductionParamsFloat(const bool keep_dims)
     std::vector<float> in = generateRandomVector(1000000);
     float res = static_cast<float>(std::accumulate(std::begin(in), std::end(in), 0.f));
     std::vector<ReductionParams> params = {
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{0},
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{0},
                         reference_tests::Tensor({1000000}, element::f32, in),
-                        reference_tests::Tensor(reduce(Shape{1000000}, AxisSet{0}, keep_dims), element::f32, std::vector<float>{res})),
-        ReductionParams(ReductionType::Sum, keep_dims, std::vector<int64_t>{0},
-                        reference_tests::Tensor({20}, element::f32, std::vector<float>{10000000.0f, 0.9f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f,
-                                                                      0.8f,        0.1f, 0.9f, 0.5f, 0.2f, 0.3f, 0.4f,
-                                                                      0.5f,        0.6f, 0.7f, 0.8f, 0.9f, 0.1f}),
-                        reference_tests::Tensor(reduce(Shape{20}, AxisSet{0}, keep_dims), element::f32, std::vector<float>{10000010.2f}))
-    };
+                        reference_tests::Tensor(reduce(Shape{1000000}, AxisSet{0}, keep_dims),
+                                                element::f32,
+                                                std::vector<float>{res})),
+        ReductionParams(ReductionType::Sum,
+                        keep_dims,
+                        std::vector<int64_t>{0},
+                        reference_tests::Tensor(
+                            {20},
+                            element::f32,
+                            std::vector<float>{10000000.0f, 0.9f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f, 0.1f, 0.9f,
+                                               0.5f,        0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f, 0.9f, 0.1f}),
+                        reference_tests::Tensor(reduce(Shape{20}, AxisSet{0}, keep_dims),
+                                                element::f32,
+                                                std::vector<float>{10000010.2f}))};
     return params;
 }
 
 std::vector<ReductionParams> generateReductionCombinedParams() {
-    const std::vector<std::vector<ReductionParams>> reductionTypeParams {
+    const std::vector<std::vector<ReductionParams>> reductionTypeParams{
         generateReductionParams<element::Type_t::f32>(true),
         generateReductionParams<element::Type_t::f32>(false),
         generateReductionParams<element::Type_t::f16>(true),
@@ -110,16 +160,17 @@ std::vector<ReductionParams> generateReductionCombinedParams() {
         generateReductionParams<element::Type_t::u64>(true),
         generateReductionParams<element::Type_t::u64>(false),
         generateReductionParamsFloat(true),
-        generateReductionParamsFloat(false)
-    };
+        generateReductionParamsFloat(false)};
     std::vector<ReductionParams> combinedParams;
     std::for_each(reductionTypeParams.begin(), reductionTypeParams.end(), [&](std::vector<ReductionParams> params) {
         combinedParams.insert(combinedParams.end(), params.begin(), params.end());
     });
     return combinedParams;
 }
-} // namespace
-INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs, ReferenceReductionLayerTest, ::testing::ValuesIn(generateReductionCombinedParams()),
+}  // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Reduction_With_Hardcoded_Refs,
+                         ReferenceReductionLayerTest,
+                         ::testing::ValuesIn(generateReductionCombinedParams()),
                          ReferenceReductionLayerTest::getTestCaseName);
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/reduction.cpp b/src/plugins/template/tests/functional/op_reference/reduction.cpp
index d36cad37678ca7..98a0133ee62423 100644
--- a/src/plugins/template/tests/functional/op_reference/reduction.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reduction.cpp
@@ -10,6 +10,6 @@ namespace {
 TEST_P(ReferenceReductionLayerTest, CompareWithHardcodedRefs) {
     Exec();
 }
-} // namespace
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/reduction.hpp b/src/plugins/template/tests/functional/op_reference/reduction.hpp
index 30f6ca559fca5a..f3f58587913da9 100644
--- a/src/plugins/template/tests/functional/op_reference/reduction.hpp
+++ b/src/plugins/template/tests/functional/op_reference/reduction.hpp
@@ -6,16 +6,16 @@
 
 #include "base_reference_test.hpp"
 #include "common_test_utils/test_enums.hpp"
-#include "shared_test_classes/base/layer_test_utils.hpp"
-#include "openvino/op/reduce_logical_and.hpp"
-#include "openvino/op/reduce_logical_or.hpp"
 #include "openvino/op/reduce_l1.hpp"
 #include "openvino/op/reduce_l2.hpp"
-#include "openvino/op/reduce_min.hpp"
+#include "openvino/op/reduce_logical_and.hpp"
+#include "openvino/op/reduce_logical_or.hpp"
 #include "openvino/op/reduce_max.hpp"
 #include "openvino/op/reduce_mean.hpp"
+#include "openvino/op/reduce_min.hpp"
 #include "openvino/op/reduce_prod.hpp"
 #include "openvino/op/reduce_sum.hpp"
+#include "shared_test_classes/base/layer_test_utils.hpp"
 
 using namespace ov;
 
@@ -42,9 +42,16 @@ AXIS_VALUES reduce(const AXIS_VALUES& axis_values, const ov::AxisSet& deleted_ax
 }
 
 struct ReductionParams {
-    ReductionParams(const ReductionType& reductType, const bool keepDims, const std::vector<int64_t>& axes,
-        const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& outputTensor) : reductionType(reductType), keepDimensions(keepDims), reductionAxes(axes),
-        data(dataTensor), output(outputTensor) {}
+    ReductionParams(const ReductionType& reductType,
+                    const bool keepDims,
+                    const std::vector<int64_t>& axes,
+                    const reference_tests::Tensor& dataTensor,
+                    const reference_tests::Tensor& outputTensor)
+        : reductionType(reductType),
+          keepDimensions(keepDims),
+          reductionAxes(axes),
+          data(dataTensor),
+          output(outputTensor) {}
 
     ReductionType reductionType;
     bool keepDimensions;
@@ -53,7 +60,7 @@ struct ReductionParams {
     reference_tests::Tensor output;
 };
 
-class ReferenceReductionLayerTest : public  testing::TestWithParam<ReductionParams>, public CommonReferenceTest {
+class ReferenceReductionLayerTest : public testing::TestWithParam<ReductionParams>, public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -125,5 +132,5 @@ class ReferenceReductionLayerTest : public  testing::TestWithParam<ReductionPara
         return std::make_shared<ov::Model>(reduction, ov::ParameterVector{data});
     }
 };
-} // namespace ReductionOpsRefTestDefinitions
-} // namespace reference_tests
+}  // namespace ReductionOpsRefTestDefinitions
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/region_yolo.cpp b/src/plugins/template/tests/functional/op_reference/region_yolo.cpp
index 1ffb4ae1bd30e6..f1160722810f69 100644
--- a/src/plugins/template/tests/functional/op_reference/region_yolo.cpp
+++ b/src/plugins/template/tests/functional/op_reference/region_yolo.cpp
@@ -2,12 +2,14 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/region_yolo.hpp"
+
 #include <gtest/gtest.h>
+
 #include <fstream>
 #include <iomanip>
 #include <iostream>
 
-#include "openvino/op/region_yolo.hpp"
 #include "base_reference_test.hpp"
 #include "openvino/util/file_util.hpp"
 
@@ -18,20 +20,20 @@ namespace {
 struct RegionYoloParams {
     template <class IT>
     RegionYoloParams(const size_t num,
-                    const size_t coords,
-                    const size_t classes,
-                    const bool do_softmax,
-                    const int axis,
-                    const int end_axis,
-                    const size_t batch,
-                    const size_t channels,
-                    const size_t width,
-                    const size_t height,
-                    const std::vector<int64_t>& mask,
-                    const ov::element::Type& iType,
-                    const std::vector<IT>& iValues,
-                    const std::vector<IT>& oValues,
-                    const std::string& testcaseName = "")
+                     const size_t coords,
+                     const size_t classes,
+                     const bool do_softmax,
+                     const int axis,
+                     const int end_axis,
+                     const size_t batch,
+                     const size_t channels,
+                     const size_t width,
+                     const size_t height,
+                     const std::vector<int64_t>& mask,
+                     const ov::element::Type& iType,
+                     const std::vector<IT>& iValues,
+                     const std::vector<IT>& oValues,
+                     const std::string& testcaseName = "")
         : num(num),
           coords(coords),
           classes(classes),
@@ -48,8 +50,8 @@ struct RegionYoloParams {
           inputData(CreateTensor(iType, iValues)),
           refData(CreateTensor(iType, oValues)),
           testcaseName(testcaseName) {
-              inputShape = Shape{batch, channels, height, width};
-          }
+        inputShape = Shape{batch, channels, height, width};
+    }
 
     size_t num;
     size_t coords;
@@ -107,7 +109,7 @@ class ReferenceRegionYoloLayerTest : public testing::TestWithParam<RegionYoloPar
                                                                      params.mask,
                                                                      params.axis,
                                                                      params.end_axis);
-        return std::make_shared<ov::Model>(NodeVector {RegionYolo}, ParameterVector {p});
+        return std::make_shared<ov::Model>(NodeVector{RegionYolo}, ParameterVector{p});
     }
 };
 
@@ -119,28 +121,36 @@ template <element::Type_t IN_ET>
 std::vector<RegionYoloParams> generateRegionYoloParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<RegionYoloParams> regionYoloParams {
-        RegionYoloParams(1, 4, 1, false, 1, 3,
-                        1, 8, 2, 2,
-                        std::vector<int64_t>{0},
-                        IN_ET,
-                        std::vector<T>{0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f, 0.1f, 0.2f, 0.3f,
-                                       0.4f, 0.5f, 0.6f, 0.7f, 0.8f, 0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.6f,
-                                       0.7f, 0.8f, 0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f},
-                        std::vector<T>{0.52497f, 0.54983f, 0.57444f, 0.59868f, 0.62245f, 0.64565f, 0.66818f, 0.68997f,
-                                       0.1f,     0.2f,     0.3f,     0.4f,     0.5f,     0.6f,     0.7f,     0.8f,
-                                       0.52497f, 0.54983f, 0.57444f, 0.59868f, 0.62245f, 0.64565f, 0.66818f, 0.68997f}),
+    std::vector<RegionYoloParams> regionYoloParams{
+        RegionYoloParams(
+            1,
+            4,
+            1,
+            false,
+            1,
+            3,
+            1,
+            8,
+            2,
+            2,
+            std::vector<int64_t>{0},
+            IN_ET,
+            std::vector<T>{0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f, 0.1f, 0.2f, 0.3f,
+                           0.4f, 0.5f, 0.6f, 0.7f, 0.8f, 0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.6f,
+                           0.7f, 0.8f, 0.1f, 0.2f, 0.3f, 0.4f, 0.5f, 0.6f, 0.7f, 0.8f},
+            std::vector<T>{0.52497f, 0.54983f, 0.57444f, 0.59868f, 0.62245f, 0.64565f, 0.66818f, 0.68997f,
+                           0.1f,     0.2f,     0.3f,     0.4f,     0.5f,     0.6f,     0.7f,     0.8f,
+                           0.52497f, 0.54983f, 0.57444f, 0.59868f, 0.62245f, 0.64565f, 0.66818f, 0.68997f}),
     };
     return regionYoloParams;
 }
 
 std::vector<RegionYoloParams> generateRegionYoloCombinedParams() {
-    const std::vector<std::vector<RegionYoloParams>> regionYoloTypeParams {
+    const std::vector<std::vector<RegionYoloParams>> regionYoloTypeParams{
         generateRegionYoloParams<element::Type_t::f64>(),
         generateRegionYoloParams<element::Type_t::f32>(),
         generateRegionYoloParams<element::Type_t::f16>(),
-        generateRegionYoloParams<element::Type_t::bf16>()
-        };
+        generateRegionYoloParams<element::Type_t::bf16>()};
     std::vector<RegionYoloParams> combinedParams;
 
     for (const auto& params : regionYoloTypeParams) {
@@ -149,7 +159,9 @@ std::vector<RegionYoloParams> generateRegionYoloCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_RegionYolo_With_Hardcoded_Refs, ReferenceRegionYoloLayerTest,
-    testing::ValuesIn(generateRegionYoloCombinedParams()), ReferenceRegionYoloLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_RegionYolo_With_Hardcoded_Refs,
+                         ReferenceRegionYoloLayerTest,
+                         testing::ValuesIn(generateRegionYoloCombinedParams()),
+                         ReferenceRegionYoloLayerTest::getTestCaseName);
 
-} // namespace
\ No newline at end of file
+}  // namespace
\ No newline at end of file
diff --git a/src/plugins/template/tests/functional/op_reference/relu.cpp b/src/plugins/template/tests/functional/op_reference/relu.cpp
index 2e31a299fd2d10..2df326758fdabc 100644
--- a/src/plugins/template/tests/functional/op_reference/relu.cpp
+++ b/src/plugins/template/tests/functional/op_reference/relu.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/relu.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/relu.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,7 +14,10 @@ using namespace ov;
 namespace {
 struct ReluParams {
     template <class IT>
-    ReluParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    ReluParams(const ov::PartialShape& shape,
+               const ov::element::Type& iType,
+               const std::vector<IT>& iValues,
+               const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -45,11 +49,12 @@ class ReferenceReluLayerTest : public testing::TestWithParam<ReluParams>, public
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& Reluected_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& Reluected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Relu = std::make_shared<op::v0::Relu>(in);
-        return std::make_shared<ov::Model>(NodeVector {Relu}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Relu}, ParameterVector{in});
     }
 };
 
@@ -57,21 +62,19 @@ TEST_P(ReferenceReluLayerTest, CompareWithRefs) {
     Exec();
 }
 
-
 template <element::Type_t IN_ET>
 std::vector<ReluParams> generateReluFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ReluParams> reluParams {
-        ReluParams(ov::PartialShape {2, 5},
-                    IN_ET,
-                    std::vector<T>{1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5},
-                    std::vector<T>{1, 8, 0, 17, 0, 1, 8, 0, 17, 0}),
-        ReluParams(ov::PartialShape {2, 2, 2, 2},
-                    IN_ET,
-                    std::vector<T>{1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5, 1},
-                    std::vector<T>{1, 8, 0, 17, 0, 1, 8, 0, 17, 0, 1, 8, 0, 17, 0, 1})
-    };
+    std::vector<ReluParams> reluParams{
+        ReluParams(ov::PartialShape{2, 5},
+                   IN_ET,
+                   std::vector<T>{1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5},
+                   std::vector<T>{1, 8, 0, 17, 0, 1, 8, 0, 17, 0}),
+        ReluParams(ov::PartialShape{2, 2, 2, 2},
+                   IN_ET,
+                   std::vector<T>{1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5, 1, 8, -8, 17, -0.5, 1},
+                   std::vector<T>{1, 8, 0, 17, 0, 1, 8, 0, 17, 0, 1, 8, 0, 17, 0, 1})};
     return reluParams;
 }
 
@@ -79,12 +82,10 @@ template <element::Type_t IN_ET>
 std::vector<ReluParams> generateReluIntParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ReluParams> reluParams {
-        ReluParams(ov::PartialShape {2, 5},
-                    IN_ET,
-                    std::vector<T>{1, 8, -8, 17, -2, 1, 8, -8, 17, -1},
-                    std::vector<T>{1, 8, 0, 17, 0, 1, 8, 0, 17, 0})
-    };
+    std::vector<ReluParams> reluParams{ReluParams(ov::PartialShape{2, 5},
+                                                  IN_ET,
+                                                  std::vector<T>{1, 8, -8, 17, -2, 1, 8, -8, 17, -1},
+                                                  std::vector<T>{1, 8, 0, 17, 0, 1, 8, 0, 17, 0})};
     return reluParams;
 }
 
@@ -92,24 +93,20 @@ template <element::Type_t IN_ET>
 std::vector<ReluParams> generateReluUintParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ReluParams> reluParams {
-        ReluParams(ov::PartialShape {2, 5},
-                    IN_ET,
-                    std::vector<T>{1, 8, 17, 1, 8, 17, 1, 8, 17, 0},
-                    std::vector<T>{1, 8, 17, 1, 8, 17, 1, 8, 17, 0})
-    };
+    std::vector<ReluParams> reluParams{ReluParams(ov::PartialShape{2, 5},
+                                                  IN_ET,
+                                                  std::vector<T>{1, 8, 17, 1, 8, 17, 1, 8, 17, 0},
+                                                  std::vector<T>{1, 8, 17, 1, 8, 17, 1, 8, 17, 0})};
     return reluParams;
 }
 
 std::vector<ReluParams> generateReluCombinedParams() {
-    const std::vector<std::vector<ReluParams>> reluTypeParams {
-        generateReluFloatParams<element::Type_t::f32>(),
-        generateReluFloatParams<element::Type_t::f16>(),
-        generateReluIntParams<element::Type_t::i64>(),
-        generateReluIntParams<element::Type_t::i32>(),
-        generateReluUintParams<element::Type_t::u64>(),
-        generateReluUintParams<element::Type_t::u32>()
-        };
+    const std::vector<std::vector<ReluParams>> reluTypeParams{generateReluFloatParams<element::Type_t::f32>(),
+                                                              generateReluFloatParams<element::Type_t::f16>(),
+                                                              generateReluIntParams<element::Type_t::i64>(),
+                                                              generateReluIntParams<element::Type_t::i32>(),
+                                                              generateReluUintParams<element::Type_t::u64>(),
+                                                              generateReluUintParams<element::Type_t::u32>()};
     std::vector<ReluParams> combinedParams;
 
     for (const auto& params : reluTypeParams) {
@@ -118,7 +115,9 @@ std::vector<ReluParams> generateReluCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Relu_With_Hardcoded_Refs, ReferenceReluLayerTest,
-    testing::ValuesIn(generateReluCombinedParams()), ReferenceReluLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Relu_With_Hardcoded_Refs,
+                         ReferenceReluLayerTest,
+                         testing::ValuesIn(generateReluCombinedParams()),
+                         ReferenceReluLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/reorg_yolo.cpp b/src/plugins/template/tests/functional/op_reference/reorg_yolo.cpp
index ddea9ce114b6f5..43e509b4b051a1 100644
--- a/src/plugins/template/tests/functional/op_reference/reorg_yolo.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reorg_yolo.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reorg_yolo.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reorg_yolo.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -30,10 +31,10 @@ struct ReorgYoloParams {
           outType(iType),
           refData(CreateTensor(iType, oValues)),
           testcaseName(testcaseName) {
-              std::vector<IT> iValues(shape_size(inputShape.get_shape()));
-              std::iota(iValues.begin(), iValues.end(), 0);
-              inputData = CreateTensor(iType, iValues);
-          }
+        std::vector<IT> iValues(shape_size(inputShape.get_shape()));
+        std::iota(iValues.begin(), iValues.end(), 0);
+        inputData = CreateTensor(iType, iValues);
+    }
 
     ov::Strides stride;
     ov::PartialShape inputShape;
@@ -72,7 +73,7 @@ class ReferenceReorgYoloLayerTest : public testing::TestWithParam<ReorgYoloParam
     static std::shared_ptr<Model> CreateFunction(const ReorgYoloParams& params) {
         const auto p = std::make_shared<op::v0::Parameter>(params.inType, params.inputShape);
         const auto ReorgYolo = std::make_shared<op::v0::ReorgYolo>(p, params.stride);
-        return std::make_shared<ov::Model>(NodeVector {ReorgYolo}, ParameterVector {p});
+        return std::make_shared<ov::Model>(NodeVector{ReorgYolo}, ParameterVector{p});
     }
 };
 
@@ -84,28 +85,32 @@ template <element::Type_t IN_ET>
 std::vector<ReorgYoloParams> generateReorgYoloParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<ReorgYoloParams> reorgYoloParams {
+    std::vector<ReorgYoloParams> reorgYoloParams{
         ReorgYoloParams({2},
-                        PartialShape {1, 8, 4, 4},
-                        IN_ET,
-                        std::vector<T>{0,   2,   4,   6,   16,  18,  20,  22,  32,  34,  36,  38,  48,  50,  52,  54,  64,  66,  68,  70,  80, 82,
-                                       84,  86,  96,  98,  100, 102, 112, 114, 116, 118, 1,   3,   5,   7,   17,  19,  21,  23,  33,  35,  37, 39,
-                                       49,  51,  53,  55,  65,  67,  69,  71,  81,  83,  85,  87,  97,  99,  101, 103, 113, 115, 117, 119, 8,  10,
-                                       12,  14,  24,  26,  28,  30,  40,  42,  44,  46,  56,  58,  60,  62,  72,  74,  76,  78,  88,  90,  92, 94,
-                                       104, 106, 108, 110, 120, 122, 124, 126, 9,   11,  13,  15,  25,  27,  29,  31,  41,  43,  45,  47,  57, 59,
-                                       61,  63,  73,  75,  77,  79,  89,  91,  93,  95,  105, 107, 109, 111, 121, 123, 125, 127}),
-        ReorgYoloParams({3},
-                        PartialShape {1, 9, 3, 3},
+                        PartialShape{1, 8, 4, 4},
                         IN_ET,
-                        std::vector<T>{0,  3,  6,  27, 30, 33, 54, 57, 60, 1,  4,  7,  28, 31, 34, 55, 58, 61, 2,  5,  8,  29, 32, 35, 56, 59, 62,
-                                       9,  12, 15, 36, 39, 42, 63, 66, 69, 10, 13, 16, 37, 40, 43, 64, 67, 70, 11, 14, 17, 38, 41, 44, 65, 68, 71,
-                                       18, 21, 24, 45, 48, 51, 72, 75, 78, 19, 22, 25, 46, 49, 52, 73, 76, 79, 20, 23, 26, 47, 50, 53, 74, 77, 80}),
+                        std::vector<T>{0,  2,  4,  6,  16, 18, 20, 22, 32,  34,  36,  38,  48,  50,  52,  54,
+                                       64, 66, 68, 70, 80, 82, 84, 86, 96,  98,  100, 102, 112, 114, 116, 118,
+                                       1,  3,  5,  7,  17, 19, 21, 23, 33,  35,  37,  39,  49,  51,  53,  55,
+                                       65, 67, 69, 71, 81, 83, 85, 87, 97,  99,  101, 103, 113, 115, 117, 119,
+                                       8,  10, 12, 14, 24, 26, 28, 30, 40,  42,  44,  46,  56,  58,  60,  62,
+                                       72, 74, 76, 78, 88, 90, 92, 94, 104, 106, 108, 110, 120, 122, 124, 126,
+                                       9,  11, 13, 15, 25, 27, 29, 31, 41,  43,  45,  47,  57,  59,  61,  63,
+                                       73, 75, 77, 79, 89, 91, 93, 95, 105, 107, 109, 111, 121, 123, 125, 127}),
+        ReorgYoloParams(
+            {3},
+            PartialShape{1, 9, 3, 3},
+            IN_ET,
+            std::vector<T>{0,  3,  6,  27, 30, 33, 54, 57, 60, 1,  4,  7,  28, 31, 34, 55, 58, 61, 2,  5,  8,
+                           29, 32, 35, 56, 59, 62, 9,  12, 15, 36, 39, 42, 63, 66, 69, 10, 13, 16, 37, 40, 43,
+                           64, 67, 70, 11, 14, 17, 38, 41, 44, 65, 68, 71, 18, 21, 24, 45, 48, 51, 72, 75, 78,
+                           19, 22, 25, 46, 49, 52, 73, 76, 79, 20, 23, 26, 47, 50, 53, 74, 77, 80}),
     };
     return reorgYoloParams;
 }
 
 std::vector<ReorgYoloParams> generateReorgYoloCombinedParams() {
-    const std::vector<std::vector<ReorgYoloParams>> reorgYoloTypeParams {
+    const std::vector<std::vector<ReorgYoloParams>> reorgYoloTypeParams{
         generateReorgYoloParams<element::Type_t::f64>(),
         generateReorgYoloParams<element::Type_t::f32>(),
         generateReorgYoloParams<element::Type_t::f16>(),
@@ -118,7 +123,7 @@ std::vector<ReorgYoloParams> generateReorgYoloCombinedParams() {
         generateReorgYoloParams<element::Type_t::u32>(),
         generateReorgYoloParams<element::Type_t::u16>(),
         generateReorgYoloParams<element::Type_t::u8>(),
-        };
+    };
     std::vector<ReorgYoloParams> combinedParams;
 
     for (const auto& params : reorgYoloTypeParams) {
@@ -127,7 +132,9 @@ std::vector<ReorgYoloParams> generateReorgYoloCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ReorgYolo_With_Hardcoded_Refs, ReferenceReorgYoloLayerTest,
-    testing::ValuesIn(generateReorgYoloCombinedParams()), ReferenceReorgYoloLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_ReorgYolo_With_Hardcoded_Refs,
+                         ReferenceReorgYoloLayerTest,
+                         testing::ValuesIn(generateReorgYoloCombinedParams()),
+                         ReferenceReorgYoloLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/reshape.cpp b/src/plugins/template/tests/functional/op_reference/reshape.cpp
index dabd4c20ce11bd..85dabdd6ce8add 100644
--- a/src/plugins/template/tests/functional/op_reference/reshape.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reshape.cpp
@@ -2,15 +2,16 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reshape.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reshape.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
-//using T1 = typename element_type_traits<IT>::value_type;
+// using T1 = typename element_type_traits<IT>::value_type;
 namespace {
 
 struct ReshapeParams {
@@ -27,15 +28,13 @@ struct ReshapeParams {
         m_input_type = input_type;
         m_expected_type = expected_type;
         m_zero_flag = zero_flag;
-        m_input_value = input_shape.size() > 0
-            ? CreateTensor(input_shape, input_type, input_value)
-            : CreateTensor(input_type, input_value);
-        m_expected_value = expected_shape.size() > 0
-            ? CreateTensor(expected_shape, expected_type, expected_value)
-            : CreateTensor(expected_type, expected_value);
+        m_input_value = input_shape.size() > 0 ? CreateTensor(input_shape, input_type, input_value)
+                                               : CreateTensor(input_type, input_value);
+        m_expected_value = expected_shape.size() > 0 ? CreateTensor(expected_shape, expected_type, expected_value)
+                                                     : CreateTensor(expected_type, expected_value);
     }
 
-    template<class T>
+    template <class T>
     ReshapeParams(const Shape& input_shape,
                   const Shape& expected_shape,
                   const element::Type& input_type,
@@ -69,7 +68,7 @@ struct ReshapeParams {
 };
 
 struct ReshapeShuffleParams {
-    template<class T>
+    template <class T>
     ReshapeShuffleParams(const Shape& input_shape1,
                          const Shape& input_shape2,
                          const Shape& input_shape3,
@@ -130,10 +129,10 @@ class ReferenceReshapeLayerTest : public testing::TestWithParam<ReshapeParams>,
 
 private:
     static std::shared_ptr<Model> CreateFunction(const element::Type& input_type,
-                                                    const element::Type& expected_type,
-                                                    const Shape& input_shape,
-                                                    const Shape& expected_shape,
-                                                    const bool zero_flag) {
+                                                 const element::Type& expected_type,
+                                                 const Shape& input_shape,
+                                                 const Shape& expected_shape,
+                                                 const bool zero_flag) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto reshape = std::make_shared<op::v1::Reshape>(
             in,
@@ -143,7 +142,8 @@ class ReferenceReshapeLayerTest : public testing::TestWithParam<ReshapeParams>,
     }
 };
 
-class ReferenceReshapeShuffleLayerTest : public testing::TestWithParam<ReshapeShuffleParams>, public CommonReferenceTest {
+class ReferenceReshapeShuffleLayerTest : public testing::TestWithParam<ReshapeShuffleParams>,
+                                         public CommonReferenceTest {
 public:
     void SetUp() override {
         const auto params = GetParam();
@@ -172,12 +172,12 @@ class ReferenceReshapeShuffleLayerTest : public testing::TestWithParam<ReshapeSh
 
 private:
     static std::shared_ptr<Model> CreateFunction(const element::Type& input_type,
-                                                    const element::Type& expected_type,
-                                                    const Shape& input_shape1,
-                                                    const Shape& input_shape2,
-                                                    const Shape& input_shape3,
-                                                    const Shape& expected_shape,
-                                                    const bool zero_flag) {
+                                                 const element::Type& expected_type,
+                                                 const Shape& input_shape1,
+                                                 const Shape& input_shape2,
+                                                 const Shape& input_shape3,
+                                                 const Shape& expected_shape,
+                                                 const bool zero_flag) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto reshape1 = std::make_shared<op::v1::Reshape>(
             in,
@@ -215,41 +215,11 @@ std::vector<ReshapeParams> generateParamsForReshape() {
                       std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
                       std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
                       false),
-        ReshapeParams(Shape{1, 1, 1},
-                      Shape{},
-                      ET,
-                      ET,
-                      std::vector<T>{6},
-                      std::vector<T>{6},
-                      false),
-        ReshapeParams(Shape{},
-                      Shape{1, 1, 1, 1, 1, 1},
-                      ET,
-                      ET,
-                      std::vector<T>{42},
-                      std::vector<T>{42},
-                      false),
-        ReshapeParams(Shape{3},
-                      Shape{3, 1},
-                      ET,
-                      ET,
-                      std::vector<T>{1, 2, 3},
-                      std::vector<T>{1, 2, 3},
-                      false),
-        ReshapeParams(Shape{3},
-                      Shape{1, 3},
-                      ET,
-                      ET,
-                      std::vector<T>{1, 2, 3},
-                      std::vector<T>{1, 2, 3},
-                      false),
-        ReshapeParams(Shape{3},
-                      Shape{1, 3, 1},
-                      ET,
-                      ET,
-                      std::vector<T>{1, 2, 3},
-                      std::vector<T>{1, 2, 3},
-                      false),
+        ReshapeParams(Shape{1, 1, 1}, Shape{}, ET, ET, std::vector<T>{6}, std::vector<T>{6}, false),
+        ReshapeParams(Shape{}, Shape{1, 1, 1, 1, 1, 1}, ET, ET, std::vector<T>{42}, std::vector<T>{42}, false),
+        ReshapeParams(Shape{3}, Shape{3, 1}, ET, ET, std::vector<T>{1, 2, 3}, std::vector<T>{1, 2, 3}, false),
+        ReshapeParams(Shape{3}, Shape{1, 3}, ET, ET, std::vector<T>{1, 2, 3}, std::vector<T>{1, 2, 3}, false),
+        ReshapeParams(Shape{3}, Shape{1, 3, 1}, ET, ET, std::vector<T>{1, 2, 3}, std::vector<T>{1, 2, 3}, false),
         ReshapeParams(Shape{3, 3},
                       Shape{3, 3},
                       ET,
@@ -257,34 +227,10 @@ std::vector<ReshapeParams> generateParamsForReshape() {
                       std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9},
                       std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9},
                       false),
-        ReshapeParams(Shape{1},
-                      Shape{},
-                      ET,
-                      ET,
-                      std::vector<T>{1},
-                      std::vector<T>{1},
-                      false),
-        ReshapeParams(Shape{},
-                      Shape{},
-                      ET,
-                      ET,
-                      std::vector<T>{1},
-                      std::vector<T>{1},
-                      false),
-        ReshapeParams(Shape{2, 2, 3, 3, 2, 4},
-                      Shape{3, 2, 2, 4, 3, 2},
-                      ET,
-                      ET,
-                      false,
-                      static_cast<T>(1)),
-        ReshapeParams(Shape{2, 2, 5, 5},
-                      Shape{2, 5, 5, 2},
-                      ET,
-                      ET,
-                      true,
-                      static_cast<T>(1),
-                      Shape{0, 5, 0, 2})
-    };
+        ReshapeParams(Shape{1}, Shape{}, ET, ET, std::vector<T>{1}, std::vector<T>{1}, false),
+        ReshapeParams(Shape{}, Shape{}, ET, ET, std::vector<T>{1}, std::vector<T>{1}, false),
+        ReshapeParams(Shape{2, 2, 3, 3, 2, 4}, Shape{3, 2, 2, 4, 3, 2}, ET, ET, false, static_cast<T>(1)),
+        ReshapeParams(Shape{2, 2, 5, 5}, Shape{2, 5, 5, 2}, ET, ET, true, static_cast<T>(1), Shape{0, 5, 0, 2})};
 
     return params;
 }
@@ -301,56 +247,13 @@ std::vector<ReshapeParams> generateParamsForReshape8Bit() {
                       std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
                       std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12},
                       false),
-        ReshapeParams(Shape{1, 1, 1},
-                      Shape{},
-                      ET,
-                      ET,
-                      std::vector<T>{6},
-                      std::vector<T>{6},
-                      false),
-        ReshapeParams(Shape{},
-                      Shape{1, 1, 1, 1, 1, 1},
-                      ET,
-                      ET,
-                      std::vector<T>{42},
-                      std::vector<T>{42},
-                      false),
-        ReshapeParams(Shape{3},
-                      Shape{3, 1},
-                      ET,
-                      ET,
-                      std::vector<T>{1, 2, 3},
-                      std::vector<T>{1, 2, 3},
-                      false),
-        ReshapeParams(Shape{3},
-                      Shape{1, 3},
-                      ET,
-                      ET,
-                      std::vector<T>{1, 2, 3},
-                      std::vector<T>{1, 2, 3},
-                      false),
-        ReshapeParams(Shape{3},
-                      Shape{1, 3, 1},
-                      ET,
-                      ET,
-                      std::vector<T>{1, 2, 3},
-                      std::vector<T>{1, 2, 3},
-                      false),
-        ReshapeParams(Shape{1},
-                      Shape{},
-                      ET,
-                      ET,
-                      std::vector<T>{1},
-                      std::vector<T>{1},
-                      false),
-        ReshapeParams(Shape{},
-                      Shape{},
-                      ET,
-                      ET,
-                      std::vector<T>{1},
-                      std::vector<T>{1},
-                      false)
-    };
+        ReshapeParams(Shape{1, 1, 1}, Shape{}, ET, ET, std::vector<T>{6}, std::vector<T>{6}, false),
+        ReshapeParams(Shape{}, Shape{1, 1, 1, 1, 1, 1}, ET, ET, std::vector<T>{42}, std::vector<T>{42}, false),
+        ReshapeParams(Shape{3}, Shape{3, 1}, ET, ET, std::vector<T>{1, 2, 3}, std::vector<T>{1, 2, 3}, false),
+        ReshapeParams(Shape{3}, Shape{1, 3}, ET, ET, std::vector<T>{1, 2, 3}, std::vector<T>{1, 2, 3}, false),
+        ReshapeParams(Shape{3}, Shape{1, 3, 1}, ET, ET, std::vector<T>{1, 2, 3}, std::vector<T>{1, 2, 3}, false),
+        ReshapeParams(Shape{1}, Shape{}, ET, ET, std::vector<T>{1}, std::vector<T>{1}, false),
+        ReshapeParams(Shape{}, Shape{}, ET, ET, std::vector<T>{1}, std::vector<T>{1}, false)};
 
     return params;
 }
@@ -359,32 +262,28 @@ template <element::Type_t ET>
 std::vector<ReshapeShuffleParams> generateParamsForReshapeShuffle() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<ReshapeShuffleParams> params{
-        ReshapeShuffleParams(Shape{1, 112, 56, 56},
-                      Shape{1, 4, 28, 56, 56},
-                      Shape{1, 28, 4, 56, 56},
-                      Shape{1, 112, 56, 56},
-                      ET,
-                      ET,
-                      false,
-                      static_cast<T>(1))
-    };
+    std::vector<ReshapeShuffleParams> params{ReshapeShuffleParams(Shape{1, 112, 56, 56},
+                                                                  Shape{1, 4, 28, 56, 56},
+                                                                  Shape{1, 28, 4, 56, 56},
+                                                                  Shape{1, 112, 56, 56},
+                                                                  ET,
+                                                                  ET,
+                                                                  false,
+                                                                  static_cast<T>(1))};
 
     return params;
 }
 
 std::vector<ReshapeParams> generateCombinedParamsForReshape() {
-    const std::vector<std::vector<ReshapeParams>> allTypeParams{
-        generateParamsForReshape<element::Type_t::f32>(),
-        generateParamsForReshape<element::Type_t::i64>(),
-        generateParamsForReshape<element::Type_t::i32>(),
-        generateParamsForReshape<element::Type_t::i16>(),
-        generateParamsForReshape<element::Type_t::u64>(),
-        generateParamsForReshape<element::Type_t::u32>(),
-        generateParamsForReshape<element::Type_t::u16>(),
-        generateParamsForReshape8Bit<element::Type_t::i8>(),
-        generateParamsForReshape8Bit<element::Type_t::u8>()
-    };
+    const std::vector<std::vector<ReshapeParams>> allTypeParams{generateParamsForReshape<element::Type_t::f32>(),
+                                                                generateParamsForReshape<element::Type_t::i64>(),
+                                                                generateParamsForReshape<element::Type_t::i32>(),
+                                                                generateParamsForReshape<element::Type_t::i16>(),
+                                                                generateParamsForReshape<element::Type_t::u64>(),
+                                                                generateParamsForReshape<element::Type_t::u32>(),
+                                                                generateParamsForReshape<element::Type_t::u16>(),
+                                                                generateParamsForReshape8Bit<element::Type_t::i8>(),
+                                                                generateParamsForReshape8Bit<element::Type_t::u8>()};
 
     std::vector<ReshapeParams> combinedParams;
 
@@ -417,16 +316,14 @@ std::vector<ReshapeShuffleParams> generateCombinedParamsForReshapeShuffle() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Reshape_With_Hardcoded_Refs,
-    ReferenceReshapeLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForReshape()),
-    ReferenceReshapeLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Reshape_Shuffle_With_Hardcoded_Refs,
-    ReferenceReshapeShuffleLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForReshapeShuffle()),
-    ReferenceReshapeShuffleLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Reshape_With_Hardcoded_Refs,
+                         ReferenceReshapeLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForReshape()),
+                         ReferenceReshapeLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Reshape_Shuffle_With_Hardcoded_Refs,
+                         ReferenceReshapeShuffleLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForReshapeShuffle()),
+                         ReferenceReshapeShuffleLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/result.cpp b/src/plugins/template/tests/functional/op_reference/result.cpp
index 38ba2ea06a03ca..9b458e4e130106 100644
--- a/src/plugins/template/tests/functional/op_reference/result.cpp
+++ b/src/plugins/template/tests/functional/op_reference/result.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/result.hpp"
+
 #include <gtest/gtest.h>
 
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
-#include "openvino/op/result.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -16,11 +17,11 @@ namespace {
 struct ResultParams {
     template <class T>
     ResultParams(const Shape& input_shape,
-                    const Shape& expected_shape,
-                    const element::Type& input_type,
-                    const element::Type& expected_type,
-                    const std::vector<T>& input_value,
-                    const std::vector<T>& expected_value)
+                 const Shape& expected_shape,
+                 const element::Type& input_type,
+                 const element::Type& expected_type,
+                 const std::vector<T>& input_value,
+                 const std::vector<T>& expected_value)
         : m_input_shape(input_shape),
           m_expected_shape(expected_shape),
           m_input_type(input_type),
@@ -74,32 +75,24 @@ std::vector<ResultParams> generateParamsForResult() {
     using T = typename element_type_traits<ET>::value_type;
 
     std::vector<ResultParams> params{
-        ResultParams(Shape{2, 2},
-                        Shape{2, 2},
-                        ET,
-                        ET,
-                        std::vector<T>{1, 2, 3, 5},
-                        std::vector<T>{1, 2, 3, 5})
-    };
+        ResultParams(Shape{2, 2}, Shape{2, 2}, ET, ET, std::vector<T>{1, 2, 3, 5}, std::vector<T>{1, 2, 3, 5})};
 
     return params;
 }
 
 std::vector<ResultParams> generateCombinedParamsForResult() {
-    const std::vector<std::vector<ResultParams>> allTypeParams{
-        generateParamsForResult<element::Type_t::boolean>(),
-        generateParamsForResult<element::Type_t::f32>(),
-        generateParamsForResult<element::Type_t::f16>(),
-        generateParamsForResult<element::Type_t::bf16>(),
-        generateParamsForResult<element::Type_t::i64>(),
-        generateParamsForResult<element::Type_t::i32>(),
-        generateParamsForResult<element::Type_t::i16>(),
-        generateParamsForResult<element::Type_t::i8>(),
-        generateParamsForResult<element::Type_t::u64>(),
-        generateParamsForResult<element::Type_t::u32>(),
-        generateParamsForResult<element::Type_t::u16>(),
-        generateParamsForResult<element::Type_t::u8>()
-    };
+    const std::vector<std::vector<ResultParams>> allTypeParams{generateParamsForResult<element::Type_t::boolean>(),
+                                                               generateParamsForResult<element::Type_t::f32>(),
+                                                               generateParamsForResult<element::Type_t::f16>(),
+                                                               generateParamsForResult<element::Type_t::bf16>(),
+                                                               generateParamsForResult<element::Type_t::i64>(),
+                                                               generateParamsForResult<element::Type_t::i32>(),
+                                                               generateParamsForResult<element::Type_t::i16>(),
+                                                               generateParamsForResult<element::Type_t::i8>(),
+                                                               generateParamsForResult<element::Type_t::u64>(),
+                                                               generateParamsForResult<element::Type_t::u32>(),
+                                                               generateParamsForResult<element::Type_t::u16>(),
+                                                               generateParamsForResult<element::Type_t::u8>()};
 
     std::vector<ResultParams> combinedParams;
 
@@ -110,10 +103,9 @@ std::vector<ResultParams> generateCombinedParamsForResult() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Result_With_Hardcoded_Refs,
-    ReferenceResultLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForResult()),
-    ReferenceResultLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Result_With_Hardcoded_Refs,
+                         ReferenceResultLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForResult()),
+                         ReferenceResultLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/reverse.cpp b/src/plugins/template/tests/functional/op_reference/reverse.cpp
index 48d3387cbd4ca9..b7e19dfbdaf619 100644
--- a/src/plugins/template/tests/functional/op_reference/reverse.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reverse.cpp
@@ -9,7 +9,6 @@
 #include "base_reference_test.hpp"
 #include "openvino/op/constant.hpp"
 
-
 using namespace reference_tests;
 using namespace ov;
 
diff --git a/src/plugins/template/tests/functional/op_reference/reverse_sequence.cpp b/src/plugins/template/tests/functional/op_reference/reverse_sequence.cpp
index c4861456ffac55..8135f94b3600f7 100644
--- a/src/plugins/template/tests/functional/op_reference/reverse_sequence.cpp
+++ b/src/plugins/template/tests/functional/op_reference/reverse_sequence.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/reverse_sequence.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/reverse_sequence.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,9 +13,16 @@ using namespace ov;
 
 namespace {
 struct ReverseSequenceParams {
-    ReverseSequenceParams(const int64_t batchAxis, const int64_t seqAxis, const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& seqLengthsTensor,
-                          const reference_tests::Tensor& expectedTensor) : mBatchAxis(batchAxis), mSeqAxis(seqAxis), mDataTensor(dataTensor),
-                          mSeqLengthsTensor(seqLengthsTensor), mExpectedTensor(expectedTensor) {}
+    ReverseSequenceParams(const int64_t batchAxis,
+                          const int64_t seqAxis,
+                          const reference_tests::Tensor& dataTensor,
+                          const reference_tests::Tensor& seqLengthsTensor,
+                          const reference_tests::Tensor& expectedTensor)
+        : mBatchAxis(batchAxis),
+          mSeqAxis(seqAxis),
+          mDataTensor(dataTensor),
+          mSeqLengthsTensor(seqLengthsTensor),
+          mExpectedTensor(expectedTensor) {}
     int64_t mBatchAxis;
     int64_t mSeqAxis;
     reference_tests::Tensor mDataTensor;
@@ -45,9 +53,11 @@ class ReferenceReverseSequenceTest : public testing::TestWithParam<ReverseSequen
 private:
     static std::shared_ptr<Model> CreateFunction(const ReverseSequenceParams& params) {
         const auto data = std::make_shared<op::v0::Parameter>(params.mDataTensor.type, params.mDataTensor.shape);
-        const auto seqLengths = std::make_shared<op::v0::Parameter>(params.mSeqLengthsTensor.type, params.mSeqLengthsTensor.shape);
-        const auto reverseSequence = std::make_shared<op::v0::ReverseSequence>(data, seqLengths, params.mBatchAxis, params.mSeqAxis);
-        return std::make_shared<ov::Model>(NodeVector {reverseSequence}, ParameterVector {data, seqLengths});
+        const auto seqLengths =
+            std::make_shared<op::v0::Parameter>(params.mSeqLengthsTensor.type, params.mSeqLengthsTensor.shape);
+        const auto reverseSequence =
+            std::make_shared<op::v0::ReverseSequence>(data, seqLengths, params.mBatchAxis, params.mSeqAxis);
+        return std::make_shared<ov::Model>(NodeVector{reverseSequence}, ParameterVector{data, seqLengths});
     }
 };
 
@@ -58,76 +68,93 @@ TEST_P(ReferenceReverseSequenceTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<ReverseSequenceParams> generateReverseSeqParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<ReverseSequenceParams> reverseSeqParams {
+    std::vector<ReverseSequenceParams> reverseSeqParams{
         // 2D
-        ReverseSequenceParams(1, 0,
-                              reference_tests::Tensor({4, 4}, IN_ET, std::vector<T>{0, 4, 8, 12,
-                                                                   1, 5, 9, 13,
-                                                                   2, 6, 10, 14,
-                                                                   3, 7, 11, 15}),
-                              reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{4, 3, 2, 1}),
-                              reference_tests::Tensor({4, 4}, IN_ET, std::vector<T>{3, 6, 9,  12,
-                                                                   2, 5, 8,  13,
-                                                                   1, 4, 10, 14,
-                                                                   0, 7, 11, 15})),
-        ReverseSequenceParams(0, 1,
-                              reference_tests::Tensor({4, 4}, IN_ET, std::vector<T>{0, 1, 2, 3,
-                                                                   4, 5, 6, 7,
-                                                                   8, 9, 10, 11,
-                                                                   12, 13, 14, 15}),
-                              reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 3, 4}),
-                              reference_tests::Tensor({4, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,
-                                                                   5,  4,  6,  7,
-                                                                   10, 9,  8,  11,
-                                                                   15, 14, 13, 12})),
+        ReverseSequenceParams(
+            1,
+            0,
+            reference_tests::Tensor({4, 4},
+                                    IN_ET,
+                                    std::vector<T>{0, 4, 8, 12, 1, 5, 9, 13, 2, 6, 10, 14, 3, 7, 11, 15}),
+            reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{4, 3, 2, 1}),
+            reference_tests::Tensor({4, 4},
+                                    IN_ET,
+                                    std::vector<T>{3, 6, 9, 12, 2, 5, 8, 13, 1, 4, 10, 14, 0, 7, 11, 15})),
+        ReverseSequenceParams(
+            0,
+            1,
+            reference_tests::Tensor({4, 4},
+                                    IN_ET,
+                                    std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}),
+            reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 3, 4}),
+            reference_tests::Tensor({4, 4},
+                                    IN_ET,
+                                    std::vector<T>{0, 1, 2, 3, 5, 4, 6, 7, 10, 9, 8, 11, 15, 14, 13, 12})),
         // 4D
-        ReverseSequenceParams(2, 1,
-                              reference_tests::Tensor({2, 3, 4, 2}, IN_ET, std::vector<T>{
-                                  0,  0, 3,  0, 6,  0, 9,  0, 1,  0, 4,  0, 7,  0, 10, 0, 2,  0, 5,  0, 8,  0, 11, 0,
-                                  12, 0, 15, 0, 18, 0, 21, 0, 13, 0, 16, 0, 19, 0, 22, 0, 14, 0, 17, 0, 20, 0, 23, 0}),
-                              reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 1, 2}),
-                              reference_tests::Tensor({2, 3, 4, 2}, IN_ET, std::vector<T>{
-                                  0,  0, 4,  0, 6,  0, 10, 0, 1,  0, 3,  0, 7,  0, 9,  0, 2,  0, 5,  0, 8,  0, 11, 0,
-                                  12, 0, 16, 0, 18, 0, 22, 0, 13, 0, 15, 0, 19, 0, 21, 0, 14, 0, 17, 0, 20, 0, 23, 0})),
-        ReverseSequenceParams(-2, -3,
-                              reference_tests::Tensor({2, 3, 4, 2}, IN_ET, std::vector<T>{
-                                  0,  0, 3,  0, 6,  0, 9,  0, 1,  0, 4,  0, 7,  0, 10, 0, 2,  0, 5,  0, 8,  0, 11, 0,
-                                  12, 0, 15, 0, 18, 0, 21, 0, 13, 0, 16, 0, 19, 0, 22, 0, 14, 0, 17, 0, 20, 0, 23, 0}),
-                              reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 1, 2}),
-                              reference_tests::Tensor({2, 3, 4, 2}, IN_ET, std::vector<T>{
-                                  0,  0, 4,  0, 6,  0, 10, 0, 1,  0, 3,  0, 7,  0, 9,  0, 2,  0, 5,  0, 8,  0, 11, 0,
-                                  12, 0, 16, 0, 18, 0, 22, 0, 13, 0, 15, 0, 19, 0, 21, 0, 14, 0, 17, 0, 20, 0, 23, 0})),
-        ReverseSequenceParams(0, 1,
-                              reference_tests::Tensor({4, 3, 2, 2}, IN_ET, std::vector<T>{
-                                  0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15,
-                                  16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
-                                  32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47}),
-                              reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 3, 3}),
-                              reference_tests::Tensor({4, 3, 2, 2}, IN_ET, std::vector<T>{
-                                  0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 16, 17, 18, 19,
-                                  12, 13, 14, 15, 20, 21, 22, 23, 32, 33, 34, 35, 28, 29, 30, 31,
-                                  24, 25, 26, 27, 44, 45, 46, 47, 40, 41, 42, 43, 36, 37, 38, 39})),
+        ReverseSequenceParams(
+            2,
+            1,
+            reference_tests::Tensor({2, 3, 4, 2}, IN_ET, std::vector<T>{0,  0, 3,  0, 6,  0, 9,  0, 1,  0, 4,  0,
+                                                                        7,  0, 10, 0, 2,  0, 5,  0, 8,  0, 11, 0,
+                                                                        12, 0, 15, 0, 18, 0, 21, 0, 13, 0, 16, 0,
+                                                                        19, 0, 22, 0, 14, 0, 17, 0, 20, 0, 23, 0}),
+            reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 1, 2}),
+            reference_tests::Tensor({2, 3, 4, 2}, IN_ET, std::vector<T>{0,  0, 4,  0, 6,  0, 10, 0, 1,  0, 3,  0,
+                                                                        7,  0, 9,  0, 2,  0, 5,  0, 8,  0, 11, 0,
+                                                                        12, 0, 16, 0, 18, 0, 22, 0, 13, 0, 15, 0,
+                                                                        19, 0, 21, 0, 14, 0, 17, 0, 20, 0, 23, 0})),
+        ReverseSequenceParams(
+            -2,
+            -3,
+            reference_tests::Tensor({2, 3, 4, 2}, IN_ET, std::vector<T>{0,  0, 3,  0, 6,  0, 9,  0, 1,  0, 4,  0,
+                                                                        7,  0, 10, 0, 2,  0, 5,  0, 8,  0, 11, 0,
+                                                                        12, 0, 15, 0, 18, 0, 21, 0, 13, 0, 16, 0,
+                                                                        19, 0, 22, 0, 14, 0, 17, 0, 20, 0, 23, 0}),
+            reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 1, 2}),
+            reference_tests::Tensor({2, 3, 4, 2}, IN_ET, std::vector<T>{0,  0, 4,  0, 6,  0, 10, 0, 1,  0, 3,  0,
+                                                                        7,  0, 9,  0, 2,  0, 5,  0, 8,  0, 11, 0,
+                                                                        12, 0, 16, 0, 18, 0, 22, 0, 13, 0, 15, 0,
+                                                                        19, 0, 21, 0, 14, 0, 17, 0, 20, 0, 23, 0})),
+        ReverseSequenceParams(
+            0,
+            1,
+            reference_tests::Tensor({4, 3, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15,
+                                                   16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
+                                                   32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47}),
+            reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 3, 3}),
+            reference_tests::Tensor({4, 3, 2, 2},
+                                    IN_ET,
+                                    std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 16, 17, 18, 19,
+                                                   12, 13, 14, 15, 20, 21, 22, 23, 32, 33, 34, 35, 28, 29, 30, 31,
+                                                   24, 25, 26, 27, 44, 45, 46, 47, 40, 41, 42, 43, 36, 37, 38, 39})),
         // 5D
-        ReverseSequenceParams(0, 2,
-                              reference_tests::Tensor({4, 2, 3, 2, 2}, IN_ET, std::vector<T>{
-                                  0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                  20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                                  40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
-                                  60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
-                                  80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95}),
-                              reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 1, 2}),
-                              reference_tests::Tensor({4, 3, 2, 2}, IN_ET, std::vector<T>{
-                                  0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                  20, 21, 22, 23, 28, 29, 30, 31, 24, 25, 26, 27, 32, 33, 34, 35, 40, 41, 42, 43,
-                                  36, 37, 38, 39, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
-                                  60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 76, 77, 78, 79, 72, 73, 74, 75,
-                                  80, 81, 82, 83, 88, 89, 90, 91, 84, 85, 86, 87, 92, 93, 94, 95}))
-    };
+        ReverseSequenceParams(
+            0,
+            2,
+            reference_tests::Tensor(
+                {4, 2, 3, 2, 2},
+                IN_ET,
+                std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                               20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                               40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+                               60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
+                               80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95}),
+            reference_tests::Tensor({4}, element::i32, std::vector<int32_t>{1, 2, 1, 2}),
+            reference_tests::Tensor(
+                {4, 3, 2, 2},
+                IN_ET,
+                std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                               20, 21, 22, 23, 28, 29, 30, 31, 24, 25, 26, 27, 32, 33, 34, 35, 40, 41, 42, 43,
+                               36, 37, 38, 39, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+                               60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 76, 77, 78, 79, 72, 73, 74, 75,
+                               80, 81, 82, 83, 88, 89, 90, 91, 84, 85, 86, 87, 92, 93, 94, 95}))};
     return reverseSeqParams;
 }
 
 std::vector<ReverseSequenceParams> generateReverseSeqCombinedParams() {
-    const std::vector<std::vector<ReverseSequenceParams>> reverseSeqTypeParams {
+    const std::vector<std::vector<ReverseSequenceParams>> reverseSeqTypeParams{
         generateReverseSeqParams<element::Type_t::f32>(),
         generateReverseSeqParams<element::Type_t::f16>(),
         generateReverseSeqParams<element::Type_t::i32>(),
@@ -142,6 +169,8 @@ std::vector<ReverseSequenceParams> generateReverseSeqCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ReverseSequence_With_Hardcoded_Refs, ReferenceReverseSequenceTest,
-    testing::ValuesIn(generateReverseSeqCombinedParams()), ReferenceReverseSequenceTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_ReverseSequence_With_Hardcoded_Refs,
+                         ReferenceReverseSequenceTest,
+                         testing::ValuesIn(generateReverseSeqCombinedParams()),
+                         ReferenceReverseSequenceTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/rnn_cell.cpp b/src/plugins/template/tests/functional/op_reference/rnn_cell.cpp
index 8d0c36d94d927c..ae9685174a182b 100644
--- a/src/plugins/template/tests/functional/op_reference/rnn_cell.cpp
+++ b/src/plugins/template/tests/functional/op_reference/rnn_cell.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/rnn_cell.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/rnn_cell.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,12 +13,26 @@ using namespace ov;
 
 namespace {
 struct RNNCellParams {
-    RNNCellParams(
-        int32_t batchSize, int32_t inputSize, int32_t hiddenSize,
-        const reference_tests::Tensor& X, const reference_tests::Tensor& H_t, const reference_tests::Tensor& W, const reference_tests::Tensor& R, const reference_tests::Tensor& B,
-        const reference_tests::Tensor& Ho, const std::string& testcaseName = "") :
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize),
-        X(X), H_t(H_t), W(W), R(R), B(B), Ho(Ho), testcaseName(testcaseName) {}
+    RNNCellParams(int32_t batchSize,
+                  int32_t inputSize,
+                  int32_t hiddenSize,
+                  const reference_tests::Tensor& X,
+                  const reference_tests::Tensor& H_t,
+                  const reference_tests::Tensor& W,
+                  const reference_tests::Tensor& R,
+                  const reference_tests::Tensor& B,
+                  const reference_tests::Tensor& Ho,
+                  const std::string& testcaseName = "")
+        : batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          X(X),
+          H_t(H_t),
+          W(W),
+          R(R),
+          B(B),
+          Ho(Ho),
+          testcaseName(testcaseName) {}
 
     int32_t batchSize;
     int32_t inputSize;
@@ -89,9 +104,16 @@ class ReferenceRNNCellTestBiasClip : public ReferenceRNNCellTest {
         const auto R = std::make_shared<op::v0::Parameter>(params.R.type, params.R.shape);
         const auto B = std::make_shared<op::v0::Parameter>(params.B.type, params.B.shape);
 
-        const auto rnn_cell = std::make_shared<op::v0::RNNCell>(
-            X, H_t, W, R, B, params.hiddenSize,
-            std::vector<std::string>{"tanh"}, std::vector<float>{}, std::vector<float>{}, clip);
+        const auto rnn_cell = std::make_shared<op::v0::RNNCell>(X,
+                                                                H_t,
+                                                                W,
+                                                                R,
+                                                                B,
+                                                                params.hiddenSize,
+                                                                std::vector<std::string>{"tanh"},
+                                                                std::vector<float>{},
+                                                                std::vector<float>{},
+                                                                clip);
         auto function = std::make_shared<Model>(NodeVector{rnn_cell}, ParameterVector{X, H_t, W, R, B});
         return function;
     }
@@ -146,40 +168,52 @@ TEST_P(ReferenceRNNCellTestSigmoidActivationFunction, CompareWithRefs) {
 template <element::Type_t ET>
 std::vector<RNNCellParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<RNNCellParams> params {
-        RNNCellParams(
-            2, 3, 3,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.3432185f, 0.612268f, 0.20272376f, 0.9513413f, 0.30585995f, 0.7265472f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.12444675f, 0.52055854f, 0.46489045f, 0.4983964f, 0.7730452f, 0.28439692f}),
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{0.41930267f,
-                                              0.7872176f,
-                                              0.89940447f,
-                                              0.23659843f,
-                                              0.24676207f,
-                                              0.17101714f,
-                                              0.3147149f,
-                                              0.6555601f,
-                                              0.4559603f}),
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{0.8374871f,
-                                              0.86660194f,
-                                              0.82114047f,
-                                              0.71549815f,
-                                              0.18775631f,
-                                              0.3182116f,
-                                              0.25392973f,
-                                              0.38301638f,
-                                              0.85531586f}),
-            reference_tests::Tensor(ET, {3}, std::vector<T>{0.0f, 0.0f, 0.0f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.9408395f, 0.53823817f, 0.84270686f, 0.98932856f, 0.768665f, 0.90461975f}),
-            "rnn_cell_zero_bias_default_attrs"),
+    std::vector<RNNCellParams> params{
+        RNNCellParams(2,
+                      3,
+                      3,
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.3432185f, 0.612268f, 0.20272376f, 0.9513413f, 0.30585995f, 0.7265472f}),
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.12444675f, 0.52055854f, 0.46489045f, 0.4983964f, 0.7730452f, 0.28439692f}),
+                      reference_tests::Tensor(ET,
+                                              {3, 3},
+                                              std::vector<T>{0.41930267f,
+                                                             0.7872176f,
+                                                             0.89940447f,
+                                                             0.23659843f,
+                                                             0.24676207f,
+                                                             0.17101714f,
+                                                             0.3147149f,
+                                                             0.6555601f,
+                                                             0.4559603f}),
+                      reference_tests::Tensor(ET,
+                                              {3, 3},
+                                              std::vector<T>{0.8374871f,
+                                                             0.86660194f,
+                                                             0.82114047f,
+                                                             0.71549815f,
+                                                             0.18775631f,
+                                                             0.3182116f,
+                                                             0.25392973f,
+                                                             0.38301638f,
+                                                             0.85531586f}),
+                      reference_tests::Tensor(ET, {3}, std::vector<T>{0.0f, 0.0f, 0.0f}),
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.9408395f, 0.53823817f, 0.84270686f, 0.98932856f, 0.768665f, 0.90461975f}),
+                      "rnn_cell_zero_bias_default_attrs"),
     };
     return params;
 }
 
 std::vector<RNNCellParams> generateCombinedParams() {
-    const std::vector<std::vector<RNNCellParams>> generatedParams {
+    const std::vector<std::vector<RNNCellParams>> generatedParams{
         generateParams<element::Type_t::bf16>(),
         generateParams<element::Type_t::f16>(),
         generateParams<element::Type_t::f32>(),
@@ -196,40 +230,52 @@ std::vector<RNNCellParams> generateCombinedParams() {
 template <element::Type_t ET>
 std::vector<RNNCellParams> generateParamsBiasClip() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<RNNCellParams> params {
-        RNNCellParams(
-            2, 3, 3,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.3432185f, 0.612268f, 0.20272376f, 0.9513413f, 0.30585995f, 0.7265472f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.12444675f, 0.52055854f, 0.46489045f, 0.4983964f, 0.7730452f, 0.28439692f}),
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{0.41930267f,
-                                              0.7872176f,
-                                              0.89940447f,
-                                              0.23659843f,
-                                              0.24676207f,
-                                              0.17101714f,
-                                              0.3147149f,
-                                              0.6555601f,
-                                              0.4559603f}),
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{0.8374871f,
-                                              0.86660194f,
-                                              0.82114047f,
-                                              0.71549815f,
-                                              0.18775631f,
-                                              0.3182116f,
-                                              0.25392973f,
-                                              0.38301638f,
-                                              0.85531586f}),
-            reference_tests::Tensor(ET, {3}, std::vector<T>{1.0289404f, 1.6362579f, 0.4370661f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.9922437f, 0.97749525f, 0.9312212f, 0.9937176f, 0.9901317f, 0.95906746f}),
-            "rnn_cell_bias_clip"),
+    std::vector<RNNCellParams> params{
+        RNNCellParams(2,
+                      3,
+                      3,
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.3432185f, 0.612268f, 0.20272376f, 0.9513413f, 0.30585995f, 0.7265472f}),
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.12444675f, 0.52055854f, 0.46489045f, 0.4983964f, 0.7730452f, 0.28439692f}),
+                      reference_tests::Tensor(ET,
+                                              {3, 3},
+                                              std::vector<T>{0.41930267f,
+                                                             0.7872176f,
+                                                             0.89940447f,
+                                                             0.23659843f,
+                                                             0.24676207f,
+                                                             0.17101714f,
+                                                             0.3147149f,
+                                                             0.6555601f,
+                                                             0.4559603f}),
+                      reference_tests::Tensor(ET,
+                                              {3, 3},
+                                              std::vector<T>{0.8374871f,
+                                                             0.86660194f,
+                                                             0.82114047f,
+                                                             0.71549815f,
+                                                             0.18775631f,
+                                                             0.3182116f,
+                                                             0.25392973f,
+                                                             0.38301638f,
+                                                             0.85531586f}),
+                      reference_tests::Tensor(ET, {3}, std::vector<T>{1.0289404f, 1.6362579f, 0.4370661f}),
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.9922437f, 0.97749525f, 0.9312212f, 0.9937176f, 0.9901317f, 0.95906746f}),
+                      "rnn_cell_bias_clip"),
     };
     return params;
 }
 
 std::vector<RNNCellParams> generateCombinedParamsBiasClip() {
-    const std::vector<std::vector<RNNCellParams>> generatedParams {
+    const std::vector<std::vector<RNNCellParams>> generatedParams{
         generateParamsBiasClip<element::Type_t::bf16>(),
         generateParamsBiasClip<element::Type_t::f16>(),
         generateParamsBiasClip<element::Type_t::f32>(),
@@ -246,40 +292,52 @@ std::vector<RNNCellParams> generateCombinedParamsBiasClip() {
 template <element::Type_t ET>
 std::vector<RNNCellParams> generateParamsSigmoidActivationFunction() {
     using T = typename element_type_traits<ET>::value_type;
-    std::vector<RNNCellParams> params {
-        RNNCellParams(
-            2, 3, 3,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.3432185f, 0.612268f, 0.20272376f, 0.9513413f, 0.30585995f, 0.7265472f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                0.12444675f, 0.52055854f, 0.46489045f, 0.4983964f, 0.7730452f, 0.28439692f}),
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{0.41930267f,
-                                              0.7872176f,
-                                              0.89940447f,
-                                              0.23659843f,
-                                              0.24676207f,
-                                              0.17101714f,
-                                              0.3147149f,
-                                              0.6555601f,
-                                              0.4559603f}),
-            reference_tests::Tensor(ET, {3, 3}, std::vector<T>{0.8374871f,
-                                              0.86660194f,
-                                              0.82114047f,
-                                              0.71549815f,
-                                              0.18775631f,
-                                              0.3182116f,
-                                              0.25392973f,
-                                              0.38301638f,
-                                              0.85531586f}),
-            reference_tests::Tensor(ET, {3}, std::vector<T>{1.0289404f, 1.6362579f, 0.4370661f}),
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{0.94126844f, 0.9036043f, 0.841243f, 0.9468489f, 0.934215f, 0.873708f}),
-            "rnn_cell_sigmoid_activation_function"),
+    std::vector<RNNCellParams> params{
+        RNNCellParams(2,
+                      3,
+                      3,
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.3432185f, 0.612268f, 0.20272376f, 0.9513413f, 0.30585995f, 0.7265472f}),
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.12444675f, 0.52055854f, 0.46489045f, 0.4983964f, 0.7730452f, 0.28439692f}),
+                      reference_tests::Tensor(ET,
+                                              {3, 3},
+                                              std::vector<T>{0.41930267f,
+                                                             0.7872176f,
+                                                             0.89940447f,
+                                                             0.23659843f,
+                                                             0.24676207f,
+                                                             0.17101714f,
+                                                             0.3147149f,
+                                                             0.6555601f,
+                                                             0.4559603f}),
+                      reference_tests::Tensor(ET,
+                                              {3, 3},
+                                              std::vector<T>{0.8374871f,
+                                                             0.86660194f,
+                                                             0.82114047f,
+                                                             0.71549815f,
+                                                             0.18775631f,
+                                                             0.3182116f,
+                                                             0.25392973f,
+                                                             0.38301638f,
+                                                             0.85531586f}),
+                      reference_tests::Tensor(ET, {3}, std::vector<T>{1.0289404f, 1.6362579f, 0.4370661f}),
+                      reference_tests::Tensor(
+                          ET,
+                          {2, 3},
+                          std::vector<T>{0.94126844f, 0.9036043f, 0.841243f, 0.9468489f, 0.934215f, 0.873708f}),
+                      "rnn_cell_sigmoid_activation_function"),
     };
     return params;
 }
 
 std::vector<RNNCellParams> generateCombinedParamsSigmoidActivationFunction() {
-    const std::vector<std::vector<RNNCellParams>> generatedParams {
+    const std::vector<std::vector<RNNCellParams>> generatedParams{
         generateParamsSigmoidActivationFunction<element::Type_t::bf16>(),
         generateParamsSigmoidActivationFunction<element::Type_t::f16>(),
         generateParamsSigmoidActivationFunction<element::Type_t::f32>(),
@@ -293,12 +351,18 @@ std::vector<RNNCellParams> generateCombinedParamsSigmoidActivationFunction() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_RNNCell_With_Hardcoded_Refs, ReferenceRNNCellTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceRNNCellTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_RNNCell_With_Hardcoded_Refs,
+                         ReferenceRNNCellTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceRNNCellTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_RNNCell_With_Hardcoded_Refs, ReferenceRNNCellTestBiasClip,
-    testing::ValuesIn(generateCombinedParamsBiasClip()), ReferenceRNNCellTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_RNNCell_With_Hardcoded_Refs,
+                         ReferenceRNNCellTestBiasClip,
+                         testing::ValuesIn(generateCombinedParamsBiasClip()),
+                         ReferenceRNNCellTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_RNNCell_With_Hardcoded_Refs, ReferenceRNNCellTestSigmoidActivationFunction,
-    testing::ValuesIn(generateCombinedParamsSigmoidActivationFunction()), ReferenceRNNCellTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_RNNCell_With_Hardcoded_Refs,
+                         ReferenceRNNCellTestSigmoidActivationFunction,
+                         testing::ValuesIn(generateCombinedParamsSigmoidActivationFunction()),
+                         ReferenceRNNCellTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/rnn_sequence.cpp b/src/plugins/template/tests/functional/op_reference/rnn_sequence.cpp
index 2a8d5519fb9044..de19641733b55f 100644
--- a/src/plugins/template/tests/functional/op_reference/rnn_sequence.cpp
+++ b/src/plugins/template/tests/functional/op_reference/rnn_sequence.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/rnn_sequence.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/rnn_sequence.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,37 +14,51 @@ using namespace ov;
 namespace {
 struct RNNSequenceParams {
     template <class T>
-    RNNSequenceParams(
-        const size_t batchSize, const size_t inputSize, const size_t hiddenSize, const size_t seqLength,
-        const float clip, const op::RecurrentSequenceDirection& rnn_direction,
-        const element::Type_t& iType,
-        const std::vector<T>& XValues, const std::vector<T>& H_tValues, const std::vector<int64_t>& seqLengthsValues,
-        const std::vector<T>& WValues, const std::vector<T>& RValues, const std::vector<T>& BValues,
-        const std::vector<T>& YValues, const std::vector<T>& HoValues,
-        const std::string& testcaseName = "") :
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize), seqLength(seqLength),
-        clip(clip), rnn_direction(rnn_direction), iType(iType), oType(iType),
-        testcaseName(testcaseName) {
-            numDirections = (rnn_direction == op::RecurrentSequenceDirection::BIDIRECTIONAL) ? 2 : 1;
+    RNNSequenceParams(const size_t batchSize,
+                      const size_t inputSize,
+                      const size_t hiddenSize,
+                      const size_t seqLength,
+                      const float clip,
+                      const op::RecurrentSequenceDirection& rnn_direction,
+                      const element::Type_t& iType,
+                      const std::vector<T>& XValues,
+                      const std::vector<T>& H_tValues,
+                      const std::vector<int64_t>& seqLengthsValues,
+                      const std::vector<T>& WValues,
+                      const std::vector<T>& RValues,
+                      const std::vector<T>& BValues,
+                      const std::vector<T>& YValues,
+                      const std::vector<T>& HoValues,
+                      const std::string& testcaseName = "")
+        : batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          seqLength(seqLength),
+          clip(clip),
+          rnn_direction(rnn_direction),
+          iType(iType),
+          oType(iType),
+          testcaseName(testcaseName) {
+        numDirections = (rnn_direction == op::RecurrentSequenceDirection::BIDIRECTIONAL) ? 2 : 1;
 
-            Shape XShape = Shape{batchSize, seqLength, inputSize};
-            Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
-            Shape seqLengthsShape = Shape{batchSize};
-            Shape WShape = Shape{numDirections, hiddenSize, inputSize};
-            Shape RShape = Shape{numDirections, hiddenSize, hiddenSize};
-            Shape BShape = Shape{numDirections, hiddenSize};
-            Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
-            Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape XShape = Shape{batchSize, seqLength, inputSize};
+        Shape H_tShape = Shape{batchSize, numDirections, hiddenSize};
+        Shape seqLengthsShape = Shape{batchSize};
+        Shape WShape = Shape{numDirections, hiddenSize, inputSize};
+        Shape RShape = Shape{numDirections, hiddenSize, hiddenSize};
+        Shape BShape = Shape{numDirections, hiddenSize};
+        Shape YShape = Shape{batchSize, numDirections, seqLength, hiddenSize};
+        Shape HoShape = Shape{batchSize, numDirections, hiddenSize};
 
-            X = reference_tests::Tensor(XShape, iType, XValues);
-            H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
-            sequence_lengths = reference_tests::Tensor(seqLengthsShape, element::Type_t::i64, seqLengthsValues);
-            W = reference_tests::Tensor(WShape, iType, WValues);
-            R = reference_tests::Tensor(RShape, iType, RValues);
-            B = reference_tests::Tensor(BShape, iType, BValues);
-            Y = reference_tests::Tensor(YShape, oType, YValues);
-            Ho = reference_tests::Tensor(HoShape, oType, HoValues);
-        }
+        X = reference_tests::Tensor(XShape, iType, XValues);
+        H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
+        sequence_lengths = reference_tests::Tensor(seqLengthsShape, element::Type_t::i64, seqLengthsValues);
+        W = reference_tests::Tensor(WShape, iType, WValues);
+        R = reference_tests::Tensor(RShape, iType, RValues);
+        B = reference_tests::Tensor(BShape, iType, BValues);
+        Y = reference_tests::Tensor(YShape, oType, YValues);
+        Ho = reference_tests::Tensor(HoShape, oType, HoValues);
+    }
 
     size_t batchSize;
     size_t inputSize;
@@ -71,7 +86,8 @@ class ReferenceRNNSequenceTest : public testing::TestWithParam<RNNSequenceParams
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.X.data, params.H_t.data, params.sequence_lengths.data, params.W.data, params.R.data, params.B.data};
+        inputData =
+            {params.X.data, params.H_t.data, params.sequence_lengths.data, params.W.data, params.R.data, params.B.data};
         refOutData = {params.Y.data, params.Ho.data};
     }
 
@@ -99,26 +115,27 @@ class ReferenceRNNSequenceTest : public testing::TestWithParam<RNNSequenceParams
     static std::shared_ptr<Model> CreateFunction(const RNNSequenceParams& params) {
         const auto X = std::make_shared<op::v0::Parameter>(params.X.type, params.X.shape);
         const auto H_t = std::make_shared<op::v0::Parameter>(params.H_t.type, params.H_t.shape);
-        const auto sequence_lengths = std::make_shared<op::v0::Parameter>(params.sequence_lengths.type, params.sequence_lengths.shape);
+        const auto sequence_lengths =
+            std::make_shared<op::v0::Parameter>(params.sequence_lengths.type, params.sequence_lengths.shape);
         const auto W = std::make_shared<op::v0::Parameter>(params.W.type, params.W.shape);
         const auto R = std::make_shared<op::v0::Parameter>(params.R.type, params.R.shape);
         const auto B = std::make_shared<op::v0::Parameter>(params.B.type, params.B.shape);
 
-        const auto rnn_sequence =
-            std::make_shared<op::v5::RNNSequence>(X,
-                                                  H_t,
-                                                  sequence_lengths,
-                                                  W,
-                                                  R,
-                                                  B,
-                                                  params.hiddenSize,
-                                                  params.rnn_direction,
-                                                  std::vector<std::string>{"tanh"},
-                                                  std::vector<float>{},
-                                                  std::vector<float>{},
-                                                  params.clip);
+        const auto rnn_sequence = std::make_shared<op::v5::RNNSequence>(X,
+                                                                        H_t,
+                                                                        sequence_lengths,
+                                                                        W,
+                                                                        R,
+                                                                        B,
+                                                                        params.hiddenSize,
+                                                                        params.rnn_direction,
+                                                                        std::vector<std::string>{"tanh"},
+                                                                        std::vector<float>{},
+                                                                        std::vector<float>{},
+                                                                        params.clip);
 
-        auto function = std::make_shared<Model>(rnn_sequence->outputs(), ParameterVector{X, H_t, sequence_lengths, W, R, B});
+        auto function =
+            std::make_shared<Model>(rnn_sequence->outputs(), ParameterVector{X, H_t, sequence_lengths, W, R, B});
         return function;
     }
 };
@@ -131,442 +148,564 @@ template <element::Type_t ET>
 std::vector<RNNSequenceParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<RNNSequenceParams> params {
+    std::vector<RNNSequenceParams> params{
         RNNSequenceParams(
-            5, 10, 10, 10,
-            0.f, op::RecurrentSequenceDirection::FORWARD,
+            5,
+            10,
+            10,
+            10,
+            0.f,
+            op::RecurrentSequenceDirection::FORWARD,
             ET,
-            std::vector<T>{
-                -1, 0.780309, -0.738585, -0.920481, 0.652872, 0.0641558, 0.91262, -0.0761474, 0.847476, -0.252158,
-                -0.690053, 0.784687, -0.946421, -0.416995, -0.202512, 0.614577, 0.254189, 0.81585, 0.112795, 0.679838,
-                -0.899024, 0.61247, 0.861631, -0.271941, 0.381896, -0.741371, 0.665373, -0.363293, 0.474405, 0.193539,
-                -0.272586, 0.589941, 0.396962, 0.643758, 0.798932, 0.663799, 0.819915, 0.949827, 0.312239, 0.623979,
-                -0.794512, -0.524943, -0.24131, 0.398472, -0.0301095, -0.169556, 0.277324, 0.51858, 0.115046, 0.386911,
-                0.826518, -0.950774, 0.674757, -0.23359, -0.402458, -0.987406, -0.124885, 0.475875, -0.248479, -0.0135011,
-                -0.971921, -0.501126, -0.30573, 0.593373, 0.876799, -0.798956, 0.470805, 0.952874, 0.411772, 0.903529,
-                0.855695, -0.179938, -0.32381, 0.538217, -0.330704, -0.834627, 0.797116, 0.57467, 0.434931, -0.11202,
-                0.501784, 0.315797, -0.278605, -0.243354, 0.299264, -0.888726, -0.843481, -0.816194, 0.61021, -0.869385,
-                -0.551361, -0.695734, 0.361182, -0.748082, -0.485284, -0.124065, -0.780665, -0.370868, -0.298536, 0.522286,
-                -0.802298, 0.862921, -0.347842, -0.146729, -0.458638, 0.57622, -0.0933521, -0.833528, -0.859246, -0.340501,
-                -0.61579, 0.675731, -0.876629, 0.108469, 0.141222, -0.0757794, 0.897658, -0.310452, 0.768898, -0.13792,
-                0.98896, 0.601007, 0.883268, -0.241041, -0.18915, -0.426225, -0.0989319, 0.530222, 0.159798, -0.243754,
-                0.244787, 0.478345, 0.826766, 0.0642072, 0.0356427, -0.794826, -0.75666, 0.287393, -0.108071, -0.84735,
-                -0.694862, -0.840984, 0.758743, -0.677052, 0.845901, -0.992841, 0.605204, -0.392934, -0.510492, 0.536422,
-                0.406964, 0.772353, 0.826283, -0.549379, -0.157033, -0.668275, -0.57833, 0.679797, 0.830901, 0.363183,
-                -0.181486, -0.555743, 0.6706, 0.553474, 0.474691, 0.717404, 0.945023, -0.180081, 0.194028, 0.476884,
-                -0.466581, 0.526266, 0.861006, 0.749377, -0.767673, 0.934578, -0.394025, 0.218032, -0.664486, 0.716852,
-                0.452785, -0.869765, 0.0361971, 0.190971, -0.0841559, 0.184484, -0.361089, 0.639664, -0.814522, -0.64626,
-                -0.558575, -0.0518135, 0.834904, 0.983071, 0.208429, 0.841115, -0.266728, -0.984396, 0.310033, -0.663894,
-                -0.00708379, 0.581608, 0.635922, -0.266473, -0.742514, -0.605766, -0.958209, 0.267088, -0.0427639, -0.575115,
-                -0.469043, -0.622282, 0.77962, 0.432287, -0.862854, -0.508723, 0.840711, -0.59019, -0.0682369, 0.526142,
-                0.0647325, 0.102044, -0.529739, -0.448041, -0.966308, -0.155126, -0.906004, -0.881601, -0.362032, -0.113877,
-                -0.662836, -0.397345, -0.101194, -0.0538374, 0.408442, 0.40128, 0.187299, 0.94587, 0.324356, 0.75563,
-                -0.171329, 0.59615, -0.724044, -0.477747, -0.546406, 0.064904, 0.389431, -0.512046, -0.609801, 0.580285,
-                -0.18924, -0.129838, 0.252768, 0.357634, -0.137093, -0.409645, 0.99457, -0.60545, 0.115919, -0.0537746,
-                -0.822487, -0.37496, 0.197357, -0.901543, -0.264034, -0.743536, -0.948014, 0.464231, -0.473613, 0.422959,
-                0.354869, 0.641287, 0.582011, 0.21152, 0.00800619, -0.138603, -0.798317, -0.0269492, -0.19921, 0.174343,
-                -0.111682, -0.532153, 0.268423, -0.541535, -0.497098, 0.957141, -0.106795, -0.838224, -0.760405, -0.0744435,
-                0.556972, -0.203011, 0.248964, 0.59689, -0.0109004, -0.925239, 0.438413, 0.386685, -0.369077, 0.673153,
-                -0.919203, 0.259205, -0.956505, 0.483536, -0.206068, 0.0391633, -0.0715966, 0.34823, 0.700705, -0.3679,
-                -0.368349, -0.665279, 0.36909, 0.636464, -0.634393, -0.931031, 0.0198778, 0.556591, 0.233121, 0.880379,
-                -0.544078, 0.565815, -0.177247, 0.388592, -0.498401, 0.0146546, -0.43808, -0.562895, 0.847527, 0.556404,
-                -0.481485, -0.54575, 0.586809, -0.645919, -0.411731, 0.634336, -0.107599, 0.699691, 0.879165, -0.605746,
-                0.851844, -0.197677, -0.0638249, -0.550345, 0.427207, 0.281324, 0.82633, -0.00911417, -0.523082, 0.360537,
-                0.295952, 0.537166, 0.235453, 0.414191, 0.340562, -0.0328213, 0.828018, -0.944312, 0.806772, -0.108092,
-                0.089091, -0.960954, 0.725746, 0.269557, -0.000429476, -0.231468, -0.991745, 0.471178, -0.496647, 0.943754,
-                -0.815517, -0.069551, 0.263998, -0.226304, -0.684247, -0.0426104, 0.0763018, 0.903734, 0.36846, -0.0844384,
-                -0.0746106, -0.641445, 0.969822, 0.997518, 0.307509, 0.622212, -0.349354, -0.876697, -0.7214, -0.594663,
-                -0.919986, 0.409152, -0.603743, -0.4911, 0.703263, 0.314707, 0.612499, -0.369318, 0.614946, 0.770576,
-                0.371061, 0.593678, 0.750314, -0.364852, 0.698688, 0.609751, 0.142622, -0.787519, 0.509953, 0.415293,
-                -0.640467, 0.701937, 0.649218, 0.824335, 0.711544, -0.57001, -0.32463, -0.921129, -0.52984, -0.750256,
-                -0.445129, -0.122558, 0.719862, -0.354157, 0.975094, 0.930568, 0.390521, 0.340562, -0.927739, 0.570913,
-                0.0577081, 0.345886, -0.147266, -0.920045, 0.290715, 0.137354, 0.409865, 0.407486, -0.548271, 0.969365,
-                -0.763785, -0.589062, 0.906249, 0.869164, -0.322404, 0.860601, -0.792338, -0.74819, -0.11752, 0.246401,
-                0.215602, -0.659965, -0.334239, -0.701839, 0.916408, -0.870779, -0.765881, -0.0786394, -0.25551, 0.903985,
-                0.159976, -0.731893, -0.88472, 0.310355, 0.421346, -0.190523, 0.320507, 0.689287, 0.976754, 0.910255,
-                0.467333, -0.411659, 0.410252, 0.00145024, -0.329416, 0.0472609, 0.792444, 0.874022, -0.108247, 0.452289,
-                0.613927, -0.608009, 0.0925679, -0.701885, -0.625309, -0.233405, -0.885755, 0.356572, 0.775295, -0.312218,
-                -0.485195, -0.760842, -0.196276, -0.326445, -0.837129, 0.260253, 0.125437, -0.848069, -0.850426, 1},
-            std::vector<T>{
-                -1, 0.0194419, -0.633291, 0.617539, 0.87557, -0.940787, 0.569968, -0.672245, -0.132298, 0.148535,
-                -0.565955, 0.661358, -0.40092, -0.278338, 0.738713, -0.975645, 0.350663, -0.0375085, 0.954534, -0.57807,
-                -0.573083, 0.887977, -0.347673, 0.972259, -0.125333, 0.930768, -0.484139, 0.519932, -0.615546, -0.434102,
-                0.539075, -0.983636, -0.29435, -0.532884, -0.229788, -0.78175, -0.185304, -0.189241, 0.540048, 0.68374,
-                -0.213783, -0.0673415, -0.791954, -0.618463, 0.345361, -0.0507364, 0.603086, -0.504686, 0.482923, 1},
+            std::vector<T>{-1,           0.780309,   -0.738585,  -0.920481,  0.652872,    0.0641558,  0.91262,
+                           -0.0761474,   0.847476,   -0.252158,  -0.690053,  0.784687,    -0.946421,  -0.416995,
+                           -0.202512,    0.614577,   0.254189,   0.81585,    0.112795,    0.679838,   -0.899024,
+                           0.61247,      0.861631,   -0.271941,  0.381896,   -0.741371,   0.665373,   -0.363293,
+                           0.474405,     0.193539,   -0.272586,  0.589941,   0.396962,    0.643758,   0.798932,
+                           0.663799,     0.819915,   0.949827,   0.312239,   0.623979,    -0.794512,  -0.524943,
+                           -0.24131,     0.398472,   -0.0301095, -0.169556,  0.277324,    0.51858,    0.115046,
+                           0.386911,     0.826518,   -0.950774,  0.674757,   -0.23359,    -0.402458,  -0.987406,
+                           -0.124885,    0.475875,   -0.248479,  -0.0135011, -0.971921,   -0.501126,  -0.30573,
+                           0.593373,     0.876799,   -0.798956,  0.470805,   0.952874,    0.411772,   0.903529,
+                           0.855695,     -0.179938,  -0.32381,   0.538217,   -0.330704,   -0.834627,  0.797116,
+                           0.57467,      0.434931,   -0.11202,   0.501784,   0.315797,    -0.278605,  -0.243354,
+                           0.299264,     -0.888726,  -0.843481,  -0.816194,  0.61021,     -0.869385,  -0.551361,
+                           -0.695734,    0.361182,   -0.748082,  -0.485284,  -0.124065,   -0.780665,  -0.370868,
+                           -0.298536,    0.522286,   -0.802298,  0.862921,   -0.347842,   -0.146729,  -0.458638,
+                           0.57622,      -0.0933521, -0.833528,  -0.859246,  -0.340501,   -0.61579,   0.675731,
+                           -0.876629,    0.108469,   0.141222,   -0.0757794, 0.897658,    -0.310452,  0.768898,
+                           -0.13792,     0.98896,    0.601007,   0.883268,   -0.241041,   -0.18915,   -0.426225,
+                           -0.0989319,   0.530222,   0.159798,   -0.243754,  0.244787,    0.478345,   0.826766,
+                           0.0642072,    0.0356427,  -0.794826,  -0.75666,   0.287393,    -0.108071,  -0.84735,
+                           -0.694862,    -0.840984,  0.758743,   -0.677052,  0.845901,    -0.992841,  0.605204,
+                           -0.392934,    -0.510492,  0.536422,   0.406964,   0.772353,    0.826283,   -0.549379,
+                           -0.157033,    -0.668275,  -0.57833,   0.679797,   0.830901,    0.363183,   -0.181486,
+                           -0.555743,    0.6706,     0.553474,   0.474691,   0.717404,    0.945023,   -0.180081,
+                           0.194028,     0.476884,   -0.466581,  0.526266,   0.861006,    0.749377,   -0.767673,
+                           0.934578,     -0.394025,  0.218032,   -0.664486,  0.716852,    0.452785,   -0.869765,
+                           0.0361971,    0.190971,   -0.0841559, 0.184484,   -0.361089,   0.639664,   -0.814522,
+                           -0.64626,     -0.558575,  -0.0518135, 0.834904,   0.983071,    0.208429,   0.841115,
+                           -0.266728,    -0.984396,  0.310033,   -0.663894,  -0.00708379, 0.581608,   0.635922,
+                           -0.266473,    -0.742514,  -0.605766,  -0.958209,  0.267088,    -0.0427639, -0.575115,
+                           -0.469043,    -0.622282,  0.77962,    0.432287,   -0.862854,   -0.508723,  0.840711,
+                           -0.59019,     -0.0682369, 0.526142,   0.0647325,  0.102044,    -0.529739,  -0.448041,
+                           -0.966308,    -0.155126,  -0.906004,  -0.881601,  -0.362032,   -0.113877,  -0.662836,
+                           -0.397345,    -0.101194,  -0.0538374, 0.408442,   0.40128,     0.187299,   0.94587,
+                           0.324356,     0.75563,    -0.171329,  0.59615,    -0.724044,   -0.477747,  -0.546406,
+                           0.064904,     0.389431,   -0.512046,  -0.609801,  0.580285,    -0.18924,   -0.129838,
+                           0.252768,     0.357634,   -0.137093,  -0.409645,  0.99457,     -0.60545,   0.115919,
+                           -0.0537746,   -0.822487,  -0.37496,   0.197357,   -0.901543,   -0.264034,  -0.743536,
+                           -0.948014,    0.464231,   -0.473613,  0.422959,   0.354869,    0.641287,   0.582011,
+                           0.21152,      0.00800619, -0.138603,  -0.798317,  -0.0269492,  -0.19921,   0.174343,
+                           -0.111682,    -0.532153,  0.268423,   -0.541535,  -0.497098,   0.957141,   -0.106795,
+                           -0.838224,    -0.760405,  -0.0744435, 0.556972,   -0.203011,   0.248964,   0.59689,
+                           -0.0109004,   -0.925239,  0.438413,   0.386685,   -0.369077,   0.673153,   -0.919203,
+                           0.259205,     -0.956505,  0.483536,   -0.206068,  0.0391633,   -0.0715966, 0.34823,
+                           0.700705,     -0.3679,    -0.368349,  -0.665279,  0.36909,     0.636464,   -0.634393,
+                           -0.931031,    0.0198778,  0.556591,   0.233121,   0.880379,    -0.544078,  0.565815,
+                           -0.177247,    0.388592,   -0.498401,  0.0146546,  -0.43808,    -0.562895,  0.847527,
+                           0.556404,     -0.481485,  -0.54575,   0.586809,   -0.645919,   -0.411731,  0.634336,
+                           -0.107599,    0.699691,   0.879165,   -0.605746,  0.851844,    -0.197677,  -0.0638249,
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+                           -0.954406,   0.834608,  -0.410929, -0.529981,  -0.925456, -0.914565,  0.943016,   0.886728,
+                           0.71595,     0.984002,  0.975321,  -0.999722,  0.963597,  -0.667433,  0.533139,   0.971698,
+                           -0.977911,   -0.189758, -0.998167, 0.570572,   0.819584,  0.819533,   -0.15264,   0.924569,
+                           0.874921,    -0.774673, 0.829862,  0.826993,   0.0484993, -0.745097,  0.170151,   0.999774,
+                           -0.934382,   -0.591278, -0.185407, -0.771122,  -0.762141, -0.048014,  -0.946054,  0.955278,
+                           0.99961,     -0.731922, 0.138094,  -0.0371518, 0.817227,  0.449736,   -0.571427,  -0.905313,
+                           0.923767,    -0.388737, -0.972294, 0.647981,   -0.360347, -0.944748,  -0.993917,  0.537831,
+                           0.994776,    -0.484682, -0.990703, 0.999149,   0.779736,  0.0102033,  -0.709741,  0.998436,
+                           -0.511018,   0.152785,  -0.937848, -0.687825,  0.905885,  0.312886,   -0.950348,  0.917466,
+                           -0.957475,   0.399452,  0.226108,  -0.996484,  0.38622,   0.99715,    -0.317704,  -0.497559,
+                           -0.118911,   -0.961001, 0.965842,  0.999756,   0.999437,  0.996626,   0.982077,   -0.793749,
+                           0.977901,    0.469991,  -0.972339, 0.344807,   -0.994449, 0.999891,   -0.566665,  0.985128,
+                           -0.950463,   0.389667,  -0.171013, -0.494231,  -0.288177, 0.989171,   -0.806886,  0.967839,
+                           0.956819,    0.853921,  0.78097,   0.925808,   0.681741,  -0.934712,  0.642082,   -0.933539,
+                           0.481516,    0.997935,  0.805567,  0.999646},
+            std::vector<T>{0.959354,    -0.881273, -0.970651, 0.995653,  -0.821644, -0.835365, -0.950953, 0.213407,
+                           -0.00109488, -0.896989, -0.965055, -0.78096,  -0.170206, -0.481907, -0.538034, 0.641884,
+                           -0.884119,   0.982638,  0.406508,  0.988232,  0.970184,  0.645835,  0.437802,  0.999792,
+                           -0.395441,   0.998468,  -0.983758, -0.861604, -0.102437, -0.726916, -0.878295, 0.961768,
+                           0.948726,    0.223961,  -0.142666, 0.986927,  -0.997041, 0.591299,  -0.992189, 0.781923,
+                           0.995062,    0.930073,  0.972781,  0.998503,  -0.994274, 0.999141,  -0.99872,  -0.0965485,
+                           -0.985132,   -0.7469,   0.81997,   0.78163,   0.667184,  -0.991648, 0.876578,  -0.99955,
+                           -0.697148,   0.550283,  -0.274609, 0.963469,  -0.994494, -0.237455, -0.100728, -0.975005,
+                           -0.0117797,  0.995582,  -0.986234, -0.899297, 0.439427,  0.911726,  0.203506,  0.993091,
+                           0.951738,    0.999095,  0.841566,  -0.99347,  0.350599,  -0.999231, -0.433626, -0.406675,
+                           0.994776,    -0.484682, -0.990703, 0.999149,  0.779736,  0.0102033, -0.709741, 0.998436,
+                           -0.511018,   0.152785,  -0.937848, -0.687825, 0.905885,  0.312886,  -0.950348, 0.917466,
+                           -0.957475,   0.399452,  0.226108,  -0.996484}),
     };
     return params;
 }
@@ -575,448 +714,339 @@ template <element::Type_t ET>
 std::vector<RNNSequenceParams> generateParamsBF16() {
     using T = typename element_type_traits<ET>::value_type;
 
-    std::vector<RNNSequenceParams> params {
+    std::vector<RNNSequenceParams> params{
         RNNSequenceParams(
-            5, 10, 10, 10,
-            0.f, op::RecurrentSequenceDirection::FORWARD,
+            5,
+            10,
+            10,
+            10,
+            0.f,
+            op::RecurrentSequenceDirection::FORWARD,
             ET,
             std::vector<T>{
-                -2, 2, 2, -1, -2, -2, -2, -1, 2, 0,
-                0, 0, 2, 2, 0, 1, 2, 1, -1, 1,
-                -2, 1, 2, 2, -2, -2, -1, -2, -1, -1,
-                2, 1, 1, 2, 2, 2, 0, 2, 2, 1,
-                -2, 1, 2, 1, 2, 0, -1, -1, 1, 0,
-                -2, 1, 2, 2, -1, 1, 1, 1, 0, -2,
-                -1, -2, 1, 2, 1, 2, 2, -2, 2, 0,
-                2, 0, 2, 0, 2, -2, 1, 2, 2, 1,
-                -2, 2, -1, 0, -1, 2, 1, -2, 0, -1,
-                0, -1, 1, 0, 1, 0, 0, 1, 1, -2,
-                2, 0, -2, -2, 2, 1, -1, 2, -1, 1,
-                -2, -2, 0, 0, 1, -1, -1, 2, 0, 2,
-                -2, -1, -1, -1, -1, 0, 1, -2, 2, -2,
-                -2, 1, 1, 1, 2, 0, 1, 2, 2, 1,
-                2, 2, 0, 0, -1, -1, 1, 1, -1, 0,
-                -2, -1, 2, -1, 1, 1, 1, 0, 0, 2,
-                1, 2, 1, 0, -1, -1, -1, 1, 1, -1,
-                -2, 0, -2, -1, -2, -1, 2, 1, -2, -1,
-                -1, 1, -2, 1, 1, 2, -2, 2, -1, -2,
-                0, 2, -2, -1, -1, 2, -1, 2, 1, -2,
-                -2, -2, 2, -1, -1, 1, 0, -2, -1, -2,
-                1, 0, 0, 1, -2, 2, -2, 1, -1, 0,
-                -2, 1, 2, -1, -2, 2, 0, 0, 0, -2,
-                0, 2, 2, 1, -1, 0, 2, 1, 0, 0,
-                2, 2, 2, 0, 2, -2, -1, 0, 0, 1,
-                -1, 2, 0, 0, 1, -1, 0, -2, -1, 0,
-                1, 0, 1, -2, 2, 1, 0, 1, 0, 1,
-                -2, 0, -2, -2, 1, 2, 0, 1, -2, -2,
-                -2, -1, -2, 1, 2, -1, -2, -2, 2, -2,
-                -2, 2, 2, -1, -1, 0, -1, 0, 1, 0,
-                1, 2, 2, 1, 2, -1, -1, -2, 0, -2,
-                -2, 2, -1, 2, 2, 2, 2, -2, 1, 0,
-                0, 0, -1, -2, 2, -1, 1, 0, 1, 1,
-                2, 1, 2, 2, 0, 1, 0, 0, 1, 1,
-                -1, 2, 1, -1, 2, 2, 2, 2, -2, 1,
-                2, -1, -1, 2, 1, 2, -2, 2, 2, -2,
-                1, -2, -2, -1, 0, 2, 0, -2, 0, -2,
-                0, 1, -1, -2, 2, 1, -2, 0, -2, -2,
-                -1, 1, 0, 1, 2, -2, 2, -2, 1, 1,
-                2, -1, -1, -1, -2, 0, 1, -1, -2, 0,
-                0, 2, 1, -1, 2, 0, -1, 2, -2, -1,
-                -2, -2, -2, 0, 1, 0, 0, 1, -1, -1,
-                -1, 2, -2, 0, 2, 0, 1, 1, -2, 0,
-                -1, 1, 2, -1, -1, 1, 0, -1, 1, -2,
-                0, -1, 0, -1, -1, -2, -1, 1, -2, -1,
-                0, -2, -2, 1, -2, 0, -1, 1, 0, 1,
-                -2, -1, -1, -1, 0, -1, 0, -2, 1, -2,
-                1, -2, 0, -1, 2, -1, 1, 1, 2, 2,
-                0, 1, 1, 1, -2, -1, -1, -1, -1, -2,
-                0, 2, 1, 0, -1, 2, -2, -1, 1, 2},
-            std::vector<T>{
-                -2, 2, 0, 1, -2, 1, 2, 0, 2, 0,
-                -2, 0, 1, -2, -2, 1, 0, 0, 0, -2,
-                -1, 0, 2, -2, -1, 2, -1, 2, 2, 1,
-                -2, 2, 1, 1, 0, 2, 2, -2, -1, 1,
-                -1, 2, 2, -2, -1, -1, 2, 2, 0, 2},
+                -2, 2,  2,  -1, -2, -2, -2, -1, 2,  0,  0,  0,  2,  2,  0,  1,  2,  1,  -1, 1,  -2, 1,  2,  2,  -2,
+                -2, -1, -2, -1, -1, 2,  1,  1,  2,  2,  2,  0,  2,  2,  1,  -2, 1,  2,  1,  2,  0,  -1, -1, 1,  0,
+                -2, 1,  2,  2,  -1, 1,  1,  1,  0,  -2, -1, -2, 1,  2,  1,  2,  2,  -2, 2,  0,  2,  0,  2,  0,  2,
+                -2, 1,  2,  2,  1,  -2, 2,  -1, 0,  -1, 2,  1,  -2, 0,  -1, 0,  -1, 1,  0,  1,  0,  0,  1,  1,  -2,
+                2,  0,  -2, -2, 2,  1,  -1, 2,  -1, 1,  -2, -2, 0,  0,  1,  -1, -1, 2,  0,  2,  -2, -1, -1, -1, -1,
+                0,  1,  -2, 2,  -2, -2, 1,  1,  1,  2,  0,  1,  2,  2,  1,  2,  2,  0,  0,  -1, -1, 1,  1,  -1, 0,
+                -2, -1, 2,  -1, 1,  1,  1,  0,  0,  2,  1,  2,  1,  0,  -1, -1, -1, 1,  1,  -1, -2, 0,  -2, -1, -2,
+                -1, 2,  1,  -2, -1, -1, 1,  -2, 1,  1,  2,  -2, 2,  -1, -2, 0,  2,  -2, -1, -1, 2,  -1, 2,  1,  -2,
+                -2, -2, 2,  -1, -1, 1,  0,  -2, -1, -2, 1,  0,  0,  1,  -2, 2,  -2, 1,  -1, 0,  -2, 1,  2,  -1, -2,
+                2,  0,  0,  0,  -2, 0,  2,  2,  1,  -1, 0,  2,  1,  0,  0,  2,  2,  2,  0,  2,  -2, -1, 0,  0,  1,
+                -1, 2,  0,  0,  1,  -1, 0,  -2, -1, 0,  1,  0,  1,  -2, 2,  1,  0,  1,  0,  1,  -2, 0,  -2, -2, 1,
+                2,  0,  1,  -2, -2, -2, -1, -2, 1,  2,  -1, -2, -2, 2,  -2, -2, 2,  2,  -1, -1, 0,  -1, 0,  1,  0,
+                1,  2,  2,  1,  2,  -1, -1, -2, 0,  -2, -2, 2,  -1, 2,  2,  2,  2,  -2, 1,  0,  0,  0,  -1, -2, 2,
+                -1, 1,  0,  1,  1,  2,  1,  2,  2,  0,  1,  0,  0,  1,  1,  -1, 2,  1,  -1, 2,  2,  2,  2,  -2, 1,
+                2,  -1, -1, 2,  1,  2,  -2, 2,  2,  -2, 1,  -2, -2, -1, 0,  2,  0,  -2, 0,  -2, 0,  1,  -1, -2, 2,
+                1,  -2, 0,  -2, -2, -1, 1,  0,  1,  2,  -2, 2,  -2, 1,  1,  2,  -1, -1, -1, -2, 0,  1,  -1, -2, 0,
+                0,  2,  1,  -1, 2,  0,  -1, 2,  -2, -1, -2, -2, -2, 0,  1,  0,  0,  1,  -1, -1, -1, 2,  -2, 0,  2,
+                0,  1,  1,  -2, 0,  -1, 1,  2,  -1, -1, 1,  0,  -1, 1,  -2, 0,  -1, 0,  -1, -1, -2, -1, 1,  -2, -1,
+                0,  -2, -2, 1,  -2, 0,  -1, 1,  0,  1,  -2, -1, -1, -1, 0,  -1, 0,  -2, 1,  -2, 1,  -2, 0,  -1, 2,
+                -1, 1,  1,  2,  2,  0,  1,  1,  1,  -2, -1, -1, -1, -1, -2, 0,  2,  1,  0,  -1, 2,  -2, -1, 1,  2},
+            std::vector<T>{-2, 2,  0, 1, -2, 1,  2, 0, 2, 0, -2, 0, 1,  -2, -2, 1,  0, 0, 0,  -2, -1, 0, 2, -2, -1,
+                           2,  -1, 2, 2, 1,  -2, 2, 1, 1, 0, 2,  2, -2, -1, 1,  -1, 2, 2, -2, -1, -1, 2, 2, 0,  2},
             std::vector<int64_t>{10, 10, 10, 10, 10},
+            std::vector<T>{-2, 2,  -2, -1, -1, 2,  0,  0,  1,  1,  1,  1,  2,  1,  0,  2,  -2, 0,  2,  1,
+                           -1, -1, 1,  -2, 0,  1,  0,  2,  0,  0,  0,  0,  0,  -2, 0,  -1, -2, 2,  1,  2,
+                           -1, -1, -1, -2, -2, -2, -1, -1, 1,  -1, 2,  -2, 0,  0,  -1, -1, 0,  -2, 2,  2,
+                           0,  1,  -1, 2,  -1, 0,  -2, 0,  1,  -2, 2,  1,  -1, 0,  0,  0,  -2, -2, 2,  2,
+                           2,  -1, -1, -1, -2, 2,  -1, 1,  -2, -2, -2, -2, 1,  -2, -1, -2, 2,  -1, -2, 2},
+            std::vector<T>{-2, -2, -1, 0,  2,  -1, -2, 1,  0,  0,  2,  -2, -2, 2,  2,  -1, 0,  -1, 1,  -2,
+                           -1, -1, 1,  2,  0,  2,  -1, 1,  -1, 1,  2,  0,  2,  0,  1,  2,  2,  -1, -2, 2,
+                           -2, 0,  2,  2,  1,  -1, -1, -2, 1,  -2, -2, 1,  2,  -1, 2,  -2, 2,  0,  -2, 0,
+                           -1, 1,  2,  -2, 1,  2,  -2, -1, -2, -2, 2,  0,  0,  1,  1,  1,  -2, -2, 1,  0,
+                           2,  -1, -2, 1,  -1, -2, -1, -2, 2,  -2, 0,  -2, -2, 1,  -1, 2,  -2, 1,  -2, 2},
+            std::vector<T>{-2, 1, -2, 2, -2, -1, 2, 1, 2, 2},
             std::vector<T>{
-                -2, 2, -2, -1, -1, 2, 0, 0, 1, 1,
-                1, 1, 2, 1, 0, 2, -2, 0, 2, 1,
-                -1, -1, 1, -2, 0, 1, 0, 2, 0, 0,
-                0, 0, 0, -2, 0, -1, -2, 2, 1, 2,
-                -1, -1, -1, -2, -2, -2, -1, -1, 1, -1,
-                2, -2, 0, 0, -1, -1, 0, -2, 2, 2,
-                0, 1, -1, 2, -1, 0, -2, 0, 1, -2,
-                2, 1, -1, 0, 0, 0, -2, -2, 2, 2,
-                2, -1, -1, -1, -2, 2, -1, 1, -2, -2,
-                -2, -2, 1, -2, -1, -2, 2, -1, -2, 2},
-            std::vector<T>{
-                -2, -2, -1, 0, 2, -1, -2, 1, 0, 0,
-                2, -2, -2, 2, 2, -1, 0, -1, 1, -2,
-                -1, -1, 1, 2, 0, 2, -1, 1, -1, 1,
-                2, 0, 2, 0, 1, 2, 2, -1, -2, 2,
-                -2, 0, 2, 2, 1, -1, -1, -2, 1, -2,
-                -2, 1, 2, -1, 2, -2, 2, 0, -2, 0,
-                -1, 1, 2, -2, 1, 2, -2, -1, -2, -2,
-                2, 0, 0, 1, 1, 1, -2, -2, 1, 0,
-                2, -1, -2, 1, -1, -2, -1, -2, 2, -2,
-                0, -2, -2, 1, -1, 2, -2, 1, -2, 2},
-            std::vector<T>{
-                -2, 1, -2, 2, -2, -1, 2, 1, 2, 2},
-            std::vector<T>{
-                -1, -0.757812, -0.960938, 1, 1, 0, 0.960938, 0.757812, -1, -0.960938,
-                -0.59375, 1, 0.921875, -1, -1, 0.244141, -1, -1, -0.992188, 1,
-                -1, -1, -1, -0.953125, 1, -0.449219, 1, -0.957031, -1, 1,
-                0.898438, 1, -1, 1, -1, 1, 0.992188, 1, -1, -1,
-                -1, 1, -0.953125, 0.992188, -1, -1, 0.96875, -0.185547, -1, 0.960938,
-                -0.996094, 0.154297, -0.154297, -1, -1, -1, 0.890625, -1, -0.542969, -0.289062,
-                -1, 0.96875, -1, -1, -1, 1, 0.617188, -1, -1, -0.976562,
-                -1, 0.757812, -0.984375, 1, -1, 1, 0.992188, -0.244141, -1, -0.124023,
-                1, -0.992188, -0.96875, -1, -0.976562, -1, 1, -1, -0.773438, 1,
-                -1, 0.996094, -0.996094, 1, -1, -1, -0.984375, -1, 1, -0.507812,
-                -0.960938, -1, 0.960938, 1, -1, -0.960938, 1, -0.960938, 1, -1,
-                -1, 0.96875, 1, 1, 1, 0.640625, -1, -1, 0.757812, 1,
-                1, -1, 0.984375, -0.976562, 1, 0.996094, 1, 1, -1, 1,
-                0.765625, 0.992188, 1, 1, -1, -0.992188, 0.953125, -1, -1, 0.96875,
-                -1, -1, -1, 1, -1, 0.871094, -0.921875, 0.558594, 1, -0.992188,
-                1, 1, 1, -1, -0.992188, -1, -1, -0.996094, -0.960938, 1,
-                -1, 0.0625, -1, 1, -0.960938, -0.785156, 1, 1, 0.992188, -1,
-                1, -1, -0.554688, -1, 1, -1, -1, -1, 1, 1,
-                1, 1, -1, -0.108887, -1, -1, 1, 0.960938, 1, -1,
-                1, 1, -1, -0.75, -1, -1, 1, -0.964844, 1, -1,
-                -1, -1, 1, -1, 0.757812, -1, 1, -1, -1, 1,
-                0.984375, 1, -0.960938, 1, -0.996094, 1, 1, -0.847656, 1, -1,
-                -1, 1, 0.976562, -0.96875, 0.671875, -1, 0.757812, -1, 1, -0.726562,
-                -0.996094, 0.957031, -1, -1, -0.921875, 0.992188, 1, -1, -0.953125, -1,
-                -1, 0.996094, -1, 1, -1, 0.992188, 1, 1, -1, -0.992188,
-                -0.992188, -1, -1, -1, -1, -1, 0.960938, -0.992188, -1, 1,
-                -0.957031, 0.960938, 0.96875, 1, -1, 0.953125, -1, -1, 0.96875, 1,
-                1, -1, 1, 0, 1, -1, 0.992188, -1, 1, 0.992188,
-                -0.960938, 1, -1, 1, 1, 0.992188, 1, 1, -0.992188, -1,
-                1, 1, 1, 1, 0.960938, -0.96875, 1, -0.992188, -1, 1,
-                -1, -1, -1, 1, -0.757812, 1, 1, 0.992188, -1, -1,
-                1, 1, -1, -1, -1, -1, 0.976562, -1, -1, 0.9375,
-                -1, -1, -1, 1, -1, 1, -1, 0.96875, -1, 1,
-                -0.773438, 1, 0.992188, -0.960938, -1, -0.960938, 0.964844, 1, -1, 1,
-                0.554688, -1, 1, 1, -1, -1, -1, -1, -1, 0.976562,
-                -1, 1, 0.882812, 1, -1, -0.992188, 1, 1, 1, -1,
-                -1, -1, -1, -1, 1, 1, -0.214844, -0.992188, 1, -1,
-                1, 0.992188, -0.652344, -0.890625, 0.835938, -1, 1, 0.882812, 1, -1,
-                -1, 0.871094, -1, -1, -1, 1, -1, 0.976562, -1, -0.90625,
-                -1, -1, -0.992188, -1, -0.96875, 0.992188, 1, -0.992188, 1, 1,
-                -1, -1, 0, 1, -1, -0.992188, -0.757812, -1, -1, -1,
-                0.984375, -1, 1, -1, 1, -1, 1, -1, 1, 1,
-                0.992188, -1, -1, 1, -1, -1, -1, -0.992188, 0.960938, -1,
-                0.964844, 1, -0.960938, -1, 1, -1, -0.734375, 1, 1, 0.789062,
-                -1, -1, -1, 0.96875, 0.300781, -1, -0.960938, -1, 1, 1,
-                1, 1, -0.800781, -0.554688, 1, 0.9375, -0.59375, 1, 1, 1,
-                0.0625, -1, -0.996094, -0.71875, 1, -1, 1, 0.984375, -0.996094, 1,
-                -0.96875, 0.992188, 0.449219, 1, -1, 1, -1, -0.507812, -1, 1,
-                -1, -1, -0.0625, -0.910156, 1, -1, 1, 0.078125, 0.828125, 1,
-                1, 1, -1, 1, -1, 1, -0.0625, 1, -0.976562, -1},
-            std::vector<T>{
-                -1, 0.996094, -0.996094, 1, -1, -1, -0.984375, -1, 1, -0.507812,
-                1, 1, -1, -0.75, -1, -1, 1, -0.964844, 1, -1,
-                1, 1, 1, 1, 0.960938, -0.96875, 1, -0.992188, -1, 1,
-                -1, -1, -0.992188, -1, -0.96875, 0.992188, 1, -0.992188, 1, 1,
-                1, 1, -1, 1, -1, 1, -0.0625, 1, -0.976562, -1}),
+                -1,        -0.757812, -0.960938, 1,         1,         0,         0.960938,  0.757812,  -1,
+                -0.960938, -0.59375,  1,         0.921875,  -1,        -1,        0.244141,  -1,        -1,
+                -0.992188, 1,         -1,        -1,        -1,        -0.953125, 1,         -0.449219, 1,
+                -0.957031, -1,        1,         0.898438,  1,         -1,        1,         -1,        1,
+                0.992188,  1,         -1,        -1,        -1,        1,         -0.953125, 0.992188,  -1,
+                -1,        0.96875,   -0.185547, -1,        0.960938,  -0.996094, 0.154297,  -0.154297, -1,
+                -1,        -1,        0.890625,  -1,        -0.542969, -0.289062, -1,        0.96875,   -1,
+                -1,        -1,        1,         0.617188,  -1,        -1,        -0.976562, -1,        0.757812,
+                -0.984375, 1,         -1,        1,         0.992188,  -0.244141, -1,        -0.124023, 1,
+                -0.992188, -0.96875,  -1,        -0.976562, -1,        1,         -1,        -0.773438, 1,
+                -1,        0.996094,  -0.996094, 1,         -1,        -1,        -0.984375, -1,        1,
+                -0.507812, -0.960938, -1,        0.960938,  1,         -1,        -0.960938, 1,         -0.960938,
+                1,         -1,        -1,        0.96875,   1,         1,         1,         0.640625,  -1,
+                -1,        0.757812,  1,         1,         -1,        0.984375,  -0.976562, 1,         0.996094,
+                1,         1,         -1,        1,         0.765625,  0.992188,  1,         1,         -1,
+                -0.992188, 0.953125,  -1,        -1,        0.96875,   -1,        -1,        -1,        1,
+                -1,        0.871094,  -0.921875, 0.558594,  1,         -0.992188, 1,         1,         1,
+                -1,        -0.992188, -1,        -1,        -0.996094, -0.960938, 1,         -1,        0.0625,
+                -1,        1,         -0.960938, -0.785156, 1,         1,         0.992188,  -1,        1,
+                -1,        -0.554688, -1,        1,         -1,        -1,        -1,        1,         1,
+                1,         1,         -1,        -0.108887, -1,        -1,        1,         0.960938,  1,
+                -1,        1,         1,         -1,        -0.75,     -1,        -1,        1,         -0.964844,
+                1,         -1,        -1,        -1,        1,         -1,        0.757812,  -1,        1,
+                -1,        -1,        1,         0.984375,  1,         -0.960938, 1,         -0.996094, 1,
+                1,         -0.847656, 1,         -1,        -1,        1,         0.976562,  -0.96875,  0.671875,
+                -1,        0.757812,  -1,        1,         -0.726562, -0.996094, 0.957031,  -1,        -1,
+                -0.921875, 0.992188,  1,         -1,        -0.953125, -1,        -1,        0.996094,  -1,
+                1,         -1,        0.992188,  1,         1,         -1,        -0.992188, -0.992188, -1,
+                -1,        -1,        -1,        -1,        0.960938,  -0.992188, -1,        1,         -0.957031,
+                0.960938,  0.96875,   1,         -1,        0.953125,  -1,        -1,        0.96875,   1,
+                1,         -1,        1,         0,         1,         -1,        0.992188,  -1,        1,
+                0.992188,  -0.960938, 1,         -1,        1,         1,         0.992188,  1,         1,
+                -0.992188, -1,        1,         1,         1,         1,         0.960938,  -0.96875,  1,
+                -0.992188, -1,        1,         -1,        -1,        -1,        1,         -0.757812, 1,
+                1,         0.992188,  -1,        -1,        1,         1,         -1,        -1,        -1,
+                -1,        0.976562,  -1,        -1,        0.9375,    -1,        -1,        -1,        1,
+                -1,        1,         -1,        0.96875,   -1,        1,         -0.773438, 1,         0.992188,
+                -0.960938, -1,        -0.960938, 0.964844,  1,         -1,        1,         0.554688,  -1,
+                1,         1,         -1,        -1,        -1,        -1,        -1,        0.976562,  -1,
+                1,         0.882812,  1,         -1,        -0.992188, 1,         1,         1,         -1,
+                -1,        -1,        -1,        -1,        1,         1,         -0.214844, -0.992188, 1,
+                -1,        1,         0.992188,  -0.652344, -0.890625, 0.835938,  -1,        1,         0.882812,
+                1,         -1,        -1,        0.871094,  -1,        -1,        -1,        1,         -1,
+                0.976562,  -1,        -0.90625,  -1,        -1,        -0.992188, -1,        -0.96875,  0.992188,
+                1,         -0.992188, 1,         1,         -1,        -1,        0,         1,         -1,
+                -0.992188, -0.757812, -1,        -1,        -1,        0.984375,  -1,        1,         -1,
+                1,         -1,        1,         -1,        1,         1,         0.992188,  -1,        -1,
+                1,         -1,        -1,        -1,        -0.992188, 0.960938,  -1,        0.964844,  1,
+                -0.960938, -1,        1,         -1,        -0.734375, 1,         1,         0.789062,  -1,
+                -1,        -1,        0.96875,   0.300781,  -1,        -0.960938, -1,        1,         1,
+                1,         1,         -0.800781, -0.554688, 1,         0.9375,    -0.59375,  1,         1,
+                1,         0.0625,    -1,        -0.996094, -0.71875,  1,         -1,        1,         0.984375,
+                -0.996094, 1,         -0.96875,  0.992188,  0.449219,  1,         -1,        1,         -1,
+                -0.507812, -1,        1,         -1,        -1,        -0.0625,   -0.910156, 1,         -1,
+                1,         0.078125,  0.828125,  1,         1,         1,         -1,        1,         -1,
+                1,         -0.0625,   1,         -0.976562, -1},
+            std::vector<T>{-1,        0.996094,  -0.996094, 1,         -1,    -1,        -0.984375, -1,       1,
+                           -0.507812, 1,         1,         -1,        -0.75, -1,        -1,        1,        -0.964844,
+                           1,         -1,        1,         1,         1,     1,         0.960938,  -0.96875, 1,
+                           -0.992188, -1,        1,         -1,        -1,    -0.992188, -1,        -0.96875, 0.992188,
+                           1,         -0.992188, 1,         1,         1,     1,         -1,        1,        -1,
+                           1,         -0.0625,   1,         -0.976562, -1}),
         RNNSequenceParams(
-            5, 10, 10, 10,
-            0.f, op::RecurrentSequenceDirection::REVERSE,
+            5,
+            10,
+            10,
+            10,
+            0.f,
+            op::RecurrentSequenceDirection::REVERSE,
             ET,
             std::vector<T>{
-                -2, 2, 2, -1, -2, -2, -2, -1, 2, 0,
-                0, 0, 2, 2, 0, 1, 2, 1, -1, 1,
-                -2, 1, 2, 2, -2, -2, -1, -2, -1, -1,
-                2, 1, 1, 2, 2, 2, 0, 2, 2, 1,
-                -2, 1, 2, 1, 2, 0, -1, -1, 1, 0,
-                -2, 1, 2, 2, -1, 1, 1, 1, 0, -2,
-                -1, -2, 1, 2, 1, 2, 2, -2, 2, 0,
-                2, 0, 2, 0, 2, -2, 1, 2, 2, 1,
-                -2, 2, -1, 0, -1, 2, 1, -2, 0, -1,
-                0, -1, 1, 0, 1, 0, 0, 1, 1, -2,
-                2, 0, -2, -2, 2, 1, -1, 2, -1, 1,
-                -2, -2, 0, 0, 1, -1, -1, 2, 0, 2,
-                -2, -1, -1, -1, -1, 0, 1, -2, 2, -2,
-                -2, 1, 1, 1, 2, 0, 1, 2, 2, 1,
-                2, 2, 0, 0, -1, -1, 1, 1, -1, 0,
-                -2, -1, 2, -1, 1, 1, 1, 0, 0, 2,
-                1, 2, 1, 0, -1, -1, -1, 1, 1, -1,
-                -2, 0, -2, -1, -2, -1, 2, 1, -2, -1,
-                -1, 1, -2, 1, 1, 2, -2, 2, -1, -2,
-                0, 2, -2, -1, -1, 2, -1, 2, 1, -2,
-                -2, -2, 2, -1, -1, 1, 0, -2, -1, -2,
-                1, 0, 0, 1, -2, 2, -2, 1, -1, 0,
-                -2, 1, 2, -1, -2, 2, 0, 0, 0, -2,
-                0, 2, 2, 1, -1, 0, 2, 1, 0, 0,
-                2, 2, 2, 0, 2, -2, -1, 0, 0, 1,
-                -1, 2, 0, 0, 1, -1, 0, -2, -1, 0,
-                1, 0, 1, -2, 2, 1, 0, 1, 0, 1,
-                -2, 0, -2, -2, 1, 2, 0, 1, -2, -2,
-                -2, -1, -2, 1, 2, -1, -2, -2, 2, -2,
-                -2, 2, 2, -1, -1, 0, -1, 0, 1, 0,
-                1, 2, 2, 1, 2, -1, -1, -2, 0, -2,
-                -2, 2, -1, 2, 2, 2, 2, -2, 1, 0,
-                0, 0, -1, -2, 2, -1, 1, 0, 1, 1,
-                2, 1, 2, 2, 0, 1, 0, 0, 1, 1,
-                -1, 2, 1, -1, 2, 2, 2, 2, -2, 1,
-                2, -1, -1, 2, 1, 2, -2, 2, 2, -2,
-                1, -2, -2, -1, 0, 2, 0, -2, 0, -2,
-                0, 1, -1, -2, 2, 1, -2, 0, -2, -2,
-                -1, 1, 0, 1, 2, -2, 2, -2, 1, 1,
-                2, -1, -1, -1, -2, 0, 1, -1, -2, 0,
-                0, 2, 1, -1, 2, 0, -1, 2, -2, -1,
-                -2, -2, -2, 0, 1, 0, 0, 1, -1, -1,
-                -1, 2, -2, 0, 2, 0, 1, 1, -2, 0,
-                -1, 1, 2, -1, -1, 1, 0, -1, 1, -2,
-                0, -1, 0, -1, -1, -2, -1, 1, -2, -1,
-                0, -2, -2, 1, -2, 0, -1, 1, 0, 1,
-                -2, -1, -1, -1, 0, -1, 0, -2, 1, -2,
-                1, -2, 0, -1, 2, -1, 1, 1, 2, 2,
-                0, 1, 1, 1, -2, -1, -1, -1, -1, -2,
-                0, 2, 1, 0, -1, 2, -2, -1, 1, 2},
-            std::vector<T>{
-                -2, 2, 0, 1, -2, 1, 2, 0, 2, 0,
-                -2, 0, 1, -2, -2, 1, 0, 0, 0, -2,
-                -1, 0, 2, -2, -1, 2, -1, 2, 2, 1,
-                -2, 2, 1, 1, 0, 2, 2, -2, -1, 1,
-                -1, 2, 2, -2, -1, -1, 2, 2, 0, 2},
+                -2, 2,  2,  -1, -2, -2, -2, -1, 2,  0,  0,  0,  2,  2,  0,  1,  2,  1,  -1, 1,  -2, 1,  2,  2,  -2,
+                -2, -1, -2, -1, -1, 2,  1,  1,  2,  2,  2,  0,  2,  2,  1,  -2, 1,  2,  1,  2,  0,  -1, -1, 1,  0,
+                -2, 1,  2,  2,  -1, 1,  1,  1,  0,  -2, -1, -2, 1,  2,  1,  2,  2,  -2, 2,  0,  2,  0,  2,  0,  2,
+                -2, 1,  2,  2,  1,  -2, 2,  -1, 0,  -1, 2,  1,  -2, 0,  -1, 0,  -1, 1,  0,  1,  0,  0,  1,  1,  -2,
+                2,  0,  -2, -2, 2,  1,  -1, 2,  -1, 1,  -2, -2, 0,  0,  1,  -1, -1, 2,  0,  2,  -2, -1, -1, -1, -1,
+                0,  1,  -2, 2,  -2, -2, 1,  1,  1,  2,  0,  1,  2,  2,  1,  2,  2,  0,  0,  -1, -1, 1,  1,  -1, 0,
+                -2, -1, 2,  -1, 1,  1,  1,  0,  0,  2,  1,  2,  1,  0,  -1, -1, -1, 1,  1,  -1, -2, 0,  -2, -1, -2,
+                -1, 2,  1,  -2, -1, -1, 1,  -2, 1,  1,  2,  -2, 2,  -1, -2, 0,  2,  -2, -1, -1, 2,  -1, 2,  1,  -2,
+                -2, -2, 2,  -1, -1, 1,  0,  -2, -1, -2, 1,  0,  0,  1,  -2, 2,  -2, 1,  -1, 0,  -2, 1,  2,  -1, -2,
+                2,  0,  0,  0,  -2, 0,  2,  2,  1,  -1, 0,  2,  1,  0,  0,  2,  2,  2,  0,  2,  -2, -1, 0,  0,  1,
+                -1, 2,  0,  0,  1,  -1, 0,  -2, -1, 0,  1,  0,  1,  -2, 2,  1,  0,  1,  0,  1,  -2, 0,  -2, -2, 1,
+                2,  0,  1,  -2, -2, -2, -1, -2, 1,  2,  -1, -2, -2, 2,  -2, -2, 2,  2,  -1, -1, 0,  -1, 0,  1,  0,
+                1,  2,  2,  1,  2,  -1, -1, -2, 0,  -2, -2, 2,  -1, 2,  2,  2,  2,  -2, 1,  0,  0,  0,  -1, -2, 2,
+                -1, 1,  0,  1,  1,  2,  1,  2,  2,  0,  1,  0,  0,  1,  1,  -1, 2,  1,  -1, 2,  2,  2,  2,  -2, 1,
+                2,  -1, -1, 2,  1,  2,  -2, 2,  2,  -2, 1,  -2, -2, -1, 0,  2,  0,  -2, 0,  -2, 0,  1,  -1, -2, 2,
+                1,  -2, 0,  -2, -2, -1, 1,  0,  1,  2,  -2, 2,  -2, 1,  1,  2,  -1, -1, -1, -2, 0,  1,  -1, -2, 0,
+                0,  2,  1,  -1, 2,  0,  -1, 2,  -2, -1, -2, -2, -2, 0,  1,  0,  0,  1,  -1, -1, -1, 2,  -2, 0,  2,
+                0,  1,  1,  -2, 0,  -1, 1,  2,  -1, -1, 1,  0,  -1, 1,  -2, 0,  -1, 0,  -1, -1, -2, -1, 1,  -2, -1,
+                0,  -2, -2, 1,  -2, 0,  -1, 1,  0,  1,  -2, -1, -1, -1, 0,  -1, 0,  -2, 1,  -2, 1,  -2, 0,  -1, 2,
+                -1, 1,  1,  2,  2,  0,  1,  1,  1,  -2, -1, -1, -1, -1, -2, 0,  2,  1,  0,  -1, 2,  -2, -1, 1,  2},
+            std::vector<T>{-2, 2,  0, 1, -2, 1,  2, 0, 2, 0, -2, 0, 1,  -2, -2, 1,  0, 0, 0,  -2, -1, 0, 2, -2, -1,
+                           2,  -1, 2, 2, 1,  -2, 2, 1, 1, 0, 2,  2, -2, -1, 1,  -1, 2, 2, -2, -1, -1, 2, 2, 0,  2},
             std::vector<int64_t>{10, 10, 10, 10, 10},
+            std::vector<T>{-2, 2,  -2, -1, -1, 2,  0,  0,  1,  1,  1,  1,  2,  1,  0,  2,  -2, 0,  2,  1,
+                           -1, -1, 1,  -2, 0,  1,  0,  2,  0,  0,  0,  0,  0,  -2, 0,  -1, -2, 2,  1,  2,
+                           -1, -1, -1, -2, -2, -2, -1, -1, 1,  -1, 2,  -2, 0,  0,  -1, -1, 0,  -2, 2,  2,
+                           0,  1,  -1, 2,  -1, 0,  -2, 0,  1,  -2, 2,  1,  -1, 0,  0,  0,  -2, -2, 2,  2,
+                           2,  -1, -1, -1, -2, 2,  -1, 1,  -2, -2, -2, -2, 1,  -2, -1, -2, 2,  -1, -2, 2},
+            std::vector<T>{-2, -2, -1, 0,  2,  -1, -2, 1,  0,  0,  2,  -2, -2, 2,  2,  -1, 0,  -1, 1,  -2,
+                           -1, -1, 1,  2,  0,  2,  -1, 1,  -1, 1,  2,  0,  2,  0,  1,  2,  2,  -1, -2, 2,
+                           -2, 0,  2,  2,  1,  -1, -1, -2, 1,  -2, -2, 1,  2,  -1, 2,  -2, 2,  0,  -2, 0,
+                           -1, 1,  2,  -2, 1,  2,  -2, -1, -2, -2, 2,  0,  0,  1,  1,  1,  -2, -2, 1,  0,
+                           2,  -1, -2, 1,  -1, -2, -1, -2, 2,  -2, 0,  -2, -2, 1,  -1, 2,  -2, 1,  -2, 2},
+            std::vector<T>{-2, 1, -2, 2, -2, -1, 2, 1, 2, 2},
             std::vector<T>{
-                -2, 2, -2, -1, -1, 2, 0, 0, 1, 1,
-                1, 1, 2, 1, 0, 2, -2, 0, 2, 1,
-                -1, -1, 1, -2, 0, 1, 0, 2, 0, 0,
-                0, 0, 0, -2, 0, -1, -2, 2, 1, 2,
-                -1, -1, -1, -2, -2, -2, -1, -1, 1, -1,
-                2, -2, 0, 0, -1, -1, 0, -2, 2, 2,
-                0, 1, -1, 2, -1, 0, -2, 0, 1, -2,
-                2, 1, -1, 0, 0, 0, -2, -2, 2, 2,
-                2, -1, -1, -1, -2, 2, -1, 1, -2, -2,
-                -2, -2, 1, -2, -1, -2, 2, -1, -2, 2},
+                0.921875,  -0.507812, -0.804688,  1,         1,         -0.890625, 1,         1,         -1,
+                1,         -0.808594, 1,          -1,        -0.960938, -1,        1,         -1,        -1,
+                -0.992188, 1,         -1,         -0.960938, -1,        -1,        0.964844,  -0.992188, 1,
+                -1,        -1,        1,          -1,        1,         -0.996094, 1,         -1,        0.972656,
+                1,         1,         -0.992188,  -1,        -0.988281, 1,         -1,        0.214844,  -0.124023,
+                0.671875,  1,         -0.988281,  -1,        -1,        -1,        -1,        0.589844,  0.357422,
+                -1,        -1,        1,          -1,        -1,        -0.984375, -0.96875,  0.992188,  0.734375,
+                -1,        -1,        0.960938,   1,         -0.953125, -1,        1,         -1,        1,
+                -1,        1,         -1,         1,         -1,        0.949219,  -1,        -1,        1,
+                0.921875,  -1,        -1,         1,         -0.984375, 1,         0.585938,  1,         -1,
+                -1,        -1,        0.960938,   -0.992188, 0.757812,  -1,        -0.960938, -1,        0,
+                -1,        -0.984375, -0.765625,  1,         1,         -1,        -1,        -1,        1,
+                1,         -0.574219, 0.890625,   -0.124023, 1,         1,         -1,        -0.957031, -1,
+                -1,        -1,        1,          -0.75,     -1,        -0.996094, -0.244141, 1,         0.992188,
+                1,         0.960938,  0.847656,   1,         1,         1,         0.96875,   0,         -1,
+                -1,        -1,        -1,         -1,        0.90625,   -1,        -1,        -0.992188, 0.542969,
+                -1,        -1,        0.984375,   0.96875,   1,         1,         -0.796875, 1,         -0.757812,
+                0.75,      -1,        -0.0932617, -1,        -1,        -0.960938, 1,         1,         1,
+                -1,        0,         0.960938,   -0.992188, 1,         1,         1,         -1,        -0.992188,
+                -1,        -1,        -1,         1,         -1,        -1,        -1,        1,         1,
+                1,         1,         -1,         0.984375,  -0.992188, -1,        1,         -0.941406, 1,
+                -1,        1,         -1,         0.757812,  -0.757812, 0.992188,  -1,        1,         -1,
+                1,         -1,        -0.976562,  0.992188,  0.0625,    -1,        1,         0.59375,   -1,
+                -1,        1,         1,          -0.921875, 1,         -1,        1,         0.992188,  -0.925781,
+                1,         1,         1,          -1,        0.75,      -1,        0.984375,  0.984375,  0.460938,
+                -0.976562, 1,         -1,         0.996094,  -0.910156, -0.757812, 0.273438,  0.996094,  -1,
+                -1,        -1,        1,          -1,        -1,        1,         -1,        1,         -1,
+                1,         -1,        1,          -1,        1,         -1,        -0.640625, 0.773438,  -1,
+                -1,        -1,        1,          -1,        0.953125,  0.773438,  -1,        0.185547,  -1,
+                1,         0.953125,  1,          -1,        -0.984375, -1,        0.996094,  1,         -0.976562,
+                1,         -1,        1,          -0.0625,   -0.75,     -1,        0.960938,  -1,        1,
+                1,         -1,        0.03125,    -1,        1,         1,         0.96875,   1,         1,
+                -1,        -1,        1,          -1,        1,         1,         -0.960938, -1,        1,
+                -0.960938, -1,        1,          -1,        0.964844,  -1,        -0.992188, -1,        -0.964844,
+                0.960938,  -0.734375, -1,         -1,        1,         0.984375,  -1,        -1,        -1,
+                -1,        0.988281,  0.996094,   -1,        1,         -0.992188, -1,        -0.996094, 0.9375,
+                -1,        0.273438,  -1,         -0.96875,  -1,        1,         -1,        1,         -1,
+                -1,        -1,        0.855469,   1,         1,         1,         -1,        -0.773438, 0.71875,
+                -0.992188, -1,        -1,         -1,        -1,        -1,        1,         -0.96875,  0.992188,
+                1,         -0.960938, -1,         -1,        -1,        1,         1,         1,         -1,
+                -1,        -0.384766, -1,         -0.976562, 1,         0.796875,  -1,        1,         1,
+                -1,        1,         -0.90625,   1,         0.992188,  -1,        -1,        1,         -0.796875,
+                1,         1,         -0.90625,   -0.945312, -1,        0.980469,  0.734375,  1,         -1,
+                1,         -1,        1,          -1,        -1,        0.757812,  1,         1,         1,
+                1,         -0.757812, 0.960938,   1,         1,         1,         -0.357422, 0.921875,  -1,
+                -1,        -0.847656, -1,         1,         -0.992188, -0.617188, -0.960938, -0.757812, -1,
+                0.984375,  -1,        -0.808594,  -1,        1,         1,         0.75,      -1,        -1,
+                0.472656,  -1,        -1,         -0.390625, -1,        -0.384766, -1,        1,         1,
+                1,         -1,        1,          -0.992188, 0.992188,  0.960938,  1,         -0.757812, -1,
+                -1,        1,         1,          1,         -1,        -1,        -1,        1,         1,
+                -0.753906, 0,         -1,         1,         0.757812,  1,         1,         0.992188,  1,
+                0,         1,         -1,         1,         -1,        1,         -1,        0.996094,  -0.992188,
+                -1,        1,         -1,         -0.992188, -1,        1,         -1,        1,         -1,
+                0.890625,  -1,        0.933594,   -1,        1,         -1,        -0.90625,  -0.460938, -1,
+                1,         -0.898438, 1,          1,         0.757812,  -1,        -1,        1,         -1,
+                1,         0.992188,  0,          -1,        -1},
             std::vector<T>{
-                -2, -2, -1, 0, 2, -1, -2, 1, 0, 0,
-                2, -2, -2, 2, 2, -1, 0, -1, 1, -2,
-                -1, -1, 1, 2, 0, 2, -1, 1, -1, 1,
-                2, 0, 2, 0, 1, 2, 2, -1, -2, 2,
-                -2, 0, 2, 2, 1, -1, -1, -2, 1, -2,
-                -2, 1, 2, -1, 2, -2, 2, 0, -2, 0,
-                -1, 1, 2, -2, 1, 2, -2, -1, -2, -2,
-                2, 0, 0, 1, 1, 1, -2, -2, 1, 0,
-                2, -1, -2, 1, -1, -2, -1, -2, 2, -2,
-                0, -2, -2, 1, -1, 2, -2, 1, -2, 2},
-            std::vector<T>{
-                -2, 1, -2, 2, -2, -1, 2, 1, 2, 2},
-            std::vector<T>{
-                0.921875, -0.507812, -0.804688, 1, 1, -0.890625, 1, 1, -1, 1,
-                -0.808594, 1, -1, -0.960938, -1, 1, -1, -1, -0.992188, 1,
-                -1, -0.960938, -1, -1, 0.964844, -0.992188, 1, -1, -1, 1,
-                -1, 1, -0.996094, 1, -1, 0.972656, 1, 1, -0.992188, -1,
-                -0.988281, 1, -1, 0.214844, -0.124023, 0.671875, 1, -0.988281, -1, -1,
-                -1, -1, 0.589844, 0.357422, -1, -1, 1, -1, -1, -0.984375,
-                -0.96875, 0.992188, 0.734375, -1, -1, 0.960938, 1, -0.953125, -1, 1,
-                -1, 1, -1, 1, -1, 1, -1, 0.949219, -1, -1,
-                1, 0.921875, -1, -1, 1, -0.984375, 1, 0.585938, 1, -1,
-                -1, -1, 0.960938, -0.992188, 0.757812, -1, -0.960938, -1, 0, -1,
-                -0.984375, -0.765625, 1, 1, -1, -1, -1, 1, 1, -0.574219,
-                0.890625, -0.124023, 1, 1, -1, -0.957031, -1, -1, -1, 1,
-                -0.75, -1, -0.996094, -0.244141, 1, 0.992188, 1, 0.960938, 0.847656, 1,
-                1, 1, 0.96875, 0, -1, -1, -1, -1, -1, 0.90625,
-                -1, -1, -0.992188, 0.542969, -1, -1, 0.984375, 0.96875, 1, 1,
-                -0.796875, 1, -0.757812, 0.75, -1, -0.0932617, -1, -1, -0.960938, 1,
-                1, 1, -1, 0, 0.960938, -0.992188, 1, 1, 1, -1,
-                -0.992188, -1, -1, -1, 1, -1, -1, -1, 1, 1,
-                1, 1, -1, 0.984375, -0.992188, -1, 1, -0.941406, 1, -1,
-                1, -1, 0.757812, -0.757812, 0.992188, -1, 1, -1, 1, -1,
-                -0.976562, 0.992188, 0.0625, -1, 1, 0.59375, -1, -1, 1, 1,
-                -0.921875, 1, -1, 1, 0.992188, -0.925781, 1, 1, 1, -1,
-                0.75, -1, 0.984375, 0.984375, 0.460938, -0.976562, 1, -1, 0.996094, -0.910156,
-                -0.757812, 0.273438, 0.996094, -1, -1, -1, 1, -1, -1, 1,
-                -1, 1, -1, 1, -1, 1, -1, 1, -1, -0.640625,
-                0.773438, -1, -1, -1, 1, -1, 0.953125, 0.773438, -1, 0.185547,
-                -1, 1, 0.953125, 1, -1, -0.984375, -1, 0.996094, 1, -0.976562,
-                1, -1, 1, -0.0625, -0.75, -1, 0.960938, -1, 1, 1,
-                -1, 0.03125, -1, 1, 1, 0.96875, 1, 1, -1, -1,
-                1, -1, 1, 1, -0.960938, -1, 1, -0.960938, -1, 1,
-                -1, 0.964844, -1, -0.992188, -1, -0.964844, 0.960938, -0.734375, -1, -1,
-                1, 0.984375, -1, -1, -1, -1, 0.988281, 0.996094, -1, 1,
-                -0.992188, -1, -0.996094, 0.9375, -1, 0.273438, -1, -0.96875, -1, 1,
-                -1, 1, -1, -1, -1, 0.855469, 1, 1, 1, -1,
-                -0.773438, 0.71875, -0.992188, -1, -1, -1, -1, -1, 1, -0.96875,
-                0.992188, 1, -0.960938, -1, -1, -1, 1, 1, 1, -1,
-                -1, -0.384766, -1, -0.976562, 1, 0.796875, -1, 1, 1, -1,
-                1, -0.90625, 1, 0.992188, -1, -1, 1, -0.796875, 1, 1,
-                -0.90625, -0.945312, -1, 0.980469, 0.734375, 1, -1, 1, -1, 1,
-                -1, -1, 0.757812, 1, 1, 1, 1, -0.757812, 0.960938, 1,
-                1, 1, -0.357422, 0.921875, -1, -1, -0.847656, -1, 1, -0.992188,
-                -0.617188, -0.960938, -0.757812, -1, 0.984375, -1, -0.808594, -1, 1, 1,
-                0.75, -1, -1, 0.472656, -1, -1, -0.390625, -1, -0.384766, -1,
-                1, 1, 1, -1, 1, -0.992188, 0.992188, 0.960938, 1, -0.757812,
-                -1, -1, 1, 1, 1, -1, -1, -1, 1, 1,
-                -0.753906, 0, -1, 1, 0.757812, 1, 1, 0.992188, 1, 0,
-                1, -1, 1, -1, 1, -1, 0.996094, -0.992188, -1, 1,
-                -1, -0.992188, -1, 1, -1, 1, -1, 0.890625, -1, 0.933594,
-                -1, 1, -1, -0.90625, -0.460938, -1, 1, -0.898438, 1, 1,
-                0.757812, -1, -1, 1, -1, 1, 0.992188, 0, -1, -1},
-            std::vector<T>{
-                0.921875, -0.507812, -0.804688, 1, 1, -0.890625, 1, 1, -1, 1,
-                -0.984375, -0.765625, 1, 1, -1, -1, -1, 1, 1, -0.574219,
-                -0.976562, 0.992188, 0.0625, -1, 1, 0.59375, -1, -1, 1, 1,
-                -1, 0.964844, -1, -0.992188, -1, -0.964844, 0.960938, -0.734375, -1, -1,
-                1, 1, -0.357422, 0.921875, -1, -1, -0.847656, -1, 1, -0.992188}),
+                0.921875,  -0.507812, -0.804688, 1,         1,  -0.890625, 1,         1,         -1, 1,
+                -0.984375, -0.765625, 1,         1,         -1, -1,        -1,        1,         1,  -0.574219,
+                -0.976562, 0.992188,  0.0625,    -1,        1,  0.59375,   -1,        -1,        1,  1,
+                -1,        0.964844,  -1,        -0.992188, -1, -0.964844, 0.960938,  -0.734375, -1, -1,
+                1,         1,         -0.357422, 0.921875,  -1, -1,        -0.847656, -1,        1,  -0.992188}),
         RNNSequenceParams(
-            5, 10, 10, 5,
-            0.f, op::RecurrentSequenceDirection::BIDIRECTIONAL,
+            5,
+            10,
+            10,
+            5,
+            0.f,
+            op::RecurrentSequenceDirection::BIDIRECTIONAL,
             ET,
-            std::vector<T>{
-                -2, 2, 2, -1, -2, -2, -2, -1, 2, 0,
-                0, 0, 2, 2, 0, 1, 2, 1, -1, 1,
-                -2, 1, 2, 2, -2, -2, -1, -2, -1, -1,
-                2, 1, 1, 2, 2, 2, 0, 2, 2, 1,
-                -2, 1, 2, 1, 2, 0, -1, -1, 1, 0,
-                -2, 1, 2, 2, -1, 1, 1, 1, 0, -2,
-                -1, -2, 1, 2, 1, 2, 2, -2, 2, 0,
-                2, 0, 2, 0, 2, -2, 1, 2, 2, 1,
-                -2, 2, -1, 0, -1, 2, 1, -2, 0, -1,
-                0, -1, 1, 0, 1, 0, 0, 1, 1, -2,
-                2, 0, -2, -2, 2, 1, -1, 2, -1, 1,
-                -2, -2, 0, 0, 1, -1, -1, 2, 0, 2,
-                -2, -1, -1, -1, -1, 0, 1, -2, 2, -2,
-                -2, 1, 1, 1, 2, 0, 1, 2, 2, 1,
-                2, 2, 0, 0, -1, -1, 1, 1, -1, 0,
-                -2, -1, 2, -1, 1, 1, 1, 0, 0, 2,
-                1, 2, 1, 0, -1, -1, -1, 1, 1, -1,
-                -2, 0, -2, -1, -2, -1, 2, 1, -2, -1,
-                -1, 1, -2, 1, 1, 2, -2, 2, -1, -2,
-                0, 2, -2, -1, -1, 2, -1, 2, 1, -2,
-                -2, -2, 2, -1, -1, 1, 0, -2, -1, -2,
-                1, 0, 0, 1, -2, 2, -2, 1, -1, 0,
-                -2, 1, 2, -1, -2, 2, 0, 0, 0, -2,
-                0, 2, 2, 1, -1, 0, 2, 1, 0, 0,
-                2, 2, 2, 0, 2, -2, -1, 0, 0, 2},
-            std::vector<T>{
-                -2, 2, 0, 1, -2, 1, 2, 0, 2, 0,
-                -2, 0, 1, -2, -2, 1, 0, 0, 0, -2,
-                -1, 0, 2, -2, -1, 2, -1, 2, 2, 1,
-                -2, 2, 1, 1, 0, 2, 2, -2, -1, 1,
-                -1, 2, 2, -2, -1, -1, 2, 2, 0, 2,
-                2, -2, -1, 2, 1, -1, -2, 1, -1, -2,
-                1, 2, -2, 0, -1, 1, -1, 2, -1, -2,
-                -2, -2, 0, 0, 0, 2, 1, 1, 2, 1,
-                -1, 0, 0, 0, -2, 1, -2, 1, 1, -2,
-                0, -1, 2, -2, -1, 2, 1, -2, 1, 2},
+            std::vector<T>{-2, 2,  2,  -1, -2, -2, -2, -1, 2,  0,  0,  0,  2,  2,  0,  1,  2,  1,  -1, 1,  -2, 1,  2,
+                           2,  -2, -2, -1, -2, -1, -1, 2,  1,  1,  2,  2,  2,  0,  2,  2,  1,  -2, 1,  2,  1,  2,  0,
+                           -1, -1, 1,  0,  -2, 1,  2,  2,  -1, 1,  1,  1,  0,  -2, -1, -2, 1,  2,  1,  2,  2,  -2, 2,
+                           0,  2,  0,  2,  0,  2,  -2, 1,  2,  2,  1,  -2, 2,  -1, 0,  -1, 2,  1,  -2, 0,  -1, 0,  -1,
+                           1,  0,  1,  0,  0,  1,  1,  -2, 2,  0,  -2, -2, 2,  1,  -1, 2,  -1, 1,  -2, -2, 0,  0,  1,
+                           -1, -1, 2,  0,  2,  -2, -1, -1, -1, -1, 0,  1,  -2, 2,  -2, -2, 1,  1,  1,  2,  0,  1,  2,
+                           2,  1,  2,  2,  0,  0,  -1, -1, 1,  1,  -1, 0,  -2, -1, 2,  -1, 1,  1,  1,  0,  0,  2,  1,
+                           2,  1,  0,  -1, -1, -1, 1,  1,  -1, -2, 0,  -2, -1, -2, -1, 2,  1,  -2, -1, -1, 1,  -2, 1,
+                           1,  2,  -2, 2,  -1, -2, 0,  2,  -2, -1, -1, 2,  -1, 2,  1,  -2, -2, -2, 2,  -1, -1, 1,  0,
+                           -2, -1, -2, 1,  0,  0,  1,  -2, 2,  -2, 1,  -1, 0,  -2, 1,  2,  -1, -2, 2,  0,  0,  0,  -2,
+                           0,  2,  2,  1,  -1, 0,  2,  1,  0,  0,  2,  2,  2,  0,  2,  -2, -1, 0,  0,  2},
+            std::vector<T>{-2, 2, 0,  1,  -2, 1,  2,  0, 2,  0,  -2, 0,  1,  -2, -2, 1,  0,  0,  0,  -2,
+                           -1, 0, 2,  -2, -1, 2,  -1, 2, 2,  1,  -2, 2,  1,  1,  0,  2,  2,  -2, -1, 1,
+                           -1, 2, 2,  -2, -1, -1, 2,  2, 0,  2,  2,  -2, -1, 2,  1,  -1, -2, 1,  -1, -2,
+                           1,  2, -2, 0,  -1, 1,  -1, 2, -1, -2, -2, -2, 0,  0,  0,  2,  1,  1,  2,  1,
+                           -1, 0, 0,  0,  -2, 1,  -2, 1, 1,  -2, 0,  -1, 2,  -2, -1, 2,  1,  -2, 1,  2},
             std::vector<int64_t>{5, 5, 5, 5, 5},
+            std::vector<T>{-2, 2,  -2, -1, -1, 2,  0,  0,  1,  1,  1,  1,  2,  1,  0,  2,  -2, 0,  2,  1,  -1, -1, 1,
+                           -2, 0,  1,  0,  2,  0,  0,  0,  0,  0,  -2, 0,  -1, -2, 2,  1,  2,  -1, -1, -1, -2, -2, -2,
+                           -1, -1, 1,  -1, 2,  -2, 0,  0,  -1, -1, 0,  -2, 2,  2,  0,  1,  -1, 2,  -1, 0,  -2, 0,  1,
+                           -2, 2,  1,  -1, 0,  0,  0,  -2, -2, 2,  2,  2,  -1, -1, -1, -2, 2,  -1, 1,  -2, -2, -2, -2,
+                           1,  -2, -1, -2, 2,  -1, -2, 2,  -1, 0,  -2, -1, 1,  0,  1,  2,  -1, -2, -2, -2, 1,  0,  -1,
+                           -2, -2, -2, 0,  -1, 1,  2,  2,  -2, -2, 1,  -2, 2,  1,  -1, 0,  -2, -2, -1, 0,  -1, -2, 2,
+                           0,  2,  0,  2,  2,  -2, 0,  1,  -2, 2,  1,  0,  -2, 0,  2,  -1, 1,  -2, 0,  0,  -1, -1, 0,
+                           1,  0,  0,  2,  1,  1,  -1, -2, -2, 1,  1,  -1, -1, 1,  0,  -1, 0,  -2, 1,  2,  1,  1,  -1,
+                           -2, 0,  2,  2,  2,  0,  1,  1,  -2, -2, 0,  0,  0,  -1, -1, 2},
+            std::vector<T>{-2, -2, -1, 0,  2,  -1, -2, 1,  0,  0,  2,  -2, -2, 2,  2,  -1, 0,  -1, 1,  -2, -1, -1, 1,
+                           2,  0,  2,  -1, 1,  -1, 1,  2,  0,  2,  0,  1,  2,  2,  -1, -2, 2,  -2, 0,  2,  2,  1,  -1,
+                           -1, -2, 1,  -2, -2, 1,  2,  -1, 2,  -2, 2,  0,  -2, 0,  -1, 1,  2,  -2, 1,  2,  -2, -1, -2,
+                           -2, 2,  0,  0,  1,  1,  1,  -2, -2, 1,  0,  2,  -1, -2, 1,  -1, -2, -1, -2, 2,  -2, 0,  -2,
+                           -2, 1,  -1, 2,  -2, 1,  -2, 1,  -1, -2, -2, -2, -2, -2, 0,  -1, 2,  0,  0,  2,  2,  1,  0,
+                           1,  -2, -1, 0,  -1, 1,  1,  -2, 1,  -1, 1,  2,  0,  0,  -2, -1, 0,  -2, -2, 1,  2,  1,  -1,
+                           -1, 1,  -1, 0,  -2, 1,  1,  1,  -1, 2,  -2, 2,  1,  1,  -2, 2,  0,  0,  -1, -2, -1, 2,  2,
+                           1,  -2, -2, 2,  1,  -1, -2, 1,  0,  1,  2,  0,  2,  1,  0,  0,  -1, 0,  1,  -2, -1, 1,  2,
+                           1,  -1, 2,  1,  2,  -2, 2,  1,  1,  -1, -2, -1, -1, -1, -1, 2},
+            std::vector<T>{-2, 1, -2, 2, -2, -1, 2, 1, 2, -2, 0, 1, -2, 2, 0, -2, 0, 0, 0, 2},
             std::vector<T>{
-                -2, 2, -2, -1, -1, 2, 0, 0, 1, 1,
-                1, 1, 2, 1, 0, 2, -2, 0, 2, 1,
-                -1, -1, 1, -2, 0, 1, 0, 2, 0, 0,
-                0, 0, 0, -2, 0, -1, -2, 2, 1, 2,
-                -1, -1, -1, -2, -2, -2, -1, -1, 1, -1,
-                2, -2, 0, 0, -1, -1, 0, -2, 2, 2,
-                0, 1, -1, 2, -1, 0, -2, 0, 1, -2,
-                2, 1, -1, 0, 0, 0, -2, -2, 2, 2,
-                2, -1, -1, -1, -2, 2, -1, 1, -2, -2,
-                -2, -2, 1, -2, -1, -2, 2, -1, -2, 2,
-                -1, 0, -2, -1, 1, 0, 1, 2, -1, -2,
-                -2, -2, 1, 0, -1, -2, -2, -2, 0, -1,
-                1, 2, 2, -2, -2, 1, -2, 2, 1, -1,
-                0, -2, -2, -1, 0, -1, -2, 2, 0, 2,
-                0, 2, 2, -2, 0, 1, -2, 2, 1, 0,
-                -2, 0, 2, -1, 1, -2, 0, 0, -1, -1,
-                0, 1, 0, 0, 2, 1, 1, -1, -2, -2,
-                1, 1, -1, -1, 1, 0, -1, 0, -2, 1,
-                2, 1, 1, -1, -2, 0, 2, 2, 2, 0,
-                1, 1, -2, -2, 0, 0, 0, -1, -1, 2},
-            std::vector<T>{
-                -2, -2, -1, 0, 2, -1, -2, 1, 0, 0,
-                2, -2, -2, 2, 2, -1, 0, -1, 1, -2,
-                -1, -1, 1, 2, 0, 2, -1, 1, -1, 1,
-                2, 0, 2, 0, 1, 2, 2, -1, -2, 2,
-                -2, 0, 2, 2, 1, -1, -1, -2, 1, -2,
-                -2, 1, 2, -1, 2, -2, 2, 0, -2, 0,
-                -1, 1, 2, -2, 1, 2, -2, -1, -2, -2,
-                2, 0, 0, 1, 1, 1, -2, -2, 1, 0,
-                2, -1, -2, 1, -1, -2, -1, -2, 2, -2,
-                0, -2, -2, 1, -1, 2, -2, 1, -2, 1,
-                -1, -2, -2, -2, -2, -2, 0, -1, 2, 0,
-                0, 2, 2, 1, 0, 1, -2, -1, 0, -1,
-                1, 1, -2, 1, -1, 1, 2, 0, 0, -2,
-                -1, 0, -2, -2, 1, 2, 1, -1, -1, 1,
-                -1, 0, -2, 1, 1, 1, -1, 2, -2, 2,
-                1, 1, -2, 2, 0, 0, -1, -2, -1, 2,
-                2, 1, -2, -2, 2, 1, -1, -2, 1, 0,
-                1, 2, 0, 2, 1, 0, 0, -1, 0, 1,
-                -2, -1, 1, 2, 1, -1, 2, 1, 2, -2,
-                2, 1, 1, -1, -2, -1, -1, -1, -1, 2},
-            std::vector<T>{
-                -2, 1, -2, 2, -2, -1, 2, 1, 2, -2,
-                0, 1, -2, 2, 0, -2, 0, 0, 0, 2},
-            std::vector<T>{
-                -1, -0.757812, -0.960938, 1, 1, 0, 0.960938, 0.757812, -1, -1,
-                -0.59375, 1, 0.921875, -1, -1, 0.244141, -1, -1, -0.992188, 1,
-                -1, -1, -1, -0.953125, 1, -0.449219, 1, -0.957031, -1, 1,
-                0.898438, 1, -1, 1, -1, 1, 0.992188, 1, -1, -1,
-                -1, 1, -0.953125, 0.992188, -1, -1, 0.96875, -0.185547, -1, -0.757812,
-                -1, 1, 1, 0.863281, 1, 1, -1, -1, 1, -1,
-                -0.757812, -0.96875, -0.957031, 0.757812, -0.773438, -0.03125, 1, -1, -0.992188, -0.992188,
-                -1, 1, -1, -1, -1, 1, -0.960938, -1, -1, -1,
-                0.0625, -1, 1, 0.214844, 1, -1, 1, -0.832031, -0.300781, 0.996094,
-                0.757812, 1, -0.960938, -0.992188, -0.960938, -1, -0.960938, -1, -1, -1,
-                -0.757812, -1, 1, -1, -1, -1, 1, -1, -1, -1,
-                -1, 1, -1, -1, -1, 1, 1, -1, -1, -1,
-                -1, 0.757812, -0.992188, 1, -1, 1, 0.960938, -0.757812, -1, -1,
-                1, -0.652344, -1, -1, 0.515625, -1, 1, -0.984375, 0.945312, -0.835938,
-                -1, 1, -1, -0.785156, -0.992188, -1, -0.300781, -1, 1, -1,
-                1, 0, 1, -1, -1, 0.78125, 1, -1, 1, -1,
-                -1, 1, -1, -1, -1, -1, 1, -1, 0.949219, -1,
-                1, -1, 1, 1, 0.835938, -0.992188, -1, -1, 1, -1,
-                -1, 1, -1, -1, -0.859375, -1, 1, 0.03125, 1, -0.996094,
-                -1, 1, 1, 1, 1, 1, -0.757812, 0.960938, 0.992188, -1,
-                -1, -1, 0, 1, -1, 1, -1, -1, -1, -1,
-                -0.757812, 0, 1, 1, 1, -1, 0.992188, -0.757812, -0.992188, 1,
-                1, -1, -0.0078125, 0.976562, 1, 1, 1, -0.992188, -1, -0.9375,
-                0, 1, 1, 1, -1, -1, 0.953125, 0.734375, -1, -0.992188,
-                -1, -1, -1, 0.976562, -0.984375, 0.992188, 0.875, -1, 1, -1,
-                -0.734375, -1, 0.984375, 1, 1, -0.996094, -0.703125, 1, -1, 1,
-                1, 1, 0.960938, 1, -1, 0.992188, -0.0625, 0, -1, 0.785156,
-                1, 1, -1, -1, -1, 1, 1, -1, 0.925781, -1,
-                1, -1, -1, 0.820312, 1, -1, -1, -1, 1, -1,
-                -0.960938, -1, 1, -1, 1, -0.757812, 0.757812, 1, 1, 0.960938,
-                -0.992188, 0.992188, 1, -0.960938, -1, -1, -1, -1, -1, 1,
-                -1, -1, -1, 1, 0.96875, 0.992188, 1, 0.96875, -0.734375, -1,
-                1, -1, 1, -0.914062, 1, -1, -0.486328, -1, 1, 1,
-                1, 1, -0.996094, 1, -1, -1, 1, 0.785156, 1, -1,
-                1, 1, -0.996094, -0.652344, -0.914062, -1, 0.976562, -0.507812, 1, -1,
-                -1, 0.976562, -1, 0.980469, 1, 0.410156, 0.996094, -1, -1, 0.96875,
-                0.914062, -1, 1, -0.984375, 1, 1, -1, 0.757812, 1, 1,
-                1, -1, -0.53125, 1, -1, -0.882812, 0.523438, -1, -0.632812, 1,
-                1, 0, -0.757812, -0.992188, -0.960938, -1, 1, 1, -0.992188, -0.960938,
-                1, -1, 1, 1, 1, -1, -1, -1, 1, -1,
-                -0.992188, -1, 1, -1, 1, -1, 1, -1, 1, 1,
-                0.992188, 1, -1, 1, -0.757812, 1, 1, 0.757812, 1, -1,
-                -0.9375, 1, 1, -1, -0.976562, -1, -0.460938, -1, 1, -0.984375,
-                -1, -0.6875, -1, -1, -0.929688, -0.992188, 1, -1, 0.914062, -1,
-                -1, 1, -1, 0.976562, -1, 1, -1, 1, -0.914062, -1,
-                -0.460938, 1, -0.996094, -1, -0.992188, 1, -1, -1, 0.244141, -1,
-                -0.992188, 0.765625, 1, 0.992188, -1, -1, 0.992188, 1, 1, 0.960938,
-                0.984375, 1, 1, -1, 1, -0.984375, 1, -1, 1, -1,
-                -0.460938, -1, 1, -1, 1, 0.964844, -1, -1, 1, -1,
-                -1, -0.992188, -1, 1, 0, -0.757812, 0.960938, 1, -1, 1},
-            std::vector<T>{
-                -1, 1, -0.953125, 0.992188, -1, -1, 0.96875, -0.185547, -1, -0.757812,
-                -1, 1, 1, 0.863281, 1, 1, -1, -1, 1, -1,
-                -1, 1, -1, -0.785156, -0.992188, -1, -0.300781, -1, 1, -1,
-                1, 0, 1, -1, -1, 0.78125, 1, -1, 1, -1,
-                -1, -1, -1, 0.976562, -0.984375, 0.992188, 0.875, -1, 1, -1,
-                -0.734375, -1, 0.984375, 1, 1, -0.996094, -0.703125, 1, -1, 1,
-                1, 1, -0.996094, -0.652344, -0.914062, -1, 0.976562, -0.507812, 1, -1,
-                -1, 0.976562, -1, 0.980469, 1, 0.410156, 0.996094, -1, -1, 0.96875,
-                -1, 1, -1, 0.976562, -1, 1, -1, 1, -0.914062, -1,
-                -0.460938, 1, -0.996094, -1, -0.992188, 1, -1, -1, 0.244141, -1}),
+                -1,        -0.757812, -0.960938, 1,         1,         0,         0.960938,   0.757812,  -1,
+                -1,        -0.59375,  1,         0.921875,  -1,        -1,        0.244141,   -1,        -1,
+                -0.992188, 1,         -1,        -1,        -1,        -0.953125, 1,          -0.449219, 1,
+                -0.957031, -1,        1,         0.898438,  1,         -1,        1,          -1,        1,
+                0.992188,  1,         -1,        -1,        -1,        1,         -0.953125,  0.992188,  -1,
+                -1,        0.96875,   -0.185547, -1,        -0.757812, -1,        1,          1,         0.863281,
+                1,         1,         -1,        -1,        1,         -1,        -0.757812,  -0.96875,  -0.957031,
+                0.757812,  -0.773438, -0.03125,  1,         -1,        -0.992188, -0.992188,  -1,        1,
+                -1,        -1,        -1,        1,         -0.960938, -1,        -1,         -1,        0.0625,
+                -1,        1,         0.214844,  1,         -1,        1,         -0.832031,  -0.300781, 0.996094,
+                0.757812,  1,         -0.960938, -0.992188, -0.960938, -1,        -0.960938,  -1,        -1,
+                -1,        -0.757812, -1,        1,         -1,        -1,        -1,         1,         -1,
+                -1,        -1,        -1,        1,         -1,        -1,        -1,         1,         1,
+                -1,        -1,        -1,        -1,        0.757812,  -0.992188, 1,          -1,        1,
+                0.960938,  -0.757812, -1,        -1,        1,         -0.652344, -1,         -1,        0.515625,
+                -1,        1,         -0.984375, 0.945312,  -0.835938, -1,        1,          -1,        -0.785156,
+                -0.992188, -1,        -0.300781, -1,        1,         -1,        1,          0,         1,
+                -1,        -1,        0.78125,   1,         -1,        1,         -1,         -1,        1,
+                -1,        -1,        -1,        -1,        1,         -1,        0.949219,   -1,        1,
+                -1,        1,         1,         0.835938,  -0.992188, -1,        -1,         1,         -1,
+                -1,        1,         -1,        -1,        -0.859375, -1,        1,          0.03125,   1,
+                -0.996094, -1,        1,         1,         1,         1,         1,          -0.757812, 0.960938,
+                0.992188,  -1,        -1,        -1,        0,         1,         -1,         1,         -1,
+                -1,        -1,        -1,        -0.757812, 0,         1,         1,          1,         -1,
+                0.992188,  -0.757812, -0.992188, 1,         1,         -1,        -0.0078125, 0.976562,  1,
+                1,         1,         -0.992188, -1,        -0.9375,   0,         1,          1,         1,
+                -1,        -1,        0.953125,  0.734375,  -1,        -0.992188, -1,         -1,        -1,
+                0.976562,  -0.984375, 0.992188,  0.875,     -1,        1,         -1,         -0.734375, -1,
+                0.984375,  1,         1,         -0.996094, -0.703125, 1,         -1,         1,         1,
+                1,         0.960938,  1,         -1,        0.992188,  -0.0625,   0,          -1,        0.785156,
+                1,         1,         -1,        -1,        -1,        1,         1,          -1,        0.925781,
+                -1,        1,         -1,        -1,        0.820312,  1,         -1,         -1,        -1,
+                1,         -1,        -0.960938, -1,        1,         -1,        1,          -0.757812, 0.757812,
+                1,         1,         0.960938,  -0.992188, 0.992188,  1,         -0.960938,  -1,        -1,
+                -1,        -1,        -1,        1,         -1,        -1,        -1,         1,         0.96875,
+                0.992188,  1,         0.96875,   -0.734375, -1,        1,         -1,         1,         -0.914062,
+                1,         -1,        -0.486328, -1,        1,         1,         1,          1,         -0.996094,
+                1,         -1,        -1,        1,         0.785156,  1,         -1,         1,         1,
+                -0.996094, -0.652344, -0.914062, -1,        0.976562,  -0.507812, 1,          -1,        -1,
+                0.976562,  -1,        0.980469,  1,         0.410156,  0.996094,  -1,         -1,        0.96875,
+                0.914062,  -1,        1,         -0.984375, 1,         1,         -1,         0.757812,  1,
+                1,         1,         -1,        -0.53125,  1,         -1,        -0.882812,  0.523438,  -1,
+                -0.632812, 1,         1,         0,         -0.757812, -0.992188, -0.960938,  -1,        1,
+                1,         -0.992188, -0.960938, 1,         -1,        1,         1,          1,         -1,
+                -1,        -1,        1,         -1,        -0.992188, -1,        1,          -1,        1,
+                -1,        1,         -1,        1,         1,         0.992188,  1,          -1,        1,
+                -0.757812, 1,         1,         0.757812,  1,         -1,        -0.9375,    1,         1,
+                -1,        -0.976562, -1,        -0.460938, -1,        1,         -0.984375,  -1,        -0.6875,
+                -1,        -1,        -0.929688, -0.992188, 1,         -1,        0.914062,   -1,        -1,
+                1,         -1,        0.976562,  -1,        1,         -1,        1,          -0.914062, -1,
+                -0.460938, 1,         -0.996094, -1,        -0.992188, 1,         -1,         -1,        0.244141,
+                -1,        -0.992188, 0.765625,  1,         0.992188,  -1,        -1,         0.992188,  1,
+                1,         0.960938,  0.984375,  1,         1,         -1,        1,          -0.984375, 1,
+                -1,        1,         -1,        -0.460938, -1,        1,         -1,         1,         0.964844,
+                -1,        -1,        1,         -1,        -1,        -0.992188, -1,         1,         0,
+                -0.757812, 0.960938,  1,         -1,        1},
+            std::vector<T>{-1,        1,         -0.953125, 0.992188,  -1,        -1,       0.96875,   -0.185547,
+                           -1,        -0.757812, -1,        1,         1,         0.863281, 1,         1,
+                           -1,        -1,        1,         -1,        -1,        1,        -1,        -0.785156,
+                           -0.992188, -1,        -0.300781, -1,        1,         -1,       1,         0,
+                           1,         -1,        -1,        0.78125,   1,         -1,       1,         -1,
+                           -1,        -1,        -1,        0.976562,  -0.984375, 0.992188, 0.875,     -1,
+                           1,         -1,        -0.734375, -1,        0.984375,  1,        1,         -0.996094,
+                           -0.703125, 1,         -1,        1,         1,         1,        -0.996094, -0.652344,
+                           -0.914062, -1,        0.976562,  -0.507812, 1,         -1,       -1,        0.976562,
+                           -1,        0.980469,  1,         0.410156,  0.996094,  -1,       -1,        0.96875,
+                           -1,        1,         -1,        0.976562,  -1,        1,        -1,        1,
+                           -0.914062, -1,        -0.460938, 1,         -0.996094, -1,       -0.992188, 1,
+                           -1,        -1,        0.244141,  -1}),
     };
     return params;
 }
 
 std::vector<RNNSequenceParams> generateCombinedParams() {
-    const std::vector<std::vector<RNNSequenceParams>> generatedParams {
+    const std::vector<std::vector<RNNSequenceParams>> generatedParams{
         generateParams<element::Type_t::f64>(),
         generateParams<element::Type_t::f32>(),
         generateParams<element::Type_t::f16>(),
@@ -1030,7 +1060,9 @@ std::vector<RNNSequenceParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_RNNSequence_With_Hardcoded_Refs, ReferenceRNNSequenceTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceRNNSequenceTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_RNNSequence_With_Hardcoded_Refs,
+                         ReferenceRNNSequenceTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceRNNSequenceTest::getTestCaseName);
 
-} // namespace
\ No newline at end of file
+}  // namespace
\ No newline at end of file
diff --git a/src/plugins/template/tests/functional/op_reference/roi_align.cpp b/src/plugins/template/tests/functional/op_reference/roi_align.cpp
index d27fec9377aa16..ede8f75ace3c04 100644
--- a/src/plugins/template/tests/functional/op_reference/roi_align.cpp
+++ b/src/plugins/template/tests/functional/op_reference/roi_align.cpp
@@ -4,12 +4,12 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset9.hpp"
-#include "openvino/opsets/opset5.hpp"
-#include "openvino/opsets/opset4.hpp"
-#include "openvino/opsets/opset3.hpp"
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
+#include "openvino/opsets/opset3.hpp"
+#include "openvino/opsets/opset4.hpp"
+#include "openvino/opsets/opset5.hpp"
+#include "openvino/opsets/opset9.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -17,11 +17,17 @@ using namespace ov;
 namespace {
 struct ROIAlignParams {
     template <class IT>
-    ROIAlignParams(const PartialShape& pShape, const element::Type& iType, const std::vector<IT>& iValues,
+    ROIAlignParams(const PartialShape& pShape,
+                   const element::Type& iType,
+                   const std::vector<IT>& iValues,
                    const reference_tests::Tensor& expectedFeatureMap,
-                   const reference_tests::Tensor& coords, const reference_tests::Tensor& roiIdx,
-                   const int32_t pooledH, const int32_t pooledW,
-                   const float spatialScale, const int32_t poolingRatio, const std::string& poolingMode,
+                   const reference_tests::Tensor& coords,
+                   const reference_tests::Tensor& roiIdx,
+                   const int32_t pooledH,
+                   const int32_t pooledW,
+                   const float spatialScale,
+                   const int32_t poolingRatio,
+                   const std::string& poolingMode,
                    const std::string& testcaseName)
         : pShape(pShape),
           iType(iType),
@@ -52,12 +58,19 @@ struct ROIAlignParams {
 
 struct ROIAlignV9Params {
     template <class IT>
-    ROIAlignV9Params(const PartialShape& pShape, const element::Type& iType, const std::vector<IT>& iValues,
-                   const reference_tests::Tensor& expectedFeatureMap,
-                   const reference_tests::Tensor& coords, const reference_tests::Tensor& roiIdx,
-                   const int32_t pooledH, const int32_t pooledW,
-                   const float spatialScale, const int32_t poolingRatio, const std::string& poolingMode,
-                   const std::string& alignedMode, const std::string& testcaseName)
+    ROIAlignV9Params(const PartialShape& pShape,
+                     const element::Type& iType,
+                     const std::vector<IT>& iValues,
+                     const reference_tests::Tensor& expectedFeatureMap,
+                     const reference_tests::Tensor& coords,
+                     const reference_tests::Tensor& roiIdx,
+                     const int32_t pooledH,
+                     const int32_t pooledW,
+                     const float spatialScale,
+                     const int32_t poolingRatio,
+                     const std::string& poolingMode,
+                     const std::string& alignedMode,
+                     const std::string& testcaseName)
         : pShape(pShape),
           iType(iType),
           featureMap(CreateTensor(iType, iValues)),
@@ -121,8 +134,10 @@ class ReferenceROIAlignTest : public testing::TestWithParam<ROIAlignParams>, pub
 private:
     static std::shared_ptr<Model> CreateFunction(const ROIAlignParams& params) {
         const auto featureMap = std::make_shared<opset1::Parameter>(params.iType, params.pShape);
-        const auto coords = std::make_shared<opset1::Constant>(params.coords.type, params.coords.shape, params.coords.data.data());
-        const auto roisIdx = std::make_shared<opset1::Constant>(params.roiIdx.type, params.roiIdx.shape, params.roiIdx.data.data());
+        const auto coords =
+            std::make_shared<opset1::Constant>(params.coords.type, params.coords.shape, params.coords.data.data());
+        const auto roisIdx =
+            std::make_shared<opset1::Constant>(params.roiIdx.type, params.roiIdx.shape, params.roiIdx.data.data());
         const auto roi_align = std::make_shared<opset3::ROIAlign>(featureMap,
                                                                   coords,
                                                                   roisIdx,
@@ -171,8 +186,10 @@ class ReferenceROIAlignV9Test : public testing::TestWithParam<ROIAlignV9Params>,
 private:
     static std::shared_ptr<Model> CreateFunction(const ROIAlignV9Params& params) {
         const auto featureMap = std::make_shared<opset1::Parameter>(params.iType, params.pShape);
-        const auto coords = std::make_shared<opset1::Constant>(params.coords.type, params.coords.shape, params.coords.data.data());
-        const auto roisIdx = std::make_shared<opset1::Constant>(params.roiIdx.type, params.roiIdx.shape, params.roiIdx.data.data());
+        const auto coords =
+            std::make_shared<opset1::Constant>(params.coords.type, params.coords.shape, params.coords.data.data());
+        const auto roisIdx =
+            std::make_shared<opset1::Constant>(params.roiIdx.type, params.roiIdx.shape, params.roiIdx.data.data());
         const auto pooling_mode = EnumNames<opset9::ROIAlign::PoolingMode>::as_enum(params.poolingMode);
         const auto aligned_mode = EnumNames<opset9::ROIAlign::AlignedMode>::as_enum(params.alignedMode);
         const auto roi_align = std::make_shared<opset9::ROIAlign>(featureMap,
@@ -201,64 +218,74 @@ template <element::Type_t ET, element::Type_t ET_IND>
 std::vector<ROIAlignParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<ROIAlignParams> params {
-            ROIAlignParams(PartialShape{2, 1, 8, 8}, ET,
-                           std::vector<T>{0,  1, 8, 5, 5,  2, 0,  7,  7,  10, 4,  5, 9,  0, 0,  5,
-                                          7,  0, 4, 0, 4,  7, 6,  10, 9,  5,  1,  7, 4,  7, 10, 8,
-                                          2,  0, 8, 3, 6,  8, 10, 4,  2,  10, 7,  8, 7,  0, 6,  9,
-                                          2,  4, 8, 5, 2,  3, 3,  1,  5,  9,  10, 0, 9,  5, 5,  3,
-                                          10, 5, 2, 0, 10, 0, 5,  4,  3,  10, 5,  5, 10, 0, 8,  8,
-                                          9,  1, 0, 7, 9,  6, 8,  7,  10, 9,  2,  3, 3,  5, 6,  9,
-                                          4,  9, 2, 4, 5,  5, 3,  1,  1,  6,  8,  0, 5,  5, 10, 8,
-                                          6,  9, 6, 9, 1,  2, 7,  1,  1,  3,  0,  4, 0,  7, 10, 2},
-                           reference_tests::Tensor(ET, {2, 1, 2, 2}, std::vector<T>{3, 3.75, 4.75, 5, 3, 5.5, 2.75, 3.75}),
-                           reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
-                           reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
-                           2, 2, 1, 2, "avg", "roi_align_avg"),
+    std::vector<ROIAlignParams> params{
+        ROIAlignParams(
+            PartialShape{2, 1, 8, 8},
+            ET,
+            std::vector<T>{0, 1, 8, 5, 5,  2, 0,  7, 7, 10, 4,  5, 9,  0, 0, 5,  7,  0, 4, 0, 4, 7,  6,  10, 9,  5,
+                           1, 7, 4, 7, 10, 8, 2,  0, 8, 3,  6,  8, 10, 4, 2, 10, 7,  8, 7, 0, 6, 9,  2,  4,  8,  5,
+                           2, 3, 3, 1, 5,  9, 10, 0, 9, 5,  5,  3, 10, 5, 2, 0,  10, 0, 5, 4, 3, 10, 5,  5,  10, 0,
+                           8, 8, 9, 1, 0,  7, 9,  6, 8, 7,  10, 9, 2,  3, 3, 5,  6,  9, 4, 9, 2, 4,  5,  5,  3,  1,
+                           1, 6, 8, 0, 5,  5, 10, 8, 6, 9,  6,  9, 1,  2, 7, 1,  1,  3, 0, 4, 0, 7,  10, 2},
+            reference_tests::Tensor(ET, {2, 1, 2, 2}, std::vector<T>{3, 3.75, 4.75, 5, 3, 5.5, 2.75, 3.75}),
+            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
+            2,
+            2,
+            1,
+            2,
+            "avg",
+            "roi_align_avg"),
 
-            ROIAlignParams(PartialShape{2, 1, 8, 8}, ET,
-                           std::vector<T>{0,  1, 8, 5, 5,  2, 0,  7,  7,  10, 4,  5, 9,  0, 0,  5,
-                                          7,  0, 4, 0, 4,  7, 6,  10, 9,  5,  1,  7, 4,  7, 10, 8,
-                                          2,  0, 8, 3, 6,  8, 10, 4,  2,  10, 7,  8, 7,  0, 6,  9,
-                                          2,  4, 8, 5, 2,  3, 3,  1,  5,  9,  10, 0, 9,  5, 5,  3,
-                                          10, 5, 2, 0, 10, 0, 5,  4,  3,  10, 5,  5, 10, 0, 8,  8,
-                                          9,  1, 0, 7, 9,  6, 8,  7,  10, 9,  2,  3, 3,  5, 6,  9,
-                                          4,  9, 2, 4, 5,  5, 3,  1,  1,  6,  8,  0, 5,  5, 10, 8,
-                                          6,  9, 6, 9, 1,  2, 7,  1,  1,  3,  0,  4, 0,  7, 10, 2},
-                           reference_tests::Tensor(ET, {2, 1, 2, 2}, std::vector<T>{4.375, 4.9375, 5.6875, 5.625, 4.625, 7.125, 3.3125, 4.3125}),
-                           reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
-                           reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
-                           2, 2, 1, 2, "max", "roi_align_max"),
+        ROIAlignParams(
+            PartialShape{2, 1, 8, 8},
+            ET,
+            std::vector<T>{0, 1, 8, 5, 5,  2, 0,  7, 7, 10, 4,  5, 9,  0, 0, 5,  7,  0, 4, 0, 4, 7,  6,  10, 9,  5,
+                           1, 7, 4, 7, 10, 8, 2,  0, 8, 3,  6,  8, 10, 4, 2, 10, 7,  8, 7, 0, 6, 9,  2,  4,  8,  5,
+                           2, 3, 3, 1, 5,  9, 10, 0, 9, 5,  5,  3, 10, 5, 2, 0,  10, 0, 5, 4, 3, 10, 5,  5,  10, 0,
+                           8, 8, 9, 1, 0,  7, 9,  6, 8, 7,  10, 9, 2,  3, 3, 5,  6,  9, 4, 9, 2, 4,  5,  5,  3,  1,
+                           1, 6, 8, 0, 5,  5, 10, 8, 6, 9,  6,  9, 1,  2, 7, 1,  1,  3, 0, 4, 0, 7,  10, 2},
+            reference_tests::Tensor(ET,
+                                    {2, 1, 2, 2},
+                                    std::vector<T>{4.375, 4.9375, 5.6875, 5.625, 4.625, 7.125, 3.3125, 4.3125}),
+            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
+            2,
+            2,
+            1,
+            2,
+            "max",
+            "roi_align_max"),
     };
     return params;
 }
 
 std::vector<ROIAlignParams> generateCombinedParams() {
-    const std::vector<std::vector<ROIAlignParams>> generatedParams {
-            generateParams<element::Type_t::bf16, element::Type_t::i8>(),
-            generateParams<element::Type_t::f16, element::Type_t::i8>(),
-            generateParams<element::Type_t::f32, element::Type_t::i8>(),
-            generateParams<element::Type_t::bf16, element::Type_t::i16>(),
-            generateParams<element::Type_t::f16, element::Type_t::i16>(),
-            generateParams<element::Type_t::f32, element::Type_t::i16>(),
-            generateParams<element::Type_t::bf16, element::Type_t::i32>(),
-            generateParams<element::Type_t::f16, element::Type_t::i32>(),
-            generateParams<element::Type_t::f32, element::Type_t::i32>(),
-            generateParams<element::Type_t::bf16, element::Type_t::i64>(),
-            generateParams<element::Type_t::f16, element::Type_t::i64>(),
-            generateParams<element::Type_t::f32, element::Type_t::i64>(),
-            generateParams<element::Type_t::bf16, element::Type_t::u8>(),
-            generateParams<element::Type_t::f16, element::Type_t::u8>(),
-            generateParams<element::Type_t::f32, element::Type_t::u8>(),
-            generateParams<element::Type_t::bf16, element::Type_t::u16>(),
-            generateParams<element::Type_t::f16, element::Type_t::u16>(),
-            generateParams<element::Type_t::f32, element::Type_t::u16>(),
-            generateParams<element::Type_t::bf16, element::Type_t::u32>(),
-            generateParams<element::Type_t::f16, element::Type_t::u32>(),
-            generateParams<element::Type_t::f32, element::Type_t::u32>(),
-            generateParams<element::Type_t::bf16, element::Type_t::u64>(),
-            generateParams<element::Type_t::f16, element::Type_t::u64>(),
-            generateParams<element::Type_t::f32, element::Type_t::u64>(),
+    const std::vector<std::vector<ROIAlignParams>> generatedParams{
+        generateParams<element::Type_t::bf16, element::Type_t::i8>(),
+        generateParams<element::Type_t::f16, element::Type_t::i8>(),
+        generateParams<element::Type_t::f32, element::Type_t::i8>(),
+        generateParams<element::Type_t::bf16, element::Type_t::i16>(),
+        generateParams<element::Type_t::f16, element::Type_t::i16>(),
+        generateParams<element::Type_t::f32, element::Type_t::i16>(),
+        generateParams<element::Type_t::bf16, element::Type_t::i32>(),
+        generateParams<element::Type_t::f16, element::Type_t::i32>(),
+        generateParams<element::Type_t::f32, element::Type_t::i32>(),
+        generateParams<element::Type_t::bf16, element::Type_t::i64>(),
+        generateParams<element::Type_t::f16, element::Type_t::i64>(),
+        generateParams<element::Type_t::f32, element::Type_t::i64>(),
+        generateParams<element::Type_t::bf16, element::Type_t::u8>(),
+        generateParams<element::Type_t::f16, element::Type_t::u8>(),
+        generateParams<element::Type_t::f32, element::Type_t::u8>(),
+        generateParams<element::Type_t::bf16, element::Type_t::u16>(),
+        generateParams<element::Type_t::f16, element::Type_t::u16>(),
+        generateParams<element::Type_t::f32, element::Type_t::u16>(),
+        generateParams<element::Type_t::bf16, element::Type_t::u32>(),
+        generateParams<element::Type_t::f16, element::Type_t::u32>(),
+        generateParams<element::Type_t::f32, element::Type_t::u32>(),
+        generateParams<element::Type_t::bf16, element::Type_t::u64>(),
+        generateParams<element::Type_t::f16, element::Type_t::u64>(),
+        generateParams<element::Type_t::f32, element::Type_t::u64>(),
     };
     std::vector<ROIAlignParams> combinedParams;
 
@@ -272,78 +299,95 @@ template <element::Type_t ET, element::Type_t ET_IND>
 std::vector<ROIAlignV9Params> generateParamsV9() {
     using T = typename element_type_traits<ET>::value_type;
     using T_IND = typename element_type_traits<ET_IND>::value_type;
-    std::vector<ROIAlignV9Params> params {
-            ROIAlignV9Params(PartialShape{2, 1, 8, 8}, ET,
-                           std::vector<T>{0,  1, 8, 5, 5,  2, 0,  7,  7,  10, 4,  5, 9,  0, 0,  5,
-                                          7,  0, 4, 0, 4,  7, 6,  10, 9,  5,  1,  7, 4,  7, 10, 8,
-                                          2,  0, 8, 3, 6,  8, 10, 4,  2,  10, 7,  8, 7,  0, 6,  9,
-                                          2,  4, 8, 5, 2,  3, 3,  1,  5,  9,  10, 0, 9,  5, 5,  3,
-                                          10, 5, 2, 0, 10, 0, 5,  4,  3,  10, 5,  5, 10, 0, 8,  8,
-                                          9,  1, 0, 7, 9,  6, 8,  7,  10, 9,  2,  3, 3,  5, 6,  9,
-                                          4,  9, 2, 4, 5,  5, 3,  1,  1,  6,  8,  0, 5,  5, 10, 8,
-                                          6,  9, 6, 9, 1,  2, 7,  1,  1,  3,  0,  4, 0,  7, 10, 2},
-                           reference_tests::Tensor(ET, {2, 1, 2, 2}, std::vector<T>{3, 3.75, 4.75, 5, 3, 5.5, 2.75, 3.75}),
-                           reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
-                           reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
-                           2, 2, 1, 2, "avg", "asymmetric", "roi_align_v9_avg_asymmetric"),
+    std::vector<ROIAlignV9Params> params{
+        ROIAlignV9Params(
+            PartialShape{2, 1, 8, 8},
+            ET,
+            std::vector<T>{0, 1, 8, 5, 5,  2, 0,  7, 7, 10, 4,  5, 9,  0, 0, 5,  7,  0, 4, 0, 4, 7,  6,  10, 9,  5,
+                           1, 7, 4, 7, 10, 8, 2,  0, 8, 3,  6,  8, 10, 4, 2, 10, 7,  8, 7, 0, 6, 9,  2,  4,  8,  5,
+                           2, 3, 3, 1, 5,  9, 10, 0, 9, 5,  5,  3, 10, 5, 2, 0,  10, 0, 5, 4, 3, 10, 5,  5,  10, 0,
+                           8, 8, 9, 1, 0,  7, 9,  6, 8, 7,  10, 9, 2,  3, 3, 5,  6,  9, 4, 9, 2, 4,  5,  5,  3,  1,
+                           1, 6, 8, 0, 5,  5, 10, 8, 6, 9,  6,  9, 1,  2, 7, 1,  1,  3, 0, 4, 0, 7,  10, 2},
+            reference_tests::Tensor(ET, {2, 1, 2, 2}, std::vector<T>{3, 3.75, 4.75, 5, 3, 5.5, 2.75, 3.75}),
+            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
+            2,
+            2,
+            1,
+            2,
+            "avg",
+            "asymmetric",
+            "roi_align_v9_avg_asymmetric"),
 
-            ROIAlignV9Params(PartialShape{2, 1, 8, 8}, ET,
-                           std::vector<T>{0,  1, 8, 5, 5,  2, 0,  7,  7,  10, 4,  5, 9,  0, 0,  5,
-                                          7,  0, 4, 0, 4,  7, 6,  10, 9,  5,  1,  7, 4,  7, 10, 8,
-                                          2,  0, 8, 3, 6,  8, 10, 4,  2,  10, 7,  8, 7,  0, 6,  9,
-                                          2,  4, 8, 5, 2,  3, 3,  1,  5,  9,  10, 0, 9,  5, 5,  3,
-                                          10, 5, 2, 0, 10, 0, 5,  4,  3,  10, 5,  5, 10, 0, 8,  8,
-                                          9,  1, 0, 7, 9,  6, 8,  7,  10, 9,  2,  3, 3,  5, 6,  9,
-                                          4,  9, 2, 4, 5,  5, 3,  1,  1,  6,  8,  0, 5,  5, 10, 8,
-                                          6,  9, 6, 9, 1,  2, 7,  1,  1,  3,  0,  4, 0,  7, 10, 2},
-                           reference_tests::Tensor(ET, {2, 1, 2, 2}, std::vector<T>{3.14, 2.16, 2.86, 5.03, 1.83, 5.84, 2.77, 3.44}),
-                           reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
-                           reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
-                           2, 2, 1, 2, "avg", "half_pixel_for_nn", "roi_align_v9_avg_half_pixel_for_nn"),
+        ROIAlignV9Params(
+            PartialShape{2, 1, 8, 8},
+            ET,
+            std::vector<T>{0, 1, 8, 5, 5,  2, 0,  7, 7, 10, 4,  5, 9,  0, 0, 5,  7,  0, 4, 0, 4, 7,  6,  10, 9,  5,
+                           1, 7, 4, 7, 10, 8, 2,  0, 8, 3,  6,  8, 10, 4, 2, 10, 7,  8, 7, 0, 6, 9,  2,  4,  8,  5,
+                           2, 3, 3, 1, 5,  9, 10, 0, 9, 5,  5,  3, 10, 5, 2, 0,  10, 0, 5, 4, 3, 10, 5,  5,  10, 0,
+                           8, 8, 9, 1, 0,  7, 9,  6, 8, 7,  10, 9, 2,  3, 3, 5,  6,  9, 4, 9, 2, 4,  5,  5,  3,  1,
+                           1, 6, 8, 0, 5,  5, 10, 8, 6, 9,  6,  9, 1,  2, 7, 1,  1,  3, 0, 4, 0, 7,  10, 2},
+            reference_tests::Tensor(ET, {2, 1, 2, 2}, std::vector<T>{3.14, 2.16, 2.86, 5.03, 1.83, 5.84, 2.77, 3.44}),
+            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
+            2,
+            2,
+            1,
+            2,
+            "avg",
+            "half_pixel_for_nn",
+            "roi_align_v9_avg_half_pixel_for_nn"),
 
-            ROIAlignV9Params(PartialShape{2, 1, 8, 8}, ET,
-                           std::vector<T>{0,  1, 8, 5, 5,  2, 0,  7,  7,  10, 4,  5, 9,  0, 0,  5,
-                                          7,  0, 4, 0, 4,  7, 6,  10, 9,  5,  1,  7, 4,  7, 10, 8,
-                                          2,  0, 8, 3, 6,  8, 10, 4,  2,  10, 7,  8, 7,  0, 6,  9,
-                                          2,  4, 8, 5, 2,  3, 3,  1,  5,  9,  10, 0, 9,  5, 5,  3,
-                                          10, 5, 2, 0, 10, 0, 5,  4,  3,  10, 5,  5, 10, 0, 8,  8,
-                                          9,  1, 0, 7, 9,  6, 8,  7,  10, 9,  2,  3, 3,  5, 6,  9,
-                                          4,  9, 2, 4, 5,  5, 3,  1,  1,  6,  8,  0, 5,  5, 10, 8,
-                                          6,  9, 6, 9, 1,  2, 7,  1,  1,  3,  0,  4, 0,  7, 10, 2},
-                           reference_tests::Tensor(ET, {2, 1, 2, 2}, std::vector<T>{4.375, 4.9375, 5.6875, 5.625, 4.625, 7.125, 3.3125, 4.3125}),
-                           reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
-                           reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
-                           2, 2, 1, 2, "max", "half_pixel", "roi_align_v9_max_half_pixel"),
+        ROIAlignV9Params(
+            PartialShape{2, 1, 8, 8},
+            ET,
+            std::vector<T>{0, 1, 8, 5, 5,  2, 0,  7, 7, 10, 4,  5, 9,  0, 0, 5,  7,  0, 4, 0, 4, 7,  6,  10, 9,  5,
+                           1, 7, 4, 7, 10, 8, 2,  0, 8, 3,  6,  8, 10, 4, 2, 10, 7,  8, 7, 0, 6, 9,  2,  4,  8,  5,
+                           2, 3, 3, 1, 5,  9, 10, 0, 9, 5,  5,  3, 10, 5, 2, 0,  10, 0, 5, 4, 3, 10, 5,  5,  10, 0,
+                           8, 8, 9, 1, 0,  7, 9,  6, 8, 7,  10, 9, 2,  3, 3, 5,  6,  9, 4, 9, 2, 4,  5,  5,  3,  1,
+                           1, 6, 8, 0, 5,  5, 10, 8, 6, 9,  6,  9, 1,  2, 7, 1,  1,  3, 0, 4, 0, 7,  10, 2},
+            reference_tests::Tensor(ET,
+                                    {2, 1, 2, 2},
+                                    std::vector<T>{4.375, 4.9375, 5.6875, 5.625, 4.625, 7.125, 3.3125, 4.3125}),
+            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{2, 2, 4, 4, 2, 2, 4, 4}),
+            reference_tests::Tensor(ET_IND, {2}, std::vector<T_IND>{0, 1}),
+            2,
+            2,
+            1,
+            2,
+            "max",
+            "half_pixel",
+            "roi_align_v9_max_half_pixel"),
     };
     return params;
 }
 
 std::vector<ROIAlignV9Params> generateCombinedParamsV9() {
-   const std::vector<std::vector<ROIAlignV9Params>> generatedParams {
-            generateParamsV9<element::Type_t::bf16, element::Type_t::i8>(),
-            generateParamsV9<element::Type_t::f16, element::Type_t::i8>(),
-            generateParamsV9<element::Type_t::f32, element::Type_t::i8>(),
-            generateParamsV9<element::Type_t::bf16, element::Type_t::i16>(),
-            generateParamsV9<element::Type_t::f16, element::Type_t::i16>(),
-            generateParamsV9<element::Type_t::f32, element::Type_t::i16>(),
-            generateParamsV9<element::Type_t::bf16, element::Type_t::i32>(),
-            generateParamsV9<element::Type_t::f16, element::Type_t::i32>(),
-            generateParamsV9<element::Type_t::f32, element::Type_t::i32>(),
-            generateParamsV9<element::Type_t::bf16, element::Type_t::i64>(),
-            generateParamsV9<element::Type_t::f16, element::Type_t::i64>(),
-            generateParamsV9<element::Type_t::f32, element::Type_t::i64>(),
-            generateParamsV9<element::Type_t::bf16, element::Type_t::u8>(),
-            generateParamsV9<element::Type_t::f16, element::Type_t::u8>(),
-            generateParamsV9<element::Type_t::f32, element::Type_t::u8>(),
-            generateParamsV9<element::Type_t::bf16, element::Type_t::u16>(),
-            generateParamsV9<element::Type_t::f16, element::Type_t::u16>(),
-            generateParamsV9<element::Type_t::f32, element::Type_t::u16>(),
-            generateParamsV9<element::Type_t::bf16, element::Type_t::u32>(),
-            generateParamsV9<element::Type_t::f16, element::Type_t::u32>(),
-            generateParamsV9<element::Type_t::f32, element::Type_t::u32>(),
-            generateParamsV9<element::Type_t::bf16, element::Type_t::u64>(),
-            generateParamsV9<element::Type_t::f16, element::Type_t::u64>(),
-            generateParamsV9<element::Type_t::f32, element::Type_t::u64>(),
+    const std::vector<std::vector<ROIAlignV9Params>> generatedParams{
+        generateParamsV9<element::Type_t::bf16, element::Type_t::i8>(),
+        generateParamsV9<element::Type_t::f16, element::Type_t::i8>(),
+        generateParamsV9<element::Type_t::f32, element::Type_t::i8>(),
+        generateParamsV9<element::Type_t::bf16, element::Type_t::i16>(),
+        generateParamsV9<element::Type_t::f16, element::Type_t::i16>(),
+        generateParamsV9<element::Type_t::f32, element::Type_t::i16>(),
+        generateParamsV9<element::Type_t::bf16, element::Type_t::i32>(),
+        generateParamsV9<element::Type_t::f16, element::Type_t::i32>(),
+        generateParamsV9<element::Type_t::f32, element::Type_t::i32>(),
+        generateParamsV9<element::Type_t::bf16, element::Type_t::i64>(),
+        generateParamsV9<element::Type_t::f16, element::Type_t::i64>(),
+        generateParamsV9<element::Type_t::f32, element::Type_t::i64>(),
+        generateParamsV9<element::Type_t::bf16, element::Type_t::u8>(),
+        generateParamsV9<element::Type_t::f16, element::Type_t::u8>(),
+        generateParamsV9<element::Type_t::f32, element::Type_t::u8>(),
+        generateParamsV9<element::Type_t::bf16, element::Type_t::u16>(),
+        generateParamsV9<element::Type_t::f16, element::Type_t::u16>(),
+        generateParamsV9<element::Type_t::f32, element::Type_t::u16>(),
+        generateParamsV9<element::Type_t::bf16, element::Type_t::u32>(),
+        generateParamsV9<element::Type_t::f16, element::Type_t::u32>(),
+        generateParamsV9<element::Type_t::f32, element::Type_t::u32>(),
+        generateParamsV9<element::Type_t::bf16, element::Type_t::u64>(),
+        generateParamsV9<element::Type_t::f16, element::Type_t::u64>(),
+        generateParamsV9<element::Type_t::f32, element::Type_t::u64>(),
     };
     std::vector<ROIAlignV9Params> combinedParams;
 
@@ -353,9 +397,13 @@ std::vector<ROIAlignV9Params> generateCombinedParamsV9() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ROIAlign_With_Hardcoded_Refs, ReferenceROIAlignTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceROIAlignTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_ROIAlign_With_Hardcoded_Refs,
+                         ReferenceROIAlignTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceROIAlignTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_ROIAlignV9_With_Hardcoded_Refs, ReferenceROIAlignV9Test,
-    testing::ValuesIn(generateCombinedParamsV9()), ReferenceROIAlignV9Test::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_ROIAlignV9_With_Hardcoded_Refs,
+                         ReferenceROIAlignV9Test,
+                         testing::ValuesIn(generateCombinedParamsV9()),
+                         ReferenceROIAlignV9Test::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/roi_pooling.cpp b/src/plugins/template/tests/functional/op_reference/roi_pooling.cpp
index de1f4c1b81d1be..cce7a1dd4eca8c 100644
--- a/src/plugins/template/tests/functional/op_reference/roi_pooling.cpp
+++ b/src/plugins/template/tests/functional/op_reference/roi_pooling.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/roi_pooling.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/roi_pooling.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -12,13 +13,30 @@ using namespace reference_tests;
 
 struct ROIPoolingParams {
     template <class T>
-    ROIPoolingParams(const size_t iH, const size_t iW, const size_t ch, const size_t rois,
-                     const size_t oH, const size_t oW, const float sS, const std::string mode,
-                     const ov::element::Type& type, const std::vector<T>& inputValues,
-                     const std::vector<T>& proposalValues, const std::vector<T>& outputValues)
-            : inputH(iH), inputW(iW), channelCount(ch), roiCount(rois), outputH(oH), outputW(oW), spatialScale(sS),
-              poolingMode(mode), dataType(type), featureMap(CreateTensor(type, inputValues)),
-              proposal(CreateTensor(type, proposalValues)), refData(CreateTensor(type, outputValues)) {}
+    ROIPoolingParams(const size_t iH,
+                     const size_t iW,
+                     const size_t ch,
+                     const size_t rois,
+                     const size_t oH,
+                     const size_t oW,
+                     const float sS,
+                     const std::string mode,
+                     const ov::element::Type& type,
+                     const std::vector<T>& inputValues,
+                     const std::vector<T>& proposalValues,
+                     const std::vector<T>& outputValues)
+        : inputH(iH),
+          inputW(iW),
+          channelCount(ch),
+          roiCount(rois),
+          outputH(oH),
+          outputW(oW),
+          spatialScale(sS),
+          poolingMode(mode),
+          dataType(type),
+          featureMap(CreateTensor(type, inputValues)),
+          proposal(CreateTensor(type, proposalValues)),
+          refData(CreateTensor(type, outputValues)) {}
     size_t inputH;
     size_t inputW;
     size_t channelCount;
@@ -33,7 +51,7 @@ struct ROIPoolingParams {
     ov::Tensor refData;
 
 public:
-    template<class T>
+    template <class T>
     inline static std::vector<T> increasinglyFilledBlob(size_t size) {
         std::vector<T> inputValues;
         T one = 1;
@@ -42,7 +60,7 @@ struct ROIPoolingParams {
         }
         return inputValues;
     }
-    template<class T>
+    template <class T>
     inline static std::vector<T> equallyFilledBlob(size_t size, T value) {
         std::vector<T> inputValues;
         for (size_t i = 0; i < size; i++) {
@@ -56,8 +74,15 @@ class ReferenceRoiPoolingLayerTest : public testing::TestWithParam<ROIPoolingPar
 public:
     void SetUp() override {
         auto params = GetParam();
-        function = CreateFunction(params.inputH, params.inputW, params.channelCount, params.roiCount,
-                                  params.outputH, params.outputW, params.spatialScale, params.poolingMode, params.dataType);
+        function = CreateFunction(params.inputH,
+                                  params.inputW,
+                                  params.channelCount,
+                                  params.roiCount,
+                                  params.outputH,
+                                  params.outputW,
+                                  params.spatialScale,
+                                  params.poolingMode,
+                                  params.dataType);
         inputData = {params.featureMap, params.proposal};
         refOutData = {params.refData};
     }
@@ -76,9 +101,15 @@ class ReferenceRoiPoolingLayerTest : public testing::TestWithParam<ROIPoolingPar
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const size_t i_h, const size_t i_w, const size_t ch, const size_t roi_count,
-                                                    const size_t o_h, const size_t o_w, const float spat_scale, const std::string mode,
-                                                    const ov::element::Type& type) {
+    static std::shared_ptr<Model> CreateFunction(const size_t i_h,
+                                                 const size_t i_w,
+                                                 const size_t ch,
+                                                 const size_t roi_count,
+                                                 const size_t o_h,
+                                                 const size_t o_w,
+                                                 const float spat_scale,
+                                                 const std::string mode,
+                                                 const ov::element::Type& type) {
         Shape feat_map_shape{1, ch, i_h, i_w};
         Shape rois_shape{roi_count, 5};
         Shape pooled_shape{o_h, o_w};
@@ -96,126 +127,209 @@ TEST_P(ReferenceRoiPoolingLayerTest, CompareWithHardcodedRefs) {
 }
 
 INSTANTIATE_TEST_SUITE_P(
-        smoke_ROIPooling_With_Hardcoded_Refs, ReferenceRoiPoolingLayerTest,
-        ::testing::Values(
-                // fp32
-                // roi_pooling_1x1_max
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 3, 3,              // channels, rois
-                                 1, 1,              // oH, oW
-                                 1.f, "max",        // scale, mode
-                                 element::f32, ROIPoolingParams::increasinglyFilledBlob<float>(3 * 6 * 6),
-                                 std::vector<float> {0, 1, 1, 2, 3, 0, 1, 1, 2, 3, 0, 1, 1, 2, 3},
-                                 std::vector<float> {2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f}),
-                // roi_pooling_2x2_max
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 1, 3,              // channels, rois
-                                 2, 2,              // oH, oW
-                                 1.f, "max",        // scale, mode
-                                 element::f32, ROIPoolingParams::increasinglyFilledBlob<float>(1 * 6 * 6),
-                                 std::vector<float> {0, 1, 1, 3, 3, 0, 1, 2, 2, 4, 0, 0, 1, 4, 5},
-                                 std::vector<float> {1.4f, 1.5f, 2.0f, 2.1f, 1.9f, 2.0f, 2.5f, 2.6f, 2.0f, 2.2f, 3.2f, 3.4f}),
-                // roi_pooling_1x1_bilinear
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 3, 2,              // channels, rois
-                                 1, 1,              // oH, oW
-                                 1.f, "bilinear",   // scale, mode
-                                 element::f32, ROIPoolingParams::increasinglyFilledBlob<float>(3 * 6 * 6),
-                                 std::vector<float> {0, 0.2, 0.2, 0.4, 0.4, 0, 0.2, 0.2, 0.6, 0.6},
-                                 std::vector<float> {1.05f, 4.65f, 8.25f, 1.4f, 5.0f, 8.6f}),
-                // roi_pooling_2x2_bilinear
-                ROIPoolingParams(8, 8,              // iH, iW
-                                 1, 3,              // channels, rois
-                                 2, 2,              // oH, oW
-                                 1.f, "bilinear",   // scale, mode
-                                 element::f32, ROIPoolingParams::increasinglyFilledBlob<float>(1 * 8 * 8),
-                                 std::vector<float> {0.f, 0.15f, 0.2f, 0.75f, 0.8f,
-                                                     0.f, 0.15f, 0.2f, 0.75f, 0.8f,
-                                                     0.f, 0.15f, 0.2f, 0.75f, 0.8f},
-                                 std::vector<float> {1.225f, 1.645f, 4.585f, 5.005f,
-                                                     1.225f, 1.645f, 4.585f, 5.005f,
-                                                     1.225f, 1.645f, 4.585f, 5.005f}),
-                // roi_pooling_2x2_bilinear_border_proposal
-                ROIPoolingParams(50, 50,            // iH, iW
-                                 1, 1,              // channels, rois
-                                 4, 4,              // oH, oW
-                                 1.f, "bilinear",   // scale, mode
-                                 element::f32, ROIPoolingParams::equallyFilledBlob<float>(1 * 50 * 50, 1),
-                                 std::vector<float> {0.f, 0.f, 0.248046786f, 0.471333951f, 1.f},
-                                 std::vector<float>(16, 1.f)),
+    smoke_ROIPooling_With_Hardcoded_Refs,
+    ReferenceRoiPoolingLayerTest,
+    ::testing::Values(
+        // fp32
+        // roi_pooling_1x1_max
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         3,
+                         3,  // channels, rois
+                         1,
+                         1,  // oH, oW
+                         1.f,
+                         "max",  // scale, mode
+                         element::f32,
+                         ROIPoolingParams::increasinglyFilledBlob<float>(3 * 6 * 6),
+                         std::vector<float>{0, 1, 1, 2, 3, 0, 1, 1, 2, 3, 0, 1, 1, 2, 3},
+                         std::vector<float>{2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f}),
+        // roi_pooling_2x2_max
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         1,
+                         3,  // channels, rois
+                         2,
+                         2,  // oH, oW
+                         1.f,
+                         "max",  // scale, mode
+                         element::f32,
+                         ROIPoolingParams::increasinglyFilledBlob<float>(1 * 6 * 6),
+                         std::vector<float>{0, 1, 1, 3, 3, 0, 1, 2, 2, 4, 0, 0, 1, 4, 5},
+                         std::vector<float>{1.4f, 1.5f, 2.0f, 2.1f, 1.9f, 2.0f, 2.5f, 2.6f, 2.0f, 2.2f, 3.2f, 3.4f}),
+        // roi_pooling_1x1_bilinear
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         3,
+                         2,  // channels, rois
+                         1,
+                         1,  // oH, oW
+                         1.f,
+                         "bilinear",  // scale, mode
+                         element::f32,
+                         ROIPoolingParams::increasinglyFilledBlob<float>(3 * 6 * 6),
+                         std::vector<float>{0, 0.2, 0.2, 0.4, 0.4, 0, 0.2, 0.2, 0.6, 0.6},
+                         std::vector<float>{1.05f, 4.65f, 8.25f, 1.4f, 5.0f, 8.6f}),
+        // roi_pooling_2x2_bilinear
+        ROIPoolingParams(
+            8,
+            8,  // iH, iW
+            1,
+            3,  // channels, rois
+            2,
+            2,  // oH, oW
+            1.f,
+            "bilinear",  // scale, mode
+            element::f32,
+            ROIPoolingParams::increasinglyFilledBlob<float>(1 * 8 * 8),
+            std::vector<
+                float>{0.f, 0.15f, 0.2f, 0.75f, 0.8f, 0.f, 0.15f, 0.2f, 0.75f, 0.8f, 0.f, 0.15f, 0.2f, 0.75f, 0.8f},
+            std::vector<
+                float>{1.225f, 1.645f, 4.585f, 5.005f, 1.225f, 1.645f, 4.585f, 5.005f, 1.225f, 1.645f, 4.585f, 5.005f}),
+        // roi_pooling_2x2_bilinear_border_proposal
+        ROIPoolingParams(50,
+                         50,  // iH, iW
+                         1,
+                         1,  // channels, rois
+                         4,
+                         4,  // oH, oW
+                         1.f,
+                         "bilinear",  // scale, mode
+                         element::f32,
+                         ROIPoolingParams::equallyFilledBlob<float>(1 * 50 * 50, 1),
+                         std::vector<float>{0.f, 0.f, 0.248046786f, 0.471333951f, 1.f},
+                         std::vector<float>(16, 1.f)),
 
-                // bf16
-                // roi_pooling_1x1_max
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 3, 3,              // channels, rois
-                                 1, 1,              // oH, oW
-                                 1.f, "max",        // scale, mode
-                                 element::bf16, ROIPoolingParams::increasinglyFilledBlob<bfloat16>(3 * 6 * 6),
-                                 std::vector<bfloat16> {0, 1, 1, 2, 3, 0, 1, 1, 2, 3, 0, 1, 1, 2, 3},
-                                 std::vector<bfloat16> {2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f}),
-                // roi_pooling_2x2_max
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 1, 3,              // channels, rois
-                                 2, 2,              // oH, oW
-                                 1.f, "max",        // scale, mode
-                                 element::bf16, ROIPoolingParams::increasinglyFilledBlob<bfloat16>(1 * 6 * 6),
-                                 std::vector<bfloat16> {0, 1, 1, 3, 3, 0, 1, 2, 2, 4, 0, 0, 1, 4, 5},
-                                 std::vector<bfloat16> {1.4f, 1.5f, 2.0f, 2.1f, 1.9f, 2.0f, 2.5f, 2.6f, 2.0f, 2.2f, 3.2f, 3.4f}),
-                // roi_pooling_1x1_bilinear
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 3, 2,              // channels, rois
-                                 1, 1,              // oH, oW
-                                 1.f, "bilinear",   // scale, mode
-                                 element::bf16, ROIPoolingParams::increasinglyFilledBlob<bfloat16>(3 * 6 * 6),
-                                 std::vector<bfloat16> {0, 0.2, 0.2, 0.4, 0.4, 0, 0.2, 0.2, 0.6, 0.6},
-                                 std::vector<bfloat16> {1.05f, 4.65f, 8.25f, 1.4f, 5.0f, 8.6f}),
-                // roi_pooling_2x2_bilinear
-                ROIPoolingParams(8, 8,              // iH, iW
-                                 1, 3,              // channels, rois
-                                 2, 2,              // oH, oW
-                                 1.f, "bilinear",   // scale, mode
-                                 element::bf16, ROIPoolingParams::increasinglyFilledBlob<bfloat16>(1 * 8 * 8),
-                                 std::vector<bfloat16> {0.f, 0.15f, 0.2f, 0.75f, 0.8f,
-                                                     0.f, 0.15f, 0.2f, 0.75f, 0.8f,
-                                                     0.f, 0.15f, 0.2f, 0.75f, 0.8f},
-                                 std::vector<bfloat16> {1.225f, 1.645f, 4.585f, 4.937f,
-                                                     1.225f, 1.645f, 4.585f, 4.937f,
-                                                     1.225f, 1.645f, 4.585f, 4.937f}),
-                // fp16
-                // roi_pooling_1x1_max
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 3, 3,              // channels, rois
-                                 1, 1,              // oH, oW
-                                 1.f, "max",        // scale, mode
-                                 element::f16, ROIPoolingParams::increasinglyFilledBlob<float16>(3 * 6 * 6),
-                                 std::vector<float16> {0, 1, 1, 2, 3, 0, 1, 1, 2, 3, 0, 1, 1, 2, 3},
-                                 std::vector<float16> {2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f}),
-                // roi_pooling_2x2_max
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 1, 3,              // channels, rois
-                                 2, 2,              // oH, oW
-                                 1.f, "max",        // scale, mode
-                                 element::f16, ROIPoolingParams::increasinglyFilledBlob<float16>(1 * 6 * 6),
-                                 std::vector<float16> {0, 1, 1, 3, 3, 0, 1, 2, 2, 4, 0, 0, 1, 4, 5},
-                                 std::vector<float16> {1.4f, 1.5f, 2.0f, 2.1f, 1.9f, 2.0f, 2.5f, 2.6f, 2.0f, 2.2f, 3.2f, 3.4f}),
-                // roi_pooling_1x1_bilinear
-                ROIPoolingParams(6, 6,              // iH, iW
-                                 3, 2,              // channels, rois
-                                 1, 1,              // oH, oW
-                                 1.f, "bilinear",   // scale, mode
-                                 element::f16, ROIPoolingParams::increasinglyFilledBlob<float16>(3 * 6 * 6),
-                                 std::vector<float16> {0, 0.2, 0.2, 0.4, 0.4, 0, 0.2, 0.2, 0.6, 0.6},
-                                 std::vector<float16> {1.05f, 4.65f, 8.25f, 1.4f, 5.0f, 8.6f}),
-                // roi_pooling_2x2_bilinear
-                ROIPoolingParams(8, 8,              // iH, iW
-                                 1, 3,              // channels, rois
-                                 2, 2,              // oH, oW
-                                 1.f, "bilinear",   // scale, mode
-                                 element::f16, ROIPoolingParams::increasinglyFilledBlob<float16>(1 * 8 * 8),
-                                 std::vector<float16> {0.f, 0.15f, 0.2f, 0.75f, 0.8f,
-                                                     0.f, 0.15f, 0.2f, 0.75f, 0.8f,
-                                                     0.f, 0.15f, 0.2f, 0.75f, 0.8f},
-                                 std::vector<float16> {1.225f, 1.645f, 4.585f, 5.005f,
-                                                     1.225f, 1.645f, 4.585f, 5.005f,
-                                                     1.225f, 1.645f, 4.585f, 5.005f})),
-        ReferenceRoiPoolingLayerTest::getTestCaseName);
+        // bf16
+        // roi_pooling_1x1_max
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         3,
+                         3,  // channels, rois
+                         1,
+                         1,  // oH, oW
+                         1.f,
+                         "max",  // scale, mode
+                         element::bf16,
+                         ROIPoolingParams::increasinglyFilledBlob<bfloat16>(3 * 6 * 6),
+                         std::vector<bfloat16>{0, 1, 1, 2, 3, 0, 1, 1, 2, 3, 0, 1, 1, 2, 3},
+                         std::vector<bfloat16>{2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f}),
+        // roi_pooling_2x2_max
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         1,
+                         3,  // channels, rois
+                         2,
+                         2,  // oH, oW
+                         1.f,
+                         "max",  // scale, mode
+                         element::bf16,
+                         ROIPoolingParams::increasinglyFilledBlob<bfloat16>(1 * 6 * 6),
+                         std::vector<bfloat16>{0, 1, 1, 3, 3, 0, 1, 2, 2, 4, 0, 0, 1, 4, 5},
+                         std::vector<bfloat16>{1.4f, 1.5f, 2.0f, 2.1f, 1.9f, 2.0f, 2.5f, 2.6f, 2.0f, 2.2f, 3.2f, 3.4f}),
+        // roi_pooling_1x1_bilinear
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         3,
+                         2,  // channels, rois
+                         1,
+                         1,  // oH, oW
+                         1.f,
+                         "bilinear",  // scale, mode
+                         element::bf16,
+                         ROIPoolingParams::increasinglyFilledBlob<bfloat16>(3 * 6 * 6),
+                         std::vector<bfloat16>{0, 0.2, 0.2, 0.4, 0.4, 0, 0.2, 0.2, 0.6, 0.6},
+                         std::vector<bfloat16>{1.05f, 4.65f, 8.25f, 1.4f, 5.0f, 8.6f}),
+        // roi_pooling_2x2_bilinear
+        ROIPoolingParams(
+            8,
+            8,  // iH, iW
+            1,
+            3,  // channels, rois
+            2,
+            2,  // oH, oW
+            1.f,
+            "bilinear",  // scale, mode
+            element::bf16,
+            ROIPoolingParams::increasinglyFilledBlob<bfloat16>(1 * 8 * 8),
+            std::vector<
+                bfloat16>{0.f, 0.15f, 0.2f, 0.75f, 0.8f, 0.f, 0.15f, 0.2f, 0.75f, 0.8f, 0.f, 0.15f, 0.2f, 0.75f, 0.8f},
+            std::vector<bfloat16>{1.225f,
+                                  1.645f,
+                                  4.585f,
+                                  4.937f,
+                                  1.225f,
+                                  1.645f,
+                                  4.585f,
+                                  4.937f,
+                                  1.225f,
+                                  1.645f,
+                                  4.585f,
+                                  4.937f}),
+        // fp16
+        // roi_pooling_1x1_max
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         3,
+                         3,  // channels, rois
+                         1,
+                         1,  // oH, oW
+                         1.f,
+                         "max",  // scale, mode
+                         element::f16,
+                         ROIPoolingParams::increasinglyFilledBlob<float16>(3 * 6 * 6),
+                         std::vector<float16>{0, 1, 1, 2, 3, 0, 1, 1, 2, 3, 0, 1, 1, 2, 3},
+                         std::vector<float16>{2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f, 2.0f, 5.6f, 9.2f}),
+        // roi_pooling_2x2_max
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         1,
+                         3,  // channels, rois
+                         2,
+                         2,  // oH, oW
+                         1.f,
+                         "max",  // scale, mode
+                         element::f16,
+                         ROIPoolingParams::increasinglyFilledBlob<float16>(1 * 6 * 6),
+                         std::vector<float16>{0, 1, 1, 3, 3, 0, 1, 2, 2, 4, 0, 0, 1, 4, 5},
+                         std::vector<float16>{1.4f, 1.5f, 2.0f, 2.1f, 1.9f, 2.0f, 2.5f, 2.6f, 2.0f, 2.2f, 3.2f, 3.4f}),
+        // roi_pooling_1x1_bilinear
+        ROIPoolingParams(6,
+                         6,  // iH, iW
+                         3,
+                         2,  // channels, rois
+                         1,
+                         1,  // oH, oW
+                         1.f,
+                         "bilinear",  // scale, mode
+                         element::f16,
+                         ROIPoolingParams::increasinglyFilledBlob<float16>(3 * 6 * 6),
+                         std::vector<float16>{0, 0.2, 0.2, 0.4, 0.4, 0, 0.2, 0.2, 0.6, 0.6},
+                         std::vector<float16>{1.05f, 4.65f, 8.25f, 1.4f, 5.0f, 8.6f}),
+        // roi_pooling_2x2_bilinear
+        ROIPoolingParams(
+            8,
+            8,  // iH, iW
+            1,
+            3,  // channels, rois
+            2,
+            2,  // oH, oW
+            1.f,
+            "bilinear",  // scale, mode
+            element::f16,
+            ROIPoolingParams::increasinglyFilledBlob<float16>(1 * 8 * 8),
+            std::vector<
+                float16>{0.f, 0.15f, 0.2f, 0.75f, 0.8f, 0.f, 0.15f, 0.2f, 0.75f, 0.8f, 0.f, 0.15f, 0.2f, 0.75f, 0.8f},
+            std::vector<float16>{1.225f,
+                                 1.645f,
+                                 4.585f,
+                                 5.005f,
+                                 1.225f,
+                                 1.645f,
+                                 4.585f,
+                                 5.005f,
+                                 1.225f,
+                                 1.645f,
+                                 4.585f,
+                                 5.005f})),
+    ReferenceRoiPoolingLayerTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/op_reference/roll.cpp b/src/plugins/template/tests/functional/op_reference/roll.cpp
index d275b15f6f5916..b9d2b54f5debb0 100644
--- a/src/plugins/template/tests/functional/op_reference/roll.cpp
+++ b/src/plugins/template/tests/functional/op_reference/roll.cpp
@@ -4,19 +4,25 @@
 
 #include <gtest/gtest.h>
 
+#include "base_reference_test.hpp"
 #include "openvino/opsets/opset1.hpp"
 #include "openvino/opsets/opset7.hpp"
-#include "base_reference_test.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct RollParams {
-    RollParams(const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& shiftTensor, const reference_tests::Tensor& axesTensor,
-               const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-               dataTensor(dataTensor), shiftTensor(shiftTensor), axesTensor(axesTensor),
-               expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    RollParams(const reference_tests::Tensor& dataTensor,
+               const reference_tests::Tensor& shiftTensor,
+               const reference_tests::Tensor& axesTensor,
+               const reference_tests::Tensor& expectedTensor,
+               const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          shiftTensor(shiftTensor),
+          axesTensor(axesTensor),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor shiftTensor;
@@ -63,7 +69,7 @@ class ReferenceRollLayerTest : public testing::TestWithParam<RollParams>, public
                                                              params.axesTensor.shape,
                                                              params.axesTensor.data.data());
         const auto roll = std::make_shared<opset7::Roll>(data, shift, axes);
-        return std::make_shared<Model>(NodeVector {roll}, ParameterVector {data});
+        return std::make_shared<Model>(NodeVector{roll}, ParameterVector{data});
     }
 };
 
@@ -74,117 +80,135 @@ TEST_P(ReferenceRollLayerTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<RollParams> generateRollParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<RollParams> rollParams {
+    std::vector<RollParams> rollParams{
         // roll_repeated_axes
-        RollParams(
-            reference_tests::Tensor({4, 3}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
-            reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{1, 2, 1}),
-            reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 1, 0}),
-            reference_tests::Tensor({4, 3}, IN_ET, std::vector<T>{8, 9, 7, 11, 12, 10, 2, 3, 1, 5, 6, 4}),
-            "roll_repeated_axes"),
+        RollParams(reference_tests::Tensor({4, 3}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+                   reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{1, 2, 1}),
+                   reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 1, 0}),
+                   reference_tests::Tensor({4, 3}, IN_ET, std::vector<T>{8, 9, 7, 11, 12, 10, 2, 3, 1, 5, 6, 4}),
+                   "roll_repeated_axes"),
 
         // roll_negative_axes
         RollParams(
-            reference_tests::Tensor({4, 2, 3}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor({4, 2, 3}, IN_ET, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                     13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
             reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{2, -1, -7}),
             reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{-1, -1, -2}),
-            reference_tests::Tensor({4, 2, 3}, IN_ET, std::vector<T>{6, 4, 5, 3, 1, 2, 12, 10, 11, 9, 7, 8, 18, 16, 17, 15, 13, 14, 24, 22, 23, 21, 19, 20}),
+            reference_tests::Tensor({4, 2, 3}, IN_ET, std::vector<T>{6,  4,  5,  3,  1,  2,  12, 10, 11, 9,  7,  8,
+                                                                     18, 16, 17, 15, 13, 14, 24, 22, 23, 21, 19, 20}),
             "roll_negative_axes"),
     };
     return rollParams;
 }
 
 std::vector<RollParams> generateRollFloatingPointParams() {
-    std::vector<RollParams> rollParams {
+    std::vector<RollParams> rollParams{
         // roll_2d_input
-        RollParams(
-            reference_tests::Tensor({4, 3}, element::f32, std::vector<float>{50.2907,
-                                                            70.8054,
-                                                            -68.3403,
-                                                            62.6444,
-                                                            4.9748,
-                                                            -18.5551,
-                                                            40.5383,
-                                                            -15.3859,
-                                                            -4.5881,
-                                                            -43.3479,
-                                                            94.1676,
-                                                            -95.7097}),
-            reference_tests::Tensor({1}, element::i64, std::vector<int64_t>{1}),
-            reference_tests::Tensor({1}, element::i64, std::vector<int64_t>{0}),
-            reference_tests::Tensor({4, 3}, element::f32, std::vector<float>{-43.3479,
-                                                            94.1676,
-                                                            -95.7097,
-                                                            50.2907,
-                                                            70.8054,
-                                                            -68.3403,
-                                                            62.6444,
-                                                            4.9748,
-                                                            -18.5551,
-                                                            40.5383,
-                                                            -15.3859,
-                                                            -4.5881}),
-            "roll_2d_input"),
+        RollParams(reference_tests::Tensor({4, 3},
+                                           element::f32,
+                                           std::vector<float>{50.2907,
+                                                              70.8054,
+                                                              -68.3403,
+                                                              62.6444,
+                                                              4.9748,
+                                                              -18.5551,
+                                                              40.5383,
+                                                              -15.3859,
+                                                              -4.5881,
+                                                              -43.3479,
+                                                              94.1676,
+                                                              -95.7097}),
+                   reference_tests::Tensor({1}, element::i64, std::vector<int64_t>{1}),
+                   reference_tests::Tensor({1}, element::i64, std::vector<int64_t>{0}),
+                   reference_tests::Tensor({4, 3},
+                                           element::f32,
+                                           std::vector<float>{-43.3479,
+                                                              94.1676,
+                                                              -95.7097,
+                                                              50.2907,
+                                                              70.8054,
+                                                              -68.3403,
+                                                              62.6444,
+                                                              4.9748,
+                                                              -18.5551,
+                                                              40.5383,
+                                                              -15.3859,
+                                                              -4.5881}),
+                   "roll_2d_input"),
 
         // roll_2d_input_negative_shift
-        RollParams(
-            reference_tests::Tensor({4, 3}, element::f32, std::vector<float>{50.2907,
-                                                            70.8054,
-                                                            -68.3403,
-                                                            62.6444,
-                                                            4.9748,
-                                                            -18.5551,
-                                                            40.5383,
-                                                            -15.3859,
-                                                            -4.5881,
-                                                            -43.3479,
-                                                            94.1676,
-                                                            -95.7097}),
-            reference_tests::Tensor({2}, element::i64, std::vector<int64_t>{-1, 2}),
-            reference_tests::Tensor({2}, element::i64, std::vector<int64_t>{0, 1}),
-            reference_tests::Tensor({4, 3}, element::f32, std::vector<float>{4.9748,
-                                                            -18.5551,
-                                                            62.6444,
-                                                            -15.3859,
-                                                            -4.5881,
-                                                            40.5383,
-                                                            94.1676,
-                                                            -95.7097,
-                                                            -43.3479,
-                                                            70.8054,
-                                                            -68.3403,
-                                                            50.2907}),
-            "roll_2d_input_negative_shift"),
+        RollParams(reference_tests::Tensor({4, 3},
+                                           element::f32,
+                                           std::vector<float>{50.2907,
+                                                              70.8054,
+                                                              -68.3403,
+                                                              62.6444,
+                                                              4.9748,
+                                                              -18.5551,
+                                                              40.5383,
+                                                              -15.3859,
+                                                              -4.5881,
+                                                              -43.3479,
+                                                              94.1676,
+                                                              -95.7097}),
+                   reference_tests::Tensor({2}, element::i64, std::vector<int64_t>{-1, 2}),
+                   reference_tests::Tensor({2}, element::i64, std::vector<int64_t>{0, 1}),
+                   reference_tests::Tensor({4, 3},
+                                           element::f32,
+                                           std::vector<float>{4.9748,
+                                                              -18.5551,
+                                                              62.6444,
+                                                              -15.3859,
+                                                              -4.5881,
+                                                              40.5383,
+                                                              94.1676,
+                                                              -95.7097,
+                                                              -43.3479,
+                                                              70.8054,
+                                                              -68.3403,
+                                                              50.2907}),
+                   "roll_2d_input_negative_shift"),
 
         // roll_3d_input
         RollParams(
-            reference_tests::Tensor({4, 2, 3}, element::f32, std::vector<float>{94.0773,  33.0599, 58.1724,  -20.3640, 54.5372, -54.3023, 10.4662, 11.7532,
-                                                               -11.7692, 56.4223, -95.3774, 8.8978,   1.9305,  13.8025,  12.0827, 81.4669,
-                                                               19.5321,  -8.9553, -75.3226, 20.8033,  20.7660, 62.7361,  14.9372, -33.0825}),
+            reference_tests::Tensor(
+                {4, 2, 3},
+                element::f32,
+                std::vector<float>{94.0773,  33.0599, 58.1724,  -20.3640, 54.5372, -54.3023, 10.4662, 11.7532,
+                                   -11.7692, 56.4223, -95.3774, 8.8978,   1.9305,  13.8025,  12.0827, 81.4669,
+                                   19.5321,  -8.9553, -75.3226, 20.8033,  20.7660, 62.7361,  14.9372, -33.0825}),
             reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{2, 1, 3}),
             reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 1, 2}),
-            reference_tests::Tensor({4, 2, 3}, element::f32, std::vector<float>{81.4669,  19.5321,  -8.9553, 1.9305,   13.8025,  12.0827, 62.7361,  14.9372,
-                                                               -33.0825, -75.3226, 20.8033, 20.7660,  -20.3640, 54.5372, -54.3023, 94.0773,
-                                                               33.0599,  58.1724,  56.4223, -95.3774, 8.8978,   10.4662, 11.7532,  -11.7692}),
+            reference_tests::Tensor(
+                {4, 2, 3},
+                element::f32,
+                std::vector<float>{81.4669,  19.5321,  -8.9553, 1.9305,   13.8025,  12.0827, 62.7361,  14.9372,
+                                   -33.0825, -75.3226, 20.8033, 20.7660,  -20.3640, 54.5372, -54.3023, 94.0773,
+                                   33.0599,  58.1724,  56.4223, -95.3774, 8.8978,   10.4662, 11.7532,  -11.7692}),
             "roll_3d_input"),
 
         // roll_3d_input_negative_shift
-        RollParams(
-            reference_tests::Tensor({4, 2, 3}, element::f32, std::vector<float>{94.0773,  33.0599, 58.1724,  -20.3640, 54.5372, -54.3023, 10.4662, 11.7532,
-                                                               -11.7692, 56.4223, -95.3774, 8.8978,   1.9305,  13.8025,  12.0827, 81.4669,
-                                                               19.5321,  -8.9553, -75.3226, 20.8033,  20.7660, 62.7361,  14.9372, -33.0825}),
-            reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{-5, 1, 3}),
-            reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 1, 1}),
-            reference_tests::Tensor({4, 2, 3}, element::f32, std::vector<float>{10.4662, 11.7532,  -11.7692, 56.4223, -95.3774, 8.8978,   1.9305,  13.8025,
-                                                               12.0827, 81.4669,  19.5321,  -8.9553, -75.3226, 20.8033,  20.7660, 62.7361,
-                                                               14.9372, -33.0825, 94.0773,  33.0599, 58.1724,  -20.3640, 54.5372, -54.3023}),
-            "roll_3d_input_negative_shift"),
+        RollParams(reference_tests::Tensor(
+                       {4, 2, 3},
+                       element::f32,
+                       std::vector<float>{94.0773,  33.0599, 58.1724,  -20.3640, 54.5372, -54.3023, 10.4662, 11.7532,
+                                          -11.7692, 56.4223, -95.3774, 8.8978,   1.9305,  13.8025,  12.0827, 81.4669,
+                                          19.5321,  -8.9553, -75.3226, 20.8033,  20.7660, 62.7361,  14.9372, -33.0825}),
+                   reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{-5, 1, 3}),
+                   reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 1, 1}),
+                   reference_tests::Tensor(
+                       {4, 2, 3},
+                       element::f32,
+                       std::vector<float>{10.4662, 11.7532,  -11.7692, 56.4223, -95.3774, 8.8978,   1.9305,  13.8025,
+                                          12.0827, 81.4669,  19.5321,  -8.9553, -75.3226, 20.8033,  20.7660, 62.7361,
+                                          14.9372, -33.0825, 94.0773,  33.0599, 58.1724,  -20.3640, 54.5372, -54.3023}),
+                   "roll_3d_input_negative_shift"),
     };
     return rollParams;
 }
 
 std::vector<RollParams> generateRollCombinedParams() {
-    const std::vector<std::vector<RollParams>> rollTypeParams {
+    const std::vector<std::vector<RollParams>> rollTypeParams{
         generateRollParams<element::Type_t::i8>(),
         generateRollParams<element::Type_t::i16>(),
         generateRollParams<element::Type_t::i32>(),
@@ -207,6 +231,8 @@ std::vector<RollParams> generateRollCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Roll_With_Hardcoded_Refs, ReferenceRollLayerTest,
-    testing::ValuesIn(generateRollCombinedParams()), ReferenceRollLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Roll_With_Hardcoded_Refs,
+                         ReferenceRollLayerTest,
+                         testing::ValuesIn(generateRollCombinedParams()),
+                         ReferenceRollLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/round.cpp b/src/plugins/template/tests/functional/op_reference/round.cpp
index 2b01faf9487d80..cb20868e575db9 100644
--- a/src/plugins/template/tests/functional/op_reference/round.cpp
+++ b/src/plugins/template/tests/functional/op_reference/round.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/round.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/round.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -13,7 +15,10 @@ namespace {
 
 struct RoundParams {
     template <class IT>
-    RoundParams(const PartialShape& shape, const element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    RoundParams(const PartialShape& shape,
+                const element::Type& iType,
+                const std::vector<IT>& iValues,
+                const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -25,7 +30,7 @@ struct RoundParams {
     element::Type outType;
     ov::Tensor inputData;
     ov::Tensor refData;
- };
+};
 
 class ReferenceRoundHalfToEvenLayerTest : public testing::TestWithParam<RoundParams>, public CommonReferenceTest {
 public:
@@ -46,8 +51,8 @@ class ReferenceRoundHalfToEvenLayerTest : public testing::TestWithParam<RoundPar
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto round = std::make_shared<op::v5::Round>(in, op::v5::Round::RoundMode::HALF_TO_EVEN);
         return std::make_shared<Model>(NodeVector{round}, ParameterVector{in});
@@ -73,8 +78,8 @@ class ReferenceRoundHalfAwayFromZeroLayerTest : public testing::TestWithParam<Ro
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto round = std::make_shared<op::v5::Round>(in, op::v5::Round::RoundMode::HALF_AWAY_FROM_ZERO);
         return std::make_shared<Model>(NodeVector{round}, ParameterVector{in});
@@ -93,12 +98,10 @@ template <element::Type_t IN_ET>
 std::vector<RoundParams> generateParamsForRoundHalfToEven() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<RoundParams> params{
-        RoundParams(ov::PartialShape{5},
-                    IN_ET,
-                    std::vector<T>{0.9f, 2.5f, 2.3f, 1.5f, -4.5f},
-                    std::vector<T>{1.0f, 2.0f, 2.0f, 2.0f, -4.0f})
-    };
+    std::vector<RoundParams> params{RoundParams(ov::PartialShape{5},
+                                                IN_ET,
+                                                std::vector<T>{0.9f, 2.5f, 2.3f, 1.5f, -4.5f},
+                                                std::vector<T>{1.0f, 2.0f, 2.0f, 2.0f, -4.0f})};
     return params;
 }
 
@@ -106,12 +109,11 @@ template <element::Type_t IN_ET>
 std::vector<RoundParams> generateParamsForRound2D() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<RoundParams> params{
-        RoundParams(ov::PartialShape{15},
-                    IN_ET,
-                    std::vector<T>{0.1f, 0.5f, 0.9f, 1.2f, 1.5f, 1.8f, 2.3f, 2.5f, 2.7f, -1.1f, -1.5f, -1.9f, -2.2f, -2.5f, -2.8f},
-                    std::vector<T>{0.f, 0.f, 1.f, 1.f, 2.f, 2.f, 2.f, 2.f, 3.f, -1.f, -2.f, -2.f, -2.f, -2.f, -3.f})
-    };
+    std::vector<RoundParams> params{RoundParams(
+        ov::PartialShape{15},
+        IN_ET,
+        std::vector<T>{0.1f, 0.5f, 0.9f, 1.2f, 1.5f, 1.8f, 2.3f, 2.5f, 2.7f, -1.1f, -1.5f, -1.9f, -2.2f, -2.5f, -2.8f},
+        std::vector<T>{0.f, 0.f, 1.f, 1.f, 2.f, 2.f, 2.f, 2.f, 3.f, -1.f, -2.f, -2.f, -2.f, -2.f, -3.f})};
     return params;
 }
 
@@ -119,11 +121,10 @@ template <element::Type_t IN_ET>
 std::vector<RoundParams> generateParamsForRoundInt64() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<RoundParams> params{
-        RoundParams(ov::PartialShape{3},
-                    IN_ET,
-                    std::vector<T>{0, 1, 0x4000000000000001},
-                    std::vector<T>{0, 1, 0x4000000000000001})};
+    std::vector<RoundParams> params{RoundParams(ov::PartialShape{3},
+                                                IN_ET,
+                                                std::vector<T>{0, 1, 0x4000000000000001},
+                                                std::vector<T>{0, 1, 0x4000000000000001})};
     return params;
 }
 
@@ -132,10 +133,7 @@ std::vector<RoundParams> generateParamsForRoundInt() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
     std::vector<RoundParams> params{
-        RoundParams(ov::PartialShape{3},
-                    IN_ET,
-                    std::vector<T>{0, 1, 0x40},
-                    std::vector<T>{0, 1, 0x40})};
+        RoundParams(ov::PartialShape{3}, IN_ET, std::vector<T>{0, 1, 0x40}, std::vector<T>{0, 1, 0x40})};
     return params;
 }
 
@@ -143,11 +141,10 @@ template <element::Type_t IN_ET>
 std::vector<RoundParams> generateParamsForRoundAwayFromZero() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<RoundParams> params{
-        RoundParams(ov::PartialShape{5},
-                    IN_ET,
-                    std::vector<T>{0.9f, 2.5f, 2.3f, 1.5f, -4.5f},
-                    std::vector<T>{1.0f, 3.0f, 2.0f, 2.0f, -5.0f})};
+    std::vector<RoundParams> params{RoundParams(ov::PartialShape{5},
+                                                IN_ET,
+                                                std::vector<T>{0.9f, 2.5f, 2.3f, 1.5f, -4.5f},
+                                                std::vector<T>{1.0f, 3.0f, 2.0f, 2.0f, -5.0f})};
     return params;
 }
 
@@ -168,11 +165,9 @@ std::vector<RoundParams> generateCombinedParamsForRoundHalfToEven() {
 }
 
 std::vector<RoundParams> generateCombinedParamsForRound2D() {
-    const std::vector<std::vector<RoundParams>> allTypeParams{
-        generateParamsForRound2D<element::Type_t::f32>(),
-        generateParamsForRound2D<element::Type_t::f16>(),
-        generateParamsForRound2D<element::Type_t::bf16>()
-    };
+    const std::vector<std::vector<RoundParams>> allTypeParams{generateParamsForRound2D<element::Type_t::f32>(),
+                                                              generateParamsForRound2D<element::Type_t::f16>(),
+                                                              generateParamsForRound2D<element::Type_t::bf16>()};
 
     std::vector<RoundParams> combinedParams;
 
@@ -184,16 +179,14 @@ std::vector<RoundParams> generateCombinedParamsForRound2D() {
 }
 
 std::vector<RoundParams> generateCombinedParamsForRoundInt() {
-    const std::vector<std::vector<RoundParams>> allTypeParams{
-        generateParamsForRoundInt64<element::Type_t::i64>(),
-        generateParamsForRoundInt<element::Type_t::i32>(),
-        generateParamsForRoundInt<element::Type_t::i16>(),
-        generateParamsForRoundInt<element::Type_t::i8>(),
-        generateParamsForRoundInt<element::Type_t::u64>(),
-        generateParamsForRoundInt<element::Type_t::u32>(),
-        generateParamsForRoundInt<element::Type_t::u16>(),
-        generateParamsForRoundInt<element::Type_t::u8>()
-    };
+    const std::vector<std::vector<RoundParams>> allTypeParams{generateParamsForRoundInt64<element::Type_t::i64>(),
+                                                              generateParamsForRoundInt<element::Type_t::i32>(),
+                                                              generateParamsForRoundInt<element::Type_t::i16>(),
+                                                              generateParamsForRoundInt<element::Type_t::i8>(),
+                                                              generateParamsForRoundInt<element::Type_t::u64>(),
+                                                              generateParamsForRoundInt<element::Type_t::u32>(),
+                                                              generateParamsForRoundInt<element::Type_t::u16>(),
+                                                              generateParamsForRoundInt<element::Type_t::u8>()};
 
     std::vector<RoundParams> combinedParams;
 
@@ -208,8 +201,7 @@ std::vector<RoundParams> generateCombinedParamsForRoundAwayFromZero() {
     const std::vector<std::vector<RoundParams>> allTypeParams{
         generateParamsForRoundAwayFromZero<element::Type_t::f32>(),
         generateParamsForRoundAwayFromZero<element::Type_t::f16>(),
-        generateParamsForRoundAwayFromZero<element::Type_t::bf16>()
-    };
+        generateParamsForRoundAwayFromZero<element::Type_t::bf16>()};
 
     std::vector<RoundParams> combinedParams;
 
@@ -220,28 +212,24 @@ std::vector<RoundParams> generateCombinedParamsForRoundAwayFromZero() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Round_Half_To_Even_With_Hardcoded_Refs,
-    ReferenceRoundHalfToEvenLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForRoundHalfToEven()),
-    ReferenceRoundHalfToEvenLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Round_2D_With_Hardcoded_Refs,
-    ReferenceRoundHalfToEvenLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForRound2D()),
-    ReferenceRoundHalfToEvenLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Round_Int_With_Hardcoded_Refs,
-    ReferenceRoundHalfToEvenLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForRoundInt()),
-    ReferenceRoundHalfToEvenLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Round_Away_From_Zero_With_Hardcoded_Refs,
-    ReferenceRoundHalfAwayFromZeroLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForRoundAwayFromZero()),
-    ReferenceRoundHalfAwayFromZeroLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Round_Half_To_Even_With_Hardcoded_Refs,
+                         ReferenceRoundHalfToEvenLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForRoundHalfToEven()),
+                         ReferenceRoundHalfToEvenLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Round_2D_With_Hardcoded_Refs,
+                         ReferenceRoundHalfToEvenLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForRound2D()),
+                         ReferenceRoundHalfToEvenLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Round_Int_With_Hardcoded_Refs,
+                         ReferenceRoundHalfToEvenLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForRoundInt()),
+                         ReferenceRoundHalfToEvenLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Round_Away_From_Zero_With_Hardcoded_Refs,
+                         ReferenceRoundHalfAwayFromZeroLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForRoundAwayFromZero()),
+                         ReferenceRoundHalfAwayFromZeroLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/scatter_elements_update.cpp b/src/plugins/template/tests/functional/op_reference/scatter_elements_update.cpp
index 18d5103aaf420c..48db3024d0b45f 100644
--- a/src/plugins/template/tests/functional/op_reference/scatter_elements_update.cpp
+++ b/src/plugins/template/tests/functional/op_reference/scatter_elements_update.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/scatter_elements_update.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/scatter_elements_update.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -31,15 +32,12 @@ struct ScatterElementsUpdateParams {
 };
 
 class ReferenceScatterElementsUpdateLayerTest : public testing::TestWithParam<ScatterElementsUpdateParams>,
-                                       public CommonReferenceTest {
+                                                public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
         function = CreateFunction(params);
-        inputData = {params.input.data,
-                     params.indices.data,
-                     params.updates.data,
-                     params.axis.data};
+        inputData = {params.input.data, params.indices.data, params.updates.data, params.axis.data};
         refOutData = {params.expected.data};
     }
     static std::string getTestCaseName(const testing::TestParamInfo<ScatterElementsUpdateParams>& obj) {
@@ -55,6 +53,7 @@ class ReferenceScatterElementsUpdateLayerTest : public testing::TestWithParam<Sc
         result << "_axis_pr=" << param.axis.type;
         return result.str();
     }
+
 private:
     static std::shared_ptr<Model> CreateFunction(const ScatterElementsUpdateParams& params) {
         const auto A = std::make_shared<op::v0::Parameter>(params.input.type, params.input.shape);
@@ -76,17 +75,19 @@ std::vector<ScatterElementsUpdateParams> generateScatterParams() {
     using T_INT = typename element_type_traits<ET_IND>::value_type;
     std::vector<ScatterElementsUpdateParams> scatterParams{
         // axis = 0
-        ScatterElementsUpdateParams(reference_tests::Tensor({2, 2}, element::Type(ET), std::vector<T>{1, 2, 3, 4}),         // input
-                                    reference_tests::Tensor({2, 2}, element::Type(ET_IND), std::vector<T_INT>{1, 1, 0, 0}), // indices
-                                    reference_tests::Tensor({2, 2}, element::Type(ET), std::vector<T>{10, 20, 30, 40}),     // updates
-                                    reference_tests::Tensor({1}, element::Type(ET_IND), std::vector<T_INT>{0}),             // axis
-                                    reference_tests::Tensor({2, 2}, element::Type(ET), std::vector<T>{30, 40, 10, 20})),    // expected
+        ScatterElementsUpdateParams(
+            reference_tests::Tensor({2, 2}, element::Type(ET), std::vector<T>{1, 2, 3, 4}),          // input
+            reference_tests::Tensor({2, 2}, element::Type(ET_IND), std::vector<T_INT>{1, 1, 0, 0}),  // indices
+            reference_tests::Tensor({2, 2}, element::Type(ET), std::vector<T>{10, 20, 30, 40}),      // updates
+            reference_tests::Tensor({1}, element::Type(ET_IND), std::vector<T_INT>{0}),              // axis
+            reference_tests::Tensor({2, 2}, element::Type(ET), std::vector<T>{30, 40, 10, 20})),     // expected
         // axis = 1
-        ScatterElementsUpdateParams(reference_tests::Tensor({2, 1}, element::Type(ET), std::vector<T>{1, 2}),         // input
-                                    reference_tests::Tensor({2, 1}, element::Type(ET_IND), std::vector<T_INT>{0, 0}), // indices
-                                    reference_tests::Tensor({2, 1}, element::Type(ET), std::vector<T>{10, 20}),       // updates
-                                    reference_tests::Tensor({1}, element::Type(ET_IND), std::vector<T_INT>{1}),       // axis
-                                    reference_tests::Tensor({2, 1}, element::Type(ET), std::vector<T>{10, 20})),      // expected
+        ScatterElementsUpdateParams(
+            reference_tests::Tensor({2, 1}, element::Type(ET), std::vector<T>{1, 2}),          // input
+            reference_tests::Tensor({2, 1}, element::Type(ET_IND), std::vector<T_INT>{0, 0}),  // indices
+            reference_tests::Tensor({2, 1}, element::Type(ET), std::vector<T>{10, 20}),        // updates
+            reference_tests::Tensor({1}, element::Type(ET_IND), std::vector<T_INT>{1}),        // axis
+            reference_tests::Tensor({2, 1}, element::Type(ET), std::vector<T>{10, 20})),       // expected
     };
     return scatterParams;
 }
@@ -167,4 +168,4 @@ INSTANTIATE_TEST_SUITE_P(smoke_ScatterEltsUpdate_With_Hardcoded_Refs,
                          ReferenceScatterElementsUpdateLayerTest,
                          ::testing::ValuesIn(generateScatterCombinedParams()),
                          ReferenceScatterElementsUpdateLayerTest::getTestCaseName);
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/scatter_nd_update.cpp b/src/plugins/template/tests/functional/op_reference/scatter_nd_update.cpp
index 334b75f118e818..090503c5c29268 100644
--- a/src/plugins/template/tests/functional/op_reference/scatter_nd_update.cpp
+++ b/src/plugins/template/tests/functional/op_reference/scatter_nd_update.cpp
@@ -2,21 +2,28 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/scatter_nd_update.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/scatter_nd_update.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct ScatterNDUpdateParams {
-    ScatterNDUpdateParams(const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& indexTensor, const reference_tests::Tensor& updateTensor,
-                const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-                dataTensor(dataTensor), indexTensor(indexTensor), updateTensor(updateTensor),
-                expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    ScatterNDUpdateParams(const reference_tests::Tensor& dataTensor,
+                          const reference_tests::Tensor& indexTensor,
+                          const reference_tests::Tensor& updateTensor,
+                          const reference_tests::Tensor& expectedTensor,
+                          const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          indexTensor(indexTensor),
+          updateTensor(updateTensor),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor indexTensor;
@@ -25,7 +32,8 @@ struct ScatterNDUpdateParams {
     std::string testcaseName;
 };
 
-class ReferenceScatterNDUpdateLayerTest : public testing::TestWithParam<ScatterNDUpdateParams>, public CommonReferenceTest {
+class ReferenceScatterNDUpdateLayerTest : public testing::TestWithParam<ScatterNDUpdateParams>,
+                                          public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -75,7 +83,7 @@ template <element::Type_t IN_ET, element::Type_t IU_ET>
 std::vector<ScatterNDUpdateParams> generateScatterNDUpdateParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
     using U = typename element_type_traits<IU_ET>::value_type;
-    std::vector<ScatterNDUpdateParams> scatterParams {
+    std::vector<ScatterNDUpdateParams> scatterParams{
         // scatter_nd_update_1x1
         ScatterNDUpdateParams(reference_tests::Tensor({1}, IN_ET, std::vector<T>{1}),
                               reference_tests::Tensor({1}, IU_ET, std::vector<U>{0}),
@@ -95,46 +103,52 @@ std::vector<ScatterNDUpdateParams> generateScatterNDUpdateParams() {
                               reference_tests::Tensor({2, 2}, IN_ET, std::vector<T>{10, 2, 3, 40}),
                               "scatter_nd_update_2x2_by_2"),
         // scatter_nd_update_3x3_by_1
-        ScatterNDUpdateParams(reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                                                      21, 22, 23, 24, 25, 26, 27, 28, 29,
-                                                                      31, 32, 33, 34, 35, 36, 37, 38, 39}),
-                              reference_tests::Tensor({2, 1}, IU_ET, std::vector<U>{0, 2}),
-                              reference_tests::Tensor({2, 3, 3}, IN_ET, std::vector<T>{91, 92, 93, 94, 95, 96, 97, 98, 99,
-                                                                      81, 82, 83, 84, 85, 86, 87, 88, 89}),
-                              reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{91, 92, 93, 94, 95, 96, 97, 98, 99,
-                                                                      21, 22, 23, 24, 25, 26, 27, 28, 29,
-                                                                      81, 82, 83, 84, 85, 86, 87, 88, 89}),
-                              "scatter_nd_update_3x3_by_1"),
+        ScatterNDUpdateParams(
+            reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{11, 12, 13, 14, 15, 16, 17, 18, 19,
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29,
+                                                                     31, 32, 33, 34, 35, 36, 37, 38, 39}),
+            reference_tests::Tensor({2, 1}, IU_ET, std::vector<U>{0, 2}),
+            reference_tests::Tensor(
+                {2, 3, 3},
+                IN_ET,
+                std::vector<T>{91, 92, 93, 94, 95, 96, 97, 98, 99, 81, 82, 83, 84, 85, 86, 87, 88, 89}),
+            reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{91, 92, 93, 94, 95, 96, 97, 98, 99,
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29,
+                                                                     81, 82, 83, 84, 85, 86, 87, 88, 89}),
+            "scatter_nd_update_3x3_by_1"),
         // scatter_nd_update_3x3_by_2v2
-        ScatterNDUpdateParams(reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                                                      21, 22, 23, 24, 25, 26, 27, 28, 29,
-                                                                      31, 32, 33, 34, 35, 36, 37, 38, 39}),
-                              reference_tests::Tensor({2, 2, 3}, IU_ET, std::vector<U>{0, 0, 0, 2, 2, 2, 1, 0, 0, 1, 2, 2}),
-                              reference_tests::Tensor({2, 2}, IN_ET, std::vector<T>{91, 92, 81, 82}),
-                              reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{91, 12, 13, 14, 15, 16, 17, 18, 19,
-                                                                      81, 22, 23, 24, 25, 26, 27, 28, 82,
-                                                                      31, 32, 33, 34, 35, 36, 37, 38, 92}),
-                              "scatter_nd_update_3x3_by_2v2"),
+        ScatterNDUpdateParams(
+            reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{11, 12, 13, 14, 15, 16, 17, 18, 19,
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29,
+                                                                     31, 32, 33, 34, 35, 36, 37, 38, 39}),
+            reference_tests::Tensor({2, 2, 3}, IU_ET, std::vector<U>{0, 0, 0, 2, 2, 2, 1, 0, 0, 1, 2, 2}),
+            reference_tests::Tensor({2, 2}, IN_ET, std::vector<T>{91, 92, 81, 82}),
+            reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{91, 12, 13, 14, 15, 16, 17, 18, 19,
+                                                                     81, 22, 23, 24, 25, 26, 27, 28, 82,
+                                                                     31, 32, 33, 34, 35, 36, 37, 38, 92}),
+            "scatter_nd_update_3x3_by_2v2"),
         // scatter_nd_update_3x3_by_2
-        ScatterNDUpdateParams(reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                                                      21, 22, 23, 24, 25, 26, 27, 28, 29,
-                                                                      31, 32, 33, 34, 35, 36, 37, 38, 39}),
-                              reference_tests::Tensor({2, 2}, IU_ET, std::vector<U>{0, 0, 2, 2}),
-                              reference_tests::Tensor({2, 3}, IN_ET, std::vector<T>{91, 92, 93, 87, 88, 89}),
-                              reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{91, 92, 93, 14, 15, 16, 17, 18, 19,
-                                                                      21, 22, 23, 24, 25, 26, 27, 28, 29,
-                                                                      31, 32, 33, 34, 35, 36, 87, 88, 89}),
-                              "scatter_nd_update_3x3_by_2"),
+        ScatterNDUpdateParams(
+            reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{11, 12, 13, 14, 15, 16, 17, 18, 19,
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29,
+                                                                     31, 32, 33, 34, 35, 36, 37, 38, 39}),
+            reference_tests::Tensor({2, 2}, IU_ET, std::vector<U>{0, 0, 2, 2}),
+            reference_tests::Tensor({2, 3}, IN_ET, std::vector<T>{91, 92, 93, 87, 88, 89}),
+            reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{91, 92, 93, 14, 15, 16, 17, 18, 19,
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29,
+                                                                     31, 32, 33, 34, 35, 36, 87, 88, 89}),
+            "scatter_nd_update_3x3_by_2"),
         // scatter_nd_update_3x3_by_3
-        ScatterNDUpdateParams(reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                                                      21, 22, 23, 24, 25, 26, 27, 28, 29,
-                                                                      31, 32, 33, 34, 35, 36, 37, 38, 39}),
-                              reference_tests::Tensor({2, 3}, IU_ET, std::vector<U>{0, 0, 0, 2, 2, 2}),
-                              reference_tests::Tensor({2}, IN_ET, std::vector<T>{91, 99}),
-                              reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{91, 12, 13, 14, 15, 16, 17, 18, 19,
-                                                                      21, 22, 23, 24, 25, 26, 27, 28, 29,
-                                                                      31, 32, 33, 34, 35, 36, 37, 38, 99}),
-                              "scatter_nd_update_3x3_by_3"),
+        ScatterNDUpdateParams(
+            reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{11, 12, 13, 14, 15, 16, 17, 18, 19,
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29,
+                                                                     31, 32, 33, 34, 35, 36, 37, 38, 39}),
+            reference_tests::Tensor({2, 3}, IU_ET, std::vector<U>{0, 0, 0, 2, 2, 2}),
+            reference_tests::Tensor({2}, IN_ET, std::vector<T>{91, 99}),
+            reference_tests::Tensor({3, 3, 3}, IN_ET, std::vector<T>{91, 12, 13, 14, 15, 16, 17, 18, 19,
+                                                                     21, 22, 23, 24, 25, 26, 27, 28, 29,
+                                                                     31, 32, 33, 34, 35, 36, 37, 38, 99}),
+            "scatter_nd_update_3x3_by_3"),
         // scatter_nd_update_1d_from_examples
         ScatterNDUpdateParams(reference_tests::Tensor({8}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8}),
                               reference_tests::Tensor({4, 1}, IU_ET, std::vector<U>{4, 3, 1, 7}),
@@ -142,37 +156,41 @@ std::vector<ScatterNDUpdateParams> generateScatterNDUpdateParams() {
                               reference_tests::Tensor({8}, IN_ET, std::vector<T>{1, 11, 3, 10, 9, 6, 7, 12}),
                               "scatter_nd_update_1d_from_examples"),
         // scatter_nd_update_4x4_shape_from_examples
-        ScatterNDUpdateParams(reference_tests::Tensor({4, 4, 4}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
-                                                                      1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
-                                                                      8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8,
-                                                                      8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8}),
-                              reference_tests::Tensor({2, 1}, IU_ET, std::vector<U>{0, 2}),
-                              reference_tests::Tensor({2, 4, 4}, IN_ET, std::vector<T>{5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8,
-                                                                      1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4}),
-                              reference_tests::Tensor({4, 4, 4}, IN_ET, std::vector<T>{5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8,
-                                                                      1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
-                                                                      1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4,
-                                                                      8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8}),
-                              "scatter_nd_update_4x4_shape_from_examples"),
+        ScatterNDUpdateParams(
+            reference_tests::Tensor({4, 4, 4}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
+                                                                     1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
+                                                                     8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8,
+                                                                     8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8}),
+            reference_tests::Tensor({2, 1}, IU_ET, std::vector<U>{0, 2}),
+            reference_tests::Tensor({2, 4, 4}, IN_ET, std::vector<T>{5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8,
+                                                                     1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4}),
+            reference_tests::Tensor({4, 4, 4}, IN_ET, std::vector<T>{5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8,
+                                                                     1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
+                                                                     1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4,
+                                                                     8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8}),
+            "scatter_nd_update_4x4_shape_from_examples"),
         // scatter_nd_update_4x4_v2
-        ScatterNDUpdateParams(reference_tests::Tensor({4, 4, 4}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
-                                                                      1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
-                                                                      8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8,
-                                                                      8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8}),
-                              reference_tests::Tensor({2, 2, 2}, IU_ET, std::vector<U>{0, 0, 2, 2, 1, 1, 3, 3}),
-                              reference_tests::Tensor({2, 2, 4}, IN_ET, std::vector<T>{15, 16, 17, 18, 25, 26, 27, 28,
-                                                                      35, 36, 37, 38, 45, 46, 47, 58}),
-                              reference_tests::Tensor({4, 4, 4}, IN_ET, std::vector<T>{15, 16, 17, 18, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
-                                                                      1, 2, 3, 4, 35, 36, 37, 38, 8, 7, 6, 5, 4, 3, 2, 1,
-                                                                      8, 7, 6, 5, 4, 3, 2, 1, 25, 26, 27, 28, 5, 6, 7, 8,
-                                                                      8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 45, 46, 47, 58}),
-                              "scatter_nd_update_4x4_v2"),
+        ScatterNDUpdateParams(
+            reference_tests::Tensor({4, 4, 4}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
+                                                                     1, 2, 3, 4, 5, 6, 7, 8, 8, 7, 6, 5, 4, 3, 2, 1,
+                                                                     8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8,
+                                                                     8, 7, 6, 5, 4, 3, 2, 1, 1, 2, 3, 4, 5, 6, 7, 8}),
+            reference_tests::Tensor({2, 2, 2}, IU_ET, std::vector<U>{0, 0, 2, 2, 1, 1, 3, 3}),
+            reference_tests::Tensor({2, 2, 4},
+                                    IN_ET,
+                                    std::vector<T>{15, 16, 17, 18, 25, 26, 27, 28, 35, 36, 37, 38, 45, 46, 47, 58}),
+            reference_tests::Tensor({4, 4, 4}, IN_ET, std::vector<T>{15, 16, 17, 18, 5,  6, 7, 8,  8,  7,  6,  5, 4,
+                                                                     3,  2,  1,  1,  2,  3, 4, 35, 36, 37, 38, 8, 7,
+                                                                     6,  5,  4,  3,  2,  1, 8, 7,  6,  5,  4,  3, 2,
+                                                                     1,  25, 26, 27, 28, 5, 6, 7,  8,  8,  7,  6, 5,
+                                                                     4,  3,  2,  1,  1,  2, 3, 4,  45, 46, 47, 58}),
+            "scatter_nd_update_4x4_v2"),
     };
     return scatterParams;
 }
 
 std::vector<ScatterNDUpdateParams> generateScatterNDUpdateCombinedParams() {
-    const std::vector<std::vector<ScatterNDUpdateParams>> scatterTypeParams {
+    const std::vector<std::vector<ScatterNDUpdateParams>> scatterTypeParams{
         generateScatterNDUpdateParams<element::Type_t::i32, element::Type_t::i32>(),
         generateScatterNDUpdateParams<element::Type_t::i64, element::Type_t::i32>(),
         generateScatterNDUpdateParams<element::Type_t::u32, element::Type_t::i32>(),
@@ -196,11 +214,12 @@ std::vector<ScatterNDUpdateParams> generateScatterNDUpdateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ScatterNDUpdate_With_Hardcoded_Refs, ReferenceScatterNDUpdateLayerTest,
-    testing::ValuesIn(generateScatterNDUpdateCombinedParams()), ReferenceScatterNDUpdateLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_ScatterNDUpdate_With_Hardcoded_Refs,
+                         ReferenceScatterNDUpdateLayerTest,
+                         testing::ValuesIn(generateScatterNDUpdateCombinedParams()),
+                         ReferenceScatterNDUpdateLayerTest::getTestCaseName);
 
-class ReferenceScatterNDUpdateLayerNegativeTest : public ReferenceScatterNDUpdateLayerTest{
-};
+class ReferenceScatterNDUpdateLayerNegativeTest : public ReferenceScatterNDUpdateLayerTest {};
 
 TEST_P(ReferenceScatterNDUpdateLayerNegativeTest, CompareWithRefsNegative) {
     LoadNetwork();
@@ -219,7 +238,7 @@ template <element::Type_t IN_ET, element::Type_t IU_ET>
 std::vector<ScatterNDUpdateParams> generateScatterNDUpdateNegativeParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
     using U = typename element_type_traits<IU_ET>::value_type;
-    std::vector<ScatterNDUpdateParams> scatterParams {
+    std::vector<ScatterNDUpdateParams> scatterParams{
         // scatter_nd_update_2x3_with_out_of_bounds_index
         ScatterNDUpdateParams(reference_tests::Tensor({2, 3}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6}),
                               reference_tests::Tensor({1, 2}, IU_ET, std::vector<U>{1, 3}),
@@ -231,9 +250,8 @@ std::vector<ScatterNDUpdateParams> generateScatterNDUpdateNegativeParams() {
 }
 
 std::vector<ScatterNDUpdateParams> generateScatterNDUpdateCombinedNegativeParams() {
-    const std::vector<std::vector<ScatterNDUpdateParams>> scatterTypeParams {
-        generateScatterNDUpdateNegativeParams<element::Type_t::f32, element::Type_t::i64>()
-    };
+    const std::vector<std::vector<ScatterNDUpdateParams>> scatterTypeParams{
+        generateScatterNDUpdateNegativeParams<element::Type_t::f32, element::Type_t::i64>()};
     std::vector<ScatterNDUpdateParams> combinedParams;
 
     for (const auto& params : scatterTypeParams) {
@@ -242,9 +260,9 @@ std::vector<ScatterNDUpdateParams> generateScatterNDUpdateCombinedNegativeParams
     return combinedParams;
 }
 
+INSTANTIATE_TEST_SUITE_P(smoke_ScatterNDUpdate_With_Hardcoded_Refs,
+                         ReferenceScatterNDUpdateLayerNegativeTest,
+                         testing::ValuesIn(generateScatterNDUpdateCombinedNegativeParams()),
+                         ReferenceScatterNDUpdateLayerNegativeTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_ScatterNDUpdate_With_Hardcoded_Refs, ReferenceScatterNDUpdateLayerNegativeTest,
-    testing::ValuesIn(generateScatterNDUpdateCombinedNegativeParams()), ReferenceScatterNDUpdateLayerNegativeTest::getTestCaseName);
-
-
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/scatter_update.cpp b/src/plugins/template/tests/functional/op_reference/scatter_update.cpp
index 47d17750c0822b..c3f210d7bfdd41 100644
--- a/src/plugins/template/tests/functional/op_reference/scatter_update.cpp
+++ b/src/plugins/template/tests/functional/op_reference/scatter_update.cpp
@@ -2,13 +2,13 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/scatter_update.hpp"
 
 #include <vector>
 
 #include "base_reference_test.hpp"
 #include "gtest/gtest.h"
 #include "openvino/op/parameter.hpp"
-#include "openvino/op/scatter_update.hpp"
 
 using namespace reference_tests;
 
@@ -34,7 +34,8 @@ struct Builder : ParamsBuilder<ScatterUpdate3Params> {
     REFERENCE_TESTS_ADD_SET_PARAM(Builder, expected);
 };
 
-class ReferenceScatterUpdate6LayerTest : public testing::TestWithParam<ScatterUpdate3Params>, public CommonReferenceTest {
+class ReferenceScatterUpdate6LayerTest : public testing::TestWithParam<ScatterUpdate3Params>,
+                                         public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -73,7 +74,8 @@ class ReferenceScatterUpdate6LayerTest : public testing::TestWithParam<ScatterUp
         const auto updates = std::make_shared<ov::op::v0::Parameter>(numeric_type, updates_shape);
         const auto axis = std::make_shared<ov::op::v0::Parameter>(axis_type, axis_shape);
         const auto scatter_update = std::make_shared<ov::op::v3::ScatterUpdate>(data, indices, updates, axis);
-        return std::make_shared<ov::Model>(ov::NodeVector {scatter_update}, ov::ParameterVector {data, indices, updates, axis});
+        return std::make_shared<ov::Model>(ov::NodeVector{scatter_update},
+                                           ov::ParameterVector{data, indices, updates, axis});
     }
 };
 
@@ -82,855 +84,386 @@ TEST_P(ReferenceScatterUpdate6LayerTest, ScatterUpdateWithHardcodedRefs) {
 }
 
 template <ov::element::Type_t NUM_ET, ov::element::Type_t INT_ET>
-std::vector<ScatterUpdate3Params> generateScatterUpdate3Params(const ov::element::Type& numeric_type, const ov::element::Type& integer_type) {
+std::vector<ScatterUpdate3Params> generateScatterUpdate3Params(const ov::element::Type& numeric_type,
+                                                               const ov::element::Type& integer_type) {
     using N = typename ov::element_type_traits<NUM_ET>::value_type;
     using I = typename ov::element_type_traits<INT_ET>::value_type;
-    std::vector<ScatterUpdate3Params> ScatterUpdateParams {
-        Builder {}
-            .data({{3, 2, 2, 3}, numeric_type, std::vector<N> {
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0,
-                                                               0, 0, 0}})
-            .indices({{2, 1}, integer_type, std::vector<I> {0, 1}})
-            .updates({{3, 3, 2, 2, 2}, numeric_type, std::vector<N> {
-                                                                     1, 2,
-                                                                     3, 4,
-                                                                     5, 6,
-                                                                     7, 8,
-                                                                     9, 10,
-                                                                     11, 12,
-                                                                     13, 14,
-                                                                     15, 16,
-                                                                     17, 18,
-                                                                     19, 20,
-                                                                     21, 22,
-                                                                     23, 24,
-                                                                     25, 26,
-                                                                     27, 28,
-                                                                     29, 30,
-                                                                     31, 32,
-                                                                     33, 34,
-                                                                     35, 36,
-                                                                     37, 38,
-                                                                     39, 40,
-                                                                     41, 42,
-                                                                     43, 44,
-                                                                     45, 46,
-                                                                     47, 48,
-                                                                     49, 50,
-                                                                     51, 52,
-                                                                     53, 54,
-                                                                     55, 56,
-                                                                     57, 58,
-                                                                     59, 60,
-                                                                     61, 62,
-                                                                     63, 64,
-                                                                     65, 66,
-                                                                     67, 68,
-                                                                     69, 70,
-                                                                     71, 72}})
-            .axis({{1}, integer_type, std::vector<I> {2}})
-            .expected({{3, 2, 2, 3}, numeric_type, std::vector<N> {
-                                                               1, 2, 9,
-                                                               3, 4, 11,
-                                                               10, 17, 18,
-                                                               12, 19, 20,
-                                                               25, 26, 33,
-                                                               27, 28, 35,
-                                                               34, 41, 42,
-                                                               36, 43, 44,
-                                                               49, 50, 57,
-                                                               51, 52, 59,
-                                                               58, 65, 66,
-                                                               60, 67, 68}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                         0, 0, 0,
-                                                         0, 0, 0}})
-            .indices({{2}, integer_type, std::vector<I> {1, 2}})
-            .updates({{3, 2}, numeric_type, std::vector<N> {1, 1,
-                                                            1, 2,
-                                                            2, 2}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {0, 1, 1,
-                                                             0, 1, 2,
-                                                             0, 2, 2}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                         0, 0, 0,
-                                                         0, 0, 0}})
-            .indices({{2}, integer_type, std::vector<I> {1, 2}})
-            .updates({{2, 3}, numeric_type, std::vector<N> {1, 1, 1,
-                                                            2, 2, 2}})
-            .axis({{1}, integer_type, std::vector<I> {0}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                             1, 1, 1,
-                                                             2, 2, 2}}),
-        Builder {}
-            .data({{3, 4}, numeric_type, std::vector<N> {0, 0, 0, 0,
-                                                         0, 0, 0, 0,
-                                                         0, 0, 0, 0}})
-            .indices({{2}, integer_type, std::vector<I> {0, 2}})
-            .updates({{3, 4}, numeric_type, std::vector<N> {1, 2, 3, 7,
-                                                            4, 5, 6, 8,
-                                                            7, 8, 9, 10}})
-            .axis({{1}, integer_type, std::vector<I> {0}})
-            .expected({{3, 4}, numeric_type, std::vector<N> {1, 2, 3, 7,
-                                                             0, 0, 0, 0,
-                                                             4, 5, 6, 8}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                         0, 0, 0,
-                                                         0, 0, 0}})
-            .indices({{2}, integer_type, std::vector<I> {0, 2}})
-            .updates({{3, 5}, numeric_type, std::vector<N> {1, 2, 3, 4, 5,
-                                                            6, 7, 8, 9, 10,
-                                                            11, 12, 13, 14, 15}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {1, 0, 2,
-                                                             6, 0, 7,
-                                                             11, 0, 12}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 2}, integer_type, std::vector<I> {1, 2}})
-            .updates({{1, 2, 3}, numeric_type, std::vector<N> {1, 2, 3,
-                                                               4, 5, 6}})
-            .axis({{1}, integer_type, std::vector<I> {0}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                             1, 2, 3,
-                                                             4, 5, 6}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 2}, integer_type, std::vector<I> {1, 2}})
-            .updates({{3, 1, 2}, numeric_type, std::vector<N> {1, 2,
-                                                               3, 4,
-                                                               5, 6}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {0, 1, 2,
-                                                             0, 3, 4,
-                                                             0, 5, 6}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 2}, integer_type, std::vector<I> {1, 2}})
-            .updates({{4, 4, 4}, numeric_type, std::vector<N> {1, 2, 3, 4,
-                                                               5, 6, 7, 8,
-                                                               9, 10, 11, 12,
-                                                               13, 14, 15, 16,
-                                                               17, 18, 19, 20,
-                                                               21, 22, 23, 24,
-                                                               25, 26, 27, 28,
-                                                               29, 30, 31, 32,
-                                                               33, 34, 35, 36,
-                                                               37, 38, 39, 40,
-                                                               41, 42, 43, 44,
-                                                               45, 46, 47, 48,
-                                                               49, 50, 51, 52,
-                                                               53, 54, 55, 56,
-                                                               57, 58, 59, 60,
-                                                               61, 62, 63, 64}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {0, 1, 2,
-                                                             0, 17, 18,
-                                                             0, 33, 34}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 3}, integer_type, std::vector<I> {0, 1, 2}})
-            .updates({{4, 4, 4}, numeric_type, std::vector<N> {1, 2, 3, 4,
-                                                               5, 6, 7, 8,
-                                                               9, 10, 11, 12,
-                                                               13, 14, 15, 16,
-                                                               17, 18, 19, 20,
-                                                               21, 22, 23, 24,
-                                                               25, 26, 27, 28,
-                                                               29, 30, 31, 32,
-                                                               33, 34, 35, 36,
-                                                               37, 38, 39, 40,
-                                                               41, 42, 43, 44,
-                                                               45, 46, 47, 48,
-                                                               49, 50, 51, 52,
-                                                               53, 54, 55, 56,
-                                                               57, 58, 59, 60,
-                                                               61, 62, 63, 64}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {1, 2, 3,
-                                                             17, 18, 19,
-                                                             33, 34, 35}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 1}, integer_type, std::vector<I> {2}})
-            .updates({{2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               7, 8}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {0, 0, 1,
-                                                             0, 0, 5,
-                                                             0, 0, 0}}),
-        Builder {}
-            .data({{3, 4}, numeric_type, std::vector<N> {0, 0, 0, 0,
-                                                         0, 0, 0, 0,
-                                                         0, 0, 0, 0}})
-            .indices({{1, 4}, integer_type, std::vector<I> {0, 1, 2, 3}})
-            .updates({{2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               7, 8}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{3, 4}, numeric_type, std::vector<N> {1, 2, 3, 4,
-                                                             5, 6, 7, 8,
-                                                             0, 0, 0, 0}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 3}, integer_type, std::vector<I> {0, 1, 2}})
-            .updates({{2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               7, 8}})
-            .axis({{1}, integer_type, std::vector<I> {0}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {1, 2, 0,
-                                                             3, 4, 0,
-                                                             5, 6, 0}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 3}, integer_type, std::vector<I> {0, 1, 2}})
-            .updates({{2, 2, 1}, numeric_type, std::vector<N> {1, 2,
-                                                               3, 4}})
-            .axis({{1}, integer_type, std::vector<I> {0}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {1, 0, 0,
-                                                             2, 0, 0,
-                                                             3, 0, 0}}),
-        Builder {}
-            .data({{3, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 3}, integer_type, std::vector<I> {0, 1, 2}})
-            .updates({{1, 1, 1}, numeric_type, std::vector<N> {1}})
-            .axis({{1}, integer_type, std::vector<I> {0}})
-            .expected({{3, 3}, numeric_type, std::vector<N> {1, 0, 0,
-                                                             0, 0, 0,
-                                                             0, 0, 0}}),
-        Builder {}
-            .data({{2, 2}, numeric_type, std::vector<N> {0, 0,
-                                                         0, 0}})
-            .indices({{2, 1}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               7, 8}})
-            .axis({{1}, integer_type, std::vector<I> {0}})
-            .expected({{2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                             3, 4}}),
-        Builder {}
-            .data({{4, 4}, numeric_type, std::vector<N> {0, 0, 0, 0,
-                                                         0, 0, 0, 0,
-                                                         0, 0, 0, 0,
-                                                         0, 0, 0, 0}})
-            .indices({{4, 1}, integer_type, std::vector<I> {0, 1, 2, 3}})
-            .updates({{2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               7, 8}})
-            .axis({{1}, integer_type, std::vector<I> {0}})
-            .expected({{4, 4}, numeric_type, std::vector<N> {1, 2, 0, 0,
-                                                             3, 4, 0, 0,
-                                                             5, 6, 0, 0,
-                                                             7, 8, 0, 0}}),
-        Builder {}
-            .data({{2, 3, 4, 2}, numeric_type, std::vector<N> {0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}})
-            .indices({{3, 1}, integer_type, std::vector<I> {0, 1, 2}})
-            .updates({{3, 2, 3, 3, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                     3, 4,
-                                                                     5, 6,
-                                                                     7, 8,
-                                                                     9, 10,
-                                                                     11, 12,
-                                                                     13, 14,
-                                                                     15, 16,
-                                                                     17, 18,
-                                                                     19, 20,
-                                                                     21, 22,
-                                                                     23, 24,
-                                                                     25, 26,
-                                                                     27, 28,
-                                                                     29, 30,
-                                                                     31, 32,
-                                                                     33, 34,
-                                                                     35, 36,
-                                                                     37, 38,
-                                                                     39, 40,
-                                                                     41, 42,
-                                                                     43, 44,
-                                                                     45, 46,
-                                                                     47, 48,
-                                                                     49, 50,
-                                                                     51, 52,
-                                                                     53, 54,
-                                                                     55, 56,
-                                                                     57, 58,
-                                                                     59, 60,
-                                                                     61, 62,
-                                                                     63, 64,
-                                                                     65, 66,
-                                                                     67, 68,
-                                                                     69, 70,
-                                                                     71, 72,
-                                                                     73, 74,
-                                                                     75, 76,
-                                                                     77, 78,
-                                                                     79, 80,
-                                                                     81, 82,
-                                                                     83, 84,
-                                                                     85, 86,
-                                                                     87, 88,
-                                                                     89, 90,
-                                                                     91, 92,
-                                                                     93, 94,
-                                                                     95, 96,
-                                                                     97, 98,
-                                                                     99, 100,
-                                                                     101, 102,
-                                                                     103, 104,
-                                                                     105, 106,
-                                                                     107, 108}})
-            .axis({{1}, integer_type, std::vector<I> {2}})
-            .expected({{2, 3, 4, 2}, numeric_type, std::vector<N> {
-                                                               1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               0, 0,
-                                                               19, 20,
-                                                               21, 22,
-                                                               23, 24,
-                                                               0, 0,
-                                                               37, 38,
-                                                               39, 40,
-                                                               41, 42,
-                                                               0, 0,
-                                                               55, 56,
-                                                               57, 58,
-                                                               59, 60,
-                                                               0, 0,
-                                                               73, 74,
-                                                               75, 76,
-                                                               77, 78,
-                                                               0, 0,
-                                                               91, 92,
-                                                               93, 94,
-                                                               95, 96,
-                                                               0, 0}}),
-        Builder {}
-            .data({{1, 3, 2, 2}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 3}, integer_type, std::vector<I> {2, 0, 1}})
-            .updates({{1, 3, 2, 2, 2}, numeric_type, std::vector<N> {
-                                                                  1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{1, 3, 2, 2}, numeric_type, std::vector<N> {
-                                                            5, 6,
-                                                            7, 8,
-                                                            9, 10,
-                                                            11, 12,
-                                                            1, 2,
-                                                            3, 4}}),
-        Builder {}
-            .data({{2, 2, 2}, numeric_type, std::vector<N> {0, 0,
-                                                            0, 0,
-                                                            0, 0,
-                                                            0, 0}})
-            .indices({{1, 2}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 3, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                3, 4,
-                                                                13, 14,
-                                                                15, 16}}),
-        Builder {}
-            .data({{2, 2, 4}, numeric_type, std::vector<N> {0, 0, 0, 0,
-                                                            0, 0, 0, 0,
-                                                            0, 0, 0, 0,
-                                                            0, 0, 0, 0}})
-            .indices({{1, 2, 1}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 3, 2, 1}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{2, 2, 2}, numeric_type, std::vector<N> {1, 13, 0, 0,
-                                                                2, 14, 0, 0,
-                                                                0, 0, 0, 0,
-                                                                0, 0, 0, 0}}),
-        Builder {}
-            .data({{2, 4, 2}, numeric_type, std::vector<N> {0, 0, 0, 0,
-                                                            0, 0, 0, 0,
-                                                            0, 0, 0, 0,
-                                                            0, 0, 0, 0}})
-            .indices({{1, 2, 1}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 3, 2, 1}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{2, 4, 2}, numeric_type, std::vector<N> {1, 13,
-                                                                2, 14,
-                                                                0, 0,
-                                                                0, 0,
-                                                                0, 0,
-                                                                0, 0,
-                                                                0, 0,
-                                                                0, 0}}),
-        Builder {}
-            .data({{2, 2, 2}, numeric_type, std::vector<N> {0, 0,
-                                                            0, 0,
-                                                            0, 0,
-                                                            0, 0}})
-            .indices({{2, 1}, integer_type, std::vector<I> {1, 0}})
-            .updates({{2, 2, 3, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24}})
-            .axis({{1}, integer_type, std::vector<I> {2}})
-            .expected({{2, 2, 2}, numeric_type, std::vector<N> {
-                                                            2, 1,
-                                                            8, 7,
-                                                            //
-                                                            14, 13,
-                                                            20, 19}}),
-Builder {}
-            .data({{2, 2, 4}, numeric_type, std::vector<N> {0, 0, 0, 0,
-                                                            0, 0, 0, 0,
-                                                            0, 0, 0, 0,
-                                                            0, 0, 0, 0}})
-            .indices({{1, 2, 1}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 3, 1, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24}})
-            .axis({{1}, integer_type, std::vector<I> {1}})
-            .expected({{2, 2, 4}, numeric_type, std::vector<N> {1, 2, 13, 14,
-                                                                3, 4, 15, 16,
-                                                                0, 0, 0, 0,
-                                                                0, 0, 0, 0}}),
+    std::vector<ScatterUpdate3Params> ScatterUpdateParams{
+        Builder{}
+            .data({{3, 2, 2, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2, 1}, integer_type, std::vector<I>{0, 1}})
+            .updates({{3, 3, 2, 2, 2},
+                      numeric_type,
+                      std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18,
+                                     19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
+                                     37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54,
+                                     55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72}})
+            .axis({{1}, integer_type, std::vector<I>{2}})
+            .expected({{3, 2, 2, 3}, numeric_type, std::vector<N>{1,  2,  9,  3,  4,  11, 10, 17, 18, 12, 19, 20,
+                                                                  25, 26, 33, 27, 28, 35, 34, 41, 42, 36, 43, 44,
+                                                                  49, 50, 57, 51, 52, 59, 58, 65, 66, 60, 67, 68}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2}, integer_type, std::vector<I>{1, 2}})
+            .updates({{3, 2}, numeric_type, std::vector<N>{1, 1, 1, 2, 2, 2}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{0, 1, 1, 0, 1, 2, 0, 2, 2}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2}, integer_type, std::vector<I>{1, 2}})
+            .updates({{2, 3}, numeric_type, std::vector<N>{1, 1, 1, 2, 2, 2}})
+            .axis({{1}, integer_type, std::vector<I>{0}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 1, 1, 1, 2, 2, 2}}),
+        Builder{}
+            .data({{3, 4}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2}, integer_type, std::vector<I>{0, 2}})
+            .updates({{3, 4}, numeric_type, std::vector<N>{1, 2, 3, 7, 4, 5, 6, 8, 7, 8, 9, 10}})
+            .axis({{1}, integer_type, std::vector<I>{0}})
+            .expected({{3, 4}, numeric_type, std::vector<N>{1, 2, 3, 7, 0, 0, 0, 0, 4, 5, 6, 8}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2}, integer_type, std::vector<I>{0, 2}})
+            .updates({{3, 5}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{1, 0, 2, 6, 0, 7, 11, 0, 12}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2}, integer_type, std::vector<I>{1, 2}})
+            .updates({{1, 2, 3}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6}})
+            .axis({{1}, integer_type, std::vector<I>{0}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 1, 2, 3, 4, 5, 6}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2}, integer_type, std::vector<I>{1, 2}})
+            .updates({{3, 1, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{0, 1, 2, 0, 3, 4, 0, 5, 6}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2}, integer_type, std::vector<I>{1, 2}})
+            .updates({{4, 4, 4}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13,
+                                                              14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26,
+                                                              27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                                                              40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52,
+                                                              53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{0, 1, 2, 0, 17, 18, 0, 33, 34}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 3}, integer_type, std::vector<I>{0, 1, 2}})
+            .updates({{4, 4, 4}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13,
+                                                              14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26,
+                                                              27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                                                              40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52,
+                                                              53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{1, 2, 3, 17, 18, 19, 33, 34, 35}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 1}, integer_type, std::vector<I>{2}})
+            .updates({{2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{0, 0, 1, 0, 0, 5, 0, 0, 0}}),
+        Builder{}
+            .data({{3, 4}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 4}, integer_type, std::vector<I>{0, 1, 2, 3}})
+            .updates({{2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{3, 4}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8, 0, 0, 0, 0}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 3}, integer_type, std::vector<I>{0, 1, 2}})
+            .updates({{2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8}})
+            .axis({{1}, integer_type, std::vector<I>{0}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{1, 2, 0, 3, 4, 0, 5, 6, 0}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 3}, integer_type, std::vector<I>{0, 1, 2}})
+            .updates({{2, 2, 1}, numeric_type, std::vector<N>{1, 2, 3, 4}})
+            .axis({{1}, integer_type, std::vector<I>{0}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{1, 0, 0, 2, 0, 0, 3, 0, 0}}),
+        Builder{}
+            .data({{3, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 3}, integer_type, std::vector<I>{0, 1, 2}})
+            .updates({{1, 1, 1}, numeric_type, std::vector<N>{1}})
+            .axis({{1}, integer_type, std::vector<I>{0}})
+            .expected({{3, 3}, numeric_type, std::vector<N>{1, 0, 0, 0, 0, 0, 0, 0, 0}}),
+        Builder{}
+            .data({{2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0}})
+            .indices({{2, 1}, integer_type, std::vector<I>{0, 1}})
+            .updates({{2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8}})
+            .axis({{1}, integer_type, std::vector<I>{0}})
+            .expected({{2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4}}),
+        Builder{}
+            .data({{4, 4}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{4, 1}, integer_type, std::vector<I>{0, 1, 2, 3}})
+            .updates({{2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8}})
+            .axis({{1}, integer_type, std::vector<I>{0}})
+            .expected({{4, 4}, numeric_type, std::vector<N>{1, 2, 0, 0, 3, 4, 0, 0, 5, 6, 0, 0, 7, 8, 0, 0}}),
+        Builder{}
+            .data({{2, 3, 4, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{3, 1}, integer_type, std::vector<I>{0, 1, 2}})
+            .updates({{3, 2, 3, 3, 2},
+                      numeric_type,
+                      std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10,  11,  12,  13,  14,  15,  16,  17,  18,
+                                     19, 20, 21, 22, 23, 24, 25, 26, 27, 28,  29,  30,  31,  32,  33,  34,  35,  36,
+                                     37, 38, 39, 40, 41, 42, 43, 44, 45, 46,  47,  48,  49,  50,  51,  52,  53,  54,
+                                     55, 56, 57, 58, 59, 60, 61, 62, 63, 64,  65,  66,  67,  68,  69,  70,  71,  72,
+                                     73, 74, 75, 76, 77, 78, 79, 80, 81, 82,  83,  84,  85,  86,  87,  88,  89,  90,
+                                     91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108}})
+            .axis({{1}, integer_type, std::vector<I>{2}})
+            .expected({{2, 3, 4, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  0,  0,  19, 20, 21, 22,
+                                                                  23, 24, 0,  0,  37, 38, 39, 40, 41, 42, 0,  0,
+                                                                  55, 56, 57, 58, 59, 60, 0,  0,  73, 74, 75, 76,
+                                                                  77, 78, 0,  0,  91, 92, 93, 94, 95, 96, 0,  0}}),
+        Builder{}
+            .data({{1, 3, 2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 3}, integer_type, std::vector<I>{2, 0, 1}})
+            .updates({{1, 3, 2, 2, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                    13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{1, 3, 2, 2}, numeric_type, std::vector<N>{5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4}}),
+        Builder{}
+            .data({{2, 2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2}, integer_type, std::vector<I>{0, 1}})
+            .updates({{2, 2, 3, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 13, 14, 15, 16}}),
+        Builder{}
+            .data({{2, 2, 4}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2, 1}, integer_type, std::vector<I>{0, 1}})
+            .updates({{2, 2, 3, 2, 1}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                    13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{2, 2, 2}, numeric_type, std::vector<N>{1, 13, 0, 0, 2, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}),
+        Builder{}
+            .data({{2, 4, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2, 1}, integer_type, std::vector<I>{0, 1}})
+            .updates({{2, 2, 3, 2, 1}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                    13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{2, 4, 2}, numeric_type, std::vector<N>{1, 13, 2, 14, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}}),
+        Builder{}
+            .data({{2, 2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2, 1}, integer_type, std::vector<I>{1, 0}})
+            .updates({{2, 2, 3, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}})
+            .axis({{1}, integer_type, std::vector<I>{2}})
+            .expected({{2, 2, 2},
+                       numeric_type,
+                       std::vector<N>{2,
+                                      1,
+                                      8,
+                                      7,
+                                      //
+                                      14,
+                                      13,
+                                      20,
+                                      19}}),
+        Builder{}
+            .data({{2, 2, 4}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2, 1}, integer_type, std::vector<I>{0, 1}})
+            .updates({{2, 2, 3, 1, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                    13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}})
+            .axis({{1}, integer_type, std::vector<I>{1}})
+            .expected({{2, 2, 4}, numeric_type, std::vector<N>{1, 2, 13, 14, 3, 4, 15, 16, 0, 0, 0, 0, 0, 0, 0, 0}}),
 
- Builder {}
-            .data({{3, 2, 2, 2}, numeric_type, std::vector<N> {0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}})
-            .indices({{2}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16}})
-            .axis({{1}, integer_type, std::vector<I> {3}})
-            .expected({{3, 2, 2, 2}, numeric_type, std::vector<N> {
-                                                               1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               7, 8,
-                                                               9, 10,
-                                                               11, 12,
-                                                               13, 14,
-                                                               15, 16,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}}),
- Builder {}
-            .data({{5, 2, 2, 2}, numeric_type, std::vector<N> {0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}})
-            .indices({{2}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16}})
-            .axis({{1}, integer_type, std::vector<I> {2}})
-            .expected({{5, 2, 2, 2}, numeric_type, std::vector<N> {
-                                                               1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               7, 8,
-                                                               9, 10,
-                                                               11, 12,
-                                                               13, 14,
-                                                               15, 16,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}}),
-Builder {}
-            .data({{5, 2, 2, 2}, numeric_type, std::vector<N> {0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}})
-            .indices({{2, 1}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24,
-                                                                  25, 26,
-                                                                  27, 28,
-                                                                  29, 30,
-                                                                  31, 32}})
-            .axis({{1}, integer_type, std::vector<I> {2}})
-            .expected({{5, 2, 2, 2}, numeric_type, std::vector<N> {
-                                                               1, 2,
-                                                               3, 4,
-                                                               9, 10,
-                                                               11, 12,
-                                                               17, 18,
-                                                               19, 20,
-                                                               25, 26,
-                                                               27, 28,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}})};
+        Builder{}
+            .data({{3, 2, 2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2}, integer_type, std::vector<I>{0, 1}})
+            .updates(
+                {{2, 2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}})
+            .axis({{1}, integer_type, std::vector<I>{3}})
+            .expected({{3, 2, 2, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5, 6, 7, 8, 9, 10, 11, 12,
+                                                                  13, 14, 15, 16, 0, 0, 0, 0, 0, 0,  0,  0}}),
+        Builder{}
+            .data({{5, 2, 2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2}, integer_type, std::vector<I>{0, 1}})
+            .updates(
+                {{2, 2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}})
+            .axis({{1}, integer_type, std::vector<I>{2}})
+            .expected({{5, 2, 2, 2}, numeric_type, std::vector<N>{1,  2,  3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
+                                                                  15, 16, 0, 0, 0, 0, 0, 0, 0, 0,  0,  0,  0,  0,
+                                                                  0,  0,  0, 0, 0, 0, 0, 0, 0, 0,  0,  0}}),
+        Builder{}
+            .data({{5, 2, 2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2, 1}, integer_type, std::vector<I>{0, 1}})
+            .updates({{2, 2, 2, 2, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
+                                                                    12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22,
+                                                                    23, 24, 25, 26, 27, 28, 29, 30, 31, 32}})
+            .axis({{1}, integer_type, std::vector<I>{2}})
+            .expected({{5, 2, 2, 2}, numeric_type, std::vector<N>{1,  2,  3, 4, 9, 10, 11, 12, 17, 18, 19, 20, 25, 26,
+                                                                  27, 28, 0, 0, 0, 0,  0,  0,  0,  0,  0,  0,  0,  0,
+                                                                  0,  0,  0, 0, 0, 0,  0,  0,  0,  0,  0,  0}})};
     return ScatterUpdateParams;
 }
 
 template <ov::element::Type_t NUM_ET, ov::element::Type_t INT_ET>
-std::vector<ScatterUpdate3Params> generateScatterUpdate3ParamsNegativeAxis(const ov::element::Type& numeric_type, const ov::element::Type& integer_type) {
+std::vector<ScatterUpdate3Params> generateScatterUpdate3ParamsNegativeAxis(const ov::element::Type& numeric_type,
+                                                                           const ov::element::Type& integer_type) {
     using N = typename ov::element_type_traits<NUM_ET>::value_type;
     using I = typename ov::element_type_traits<INT_ET>::value_type;
-    std::vector<ScatterUpdate3Params> ScatterUpdateParams {
-        Builder {}
-            .data({{2, 2, 3}, numeric_type, std::vector<N> {0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0,
-                                                            0, 0, 0}})
-            .indices({{1, 2, 1}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 3, 1, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24}})
-            .axis({{1}, integer_type, std::vector<I> {-2}})
-            .expected({{2, 2, 3}, numeric_type, std::vector<N> {1, 2, 13,
-                                                                3, 4, 15,
-                                                                14, 0, 0,
-                                                                16, 0, 0}}),
-        Builder {}
-            .data({{2, 2, 2}, numeric_type, std::vector<N> {0, 0,
-                                                            0, 0,
-                                                            0, 0,
-                                                            0, 0}})
-            .indices({{1, 2, 1}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 3, 1, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16,
-                                                                  17, 18,
-                                                                  19, 20,
-                                                                  21, 22,
-                                                                  23, 24}})
-            .axis({{1}, integer_type, std::vector<I> {-1}})
-            .expected({{2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                7, 8,
-                                                                13, 14,
-                                                                19, 20}}),
-        Builder {}
-            .data({{4, 2, 2, 2}, numeric_type, std::vector<N> {0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}})
-            .indices({{2}, integer_type, std::vector<I> {0, 1}})
-            .updates({{2, 2, 2, 2}, numeric_type, std::vector<N> {1, 2,
-                                                                  3, 4,
-                                                                  5, 6,
-                                                                  7, 8,
-                                                                  9, 10,
-                                                                  11, 12,
-                                                                  13, 14,
-                                                                  15, 16}})
-            .axis({{1}, integer_type, std::vector<I> {-3}})
-            .expected({{4, 2, 2, 2}, numeric_type, std::vector<N> {
-                                                               1, 2,
-                                                               3, 4,
-                                                               5, 6,
-                                                               7, 8,
-                                                               9, 10,
-                                                               11, 12,
-                                                               13, 14,
-                                                               15, 16,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0,
-                                                               0, 0}})};
+    std::vector<ScatterUpdate3Params> ScatterUpdateParams{
+        Builder{}
+            .data({{2, 2, 3}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2, 1}, integer_type, std::vector<I>{0, 1}})
+            .updates({{2, 2, 3, 1, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                    13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}})
+            .axis({{1}, integer_type, std::vector<I>{-2}})
+            .expected({{2, 2, 3}, numeric_type, std::vector<N>{1, 2, 13, 3, 4, 15, 14, 0, 0, 16, 0, 0}}),
+        Builder{}
+            .data({{2, 2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{1, 2, 1}, integer_type, std::vector<I>{0, 1}})
+            .updates({{2, 2, 3, 1, 2}, numeric_type, std::vector<N>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+                                                                    13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}})
+            .axis({{1}, integer_type, std::vector<I>{-1}})
+            .expected({{2, 2, 2}, numeric_type, std::vector<N>{1, 2, 7, 8, 13, 14, 19, 20}}),
+        Builder{}
+            .data({{4, 2, 2, 2}, numeric_type, std::vector<N>{0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                                                              0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}})
+            .indices({{2}, integer_type, std::vector<I>{0, 1}})
+            .updates(
+                {{2, 2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16}})
+            .axis({{1}, integer_type, std::vector<I>{-3}})
+            .expected(
+                {{4, 2, 2, 2}, numeric_type, std::vector<N>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
+                                                            0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0,  0,  0,  0,  0,  0}})};
     return ScatterUpdateParams;
 }
 
 std::vector<ScatterUpdate3Params> generateScatterUpdateCombinedParams() {
-    const std::vector<std::vector<ScatterUpdate3Params>> ScatterUpdateTypeParams {
+    const std::vector<std::vector<ScatterUpdate3Params>> ScatterUpdateTypeParams{
         // f32
-        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i16>(ov::element::f32, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i32>(ov::element::f32, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i64>(ov::element::f32, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::u32>(ov::element::f32, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::u64>(ov::element::f32, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i16>(ov::element::f32,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i32>(ov::element::f32,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i64>(ov::element::f32,
+                                                                                         ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::u32>(ov::element::f32,
+                                                                                         ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::u64>(ov::element::f32,
+                                                                                         ov::element::u64),
 
         // f16
-        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i16>(ov::element::f16, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i32>(ov::element::f16, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i64>(ov::element::f16, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::u32>(ov::element::f16, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::u64>(ov::element::f16, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i16>(ov::element::f16,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i32>(ov::element::f16,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i64>(ov::element::f16,
+                                                                                         ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::u32>(ov::element::f16,
+                                                                                         ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::u64>(ov::element::f16,
+                                                                                         ov::element::u64),
         // i8
-        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i16>(ov::element::i8, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i32>(ov::element::i8, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i64>(ov::element::i8, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::u32>(ov::element::i8, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::u64>(ov::element::i8, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i16>(ov::element::i8,
+                                                                                        ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i32>(ov::element::i8,
+                                                                                        ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i64>(ov::element::i8,
+                                                                                        ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::u32>(ov::element::i8,
+                                                                                        ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::u64>(ov::element::i8,
+                                                                                        ov::element::u64),
         // i16
-        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i16>(ov::element::i16, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i32>(ov::element::i16, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i64>(ov::element::i16, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::u32>(ov::element::i16, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::u64>(ov::element::i16, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i16>(ov::element::i16,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i32>(ov::element::i16,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i64>(ov::element::i16,
+                                                                                         ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::u32>(ov::element::i16,
+                                                                                         ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::u64>(ov::element::i16,
+                                                                                         ov::element::u64),
         // i32
-        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i16>(ov::element::i32, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i32>(ov::element::i32, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i64>(ov::element::i32, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::u32>(ov::element::i32, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::u64>(ov::element::i32, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i16>(ov::element::i32,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i32>(ov::element::i32,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i64>(ov::element::i32,
+                                                                                         ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::u32>(ov::element::i32,
+                                                                                         ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::u64>(ov::element::i32,
+                                                                                         ov::element::u64),
         // i64
-        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i16>(ov::element::i64, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i32>(ov::element::i64, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i64>(ov::element::i64, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::u32>(ov::element::i64, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::u64>(ov::element::i64, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i16>(ov::element::i64,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i32>(ov::element::i64,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i64>(ov::element::i64,
+                                                                                         ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::u32>(ov::element::i64,
+                                                                                         ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::u64>(ov::element::i64,
+                                                                                         ov::element::u64),
         // u8
-        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i16>(ov::element::u8, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i32>(ov::element::u8, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i64>(ov::element::u8, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::u32>(ov::element::u8, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::u64>(ov::element::u8, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i16>(ov::element::u8,
+                                                                                        ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i32>(ov::element::u8,
+                                                                                        ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i64>(ov::element::u8,
+                                                                                        ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::u32>(ov::element::u8,
+                                                                                        ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::u64>(ov::element::u8,
+                                                                                        ov::element::u64),
         // u16
-        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i16>(ov::element::u16, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i32>(ov::element::u16, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i64>(ov::element::u16, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::u32>(ov::element::u16, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::u64>(ov::element::u16, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i16>(ov::element::u16,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i32>(ov::element::u16,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i64>(ov::element::u16,
+                                                                                         ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::u32>(ov::element::u16,
+                                                                                         ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::u64>(ov::element::u16,
+                                                                                         ov::element::u64),
         // u32
-        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i16>(ov::element::u32, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i32>(ov::element::u32, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i64>(ov::element::u32, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::u32>(ov::element::u32, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::u64>(ov::element::u32, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i16>(ov::element::u32,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i32>(ov::element::u32,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i64>(ov::element::u32,
+                                                                                         ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::u32>(ov::element::u32,
+                                                                                         ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::u64>(ov::element::u32,
+                                                                                         ov::element::u64),
         // u64
-        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i16>(ov::element::u64, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i32>(ov::element::u64, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i64>(ov::element::u64, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::u32>(ov::element::u64, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::u64>(ov::element::u64, ov::element::u64),
+        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i16>(ov::element::u64,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i32>(ov::element::u64,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i64>(ov::element::u64,
+                                                                                         ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::u32>(ov::element::u64,
+                                                                                         ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::u64>(ov::element::u64,
+                                                                                         ov::element::u64),
         // bf16
-        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i16>(ov::element::bf16, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i32>(ov::element::bf16, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i64>(ov::element::bf16, ov::element::i64),
-        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::u32>(ov::element::bf16, ov::element::u32),
-        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::u64>(ov::element::bf16, ov::element::u64)};
+        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i16>(ov::element::bf16,
+                                                                                          ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i32>(ov::element::bf16,
+                                                                                          ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i64>(ov::element::bf16,
+                                                                                          ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::u32>(ov::element::bf16,
+                                                                                          ov::element::u32),
+        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::u64>(ov::element::bf16,
+                                                                                          ov::element::u64)};
     std::vector<ScatterUpdate3Params> combinedParams;
 
     for (const auto& params : ScatterUpdateTypeParams) {
@@ -940,51 +473,84 @@ std::vector<ScatterUpdate3Params> generateScatterUpdateCombinedParams() {
 }
 
 std::vector<ScatterUpdate3Params> generateScatterUpdateNegativeAxisParams() {
-    const std::vector<std::vector<ScatterUpdate3Params>> ScatterUpdateTypeParams {
+    const std::vector<std::vector<ScatterUpdate3Params>> ScatterUpdateTypeParams{
         // f32
-        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i16>(ov::element::f32, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i32>(ov::element::f32, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i64>(ov::element::f32, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i16>(ov::element::f32,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i32>(ov::element::f32,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::f32, ov::element::Type_t::i64>(ov::element::f32,
+                                                                                         ov::element::i64),
         // f16
-        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i16>(ov::element::f16, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i32>(ov::element::f16, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i64>(ov::element::f16, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i16>(ov::element::f16,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i32>(ov::element::f16,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::f16, ov::element::Type_t::i64>(ov::element::f16,
+                                                                                         ov::element::i64),
         // i8
-        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i16>(ov::element::i8, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i32>(ov::element::i8, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i64>(ov::element::i8, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i16>(ov::element::i8,
+                                                                                        ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i32>(ov::element::i8,
+                                                                                        ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::i8, ov::element::Type_t::i64>(ov::element::i8,
+                                                                                        ov::element::i64),
         // i16
-        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i16>(ov::element::i16, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i32>(ov::element::i16, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i64>(ov::element::i16, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i16>(ov::element::i16,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i32>(ov::element::i16,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::i16, ov::element::Type_t::i64>(ov::element::i16,
+                                                                                         ov::element::i64),
         // i32
-        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i16>(ov::element::i32, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i32>(ov::element::i32, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i64>(ov::element::i32, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i16>(ov::element::i32,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i32>(ov::element::i32,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::i32, ov::element::Type_t::i64>(ov::element::i32,
+                                                                                         ov::element::i64),
         // i64
-        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i16>(ov::element::i64, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i32>(ov::element::i64, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i64>(ov::element::i64, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i16>(ov::element::i64,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i32>(ov::element::i64,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::i64, ov::element::Type_t::i64>(ov::element::i64,
+                                                                                         ov::element::i64),
         // u8
-        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i16>(ov::element::u8, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i32>(ov::element::u8, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i64>(ov::element::u8, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i16>(ov::element::u8,
+                                                                                        ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i32>(ov::element::u8,
+                                                                                        ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::u8, ov::element::Type_t::i64>(ov::element::u8,
+                                                                                        ov::element::i64),
         // u16
-        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i16>(ov::element::u16, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i32>(ov::element::u16, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i64>(ov::element::u16, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i16>(ov::element::u16,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i32>(ov::element::u16,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::u16, ov::element::Type_t::i64>(ov::element::u16,
+                                                                                         ov::element::i64),
         // u32
-        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i16>(ov::element::u32, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i32>(ov::element::u32, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i64>(ov::element::u32, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i16>(ov::element::u32,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i32>(ov::element::u32,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::u32, ov::element::Type_t::i64>(ov::element::u32,
+                                                                                         ov::element::i64),
         // u64
-        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i16>(ov::element::u64, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i32>(ov::element::u64, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i64>(ov::element::u64, ov::element::i64),
+        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i16>(ov::element::u64,
+                                                                                         ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i32>(ov::element::u64,
+                                                                                         ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::u64, ov::element::Type_t::i64>(ov::element::u64,
+                                                                                         ov::element::i64),
         // bf16
-        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i16>(ov::element::bf16, ov::element::i16),
-        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i32>(ov::element::bf16, ov::element::i32),
-        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i64>(ov::element::bf16, ov::element::i64)};
+        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i16>(ov::element::bf16,
+                                                                                          ov::element::i16),
+        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i32>(ov::element::bf16,
+                                                                                          ov::element::i32),
+        generateScatterUpdate3Params<ov::element::Type_t::bf16, ov::element::Type_t::i64>(ov::element::bf16,
+                                                                                          ov::element::i64)};
     std::vector<ScatterUpdate3Params> combinedParams;
 
     for (const auto& params : ScatterUpdateTypeParams) {
@@ -992,11 +558,15 @@ std::vector<ScatterUpdate3Params> generateScatterUpdateNegativeAxisParams() {
     }
     return combinedParams;
 }
-} // namespace
+}  // namespace
 
-INSTANTIATE_TEST_SUITE_P(smoke_ScatterUpdate_With_Hardcoded_Refs, ReferenceScatterUpdate6LayerTest,
-                        ::testing::ValuesIn(generateScatterUpdateCombinedParams()), ReferenceScatterUpdate6LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_ScatterUpdate_With_Hardcoded_Refs,
+                         ReferenceScatterUpdate6LayerTest,
+                         ::testing::ValuesIn(generateScatterUpdateCombinedParams()),
+                         ReferenceScatterUpdate6LayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_ScatterUpdate_Negative_Axis_With_Hardcoded_Refs, ReferenceScatterUpdate6LayerTest,
-                        ::testing::ValuesIn(generateScatterUpdateNegativeAxisParams()), ReferenceScatterUpdate6LayerTest::getTestCaseName);
-} // namespace reference_tests
+INSTANTIATE_TEST_SUITE_P(smoke_ScatterUpdate_Negative_Axis_With_Hardcoded_Refs,
+                         ReferenceScatterUpdate6LayerTest,
+                         ::testing::ValuesIn(generateScatterUpdateNegativeAxisParams()),
+                         ReferenceScatterUpdate6LayerTest::getTestCaseName);
+}  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/select.cpp b/src/plugins/template/tests/functional/op_reference/select.cpp
index 4e8467fc839793..72971888f274ab 100644
--- a/src/plugins/template/tests/functional/op_reference/select.cpp
+++ b/src/plugins/template/tests/functional/op_reference/select.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/select.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/select.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,9 +13,15 @@ using namespace ov;
 
 struct SelectParams {
     template <class IT, class OT>
-    SelectParams(const element::Type& data_type, const op::AutoBroadcastSpec& broadcast, const PartialShape& select_input_pshape,
-                 const std::vector<char>& select_input, const PartialShape& if_input_pshape, const std::vector<IT>& if_input,
-                 const PartialShape& else_input_pshape, const std::vector<IT>& else_input, const std::vector<OT>& expected_output)
+    SelectParams(const element::Type& data_type,
+                 const op::AutoBroadcastSpec& broadcast,
+                 const PartialShape& select_input_pshape,
+                 const std::vector<char>& select_input,
+                 const PartialShape& if_input_pshape,
+                 const std::vector<IT>& if_input,
+                 const PartialShape& else_input_pshape,
+                 const std::vector<IT>& else_input,
+                 const std::vector<OT>& expected_output)
         : data_type(data_type),
           broadcast(broadcast),
           select_input_pshape(select_input_pshape),
@@ -40,7 +47,11 @@ class ReferenceSelectLayerTest : public testing::TestWithParam<SelectParams>, pu
 public:
     void SetUp() override {
         auto params = GetParam();
-        function = CreateFunction(params.data_type, params.broadcast, params.select_input_pshape, params.if_input_pshape, params.else_input_pshape);
+        function = CreateFunction(params.data_type,
+                                  params.broadcast,
+                                  params.select_input_pshape,
+                                  params.if_input_pshape,
+                                  params.else_input_pshape);
         inputData = {params.select_input, params.if_input, params.else_input};
         refOutData = {params.expected_output};
     }
@@ -56,12 +67,16 @@ class ReferenceSelectLayerTest : public testing::TestWithParam<SelectParams>, pu
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const element::Type& data_type, const op::AutoBroadcastSpec& broadcast,
-                                                    const PartialShape& select_pshape, const PartialShape& if_pshape, const PartialShape& else_pshape) {
+    static std::shared_ptr<Model> CreateFunction(const element::Type& data_type,
+                                                 const op::AutoBroadcastSpec& broadcast,
+                                                 const PartialShape& select_pshape,
+                                                 const PartialShape& if_pshape,
+                                                 const PartialShape& else_pshape) {
         auto A = std::make_shared<op::v0::Parameter>(element::boolean, select_pshape);
         auto B = std::make_shared<op::v0::Parameter>(data_type, if_pshape);
         auto C = std::make_shared<op::v0::Parameter>(data_type, else_pshape);
-        return std::make_shared<ov::Model>(std::make_shared<op::v1::Select>(A, B, C, broadcast), ParameterVector {A, B, C});
+        return std::make_shared<ov::Model>(std::make_shared<op::v1::Select>(A, B, C, broadcast),
+                                           ParameterVector{A, B, C});
     }
 };
 
@@ -69,66 +84,67 @@ TEST_P(ReferenceSelectLayerTest, CompareWithHardcodedRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Select_With_Hardcoded_Refs, ReferenceSelectLayerTest,
+INSTANTIATE_TEST_SUITE_P(smoke_Select_With_Hardcoded_Refs,
+                         ReferenceSelectLayerTest,
                          ::testing::Values(
                              // fp32, no brodcasting
-                             SelectParams(element::f32,                                         // if/else/output data type
-                                          op::AutoBroadcastType::NONE,                  // broadcasting type
-                                          PartialShape {2, 2, 2},                       // select shape
-                                          std::vector<char> {0, 1, 1, 0, 0, 1, 0, 1},           // select data
-                                          PartialShape {2, 2, 2},                       // if shape
-                                          std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8},          // if data
-                                          PartialShape {2, 2, 2},                       // else shape
-                                          std::vector<float> {11, 12, 13, 14, 15, 16, 17, 18},  // else data
-                                          std::vector<float> {11, 2, 3, 14, 15, 6, 17, 8}),     // expected output data
+                             SelectParams(element::f32,                                // if/else/output data type
+                                          op::AutoBroadcastType::NONE,                 // broadcasting type
+                                          PartialShape{2, 2, 2},                       // select shape
+                                          std::vector<char>{0, 1, 1, 0, 0, 1, 0, 1},   // select data
+                                          PartialShape{2, 2, 2},                       // if shape
+                                          std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8},  // if data
+                                          PartialShape{2, 2, 2},                       // else shape
+                                          std::vector<float>{11, 12, 13, 14, 15, 16, 17, 18},  // else data
+                                          std::vector<float>{11, 2, 3, 14, 15, 6, 17, 8}),     // expected output data
                              // i32, no brodcasting
-                             SelectParams(element::i32,                                         // if/else/output data type
-                                          op::AutoBroadcastType::NONE,                  // broadcasting type
-                                          PartialShape {2, 2, 2},                       // select shape
-                                          std::vector<char> {0, 1, 1, 0, 0, 1, 0, 1},           // select data
-                                          PartialShape {2, 2, 2},                       // if shape
-                                          std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8},          // if data
-                                          PartialShape {2, 2, 2},                       // else shape
-                                          std::vector<float> {11, 12, 13, 14, 15, 16, 17, 18},  // else data
-                                          std::vector<float> {11, 2, 3, 14, 15, 6, 17, 8}),     // expected output data
+                             SelectParams(element::i32,                                // if/else/output data type
+                                          op::AutoBroadcastType::NONE,                 // broadcasting type
+                                          PartialShape{2, 2, 2},                       // select shape
+                                          std::vector<char>{0, 1, 1, 0, 0, 1, 0, 1},   // select data
+                                          PartialShape{2, 2, 2},                       // if shape
+                                          std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8},  // if data
+                                          PartialShape{2, 2, 2},                       // else shape
+                                          std::vector<float>{11, 12, 13, 14, 15, 16, 17, 18},  // else data
+                                          std::vector<float>{11, 2, 3, 14, 15, 6, 17, 8}),     // expected output data
                              // fp32, numpy brodcasting
-                             SelectParams(element::f32,                                         // if/else/output data type
-                                          op::AutoBroadcastType::NUMPY,                 // broadcasting type
-                                          PartialShape {4},                             // select shape
-                                          std::vector<char> {0, 1, 1, 0},                       // select data
-                                          PartialShape {4},                             // if shape
-                                          std::vector<float> {1, 2, 3, 4},                      // if data
-                                          PartialShape {2, 4},                          // else shape
-                                          std::vector<float> {11, 12, 13, 14, 15, 16, 17, 18},  // else data
-                                          std::vector<float> {11, 2, 3, 14, 15, 2, 3, 18}),     // expected output data
+                             SelectParams(element::f32,                    // if/else/output data type
+                                          op::AutoBroadcastType::NUMPY,    // broadcasting type
+                                          PartialShape{4},                 // select shape
+                                          std::vector<char>{0, 1, 1, 0},   // select data
+                                          PartialShape{4},                 // if shape
+                                          std::vector<float>{1, 2, 3, 4},  // if data
+                                          PartialShape{2, 4},              // else shape
+                                          std::vector<float>{11, 12, 13, 14, 15, 16, 17, 18},  // else data
+                                          std::vector<float>{11, 2, 3, 14, 15, 2, 3, 18}),     // expected output data
                              // i32, numpy brodcasting
-                             SelectParams(element::i32,                                         // if/else/output data type
-                                          op::AutoBroadcastType::NUMPY,                 // broadcasting type
-                                          PartialShape {4},                             // select shape
-                                          std::vector<char> {0, 1, 1, 0},                       // select data
-                                          PartialShape {4},                             // if shape
-                                          std::vector<float> {1, 2, 3, 4},                      // if data
-                                          PartialShape {2, 4},                          // else shape
-                                          std::vector<float> {11, 12, 13, 14, 15, 16, 17, 18},  // else data
-                                          std::vector<float> {11, 2, 3, 14, 15, 2, 3, 18}),     // expected output data
+                             SelectParams(element::i32,                    // if/else/output data type
+                                          op::AutoBroadcastType::NUMPY,    // broadcasting type
+                                          PartialShape{4},                 // select shape
+                                          std::vector<char>{0, 1, 1, 0},   // select data
+                                          PartialShape{4},                 // if shape
+                                          std::vector<float>{1, 2, 3, 4},  // if data
+                                          PartialShape{2, 4},              // else shape
+                                          std::vector<float>{11, 12, 13, 14, 15, 16, 17, 18},  // else data
+                                          std::vector<float>{11, 2, 3, 14, 15, 2, 3, 18}),     // expected output data
                              // fp32, pdpd brodcasting
-                             SelectParams(element::f32,                                       // if/else/output data type
-                                          {op::AutoBroadcastType::PDPD, -1},                  // broadcasting type
-                                          PartialShape {2, 4},                        // select shape
-                                          std::vector<char> {0, 0, 0, 0, 0, 1, 1, 1},         // select data
-                                          PartialShape {2, 4},                        // if shape
-                                          std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8},        // if data
-                                          PartialShape {4},                           // else shape
-                                          std::vector<float> {11, 12, 13, 14},                // else data
-                                          std::vector<float> {11, 12, 13, 14, 11, 6, 7, 8}),  // expected output data
+                             SelectParams(element::f32,                                      // if/else/output data type
+                                          {op::AutoBroadcastType::PDPD, -1},                 // broadcasting type
+                                          PartialShape{2, 4},                                // select shape
+                                          std::vector<char>{0, 0, 0, 0, 0, 1, 1, 1},         // select data
+                                          PartialShape{2, 4},                                // if shape
+                                          std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8},        // if data
+                                          PartialShape{4},                                   // else shape
+                                          std::vector<float>{11, 12, 13, 14},                // else data
+                                          std::vector<float>{11, 12, 13, 14, 11, 6, 7, 8}),  // expected output data
                              // i32, pdpd brodcasting
-                             SelectParams(element::i32,                                        // if/else/output data type
-                                          {op::AutoBroadcastType::PDPD, -1},                   // broadcasting type
-                                          PartialShape {2, 4},                         // select shape
-                                          std::vector<char> {0, 0, 0, 0, 0, 1, 1, 1},          // select data
-                                          PartialShape {2, 4},                         // if shape
-                                          std::vector<float> {1, 2, 3, 4, 5, 6, 7, 8},         // if data
-                                          PartialShape {4},                            // else shape
-                                          std::vector<float> {11, 12, 13, 14},                 // else data
-                                          std::vector<float> {11, 12, 13, 14, 11, 6, 7, 8})),  // expected output data
+                             SelectParams(element::i32,                                // if/else/output data type
+                                          {op::AutoBroadcastType::PDPD, -1},           // broadcasting type
+                                          PartialShape{2, 4},                          // select shape
+                                          std::vector<char>{0, 0, 0, 0, 0, 1, 1, 1},   // select data
+                                          PartialShape{2, 4},                          // if shape
+                                          std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8},  // if data
+                                          PartialShape{4},                             // else shape
+                                          std::vector<float>{11, 12, 13, 14},          // else data
+                                          std::vector<float>{11, 12, 13, 14, 11, 6, 7, 8})),  // expected output data
                          ReferenceSelectLayerTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/op_reference/selu.cpp b/src/plugins/template/tests/functional/op_reference/selu.cpp
index af3ced366ae525..5feecc16b82b23 100644
--- a/src/plugins/template/tests/functional/op_reference/selu.cpp
+++ b/src/plugins/template/tests/functional/op_reference/selu.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/selu.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/selu.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,10 +14,15 @@ using namespace ov;
 namespace {
 struct SeluParams {
     template <class IT>
-    SeluParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
-                const ov::Shape& alphaShape, const ov::Shape& lambdaShape,
-                const std::vector<IT>& alphaValues, const std::vector<IT>& lambdaValues,
-                const std::string& test_name = "")
+    SeluParams(const ov::PartialShape& shape,
+               const ov::element::Type& iType,
+               const std::vector<IT>& iValues,
+               const std::vector<IT>& oValues,
+               const ov::Shape& alphaShape,
+               const ov::Shape& lambdaShape,
+               const std::vector<IT>& alphaValues,
+               const std::vector<IT>& lambdaValues,
+               const std::string& test_name = "")
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -71,7 +77,7 @@ class ReferenceSeluLayerTest : public testing::TestWithParam<SeluParams>, public
         const auto alpha = std::make_shared<op::v0::Parameter>(params.inType, params.alphaShape);
         const auto lambda = std::make_shared<op::v0::Parameter>(params.inType, params.lambdaShape);
         const auto Selu = std::make_shared<op::v0::Selu>(in, alpha, lambda);
-        return std::make_shared<ov::Model>(NodeVector {Selu}, ParameterVector {in, alpha, lambda});
+        return std::make_shared<ov::Model>(NodeVector{Selu}, ParameterVector{in, alpha, lambda});
     }
 };
 
@@ -83,49 +89,45 @@ template <element::Type_t IN_ET>
 std::vector<SeluParams> generateSeluFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<SeluParams> seluParams {
-        SeluParams(ov::PartialShape {2},
-                    IN_ET,
-                    std::vector<T>{-1, 3},
-                    std::vector<T>{-1.1113307, 3.152103},
-                    ov::Shape {1},
-                    ov::Shape {1},
-                    std::vector<T>{1.67326324},
-                    std::vector<T>{1.05070098}),
-        SeluParams(ov::PartialShape {4},
-                    IN_ET,
-                    std::vector<T>{-1.0, 0.0, 1.0, 2.0},
-                    std::vector<T>{-1.1113307, 0., 1.050701, 2.101402},
-                    ov::Shape {1},
-                    ov::Shape {1},
-                    std::vector<T>{1.67326324},
-                    std::vector<T>{1.05070098}),
-        SeluParams(ov::PartialShape {1},
-                    IN_ET,
-                    std::vector<T>{112.0},
-                    std::vector<T>{117.67851},
-                    ov::Shape {1},
-                    ov::Shape {1},
-                    std::vector<T>{1.67326324},
-                    std::vector<T>{1.05070098}),
-        SeluParams(ov::PartialShape {3},
-                    IN_ET,
-                    std::vector<T>{-3.0, -12.5, -7.0},
-                    std::vector<T>{-1.6705687, -1.7580928, -1.7564961},
-                    ov::Shape {1},
-                    ov::Shape {1},
-                    std::vector<T>{1.67326324},
-                    std::vector<T>{1.05070098})
-    };
+    std::vector<SeluParams> seluParams{SeluParams(ov::PartialShape{2},
+                                                  IN_ET,
+                                                  std::vector<T>{-1, 3},
+                                                  std::vector<T>{-1.1113307, 3.152103},
+                                                  ov::Shape{1},
+                                                  ov::Shape{1},
+                                                  std::vector<T>{1.67326324},
+                                                  std::vector<T>{1.05070098}),
+                                       SeluParams(ov::PartialShape{4},
+                                                  IN_ET,
+                                                  std::vector<T>{-1.0, 0.0, 1.0, 2.0},
+                                                  std::vector<T>{-1.1113307, 0., 1.050701, 2.101402},
+                                                  ov::Shape{1},
+                                                  ov::Shape{1},
+                                                  std::vector<T>{1.67326324},
+                                                  std::vector<T>{1.05070098}),
+                                       SeluParams(ov::PartialShape{1},
+                                                  IN_ET,
+                                                  std::vector<T>{112.0},
+                                                  std::vector<T>{117.67851},
+                                                  ov::Shape{1},
+                                                  ov::Shape{1},
+                                                  std::vector<T>{1.67326324},
+                                                  std::vector<T>{1.05070098}),
+                                       SeluParams(ov::PartialShape{3},
+                                                  IN_ET,
+                                                  std::vector<T>{-3.0, -12.5, -7.0},
+                                                  std::vector<T>{-1.6705687, -1.7580928, -1.7564961},
+                                                  ov::Shape{1},
+                                                  ov::Shape{1},
+                                                  std::vector<T>{1.67326324},
+                                                  std::vector<T>{1.05070098})};
     return seluParams;
 }
 
 std::vector<SeluParams> generateSeluCombinedParams() {
-    const std::vector<std::vector<SeluParams>> seluTypeParams {
-        generateSeluFloatParams<element::Type_t::f32>(),
-        generateSeluFloatParams<element::Type_t::f16>(),
-        generateSeluFloatParams<element::Type_t::bf16>()
-        };
+    const std::vector<std::vector<SeluParams>> seluTypeParams{generateSeluFloatParams<element::Type_t::f32>(),
+                                                              generateSeluFloatParams<element::Type_t::f16>(),
+                                                              generateSeluFloatParams<element::Type_t::bf16>()};
     std::vector<SeluParams> combinedParams;
 
     for (const auto& params : seluTypeParams) {
@@ -134,7 +136,9 @@ std::vector<SeluParams> generateSeluCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Selu_With_Hardcoded_Refs, ReferenceSeluLayerTest,
-    testing::ValuesIn(generateSeluCombinedParams()), ReferenceSeluLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Selu_With_Hardcoded_Refs,
+                         ReferenceSeluLayerTest,
+                         testing::ValuesIn(generateSeluCombinedParams()),
+                         ReferenceSeluLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/shape_of.cpp b/src/plugins/template/tests/functional/op_reference/shape_of.cpp
index 4068544f48c9a6..70069c2b9adec5 100644
--- a/src/plugins/template/tests/functional/op_reference/shape_of.cpp
+++ b/src/plugins/template/tests/functional/op_reference/shape_of.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/shape_of.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/shape_of.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -16,11 +17,11 @@ namespace {
 struct ShapeOfParamsV1 {
     template <class IT, class OT>
     ShapeOfParamsV1(const Shape& input_shape,
-                  const Shape& expected_shape,
-                  const element::Type& input_type,
-                  const element::Type& expected_type,
-                  const std::vector<IT>& input_value,
-                  const std::vector<OT>& expected_value)
+                    const Shape& expected_shape,
+                    const element::Type& input_type,
+                    const element::Type& expected_type,
+                    const std::vector<IT>& input_value,
+                    const std::vector<OT>& expected_value)
         : m_input_shape(input_shape),
           m_expected_shape(expected_shape),
           m_input_type(input_type),
@@ -139,19 +140,8 @@ std::vector<ShapeOfParamsV1> generateParamsForShapeOfSmall_V1() {
     using T2 = typename element_type_traits<OT>::value_type;
 
     std::vector<ShapeOfParamsV1> params{
-        ShapeOfParamsV1(Shape{2},
-                      Shape{1},
-                      IT,
-                      OT,
-                      std::vector<T1>{2, 0},
-                      std::vector<T2>{2}),
-        ShapeOfParamsV1(Shape{2, 4},
-                      Shape{2},
-                      IT,
-                      OT,
-                      std::vector<T1>{2 * 4, 0},
-                      std::vector<T2>{2, 4})
-    };
+        ShapeOfParamsV1(Shape{2}, Shape{1}, IT, OT, std::vector<T1>{2, 0}, std::vector<T2>{2}),
+        ShapeOfParamsV1(Shape{2, 4}, Shape{2}, IT, OT, std::vector<T1>{2 * 4, 0}, std::vector<T2>{2, 4})};
 
     return params;
 }
@@ -162,18 +152,8 @@ std::vector<ShapeOfParamsV1> generateParamsForShapeOfBig_V1() {
     using T2 = typename element_type_traits<OT>::value_type;
 
     std::vector<ShapeOfParamsV1> params{
-        ShapeOfParamsV1(Shape{2},
-                        Shape{1},
-                        IT,
-                        OT,
-                        std::vector<T1>{2, 0},
-                        std::vector<T2>{2}),
-        ShapeOfParamsV1(Shape{2, 4},
-                        Shape{2},
-                        IT,
-                        OT,
-                        std::vector<T1>{2 * 4, 0},
-                        std::vector<T2>{2, 4}),
+        ShapeOfParamsV1(Shape{2}, Shape{1}, IT, OT, std::vector<T1>{2, 0}, std::vector<T2>{2}),
+        ShapeOfParamsV1(Shape{2, 4}, Shape{2}, IT, OT, std::vector<T1>{2 * 4, 0}, std::vector<T2>{2, 4}),
         ShapeOfParamsV1(Shape{2, 4, 8, 16, 32},
                         Shape{5},
                         IT,
@@ -190,24 +170,22 @@ std::vector<ShapeOfParamsV3> generateParamsForShapeOfSmall_V3() {
     using T2 = typename element_type_traits<OT1>::value_type;
     using T3 = typename element_type_traits<OT2>::value_type;
 
-    std::vector<ShapeOfParamsV3> params{
-        ShapeOfParamsV3(Shape{2},
-                        Shape{1},
-                        IT,
-                        OT1,
-                        OT2,
-                        std::vector<T1>{2, 0},
-                        std::vector<T2>{2},
-                        std::vector<T3>{2}),
-        ShapeOfParamsV3(Shape{2, 4},
-                      Shape{2},
-                      IT,
-                      OT1,
-                      OT2,
-                      std::vector<T1>{2 * 4, 0},
-                      std::vector<T2>{2, 4},
-                      std::vector<T3>{2, 4})
-    };
+    std::vector<ShapeOfParamsV3> params{ShapeOfParamsV3(Shape{2},
+                                                        Shape{1},
+                                                        IT,
+                                                        OT1,
+                                                        OT2,
+                                                        std::vector<T1>{2, 0},
+                                                        std::vector<T2>{2},
+                                                        std::vector<T3>{2}),
+                                        ShapeOfParamsV3(Shape{2, 4},
+                                                        Shape{2},
+                                                        IT,
+                                                        OT1,
+                                                        OT2,
+                                                        std::vector<T1>{2 * 4, 0},
+                                                        std::vector<T2>{2, 4},
+                                                        std::vector<T3>{2, 4})};
 
     return params;
 }
@@ -218,32 +196,30 @@ std::vector<ShapeOfParamsV3> generateParamsForShapeOfBig_V3() {
     using T2 = typename element_type_traits<OT1>::value_type;
     using T3 = typename element_type_traits<OT2>::value_type;
 
-    std::vector<ShapeOfParamsV3> params{
-        ShapeOfParamsV3(Shape{2},
-                        Shape{1},
-                        IT,
-                        OT1,
-                        OT2,
-                        std::vector<T1>{2, 0},
-                        std::vector<T2>{2},
-                        std::vector<T3>{2}),
-        ShapeOfParamsV3(Shape{2, 4},
-                      Shape{2},
-                      IT,
-                      OT1,
-                      OT2,
-                      std::vector<T1>{2 * 4, 0},
-                      std::vector<T2>{2, 4},
-                      std::vector<T3>{2, 4}),
-        ShapeOfParamsV3(Shape{2, 4, 8, 16, 32},
-                      Shape{5},
-                      IT,
-                      OT1,
-                      OT2,
-                      std::vector<T1>{2 * 4 * 8 * 16 * 32, 0},
-                      std::vector<T2>{2, 4, 8, 16, 32},
-                      std::vector<T3>{2, 4, 8, 16, 32})
-    };
+    std::vector<ShapeOfParamsV3> params{ShapeOfParamsV3(Shape{2},
+                                                        Shape{1},
+                                                        IT,
+                                                        OT1,
+                                                        OT2,
+                                                        std::vector<T1>{2, 0},
+                                                        std::vector<T2>{2},
+                                                        std::vector<T3>{2}),
+                                        ShapeOfParamsV3(Shape{2, 4},
+                                                        Shape{2},
+                                                        IT,
+                                                        OT1,
+                                                        OT2,
+                                                        std::vector<T1>{2 * 4, 0},
+                                                        std::vector<T2>{2, 4},
+                                                        std::vector<T3>{2, 4}),
+                                        ShapeOfParamsV3(Shape{2, 4, 8, 16, 32},
+                                                        Shape{5},
+                                                        IT,
+                                                        OT1,
+                                                        OT2,
+                                                        std::vector<T1>{2 * 4 * 8 * 16 * 32, 0},
+                                                        std::vector<T2>{2, 4, 8, 16, 32},
+                                                        std::vector<T3>{2, 4, 8, 16, 32})};
 
     return params;
 }
@@ -260,8 +236,7 @@ std::vector<ShapeOfParamsV1> generateCombinedParamsForShapeOfV1() {
         generateParamsForShapeOfSmall_V1<element::Type_t::i16, element::Type_t::i64>(),
         generateParamsForShapeOfSmall_V1<element::Type_t::i8, element::Type_t::i64>(),
         generateParamsForShapeOfSmall_V1<element::Type_t::u16, element::Type_t::i64>(),
-        generateParamsForShapeOfSmall_V1<element::Type_t::u8, element::Type_t::i64>()
-    };
+        generateParamsForShapeOfSmall_V1<element::Type_t::u8, element::Type_t::i64>()};
 
     std::vector<ShapeOfParamsV1> combinedParams;
 
@@ -284,8 +259,7 @@ std::vector<ShapeOfParamsV3> generateCombinedParamsForShapeOfV3() {
         generateParamsForShapeOfSmall_V3<element::Type_t::i16, element::Type_t::i64, element::Type_t::i32>(),
         generateParamsForShapeOfSmall_V3<element::Type_t::i8, element::Type_t::i64, element::Type_t::i32>(),
         generateParamsForShapeOfSmall_V3<element::Type_t::u16, element::Type_t::i64, element::Type_t::i32>(),
-        generateParamsForShapeOfSmall_V3<element::Type_t::u8, element::Type_t::i64, element::Type_t::i32>()
-    };
+        generateParamsForShapeOfSmall_V3<element::Type_t::u8, element::Type_t::i64, element::Type_t::i32>()};
 
     std::vector<ShapeOfParamsV3> combinedParams;
 
@@ -296,16 +270,14 @@ std::vector<ShapeOfParamsV3> generateCombinedParamsForShapeOfV3() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_ShapeOf_With_Hardcoded_Refs,
-    ReferenceShapeOfV1LayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForShapeOfV1()),
-    ReferenceShapeOfV1LayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_ShapeOf_With_Hardcoded_Refs,
-    ReferenceShapeOfV3LayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForShapeOfV3()),
-    ReferenceShapeOfV3LayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_ShapeOf_With_Hardcoded_Refs,
+                         ReferenceShapeOfV1LayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForShapeOfV1()),
+                         ReferenceShapeOfV1LayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_ShapeOf_With_Hardcoded_Refs,
+                         ReferenceShapeOfV3LayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForShapeOfV3()),
+                         ReferenceShapeOfV3LayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/shuffle_channels.cpp b/src/plugins/template/tests/functional/op_reference/shuffle_channels.cpp
index 26ccdbe3dcaf9f..7b605e62680c73 100644
--- a/src/plugins/template/tests/functional/op_reference/shuffle_channels.cpp
+++ b/src/plugins/template/tests/functional/op_reference/shuffle_channels.cpp
@@ -4,18 +4,24 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct ShuffleChannelsParams {
-    ShuffleChannelsParams(const reference_tests::Tensor& dataTensor, const int32_t axis, const int32_t group,
-               const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-               dataTensor(dataTensor), axis(axis), group(group),
-               expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    ShuffleChannelsParams(const reference_tests::Tensor& dataTensor,
+                          const int32_t axis,
+                          const int32_t group,
+                          const reference_tests::Tensor& expectedTensor,
+                          const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          axis(axis),
+          group(group),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     int32_t axis;
@@ -24,7 +30,8 @@ struct ShuffleChannelsParams {
     std::string testcaseName;
 };
 
-class ReferenceShuffleChannelsLayerTest : public testing::TestWithParam<ShuffleChannelsParams>, public CommonReferenceTest {
+class ReferenceShuffleChannelsLayerTest : public testing::TestWithParam<ShuffleChannelsParams>,
+                                          public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -54,7 +61,7 @@ class ReferenceShuffleChannelsLayerTest : public testing::TestWithParam<ShuffleC
     static std::shared_ptr<Model> CreateFunction(const ShuffleChannelsParams& params) {
         const auto data = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto function = std::make_shared<opset1::ShuffleChannels>(data, params.axis, params.group);
-        return std::make_shared<Model>(NodeVector {function}, ParameterVector {data});
+        return std::make_shared<Model>(NodeVector{function}, ParameterVector{data});
     }
 };
 
@@ -65,42 +72,49 @@ TEST_P(ReferenceShuffleChannelsLayerTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<ShuffleChannelsParams> generateParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<ShuffleChannelsParams> params {
+    std::vector<ShuffleChannelsParams> params{
         // shuffle_channels_simple
         ShuffleChannelsParams(
-            reference_tests::Tensor({1, 15, 2, 2}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
+            reference_tests::Tensor(
+                {1, 15, 2, 2},
+                IN_ET,
+                std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                               20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                               40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
             1,
             5,
-            reference_tests::Tensor({1, 15, 2, 2}, IN_ET, std::vector<T>{
-                0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
-                4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
-                8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
+            reference_tests::Tensor(
+                {1, 15, 2, 2},
+                IN_ET,
+                std::vector<T>{0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
+                               4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
+                               8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
             "shuffle_channels_simple"),
 
         // shuffle_channels_negative_axis
         ShuffleChannelsParams(
-            reference_tests::Tensor({15, 2, 1, 2}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
+            reference_tests::Tensor(
+                {15, 2, 1, 2},
+                IN_ET,
+                std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                               20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                               40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
             -4,
             5,
-            reference_tests::Tensor({15, 2, 1, 2}, IN_ET, std::vector<T>{
-                0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
-                4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
-                8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
+            reference_tests::Tensor(
+                {15, 2, 1, 2},
+                IN_ET,
+                std::vector<T>{0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
+                               4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
+                               8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
             "shuffle_channels_negative_axis"),
 
         // shuffle_channels_float
-        ShuffleChannelsParams(
-            reference_tests::Tensor({6, 1, 1, 1}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5}),
-            0,
-            2,
-            reference_tests::Tensor({6, 1, 1, 1}, IN_ET, std::vector<T>{0, 3, 1, 4, 2, 5}),
-            "shuffle_channels_float"),
+        ShuffleChannelsParams(reference_tests::Tensor({6, 1, 1, 1}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5}),
+                              0,
+                              2,
+                              reference_tests::Tensor({6, 1, 1, 1}, IN_ET, std::vector<T>{0, 3, 1, 4, 2, 5}),
+                              "shuffle_channels_float"),
 
         // shuffle_channels_1d
         ShuffleChannelsParams(
@@ -112,77 +126,83 @@ std::vector<ShuffleChannelsParams> generateParams() {
 
         // shuffle_channels_2d
         ShuffleChannelsParams(
-            reference_tests::Tensor({15, 4}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
+            reference_tests::Tensor({15, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
+                                                                   12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
+                                                                   24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
+                                                                   36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
+                                                                   48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
             0,
             5,
-            reference_tests::Tensor({15, 4}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38,
-                39, 48, 49, 50, 51, 4,  5,  6,  7,  16, 17, 18, 19, 28, 29,
-                30, 31, 40, 41, 42, 43, 52, 53, 54, 55, 8,  9,  10, 11, 20,
-                21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
+            reference_tests::Tensor({15, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  12, 13, 14, 15, 24, 25, 26, 27,
+                                                                   36, 37, 38, 39, 48, 49, 50, 51, 4,  5,  6,  7,
+                                                                   16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43,
+                                                                   52, 53, 54, 55, 8,  9,  10, 11, 20, 21, 22, 23,
+                                                                   32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
             "shuffle_channels_2d"),
 
         // shuffle_channels_3d
         ShuffleChannelsParams(
-            reference_tests::Tensor({15, 2, 2}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
+            reference_tests::Tensor({15, 2, 2}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
+                                                                      12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
+                                                                      24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
+                                                                      36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
+                                                                      48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
             0,
             5,
-            reference_tests::Tensor({15, 2, 2}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38,
-                39, 48, 49, 50, 51, 4,  5,  6,  7,  16, 17, 18, 19, 28, 29,
-                30, 31, 40, 41, 42, 43, 52, 53, 54, 55, 8,  9,  10, 11, 20,
-                21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
+            reference_tests::Tensor({15, 2, 2}, IN_ET, std::vector<T>{0,  1,  2,  3,  12, 13, 14, 15, 24, 25, 26, 27,
+                                                                      36, 37, 38, 39, 48, 49, 50, 51, 4,  5,  6,  7,
+                                                                      16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43,
+                                                                      52, 53, 54, 55, 8,  9,  10, 11, 20, 21, 22, 23,
+                                                                      32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
             "shuffle_channels_3d"),
 
         // shuffle_channels_5d
         ShuffleChannelsParams(
-            reference_tests::Tensor({2, 2, 15, 2, 2}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
-
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
-
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
-
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
+            reference_tests::Tensor(
+                {2, 2, 15, 2, 2},
+                IN_ET,
+                std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                               20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                               40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+
+                               0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                               20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                               40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+
+                               0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                               20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                               40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+
+                               0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                               20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                               40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59}),
             2,
             5,
-            reference_tests::Tensor({2, 2, 15, 2, 2}, IN_ET, std::vector<T>{
-                0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
-                4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
-                8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59,
-
-                0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
-                4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
-                8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59,
-
-                0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
-                4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
-                8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59,
-
-                0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
-                4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
-                8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
+            reference_tests::Tensor(
+                {2, 2, 15, 2, 2},
+                IN_ET,
+                std::vector<T>{0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
+                               4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
+                               8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59,
+
+                               0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
+                               4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
+                               8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59,
+
+                               0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
+                               4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
+                               8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59,
+
+                               0, 1, 2,  3,  12, 13, 14, 15, 24, 25, 26, 27, 36, 37, 38, 39, 48, 49, 50, 51,
+                               4, 5, 6,  7,  16, 17, 18, 19, 28, 29, 30, 31, 40, 41, 42, 43, 52, 53, 54, 55,
+                               8, 9, 10, 11, 20, 21, 22, 23, 32, 33, 34, 35, 44, 45, 46, 47, 56, 57, 58, 59}),
             "shuffle_channels_5d"),
     };
     return params;
 }
 
 std::vector<ShuffleChannelsParams> generateShuffleChannelsCombinedParams() {
-    const std::vector<std::vector<ShuffleChannelsParams>> generatedParams {
+    const std::vector<std::vector<ShuffleChannelsParams>> generatedParams{
         generateParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
         generateParams<element::Type_t::i32>(),
@@ -204,6 +224,8 @@ std::vector<ShuffleChannelsParams> generateShuffleChannelsCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_ShuffleChannels_With_Hardcoded_Refs, ReferenceShuffleChannelsLayerTest,
-    testing::ValuesIn(generateShuffleChannelsCombinedParams()), ReferenceShuffleChannelsLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_ShuffleChannels_With_Hardcoded_Refs,
+                         ReferenceShuffleChannelsLayerTest,
+                         testing::ValuesIn(generateShuffleChannelsCombinedParams()),
+                         ReferenceShuffleChannelsLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/sigmoid.cpp b/src/plugins/template/tests/functional/op_reference/sigmoid.cpp
index e82d8b5aa45e58..b8f29219783684 100644
--- a/src/plugins/template/tests/functional/op_reference/sigmoid.cpp
+++ b/src/plugins/template/tests/functional/op_reference/sigmoid.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/sigmoid.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/sigmoid.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,7 +14,10 @@ using namespace ov;
 namespace {
 struct SigmoidParams {
     template <class IT>
-    SigmoidParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    SigmoidParams(const ov::PartialShape& shape,
+                  const ov::element::Type& iType,
+                  const std::vector<IT>& iValues,
+                  const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -45,11 +49,12 @@ class ReferenceSigmoidLayerTest : public testing::TestWithParam<SigmoidParams>,
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& Sigmoidected_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& Sigmoidected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Sigmoid = std::make_shared<op::v0::Sigmoid>(in);
-        return std::make_shared<ov::Model>(NodeVector {Sigmoid}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Sigmoid}, ParameterVector{in});
     }
 };
 
@@ -57,7 +62,6 @@ TEST_P(ReferenceSigmoidLayerTest, CompareWithRefs) {
     Exec();
 }
 
-
 template <element::Type_t IN_ET>
 std::vector<SigmoidParams> generateSigmoidFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
@@ -67,16 +71,14 @@ std::vector<SigmoidParams> generateSigmoidFloatParams() {
     float sigma1 = 1.0f / (1.0f + std::exp(-x1));
     float sigma2 = 1.0f / (1.0f + std::exp(-x2));
 
-    std::vector<SigmoidParams> sigmoidParams {
-        SigmoidParams(ov::PartialShape {1, 1, 2, 2},
-                    IN_ET,
-                    std::vector<T>{x1, x2, x1, x2},
-                    std::vector<T>{sigma1, sigma2, sigma1, sigma2}),
-        SigmoidParams(ov::PartialShape {1, 1, 4},
-                    IN_ET,
-                    std::vector<T>{x1, x2, x1, x2},
-                    std::vector<T>{sigma1, sigma2, sigma1, sigma2})
-    };
+    std::vector<SigmoidParams> sigmoidParams{SigmoidParams(ov::PartialShape{1, 1, 2, 2},
+                                                           IN_ET,
+                                                           std::vector<T>{x1, x2, x1, x2},
+                                                           std::vector<T>{sigma1, sigma2, sigma1, sigma2}),
+                                             SigmoidParams(ov::PartialShape{1, 1, 4},
+                                                           IN_ET,
+                                                           std::vector<T>{x1, x2, x1, x2},
+                                                           std::vector<T>{sigma1, sigma2, sigma1, sigma2})};
     return sigmoidParams;
 }
 
@@ -84,16 +86,9 @@ template <element::Type_t IN_ET>
 std::vector<SigmoidParams> generateSigmoidIntParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<SigmoidParams> sigmoidParams {
-        SigmoidParams(ov::PartialShape {1, 1, 2, 2},
-                    IN_ET,
-                    std::vector<T>{1, 4, -1, -4},
-                    std::vector<T>{1, 1, 0, 0}),
-        SigmoidParams(ov::PartialShape {1, 1, 4},
-                    IN_ET,
-                    std::vector<T>{1, 4, -1, -4},
-                    std::vector<T>{1, 1, 0, 0})
-    };
+    std::vector<SigmoidParams> sigmoidParams{
+        SigmoidParams(ov::PartialShape{1, 1, 2, 2}, IN_ET, std::vector<T>{1, 4, -1, -4}, std::vector<T>{1, 1, 0, 0}),
+        SigmoidParams(ov::PartialShape{1, 1, 4}, IN_ET, std::vector<T>{1, 4, -1, -4}, std::vector<T>{1, 1, 0, 0})};
     return sigmoidParams;
 }
 
@@ -101,28 +96,19 @@ template <element::Type_t IN_ET>
 std::vector<SigmoidParams> generateSigmoidUintParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<SigmoidParams> sigmoidParams {
-        SigmoidParams(ov::PartialShape {1, 1, 2, 2},
-                    IN_ET,
-                    std::vector<T>{1, 4, 1, 4},
-                    std::vector<T>{1, 1, 1, 1}),
-        SigmoidParams(ov::PartialShape {1, 1, 4},
-                    IN_ET,
-                    std::vector<T>{1, 4, 1, 4},
-                    std::vector<T>{1, 1, 1, 1})
-    };
+    std::vector<SigmoidParams> sigmoidParams{
+        SigmoidParams(ov::PartialShape{1, 1, 2, 2}, IN_ET, std::vector<T>{1, 4, 1, 4}, std::vector<T>{1, 1, 1, 1}),
+        SigmoidParams(ov::PartialShape{1, 1, 4}, IN_ET, std::vector<T>{1, 4, 1, 4}, std::vector<T>{1, 1, 1, 1})};
     return sigmoidParams;
 }
 
 std::vector<SigmoidParams> generateSigmoidCombinedParams() {
-    const std::vector<std::vector<SigmoidParams>> sigmoidTypeParams {
-        generateSigmoidFloatParams<element::Type_t::f32>(),
-        generateSigmoidFloatParams<element::Type_t::f16>(),
-        generateSigmoidIntParams<element::Type_t::i64>(),
-        generateSigmoidIntParams<element::Type_t::i32>(),
-        generateSigmoidUintParams<element::Type_t::u64>(),
-        generateSigmoidUintParams<element::Type_t::u32>()
-        };
+    const std::vector<std::vector<SigmoidParams>> sigmoidTypeParams{generateSigmoidFloatParams<element::Type_t::f32>(),
+                                                                    generateSigmoidFloatParams<element::Type_t::f16>(),
+                                                                    generateSigmoidIntParams<element::Type_t::i64>(),
+                                                                    generateSigmoidIntParams<element::Type_t::i32>(),
+                                                                    generateSigmoidUintParams<element::Type_t::u64>(),
+                                                                    generateSigmoidUintParams<element::Type_t::u32>()};
     std::vector<SigmoidParams> combinedParams;
 
     for (const auto& params : sigmoidTypeParams) {
@@ -131,7 +117,9 @@ std::vector<SigmoidParams> generateSigmoidCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Sigmoid_With_Hardcoded_Refs, ReferenceSigmoidLayerTest,
-    testing::ValuesIn(generateSigmoidCombinedParams()), ReferenceSigmoidLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Sigmoid_With_Hardcoded_Refs,
+                         ReferenceSigmoidLayerTest,
+                         testing::ValuesIn(generateSigmoidCombinedParams()),
+                         ReferenceSigmoidLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/sign.cpp b/src/plugins/template/tests/functional/op_reference/sign.cpp
index 34ac622cb4325f..ae08360aa38eac 100644
--- a/src/plugins/template/tests/functional/op_reference/sign.cpp
+++ b/src/plugins/template/tests/functional/op_reference/sign.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/sign.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/sign.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -12,9 +13,16 @@ using namespace ov;
 
 struct SignParams {
     template <class IT, class OT>
-    SignParams(const PartialShape& shape, const element::Type& iType, const element::Type& oType, const std::vector<IT>& iValues,
-                  const std::vector<OT>& oValues)
-        : pshape(shape), inType(iType), outType(oType), inputData(CreateTensor(iType, iValues)), refData(CreateTensor(oType, oValues)) {}
+    SignParams(const PartialShape& shape,
+               const element::Type& iType,
+               const element::Type& oType,
+               const std::vector<IT>& iValues,
+               const std::vector<OT>& oValues)
+        : pshape(shape),
+          inType(iType),
+          outType(oType),
+          inputData(CreateTensor(iType, iValues)),
+          refData(CreateTensor(oType, oValues)) {}
     PartialShape pshape;
     element::Type inType;
     element::Type outType;
@@ -43,7 +51,7 @@ class ReferenceSignLayerTest : public testing::TestWithParam<SignParams>, public
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto sign = std::make_shared<op::v0::Sign>(in);
-        return std::make_shared<ov::Model>(NodeVector {sign}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{sign}, ParameterVector{in});
     }
 };
 
@@ -51,25 +59,36 @@ TEST_P(ReferenceSignLayerTest, CompareWithHardcodedRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Sign_With_Hardcoded_Refs, ReferenceSignLayerTest,
-    ::testing::Values(
-        SignParams(PartialShape {6}, element::f32, element::f32,
-                      std::vector<float> {1, -2, 0, -4.8f, 4.8f, -0.0f},
-                      std::vector<float> {1, -1, 0, -1, 1, 0}),
-        SignParams(PartialShape {6}, element::f16, element::f16,
-                      std::vector<float16> {1, -2, 0, -4.8f, 4.8f, -0.0f},
-                      std::vector<float16> {1, -1, 0, -1, 1, 0}),
-        SignParams(PartialShape {6}, element::u64, element::u64,
-                      std::vector<uint64_t> {1, 2, 0, 4, 4, 0},
-                      std::vector<uint64_t> {1, 1, 0, 1, 1, 0}),
-        SignParams(PartialShape {6}, element::u32, element::u32,
-                      std::vector<uint32_t> {1, 2, 0, 4, 4, 0},
-                      std::vector<uint32_t> {1, 1, 0, 1, 1, 0}),
-        SignParams(PartialShape {6}, element::i32, element::i32,
-                      std::vector<int32_t> {1, -2, 0, -4, 4, -0},
-                      std::vector<int32_t> {1, -1, 0, -1, 1, 0}),
-        SignParams(PartialShape {6}, element::i64, element::i64,
-                      std::vector<int64_t> {1, -2, 0, -4, 4, -0},
-                      std::vector<int64_t> {1, -1, 0, -1, 1, 0})),
-    ReferenceSignLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Sign_With_Hardcoded_Refs,
+                         ReferenceSignLayerTest,
+                         ::testing::Values(SignParams(PartialShape{6},
+                                                      element::f32,
+                                                      element::f32,
+                                                      std::vector<float>{1, -2, 0, -4.8f, 4.8f, -0.0f},
+                                                      std::vector<float>{1, -1, 0, -1, 1, 0}),
+                                           SignParams(PartialShape{6},
+                                                      element::f16,
+                                                      element::f16,
+                                                      std::vector<float16>{1, -2, 0, -4.8f, 4.8f, -0.0f},
+                                                      std::vector<float16>{1, -1, 0, -1, 1, 0}),
+                                           SignParams(PartialShape{6},
+                                                      element::u64,
+                                                      element::u64,
+                                                      std::vector<uint64_t>{1, 2, 0, 4, 4, 0},
+                                                      std::vector<uint64_t>{1, 1, 0, 1, 1, 0}),
+                                           SignParams(PartialShape{6},
+                                                      element::u32,
+                                                      element::u32,
+                                                      std::vector<uint32_t>{1, 2, 0, 4, 4, 0},
+                                                      std::vector<uint32_t>{1, 1, 0, 1, 1, 0}),
+                                           SignParams(PartialShape{6},
+                                                      element::i32,
+                                                      element::i32,
+                                                      std::vector<int32_t>{1, -2, 0, -4, 4, -0},
+                                                      std::vector<int32_t>{1, -1, 0, -1, 1, 0}),
+                                           SignParams(PartialShape{6},
+                                                      element::i64,
+                                                      element::i64,
+                                                      std::vector<int64_t>{1, -2, 0, -4, 4, -0},
+                                                      std::vector<int64_t>{1, -1, 0, -1, 1, 0})),
+                         ReferenceSignLayerTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/op_reference/sin.cpp b/src/plugins/template/tests/functional/op_reference/sin.cpp
index 0db13c355a1a2c..e3466415bc91f0 100644
--- a/src/plugins/template/tests/functional/op_reference/sin.cpp
+++ b/src/plugins/template/tests/functional/op_reference/sin.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/sin.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/sin.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -42,7 +43,7 @@ class ReferenceSinLayerTest : public testing::TestWithParam<SinParams>, public C
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto Sin = std::make_shared<op::v0::Sin>(in);
-        return std::make_shared<ov::Model>(NodeVector {Sin}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Sin}, ParameterVector{in});
     }
 };
 
@@ -53,46 +54,55 @@ TEST_P(ReferenceSinLayerTest, SinWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Sin_With_Hardcoded_Refs, ReferenceSinLayerTest,
+    smoke_Sin_With_Hardcoded_Refs,
+    ReferenceSinLayerTest,
     ::testing::Values(
-        Builder {}
-            .input({{11}, element::f16, std::vector<ov::float16> {0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f}})
-            .expected({{11}, element::f16, std::vector<ov::float16> {0.00000000f,
-                                0.24740396f,
-                                -0.24740396f,
-                                0.47942554f,
-                                -0.47942554f,
-                                0.84147098f,
-                                -0.84147098f,
-                                0.90929743f,
-                                -0.90929743f,
-                                -0.75680250f,
-                                0.75680250f}}),
-        Builder {}
-            .input({{11}, element::f32, std::vector<float> {0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f}})
-            .expected({{11}, element::f32, std::vector<float> {0.00000000f,
-                                0.24740396f,
-                                -0.24740396f,
-                                0.47942554f,
-                                -0.47942554f,
-                                0.84147098f,
-                                -0.84147098f,
-                                0.90929743f,
-                                -0.90929743f,
-                                -0.75680250f,
-                                0.75680250f}}),
-        Builder {}
-            .input({{7}, element::i32, std::vector<int32_t> {0, 1, -1, 2, -2, 4, -4}})
-            .expected({{7}, element::i32, std::vector<int32_t> {0, 0, 0, 0, 0, 0, 0}}),
-        Builder {}
-            .input({{7}, element::i64, std::vector<int64_t> {0, 1, -1, 2, -2, 4, -4}})
-            .expected({{7}, element::i64, std::vector<int64_t> {0, 0, 0, 0, 0, 0, 0}}),
-        Builder {}
-            .input({{4}, element::u32, std::vector<uint32_t> {0, 1, 2, 4}})
-            .expected({{4}, element::u32, std::vector<uint32_t> {0, 0, 0, 0}}),
-        Builder {}
-            .input({{4}, element::u64, std::vector<uint64_t> {0, 1, 2, 4}})
-            .expected({{4}, element::u64, std::vector<uint64_t> {0, 0, 0, 0}})),
+        Builder{}
+            .input({{11},
+                    element::f16,
+                    std::vector<ov::float16>{0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{0.00000000f,
+                                                0.24740396f,
+                                                -0.24740396f,
+                                                0.47942554f,
+                                                -0.47942554f,
+                                                0.84147098f,
+                                                -0.84147098f,
+                                                0.90929743f,
+                                                -0.90929743f,
+                                                -0.75680250f,
+                                                0.75680250f}}),
+        Builder{}
+            .input({{11},
+                    element::f32,
+                    std::vector<float>{0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{0.00000000f,
+                                          0.24740396f,
+                                          -0.24740396f,
+                                          0.47942554f,
+                                          -0.47942554f,
+                                          0.84147098f,
+                                          -0.84147098f,
+                                          0.90929743f,
+                                          -0.90929743f,
+                                          -0.75680250f,
+                                          0.75680250f}}),
+        Builder{}
+            .input({{7}, element::i32, std::vector<int32_t>{0, 1, -1, 2, -2, 4, -4}})
+            .expected({{7}, element::i32, std::vector<int32_t>{0, 0, 0, 0, 0, 0, 0}}),
+        Builder{}
+            .input({{7}, element::i64, std::vector<int64_t>{0, 1, -1, 2, -2, 4, -4}})
+            .expected({{7}, element::i64, std::vector<int64_t>{0, 0, 0, 0, 0, 0, 0}}),
+        Builder{}
+            .input({{4}, element::u32, std::vector<uint32_t>{0, 1, 2, 4}})
+            .expected({{4}, element::u32, std::vector<uint32_t>{0, 0, 0, 0}}),
+        Builder{}
+            .input({{4}, element::u64, std::vector<uint64_t>{0, 1, 2, 4}})
+            .expected({{4}, element::u64, std::vector<uint64_t>{0, 0, 0, 0}})),
 
     ReferenceSinLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/sinh.cpp b/src/plugins/template/tests/functional/op_reference/sinh.cpp
index c93c6eb5c72bff..f966d08897d3b5 100644
--- a/src/plugins/template/tests/functional/op_reference/sinh.cpp
+++ b/src/plugins/template/tests/functional/op_reference/sinh.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/sinh.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/sinh.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -42,7 +43,7 @@ class ReferenceSinhLayerTest : public testing::TestWithParam<SinhParams>, public
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto Sinh = std::make_shared<op::v0::Sinh>(in);
-        return std::make_shared<ov::Model>(NodeVector {Sinh}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Sinh}, ParameterVector{in});
     }
 };
 
@@ -53,46 +54,55 @@ TEST_P(ReferenceSinhLayerTest, SinhWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Sinh_With_Hardcoded_Refs, ReferenceSinhLayerTest,
+    smoke_Sinh_With_Hardcoded_Refs,
+    ReferenceSinhLayerTest,
     ::testing::Values(
-        Builder {}
-            .input({{11}, element::f16, std::vector<ov::float16> {-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
-            .expected({{11}, element::f16, std::vector<ov::float16> {-27.28991720f,
-                            -3.62686041f,
-                            -1.17520120f,
-                            -0.52109531f,
-                            -0.25261232f,
-                            0.00000000f,
-                            0.25261232f,
-                            0.52109531f,
-                            1.17520120f,
-                            3.62686041f,
-                            27.28991720f}}),
-        Builder {}
-            .input({{11}, element::f32, std::vector<float> {-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
-            .expected({{11}, element::f32, std::vector<float> {-27.28991720f,
-                            -3.62686041f,
-                            -1.17520120f,
-                            -0.52109531f,
-                            -0.25261232f,
-                            0.00000000f,
-                            0.25261232f,
-                            0.52109531f,
-                            1.17520120f,
-                            3.62686041f,
-                            27.28991720f}}),
-        Builder {}
-            .input({{7}, element::i32, std::vector<int32_t> {-4, -2, -1, 0, 1, 2, 4}})
-            .expected({{7}, element::i32, std::vector<int32_t> {-27, -4, -1, 0, 1, 4, 27}}),
-        Builder {}
-            .input({{7}, element::i64, std::vector<int64_t> {-4, -2, -1, 0, 1, 2, 4}})
-            .expected({{7}, element::i64, std::vector<int64_t> {-27, -4, -1, 0, 1, 4, 27}}),
-        Builder {}
-            .input({{4}, element::u32, std::vector<uint32_t> {0, 1, 2, 4}})
-            .expected({{4}, element::u32, std::vector<uint32_t> {0, 1, 4, 27}}),
-        Builder {}
-            .input({{4}, element::u64, std::vector<uint64_t> {0, 1, 2, 4}})
-            .expected({{4}, element::u64, std::vector<uint64_t> {0, 1, 4, 27}})),
+        Builder{}
+            .input({{11},
+                    element::f16,
+                    std::vector<ov::float16>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{-27.28991720f,
+                                                -3.62686041f,
+                                                -1.17520120f,
+                                                -0.52109531f,
+                                                -0.25261232f,
+                                                0.00000000f,
+                                                0.25261232f,
+                                                0.52109531f,
+                                                1.17520120f,
+                                                3.62686041f,
+                                                27.28991720f}}),
+        Builder{}
+            .input({{11},
+                    element::f32,
+                    std::vector<float>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{-27.28991720f,
+                                          -3.62686041f,
+                                          -1.17520120f,
+                                          -0.52109531f,
+                                          -0.25261232f,
+                                          0.00000000f,
+                                          0.25261232f,
+                                          0.52109531f,
+                                          1.17520120f,
+                                          3.62686041f,
+                                          27.28991720f}}),
+        Builder{}
+            .input({{7}, element::i32, std::vector<int32_t>{-4, -2, -1, 0, 1, 2, 4}})
+            .expected({{7}, element::i32, std::vector<int32_t>{-27, -4, -1, 0, 1, 4, 27}}),
+        Builder{}
+            .input({{7}, element::i64, std::vector<int64_t>{-4, -2, -1, 0, 1, 2, 4}})
+            .expected({{7}, element::i64, std::vector<int64_t>{-27, -4, -1, 0, 1, 4, 27}}),
+        Builder{}
+            .input({{4}, element::u32, std::vector<uint32_t>{0, 1, 2, 4}})
+            .expected({{4}, element::u32, std::vector<uint32_t>{0, 1, 4, 27}}),
+        Builder{}
+            .input({{4}, element::u64, std::vector<uint64_t>{0, 1, 2, 4}})
+            .expected({{4}, element::u64, std::vector<uint64_t>{0, 1, 4, 27}})),
 
     ReferenceSinhLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/slice.cpp b/src/plugins/template/tests/functional/op_reference/slice.cpp
index b709cd7f1691a9..2fa64b2dd458d6 100644
--- a/src/plugins/template/tests/functional/op_reference/slice.cpp
+++ b/src/plugins/template/tests/functional/op_reference/slice.cpp
@@ -98,10 +98,10 @@ class ReferenceSliceLayerTest : public testing::TestWithParam<SliceParams>, publ
 
 private:
     static std::shared_ptr<Model> CreateFunction(const reference_tests::Tensor& data,
-                                                    const reference_tests::Tensor& start,
-                                                    const reference_tests::Tensor& stop,
-                                                    const reference_tests::Tensor& step,
-                                                    const reference_tests::Tensor& axes) {
+                                                 const reference_tests::Tensor& start,
+                                                 const reference_tests::Tensor& stop,
+                                                 const reference_tests::Tensor& step,
+                                                 const reference_tests::Tensor& axes) {
         const auto data_param = std::make_shared<opset8::Parameter>(data.type, data.shape);
         const auto start_param = std::make_shared<opset8::Parameter>(start.type, start.shape);
         const auto stop_param = std::make_shared<opset8::Parameter>(stop.type, stop.shape);
@@ -110,14 +110,14 @@ class ReferenceSliceLayerTest : public testing::TestWithParam<SliceParams>, publ
 
         const auto slice = std::make_shared<opset8::Slice>(data_param, start_param, stop_param, step_param, axes_param);
         return std::make_shared<Model>(NodeVector{slice},
-                                          ParameterVector{data_param, start_param, stop_param, step_param, axes_param});
+                                       ParameterVector{data_param, start_param, stop_param, step_param, axes_param});
     }
 
     // Default `axes` input
     static std::shared_ptr<Model> CreateFunction(const reference_tests::Tensor& data,
-                                                    const reference_tests::Tensor& start,
-                                                    const reference_tests::Tensor& stop,
-                                                    const reference_tests::Tensor& step) {
+                                                 const reference_tests::Tensor& start,
+                                                 const reference_tests::Tensor& stop,
+                                                 const reference_tests::Tensor& step) {
         const auto data_param = std::make_shared<opset8::Parameter>(data.type, data.shape);
         const auto start_param = std::make_shared<opset8::Parameter>(start.type, start.shape);
         const auto stop_param = std::make_shared<opset8::Parameter>(stop.type, stop.shape);
@@ -125,7 +125,7 @@ class ReferenceSliceLayerTest : public testing::TestWithParam<SliceParams>, publ
 
         const auto slice = std::make_shared<opset8::Slice>(data_param, start_param, stop_param, step_param);
         return std::make_shared<Model>(NodeVector{slice},
-                                          ParameterVector{data_param, start_param, stop_param, step_param});
+                                       ParameterVector{data_param, start_param, stop_param, step_param});
     }
 };
 
@@ -234,10 +234,12 @@ std::vector<SliceParams> generateSliceParamsUnsigned() {
                     reference_tests::Tensor{{4}, IND_ET, std::vector<IND_T>{4, 2, 3, 2}},
                     reference_tests::Tensor{{4}, IND_ET, std::vector<IND_T>{1, 1, 1, 1}},
                     reference_tests::Tensor{{4}, AXIS_ET, std::vector<AXIS_T>{0, 1, 2, 3}},
-                    reference_tests::Tensor{{4, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                                      12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
-                                                                      24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
-                                                                      36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47}},
+                    reference_tests::Tensor{
+                        {4, 2, 3, 2},
+                        DATA_ET,
+                        std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15,
+                                            16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
+                                            32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47}},
                     "4D_full_axes"),
         SliceParams(Tensor{{4, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
                                                                       12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
@@ -246,10 +248,12 @@ std::vector<SliceParams> generateSliceParamsUnsigned() {
                     reference_tests::Tensor{{4}, IND_ET, std::vector<IND_T>{0, 0, 0, 0}},
                     reference_tests::Tensor{{4}, IND_ET, std::vector<IND_T>{4, 2, 3, 2}},
                     reference_tests::Tensor{{4}, IND_ET, std::vector<IND_T>{1, 1, 1, 1}},
-                    reference_tests::Tensor{{4, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                                      12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
-                                                                      24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
-                                                                      36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47}},
+                    reference_tests::Tensor{
+                        {4, 2, 3, 2},
+                        DATA_ET,
+                        std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15,
+                                            16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
+                                            32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47}},
                     "4D_default_axes"),
         SliceParams(Tensor{{4, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
                                                                       12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
@@ -259,8 +263,9 @@ std::vector<SliceParams> generateSliceParamsUnsigned() {
                     reference_tests::Tensor{{1}, IND_ET, std::vector<IND_T>{2}},
                     reference_tests::Tensor{{1}, IND_ET, std::vector<IND_T>{1}},
                     reference_tests::Tensor{{1}, AXIS_ET, std::vector<AXIS_T>{0}},
-                    reference_tests::Tensor{{2, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                                      12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}},
+                    reference_tests::Tensor{{2, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,
+                                                                                       8,  9,  10, 11, 12, 13, 14, 15,
+                                                                                       16, 17, 18, 19, 20, 21, 22, 23}},
                     "4D_half_dim"),
         SliceParams(Tensor{{4, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
                                                                       12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
@@ -270,28 +275,31 @@ std::vector<SliceParams> generateSliceParamsUnsigned() {
                     reference_tests::Tensor{{1}, IND_ET, std::vector<IND_T>{4}},
                     reference_tests::Tensor{{1}, IND_ET, std::vector<IND_T>{2}},
                     reference_tests::Tensor{{1}, AXIS_ET, std::vector<AXIS_T>{0}},
-                    reference_tests::Tensor{{2, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                                      24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35}},
+                    reference_tests::Tensor{{2, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,
+                                                                                       8,  9,  10, 11, 24, 25, 26, 27,
+                                                                                       28, 29, 30, 31, 32, 33, 34, 35}},
                     "4D_half_dim_step"),
         SliceParams(
-            reference_tests::Tensor{{2, 4, 2, 2, 3},
-                   DATA_ET,
-                   std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                       20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                                       40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
-                                       60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
-                                       80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95}},
+            reference_tests::Tensor{
+                {2, 4, 2, 2, 3},
+                DATA_ET,
+                std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                                    20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                                    40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+                                    60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
+                                    80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95}},
             reference_tests::Tensor{{5}, IND_ET, std::vector<IND_T>{0, 0, 0, 0, 0}},
             reference_tests::Tensor{{5}, IND_ET, std::vector<IND_T>{2, 4, 2, 2, 3}},
             reference_tests::Tensor{{5}, IND_ET, std::vector<IND_T>{1, 1, 1, 1, 1}},
             reference_tests::Tensor{{5}, AXIS_ET, std::vector<AXIS_T>{0, 1, 2, 3, 4}},
-            reference_tests::Tensor{{2, 2, 2, 1, 2},
-                   DATA_ET,
-                   std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                       20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                                       40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
-                                       60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
-                                       80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95}},
+            reference_tests::Tensor{
+                {2, 2, 2, 1, 2},
+                DATA_ET,
+                std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                                    20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                                    40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+                                    60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
+                                    80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95}},
             "5D_full_axes"),
     };
     return test_params;
@@ -361,23 +369,25 @@ std::vector<SliceParams> generateSliceParams() {
                                                                       24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
                                                                       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47}},
                     reference_tests::Tensor{{4},
-                           IND_ET,
-                           std::vector<IND_T>{std::numeric_limits<IND_T>::min(),
-                                              std::numeric_limits<IND_T>::max(),
-                                              std::numeric_limits<IND_T>::max(),
-                                              std::numeric_limits<IND_T>::min()}},
+                                            IND_ET,
+                                            std::vector<IND_T>{std::numeric_limits<IND_T>::min(),
+                                                               std::numeric_limits<IND_T>::max(),
+                                                               std::numeric_limits<IND_T>::max(),
+                                                               std::numeric_limits<IND_T>::min()}},
                     reference_tests::Tensor{{4},
-                           IND_ET,
-                           std::vector<IND_T>{std::numeric_limits<IND_T>::max(),
-                                              std::numeric_limits<IND_T>::min(),
-                                              std::numeric_limits<IND_T>::min(),
-                                              std::numeric_limits<IND_T>::max()}},
+                                            IND_ET,
+                                            std::vector<IND_T>{std::numeric_limits<IND_T>::max(),
+                                                               std::numeric_limits<IND_T>::min(),
+                                                               std::numeric_limits<IND_T>::min(),
+                                                               std::numeric_limits<IND_T>::max()}},
                     reference_tests::Tensor{{4}, IND_ET, std::vector<IND_T>{1, -1, -1, 1}},
                     reference_tests::Tensor{{4}, AXIS_ET, std::vector<AXIS_T>{0, 1, 2, 3}},
-                    reference_tests::Tensor{{4, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{10, 11, 8,  9,  6,  7,  4,  5,  2,  3,  0,  1,
-                                                                      22, 23, 20, 21, 18, 19, 16, 17, 14, 15, 12, 13,
-                                                                      34, 35, 32, 33, 30, 31, 28, 29, 26, 27, 24, 25,
-                                                                      46, 47, 44, 45, 42, 43, 40, 41, 38, 39, 36, 37}},
+                    reference_tests::Tensor{
+                        {4, 2, 3, 2},
+                        DATA_ET,
+                        std::vector<DATA_T>{10, 11, 8,  9,  6,  7,  4,  5,  2,  3,  0,  1,  22, 23, 20, 21,
+                                            18, 19, 16, 17, 14, 15, 12, 13, 34, 35, 32, 33, 30, 31, 28, 29,
+                                            26, 27, 24, 25, 46, 47, 44, 45, 42, 43, 40, 41, 38, 39, 36, 37}},
                     "4D_INT_MIN_MAX_index"),
         SliceParams(Tensor{{4, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
                                                                       12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
@@ -387,24 +397,27 @@ std::vector<SliceParams> generateSliceParams() {
                     reference_tests::Tensor{{2}, IND_ET, std::vector<IND_T>{-100, 100}},
                     reference_tests::Tensor{{2}, IND_ET, std::vector<IND_T>{-1, 2}},
                     reference_tests::Tensor{{2}, AXIS_ET, std::vector<AXIS_T>{2, 0}},
-                    reference_tests::Tensor{{2, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{4,  5,  2,  3,  0,  1,  10, 11, 8,  9,  6,  7,
-                                                                      28, 29, 26, 27, 24, 25, 34, 35, 32, 33, 30, 31}},
+                    reference_tests::Tensor{{2, 2, 3, 2}, DATA_ET, std::vector<DATA_T>{4,  5,  2,  3,  0,  1,  10, 11,
+                                                                                       8,  9,  6,  7,  28, 29, 26, 27,
+                                                                                       24, 25, 34, 35, 32, 33, 30, 31}},
                     "4D_mixed"),
         SliceParams(
-            reference_tests::Tensor{{2, 4, 2, 2, 3},
-                   DATA_ET,
-                   std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
-                                       20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
-                                       40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
-                                       60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
-                                       80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95}},
+            reference_tests::Tensor{
+                {2, 4, 2, 2, 3},
+                DATA_ET,
+                std::vector<DATA_T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19,
+                                    20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39,
+                                    40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59,
+                                    60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79,
+                                    80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95}},
             reference_tests::Tensor{{5}, IND_ET, std::vector<IND_T>{0, 1, -5, 100, 1}},
             reference_tests::Tensor{{5}, IND_ET, std::vector<IND_T>{2, 6, 3, -100, 2}},
             reference_tests::Tensor{{5}, IND_ET, std::vector<IND_T>{1, 2, 2, -1, 1}},
             reference_tests::Tensor{{5}, AXIS_ET, std::vector<AXIS_T>{-5, 1, 4, 2, 3}},
-            reference_tests::Tensor{{2, 2, 2, 1, 2},
-                   DATA_ET,
-                   std::vector<DATA_T>{21, 23, 15, 17, 45, 47, 39, 41, 69, 71, 63, 65, 93, 95, 87, 89}},
+            reference_tests::Tensor{
+                {2, 2, 2, 1, 2},
+                DATA_ET,
+                std::vector<DATA_T>{21, 23, 15, 17, 45, 47, 39, 41, 69, 71, 63, 65, 93, 95, 87, 89}},
             "5D_mixed"),
     };
     const auto& unsigned_test_params = generateSliceParamsUnsigned<DATA_ET, IND_ET, AXIS_ET>();
diff --git a/src/plugins/template/tests/functional/op_reference/softmax.cpp b/src/plugins/template/tests/functional/op_reference/softmax.cpp
index 3e002d50e45a6a..4bbd11915486cd 100644
--- a/src/plugins/template/tests/functional/op_reference/softmax.cpp
+++ b/src/plugins/template/tests/functional/op_reference/softmax.cpp
@@ -2,23 +2,28 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/softmax.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/softmax.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 #ifdef _MSC_VER
-#   pragma warning(disable : 4756)
-#endif  
+#    pragma warning(disable : 4756)
+#endif
 
 namespace {
 struct SoftmaxParams {
     template <class IT>
-    SoftmaxParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues,
-                const int64_t axis, const std::string& test_name)
+    SoftmaxParams(const ov::PartialShape& shape,
+                  const ov::element::Type& iType,
+                  const std::vector<IT>& iValues,
+                  const std::vector<IT>& oValues,
+                  const int64_t axis,
+                  const std::string& test_name)
         : axis(axis),
           pshape(shape),
           inType(iType),
@@ -61,11 +66,13 @@ class ReferenceSoftmaxLayerTest : public testing::TestWithParam<SoftmaxParams>,
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& expected_output_type, const int64_t axis) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type,
+                                                 const int64_t axis) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto Softmax = std::make_shared<op::v1::Softmax>(in, axis);
-        return std::make_shared<ov::Model>(NodeVector {Softmax}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Softmax}, ParameterVector{in});
     }
 };
 
@@ -102,85 +109,83 @@ std::vector<SoftmaxParams> generateSoftmaxFloatParams() {
     auto d1_of = expf(1) + expf(4);
     auto d2_of = expf(2) + expf(5);
 
-    std::vector<SoftmaxParams> softmaxParams {
-        SoftmaxParams(ov::PartialShape {2, 2, 3},
-                    IN_ET,
-                    std::vector<T>{-10, -20, -30, -40, -50, -60, -1, -2, -3, -4, -5, -6},
-                    std::vector<T>{expf(-10) / d0,
-                                   expf(-20) / d1,
-                                   expf(-30) / d2,
-                                   expf(-40) / d3,
-                                   expf(-50) / d4,
-                                   expf(-60) / d5,
-                                   expf(-1) / d0,
-                                   expf(-2) / d1,
-                                   expf(-3) / d2,
-                                   expf(-4) / d3,
-                                   expf(-5) / d4,
-                                   expf(-6) / d5},
-                    0,
-                    ""),
-        SoftmaxParams(ov::PartialShape {2, 3},
-                    IN_ET,
-                    std::vector<T>{-10, -20, -30, -40, -50, -60},
-                    std::vector<T>{expf(-10) / d0_a1,
-                                   expf(-20) / d0_a1,
-                                   expf(-30) / d0_a1,
-                                   expf(-40) / d1_a1,
-                                   expf(-50) / d1_a1,
-                                   expf(-60) / d1_a1},
-                    1,
-                    ""),
-        SoftmaxParams(ov::PartialShape {2, 3},
-                    IN_ET,
-                    std::vector<T>{-10, -20, -30, -40, -50, -60},
-                    std::vector<T>{expf(-10) / d0_a0,
-                                   expf(-20) / d1_a0,
-                                   expf(-30) / d2_a0,
-                                   expf(-40) / d0_a0,
-                                   expf(-50) / d1_a0,
-                                   expf(-60) / d2_a0},
-                    0,
-                    "test"),
-        SoftmaxParams(ov::PartialShape {1, 2, 3},
-                    IN_ET,
-                    std::vector<T>{-10, -20, -30, -40, -50, -60},
-                    std::vector<T>{1, 1, 1, 1, 1, 1},
-                    0,
-                    "trivial"),
-        SoftmaxParams(ov::PartialShape {2, 3},
-                    IN_ET,
-                    std::vector<T>{low, 1, 2, 3, 4, 5},
-                    std::vector<T>{expf(low) / d0_uf,
-                                   expf(1) / d1_uf,
-                                   expf(2) / d2_uf,
-                                   expf(3) / d0_uf,
-                                   expf(4) / d1_uf,
-                                   expf(5) / d2_uf},
-                    0,
-                    "underflow"),
-        SoftmaxParams(ov::PartialShape {2, 3},
-                    IN_ET,
-                    std::vector<T>{high, 1, 2, 3, 4, 5},
-                    std::vector<T>{expf(high - high) / d0_of,
-                                   expf(1) / d1_of,
-                                   expf(2) / d2_of,
-                                   expf(3 - high) / d0_of,
-                                   expf(4) / d1_of,
-                                   expf(5) / d2_of},
-                    0,
-                    "overflow")
-    };
+    std::vector<SoftmaxParams> softmaxParams{
+        SoftmaxParams(ov::PartialShape{2, 2, 3},
+                      IN_ET,
+                      std::vector<T>{-10, -20, -30, -40, -50, -60, -1, -2, -3, -4, -5, -6},
+                      std::vector<T>{expf(-10) / d0,
+                                     expf(-20) / d1,
+                                     expf(-30) / d2,
+                                     expf(-40) / d3,
+                                     expf(-50) / d4,
+                                     expf(-60) / d5,
+                                     expf(-1) / d0,
+                                     expf(-2) / d1,
+                                     expf(-3) / d2,
+                                     expf(-4) / d3,
+                                     expf(-5) / d4,
+                                     expf(-6) / d5},
+                      0,
+                      ""),
+        SoftmaxParams(ov::PartialShape{2, 3},
+                      IN_ET,
+                      std::vector<T>{-10, -20, -30, -40, -50, -60},
+                      std::vector<T>{expf(-10) / d0_a1,
+                                     expf(-20) / d0_a1,
+                                     expf(-30) / d0_a1,
+                                     expf(-40) / d1_a1,
+                                     expf(-50) / d1_a1,
+                                     expf(-60) / d1_a1},
+                      1,
+                      ""),
+        SoftmaxParams(ov::PartialShape{2, 3},
+                      IN_ET,
+                      std::vector<T>{-10, -20, -30, -40, -50, -60},
+                      std::vector<T>{expf(-10) / d0_a0,
+                                     expf(-20) / d1_a0,
+                                     expf(-30) / d2_a0,
+                                     expf(-40) / d0_a0,
+                                     expf(-50) / d1_a0,
+                                     expf(-60) / d2_a0},
+                      0,
+                      "test"),
+        SoftmaxParams(ov::PartialShape{1, 2, 3},
+                      IN_ET,
+                      std::vector<T>{-10, -20, -30, -40, -50, -60},
+                      std::vector<T>{1, 1, 1, 1, 1, 1},
+                      0,
+                      "trivial"),
+        SoftmaxParams(ov::PartialShape{2, 3},
+                      IN_ET,
+                      std::vector<T>{low, 1, 2, 3, 4, 5},
+                      std::vector<T>{expf(low) / d0_uf,
+                                     expf(1) / d1_uf,
+                                     expf(2) / d2_uf,
+                                     expf(3) / d0_uf,
+                                     expf(4) / d1_uf,
+                                     expf(5) / d2_uf},
+                      0,
+                      "underflow"),
+        SoftmaxParams(ov::PartialShape{2, 3},
+                      IN_ET,
+                      std::vector<T>{high, 1, 2, 3, 4, 5},
+                      std::vector<T>{expf(high - high) / d0_of,
+                                     expf(1) / d1_of,
+                                     expf(2) / d2_of,
+                                     expf(3 - high) / d0_of,
+                                     expf(4) / d1_of,
+                                     expf(5) / d2_of},
+                      0,
+                      "overflow")};
     return softmaxParams;
 }
 
 std::vector<SoftmaxParams> generateSoftmaxCombinedParams() {
-    const std::vector<std::vector<SoftmaxParams>> softmaxTypeParams {
+    const std::vector<std::vector<SoftmaxParams>> softmaxTypeParams{
         generateSoftmaxFloatParams<element::Type_t::f64>(),
         generateSoftmaxFloatParams<element::Type_t::f32>(),
         generateSoftmaxFloatParams<element::Type_t::f16>(),
-        generateSoftmaxFloatParams<element::Type_t::bf16>()
-    };
+        generateSoftmaxFloatParams<element::Type_t::bf16>()};
     std::vector<SoftmaxParams> combinedParams;
 
     for (const auto& params : softmaxTypeParams) {
@@ -189,7 +194,9 @@ std::vector<SoftmaxParams> generateSoftmaxCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Softmax_With_Hardcoded_Refs, ReferenceSoftmaxLayerTest,
-    testing::ValuesIn(generateSoftmaxCombinedParams()), ReferenceSoftmaxLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Softmax_With_Hardcoded_Refs,
+                         ReferenceSoftmaxLayerTest,
+                         testing::ValuesIn(generateSoftmaxCombinedParams()),
+                         ReferenceSoftmaxLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/softplus.cpp b/src/plugins/template/tests/functional/op_reference/softplus.cpp
index 3530ed71ff8172..1d0e18accb985e 100644
--- a/src/plugins/template/tests/functional/op_reference/softplus.cpp
+++ b/src/plugins/template/tests/functional/op_reference/softplus.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/softplus.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/softplus.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,7 +14,10 @@ using namespace ov;
 namespace {
 struct SoftPlusParams {
     template <class IT>
-    SoftPlusParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    SoftPlusParams(const ov::PartialShape& shape,
+                   const ov::element::Type& iType,
+                   const std::vector<IT>& iValues,
+                   const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -45,11 +49,12 @@ class ReferenceSoftPlusLayerTest : public testing::TestWithParam<SoftPlusParams>
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& SoftPlusected_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& SoftPlusected_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto SoftPlus = std::make_shared<op::v4::SoftPlus>(in);
-        return std::make_shared<ov::Model>(NodeVector {SoftPlus}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{SoftPlus}, ParameterVector{in});
     }
 };
 
@@ -61,21 +66,18 @@ template <element::Type_t IN_ET>
 std::vector<SoftPlusParams> generateSoftPlusFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<SoftPlusParams> softPlusParams {
-        SoftPlusParams(ov::PartialShape {4},
-                    IN_ET,
-                    std::vector<T>{-1.0, 0.0, 1.0, 20.0},
-                    std::vector<T>{0.31326166, 0.69314718, 1.3132616, 20.0})
-    };
+    std::vector<SoftPlusParams> softPlusParams{SoftPlusParams(ov::PartialShape{4},
+                                                              IN_ET,
+                                                              std::vector<T>{-1.0, 0.0, 1.0, 20.0},
+                                                              std::vector<T>{0.31326166, 0.69314718, 1.3132616, 20.0})};
     return softPlusParams;
 }
 
 std::vector<SoftPlusParams> generateSoftPlusCombinedParams() {
-    const std::vector<std::vector<SoftPlusParams>> softPlusTypeParams {
+    const std::vector<std::vector<SoftPlusParams>> softPlusTypeParams{
         generateSoftPlusFloatParams<element::Type_t::f32>(),
         generateSoftPlusFloatParams<element::Type_t::f16>(),
-        generateSoftPlusFloatParams<element::Type_t::bf16>()
-        };
+        generateSoftPlusFloatParams<element::Type_t::bf16>()};
     std::vector<SoftPlusParams> combinedParams;
 
     for (const auto& params : softPlusTypeParams) {
@@ -84,7 +86,9 @@ std::vector<SoftPlusParams> generateSoftPlusCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_SoftPlus_With_Hardcoded_Refs, ReferenceSoftPlusLayerTest,
-    testing::ValuesIn(generateSoftPlusCombinedParams()), ReferenceSoftPlusLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_SoftPlus_With_Hardcoded_Refs,
+                         ReferenceSoftPlusLayerTest,
+                         testing::ValuesIn(generateSoftPlusCombinedParams()),
+                         ReferenceSoftPlusLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/softsign.cpp b/src/plugins/template/tests/functional/op_reference/softsign.cpp
index 6664bcf19d613c..299c108956c3fb 100644
--- a/src/plugins/template/tests/functional/op_reference/softsign.cpp
+++ b/src/plugins/template/tests/functional/op_reference/softsign.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/softsign.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/softsign.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,7 +14,10 @@ using namespace ov;
 namespace {
 struct SoftSignParams {
     template <class IT>
-    SoftSignParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues, const std::vector<IT>& oValues)
+    SoftSignParams(const ov::PartialShape& shape,
+                   const ov::element::Type& iType,
+                   const std::vector<IT>& iValues,
+                   const std::vector<IT>& oValues)
         : pshape(shape),
           inType(iType),
           outType(iType),
@@ -45,11 +49,12 @@ class ReferenceSoftSignLayerTest : public testing::TestWithParam<SoftSignParams>
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& SoftSign_output_type) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& SoftSign_output_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto SoftSign = std::make_shared<op::v9::SoftSign>(in);
-        return std::make_shared<ov::Model>(NodeVector {SoftSign}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{SoftSign}, ParameterVector{in});
     }
 };
 
@@ -61,21 +66,18 @@ template <element::Type_t IN_ET>
 std::vector<SoftSignParams> generateSoftSignFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<SoftSignParams> ParamsVector {
-        SoftSignParams(ov::PartialShape {4},
-                    IN_ET,
-                    std::vector<T>{-1.0, 0.0, 1.0, 15.0},
-                    std::vector<T>{-0.5, 0.0, 0.5, 0.9375})
-    };
+    std::vector<SoftSignParams> ParamsVector{SoftSignParams(ov::PartialShape{4},
+                                                            IN_ET,
+                                                            std::vector<T>{-1.0, 0.0, 1.0, 15.0},
+                                                            std::vector<T>{-0.5, 0.0, 0.5, 0.9375})};
     return ParamsVector;
 }
 
 std::vector<SoftSignParams> generateSoftSignCombinedParams() {
-    const std::vector<std::vector<SoftSignParams>> SoftSignTypeParams {
+    const std::vector<std::vector<SoftSignParams>> SoftSignTypeParams{
         generateSoftSignFloatParams<element::Type_t::f32>(),
         generateSoftSignFloatParams<element::Type_t::f16>(),
-        generateSoftSignFloatParams<element::Type_t::bf16>()
-        };
+        generateSoftSignFloatParams<element::Type_t::bf16>()};
     std::vector<SoftSignParams> combinedParams;
 
     for (const auto& params : SoftSignTypeParams) {
@@ -84,7 +86,9 @@ std::vector<SoftSignParams> generateSoftSignCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_SoftSign_With_Hardcoded_Refs, ReferenceSoftSignLayerTest,
-    testing::ValuesIn(generateSoftSignCombinedParams()), ReferenceSoftSignLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_SoftSign_With_Hardcoded_Refs,
+                         ReferenceSoftSignLayerTest,
+                         testing::ValuesIn(generateSoftSignCombinedParams()),
+                         ReferenceSoftSignLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/space_to_batch.cpp b/src/plugins/template/tests/functional/op_reference/space_to_batch.cpp
index cbfe36d6963f30..39cadfe89560df 100644
--- a/src/plugins/template/tests/functional/op_reference/space_to_batch.cpp
+++ b/src/plugins/template/tests/functional/op_reference/space_to_batch.cpp
@@ -4,22 +4,28 @@
 
 #include <gtest/gtest.h>
 
+#include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 #include "openvino/opsets/opset1.hpp"
 #include "openvino/opsets/opset2.hpp"
-#include "openvino/op/constant.hpp"
-#include "base_reference_test.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct SpaceToBatchParams {
-    SpaceToBatchParams(const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& blockShapeTensor,
-                       const reference_tests::Tensor& padsBeginTensor, const reference_tests::Tensor& padsEndTensor,
-                       const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-                  dataTensor(dataTensor), blockShapeTensor(blockShapeTensor),
-                  padsBeginTensor(padsBeginTensor), padsEndTensor(padsEndTensor),
-                  expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+    SpaceToBatchParams(const reference_tests::Tensor& dataTensor,
+                       const reference_tests::Tensor& blockShapeTensor,
+                       const reference_tests::Tensor& padsBeginTensor,
+                       const reference_tests::Tensor& padsEndTensor,
+                       const reference_tests::Tensor& expectedTensor,
+                       const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          blockShapeTensor(blockShapeTensor),
+          padsBeginTensor(padsBeginTensor),
+          padsEndTensor(padsEndTensor),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor blockShapeTensor;
@@ -81,55 +87,51 @@ TEST_P(ReferenceSpaceToBatchLayerTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<SpaceToBatchParams> generateParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<SpaceToBatchParams> batchToSpaceParams {
+    std::vector<SpaceToBatchParams> batchToSpaceParams{
         // space_to_batch_3D
-        SpaceToBatchParams(
-            reference_tests::Tensor({1, 2, 2}, IN_ET, std::vector<T>{1, 1, 1, 1}),
-            reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{1, 1, 1}),
-            reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 0, 0}),
-            reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 0, 0}),
-            reference_tests::Tensor({1, 2, 2}, IN_ET, std::vector<T>{1, 1, 1, 1}),
-            "space_to_batch_4D"),
+        SpaceToBatchParams(reference_tests::Tensor({1, 2, 2}, IN_ET, std::vector<T>{1, 1, 1, 1}),
+                           reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{1, 1, 1}),
+                           reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 0, 0}),
+                           reference_tests::Tensor({3}, element::i64, std::vector<int64_t>{0, 0, 0}),
+                           reference_tests::Tensor({1, 2, 2}, IN_ET, std::vector<T>{1, 1, 1, 1}),
+                           "space_to_batch_4D"),
 
         // space_to_batch_4D
-        SpaceToBatchParams(
-            reference_tests::Tensor({1, 1, 2, 2}, IN_ET, std::vector<T>{1, 1, 1, 1}),
-            reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 1, 1}),
-            reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
-            reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
-            reference_tests::Tensor({1, 1, 2, 2}, IN_ET, std::vector<T>{1, 1, 1, 1}),
-            "space_to_batch_4D"),
+        SpaceToBatchParams(reference_tests::Tensor({1, 1, 2, 2}, IN_ET, std::vector<T>{1, 1, 1, 1}),
+                           reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 1, 1}),
+                           reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
+                           reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
+                           reference_tests::Tensor({1, 1, 2, 2}, IN_ET, std::vector<T>{1, 1, 1, 1}),
+                           "space_to_batch_4D"),
 
         // space_to_batch_5D
-         SpaceToBatchParams(
-             reference_tests::Tensor({1, 1, 3, 2, 1}, IN_ET, std::vector<T>{1, 1, 1, 1, 1, 1}),
-             reference_tests::Tensor({5}, element::i64, std::vector<int64_t>{1, 1, 3, 2, 2}),
-             reference_tests::Tensor({5}, element::i64, std::vector<int64_t>{0, 0, 1, 0, 3}),
-             reference_tests::Tensor({5}, element::i64, std::vector<int64_t>{0, 0, 2, 0, 0}),
-             reference_tests::Tensor({12, 1, 2, 1, 2}, IN_ET, std::vector<T>{
-                 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,
-                 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0,
-                 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0,
-                 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0}),
-             "space_to_batch_5D"),
+        SpaceToBatchParams(reference_tests::Tensor({1, 1, 3, 2, 1}, IN_ET, std::vector<T>{1, 1, 1, 1, 1, 1}),
+                           reference_tests::Tensor({5}, element::i64, std::vector<int64_t>{1, 1, 3, 2, 2}),
+                           reference_tests::Tensor({5}, element::i64, std::vector<int64_t>{0, 0, 1, 0, 3}),
+                           reference_tests::Tensor({5}, element::i64, std::vector<int64_t>{0, 0, 2, 0, 0}),
+                           reference_tests::Tensor(
+                               {12, 1, 2, 1, 2},
+                               IN_ET,
+                               std::vector<T>{0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0,
+                                              0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0}),
+                           "space_to_batch_5D"),
 
         // space_to_batch_4x4
-        SpaceToBatchParams(
-            reference_tests::Tensor({1, 1, 4, 4}, IN_ET, std::vector<T>{
-                1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1}),
-            reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 1, 1}),
-            reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 1, 0}),
-            reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
-            reference_tests::Tensor({1, 1, 5, 4}, IN_ET, std::vector<T>{
-                0, 0, 0, 0, 1, 0, 0, 0, 0, 1,
-                0, 0, 0, 0, 1, 0, 0, 0, 0, 1}),
-            "space_to_batch_4x4"),
+        SpaceToBatchParams(reference_tests::Tensor({1, 1, 4, 4},
+                                                   IN_ET,
+                                                   std::vector<T>{1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1}),
+                           reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{1, 1, 1, 1}),
+                           reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 1, 0}),
+                           reference_tests::Tensor({4}, element::i64, std::vector<int64_t>{0, 0, 0, 0}),
+                           reference_tests::Tensor({1, 1, 5, 4}, IN_ET, std::vector<T>{0, 0, 0, 0, 1, 0, 0, 0, 0, 1,
+                                                                                       0, 0, 0, 0, 1, 0, 0, 0, 0, 1}),
+                           "space_to_batch_4x4"),
     };
     return batchToSpaceParams;
 }
 
 std::vector<SpaceToBatchParams> generateCombinedParams() {
-    const std::vector<std::vector<SpaceToBatchParams>> batchToSpaceTypeParams {
+    const std::vector<std::vector<SpaceToBatchParams>> batchToSpaceTypeParams{
         generateParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
         generateParams<element::Type_t::i32>(),
@@ -151,6 +153,8 @@ std::vector<SpaceToBatchParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_SpaceToBatch_With_Hardcoded_Refs, ReferenceSpaceToBatchLayerTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceSpaceToBatchLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_SpaceToBatch_With_Hardcoded_Refs,
+                         ReferenceSpaceToBatchLayerTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceSpaceToBatchLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/space_to_depth.cpp b/src/plugins/template/tests/functional/op_reference/space_to_depth.cpp
index ef325b7dd9367a..7420376f802af7 100644
--- a/src/plugins/template/tests/functional/op_reference/space_to_depth.cpp
+++ b/src/plugins/template/tests/functional/op_reference/space_to_depth.cpp
@@ -4,18 +4,24 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct SpaceToDepthParams {
-    SpaceToDepthParams(const reference_tests::Tensor& dataTensor, const std::string mode, const int32_t blockSize,
-                       const reference_tests::Tensor& expectedTensor, const std::string& testcaseName = "") :
-        dataTensor(dataTensor), mode(mode), blockSize(blockSize), expectedTensor(expectedTensor),
-        testcaseName(testcaseName) {}
+    SpaceToDepthParams(const reference_tests::Tensor& dataTensor,
+                       const std::string mode,
+                       const int32_t blockSize,
+                       const reference_tests::Tensor& expectedTensor,
+                       const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          mode(mode),
+          blockSize(blockSize),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     std::string mode;
@@ -50,11 +56,12 @@ class ReferenceSpaceToDepthLayerTest : public testing::TestWithParam<SpaceToDept
 
 private:
     static std::shared_ptr<Model> CreateFunction(const SpaceToDepthParams& params) {
-        opset1::SpaceToDepth::SpaceToDepthMode mode = params.mode == "DEPTH_FIRST" ?
-            opset1::SpaceToDepth::SpaceToDepthMode::DEPTH_FIRST : opset1::SpaceToDepth::SpaceToDepthMode::BLOCKS_FIRST;
+        opset1::SpaceToDepth::SpaceToDepthMode mode = params.mode == "DEPTH_FIRST"
+                                                          ? opset1::SpaceToDepth::SpaceToDepthMode::DEPTH_FIRST
+                                                          : opset1::SpaceToDepth::SpaceToDepthMode::BLOCKS_FIRST;
         const auto data = std::make_shared<opset1::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto SpaceToDepth = std::make_shared<opset1::SpaceToDepth>(data, mode, params.blockSize);
-        return std::make_shared<Model>(NodeVector {SpaceToDepth}, ParameterVector {data});
+        return std::make_shared<Model>(NodeVector{SpaceToDepth}, ParameterVector{data});
     }
 };
 
@@ -65,84 +72,80 @@ TEST_P(ReferenceSpaceToDepthLayerTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<SpaceToDepthParams> generateParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<SpaceToDepthParams> params {
+    std::vector<SpaceToDepthParams> params{
         // space_to_depth_block_first_K2_BS2
         SpaceToDepthParams(
-            reference_tests::Tensor({1, 2, 4, 4}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
-                11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
-                22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
+            reference_tests::Tensor({1, 2, 4, 4}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
+                                                                        11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
+                                                                        22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
             "BLOCKS_FIRST",
             2,
-            reference_tests::Tensor({1, 8, 2, 2}, IN_ET, std::vector<T>{
-                0, 2, 8,  10, 16, 18, 24, 26, 1, 3, 9,  11, 17, 19, 25, 27,
-                4, 6, 12, 14, 20, 22, 28, 30, 5, 7, 13, 15, 21, 23, 29, 31}),
+            reference_tests::Tensor({1, 8, 2, 2}, IN_ET, std::vector<T>{0,  2,  8,  10, 16, 18, 24, 26, 1,  3,  9,
+                                                                        11, 17, 19, 25, 27, 4,  6,  12, 14, 20, 22,
+                                                                        28, 30, 5,  7,  13, 15, 21, 23, 29, 31}),
             "space_to_depth_block_first_K2_BS2"),
 
         // space_to_depth_block_first_K2_BS3
         SpaceToDepthParams(
-            reference_tests::Tensor({1, 2, 6, 3}, IN_ET, std::vector<T>{
-                0,  4,  8,  12, 16, 20, 24, 28, 32, 1,  5,  9,
-                13, 17, 21, 25, 29, 33, 2,  6,  10, 14, 18, 22,
-                26, 30, 34, 3,  7,  11, 15, 19, 23, 27, 31, 35}),
+            reference_tests::Tensor({1, 2, 6, 3},
+                                    IN_ET,
+                                    std::vector<T>{0, 4, 8,  12, 16, 20, 24, 28, 32, 1, 5, 9,  13, 17, 21, 25, 29, 33,
+                                                   2, 6, 10, 14, 18, 22, 26, 30, 34, 3, 7, 11, 15, 19, 23, 27, 31, 35}),
             "BLOCKS_FIRST",
             3,
-            reference_tests::Tensor({1, 18, 2, 1}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17,
-                18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35}),
+            reference_tests::Tensor({1, 18, 2, 1}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,
+                                                                         9,  10, 11, 12, 13, 14, 15, 16, 17,
+                                                                         18, 19, 20, 21, 22, 23, 24, 25, 26,
+                                                                         27, 28, 29, 30, 31, 32, 33, 34, 35}),
             "space_to_depth_block_first_K2_BS3"),
 
         // space_to_depth_block_first_K1_BS3
         SpaceToDepthParams(
-            reference_tests::Tensor({1, 2, 6}, IN_ET, std::vector<T>{
-                0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11}),
+            reference_tests::Tensor({1, 2, 6}, IN_ET, std::vector<T>{0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11}),
             "BLOCKS_FIRST",
             3,
-            reference_tests::Tensor({1, 6, 2}, IN_ET, std::vector<T>{
-                0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}),
+            reference_tests::Tensor({1, 6, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}),
             "space_to_depth_block_first_K1_BS3"),
 
         // space_to_depth_depth_first_K2_BS2
         SpaceToDepthParams(
-            reference_tests::Tensor({1, 2, 4, 4}, IN_ET, std::vector<T>{
-                0,  16, 2,  18, 1,  17, 3,  19, 8,  24, 10,
-                26, 9,  25, 11, 27, 4,  20, 6,  22, 5,  21,
-                7,  23, 12, 28, 14, 30, 13, 29, 15, 31}),
+            reference_tests::Tensor({1, 2, 4, 4}, IN_ET, std::vector<T>{0,  16, 2,  18, 1,  17, 3,  19, 8,  24, 10,
+                                                                        26, 9,  25, 11, 27, 4,  20, 6,  22, 5,  21,
+                                                                        7,  23, 12, 28, 14, 30, 13, 29, 15, 31}),
             "DEPTH_FIRST",
             2,
-            reference_tests::Tensor({1, 8, 2, 2}, IN_ET, std::vector<T>{
-                0, 2, 8,  10, 16, 18, 24, 26, 1, 3, 9,  11, 17, 19, 25, 27,
-                4, 6, 12, 14, 20, 22, 28, 30, 5, 7, 13, 15, 21, 23, 29, 31}),
+            reference_tests::Tensor({1, 8, 2, 2}, IN_ET, std::vector<T>{0,  2,  8,  10, 16, 18, 24, 26, 1,  3,  9,
+                                                                        11, 17, 19, 25, 27, 4,  6,  12, 14, 20, 22,
+                                                                        28, 30, 5,  7,  13, 15, 21, 23, 29, 31}),
             "space_to_depth_depth_first_K2_BS2"),
 
         // space_to_depth_depth_first_K2_BS3
         SpaceToDepthParams(
-            reference_tests::Tensor({1, 2, 6, 3}, IN_ET, std::vector<T>{
-                0,  2,  4,  6,  8,  10, 12, 14, 16, 1,  3,  5,
-                7,  9,  11, 13, 15, 17, 18, 20, 22, 24, 26, 28,
-                30, 32, 34, 19, 21, 23, 25, 27, 29, 31, 33, 35}),
+            reference_tests::Tensor({1, 2, 6, 3}, IN_ET, std::vector<T>{0,  2,  4,  6,  8,  10, 12, 14, 16,
+                                                                        1,  3,  5,  7,  9,  11, 13, 15, 17,
+                                                                        18, 20, 22, 24, 26, 28, 30, 32, 34,
+                                                                        19, 21, 23, 25, 27, 29, 31, 33, 35}),
             "DEPTH_FIRST",
             3,
-            reference_tests::Tensor({1, 18, 2, 1}, IN_ET, std::vector<T>{
-                0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17,
-                18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35}),
+            reference_tests::Tensor({1, 18, 2, 1}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,
+                                                                         9,  10, 11, 12, 13, 14, 15, 16, 17,
+                                                                         18, 19, 20, 21, 22, 23, 24, 25, 26,
+                                                                         27, 28, 29, 30, 31, 32, 33, 34, 35}),
             "space_to_depth_depth_first_K2_BS3"),
 
         // space_to_depth_depth_first_K1_BS3
         SpaceToDepthParams(
-            reference_tests::Tensor({1, 2, 6}, IN_ET, std::vector<T>{
-                0, 2, 4, 1, 3, 5, 6, 8, 10, 7, 9, 11}),
+            reference_tests::Tensor({1, 2, 6}, IN_ET, std::vector<T>{0, 2, 4, 1, 3, 5, 6, 8, 10, 7, 9, 11}),
             "DEPTH_FIRST",
             3,
-            reference_tests::Tensor({1, 6, 2}, IN_ET, std::vector<T>{
-                0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}),
+            reference_tests::Tensor({1, 6, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}),
             "space_to_depth_depth_first_K1_BS3"),
     };
     return params;
 }
 
 std::vector<SpaceToDepthParams> generateCombinedParams() {
-    const std::vector<std::vector<SpaceToDepthParams>> generatedParams {
+    const std::vector<std::vector<SpaceToDepthParams>> generatedParams{
         generateParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
         generateParams<element::Type_t::i32>(),
@@ -164,6 +167,8 @@ std::vector<SpaceToDepthParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_SpaceToDepth_With_Hardcoded_Refs, ReferenceSpaceToDepthLayerTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceSpaceToDepthLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_SpaceToDepth_With_Hardcoded_Refs,
+                         ReferenceSpaceToDepthLayerTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceSpaceToDepthLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/split.cpp b/src/plugins/template/tests/functional/op_reference/split.cpp
index f360159b643c85..cba426f33a2a22 100644
--- a/src/plugins/template/tests/functional/op_reference/split.cpp
+++ b/src/plugins/template/tests/functional/op_reference/split.cpp
@@ -2,21 +2,28 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/split.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/split.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct SplitParams {
-    SplitParams(const reference_tests::Tensor& dataTensor, const reference_tests::Tensor& axisTensor, const size_t numSplits,
-                const std::vector<reference_tests::Tensor>& expectedTensors, const std::string& testcaseName = "") :
-                dataTensor(dataTensor), axisTensor(axisTensor), numSplits(numSplits),
-                expectedTensors(expectedTensors), testcaseName(testcaseName) {}
+    SplitParams(const reference_tests::Tensor& dataTensor,
+                const reference_tests::Tensor& axisTensor,
+                const size_t numSplits,
+                const std::vector<reference_tests::Tensor>& expectedTensors,
+                const std::string& testcaseName = "")
+        : dataTensor(dataTensor),
+          axisTensor(axisTensor),
+          numSplits(numSplits),
+          expectedTensors(expectedTensors),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor dataTensor;
     reference_tests::Tensor axisTensor;
@@ -55,10 +62,10 @@ class ReferenceSplitTest : public testing::TestWithParam<SplitParams>, public Co
     static std::shared_ptr<Model> CreateFunction(const SplitParams& params) {
         const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, params.dataTensor.shape);
         const auto axis = std::make_shared<op::v0::Constant>(params.axisTensor.type,
-                                                                 params.axisTensor.shape,
-                                                                 params.axisTensor.data.data());
+                                                             params.axisTensor.shape,
+                                                             params.axisTensor.data.data());
         const auto split = std::make_shared<op::v1::Split>(data, axis, params.numSplits);
-        return std::make_shared<ov::Model>(split->outputs(), ParameterVector {data});
+        return std::make_shared<ov::Model>(split->outputs(), ParameterVector{data});
     }
 };
 
@@ -69,91 +76,117 @@ TEST_P(ReferenceSplitTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<SplitParams> generateSplitParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<SplitParams> splitParams {
+    std::vector<SplitParams> splitParams{
         // split_1d
         SplitParams(reference_tests::Tensor({6}, IN_ET, std::vector<T>{1, 2, 3, 4, 5, 6}),
                     reference_tests::Tensor({}, element::i64, std::vector<int64_t>{0}),
                     3,
                     std::vector<reference_tests::Tensor>{reference_tests::Tensor({2}, IN_ET, std::vector<T>{1, 2}),
-                                        reference_tests::Tensor({2}, IN_ET, std::vector<T>{3, 4}),
-                                        reference_tests::Tensor({2}, IN_ET, std::vector<T>{5, 6})},
+                                                         reference_tests::Tensor({2}, IN_ET, std::vector<T>{3, 4}),
+                                                         reference_tests::Tensor({2}, IN_ET, std::vector<T>{5, 6})},
                     "split_1d"),
         // split_2d_axis_0
         SplitParams(reference_tests::Tensor({6, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}),
                     reference_tests::Tensor({}, element::i64, std::vector<int64_t>{0}),
                     2,
-                    std::vector<reference_tests::Tensor>{reference_tests::Tensor({3, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5}),
-                                        reference_tests::Tensor({3, 2}, IN_ET, std::vector<T>{6, 7, 8, 9, 10, 11})},
+                    std::vector<reference_tests::Tensor>{
+                        reference_tests::Tensor({3, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5}),
+                        reference_tests::Tensor({3, 2}, IN_ET, std::vector<T>{6, 7, 8, 9, 10, 11})},
                     "split_2d_axis_0"),
         // split_2d_axis_1
         SplitParams(reference_tests::Tensor({6, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}),
                     reference_tests::Tensor({}, element::i64, std::vector<int64_t>{1}),
                     2,
-                    std::vector<reference_tests::Tensor>{reference_tests::Tensor({6, 1}, IN_ET, std::vector<T>{0, 2, 4, 6, 8, 10}),
-                                        reference_tests::Tensor({6, 1}, IN_ET, std::vector<T>{1, 3, 5, 7, 9, 11})},
+                    std::vector<reference_tests::Tensor>{
+                        reference_tests::Tensor({6, 1}, IN_ET, std::vector<T>{0, 2, 4, 6, 8, 10}),
+                        reference_tests::Tensor({6, 1}, IN_ET, std::vector<T>{1, 3, 5, 7, 9, 11})},
                     "split_2d_axis_1"),
         // split_3d_axis_0
         SplitParams(reference_tests::Tensor({2, 2, 3}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}),
                     reference_tests::Tensor({}, element::i64, std::vector<int64_t>{0}),
                     2,
-                    std::vector<reference_tests::Tensor>{reference_tests::Tensor({1, 2, 3}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5}),
-                                        reference_tests::Tensor({1, 2, 3}, IN_ET, std::vector<T>{6, 7, 8, 9, 10, 11})},
+                    std::vector<reference_tests::Tensor>{
+                        reference_tests::Tensor({1, 2, 3}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5}),
+                        reference_tests::Tensor({1, 2, 3}, IN_ET, std::vector<T>{6, 7, 8, 9, 10, 11})},
                     "split_3d_axis_0"),
         // split_3d_axis_1
-        SplitParams(reference_tests::Tensor({2, 8, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                            16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
+        SplitParams(reference_tests::Tensor({2, 8, 2}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10,
+                                                                             11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
+                                                                             22, 23, 24, 25, 26, 27, 28, 29, 30, 31}),
                     reference_tests::Tensor({}, element::i64, std::vector<int64_t>{1}),
                     4,
-                    std::vector<reference_tests::Tensor>{reference_tests::Tensor({2, 2, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 16, 17, 18, 19}),
-                                        reference_tests::Tensor({2, 2, 2}, IN_ET, std::vector<T>{4, 5, 6, 7, 20, 21, 22, 23}),
-                                        reference_tests::Tensor({2, 2, 2}, IN_ET, std::vector<T>{8, 9, 10, 11, 24, 25, 26, 27}),
-                                        reference_tests::Tensor({2, 2, 2}, IN_ET, std::vector<T>{12, 13, 14, 15, 28, 29, 30, 31})},
+                    std::vector<reference_tests::Tensor>{
+                        reference_tests::Tensor({2, 2, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 16, 17, 18, 19}),
+                        reference_tests::Tensor({2, 2, 2}, IN_ET, std::vector<T>{4, 5, 6, 7, 20, 21, 22, 23}),
+                        reference_tests::Tensor({2, 2, 2}, IN_ET, std::vector<T>{8, 9, 10, 11, 24, 25, 26, 27}),
+                        reference_tests::Tensor({2, 2, 2}, IN_ET, std::vector<T>{12, 13, 14, 15, 28, 29, 30, 31})},
                     "split_3d_axis_1"),
         // split_3d_axis_2
         SplitParams(reference_tests::Tensor({2, 1, 6}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11}),
                     reference_tests::Tensor({}, element::i64, std::vector<int64_t>{2}),
                     2,
-                    std::vector<reference_tests::Tensor>{reference_tests::Tensor({2, 1, 3}, IN_ET, std::vector<T>{0, 1, 2, 6, 7, 8}),
-                                        reference_tests::Tensor({2, 1, 3}, IN_ET, std::vector<T>{3, 4, 5, 9, 10, 11})},
+                    std::vector<reference_tests::Tensor>{
+                        reference_tests::Tensor({2, 1, 3}, IN_ET, std::vector<T>{0, 1, 2, 6, 7, 8}),
+                        reference_tests::Tensor({2, 1, 3}, IN_ET, std::vector<T>{3, 4, 5, 9, 10, 11})},
                     "split_3d_axis_2"),
         // split_4d_axis_0
-        SplitParams(reference_tests::Tensor({3, 2, 3, 1}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17}),
-                    reference_tests::Tensor({}, element::i64, std::vector<int64_t>{0}),
-                    3,
-                    std::vector<reference_tests::Tensor>{reference_tests::Tensor({1, 2, 3, 1}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5}),
-                                        reference_tests::Tensor({1, 2, 3, 1}, IN_ET, std::vector<T>{6, 7, 8, 9, 10, 11}),
-                                        reference_tests::Tensor({1, 2, 3, 1}, IN_ET, std::vector<T>{12, 13, 14, 15, 16, 17})},
-                    "split_4d_axis_0"),
+        SplitParams(
+            reference_tests::Tensor({3, 2, 3, 1},
+                                    IN_ET,
+                                    std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17}),
+            reference_tests::Tensor({}, element::i64, std::vector<int64_t>{0}),
+            3,
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor({1, 2, 3, 1}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5}),
+                reference_tests::Tensor({1, 2, 3, 1}, IN_ET, std::vector<T>{6, 7, 8, 9, 10, 11}),
+                reference_tests::Tensor({1, 2, 3, 1}, IN_ET, std::vector<T>{12, 13, 14, 15, 16, 17})},
+            "split_4d_axis_0"),
         // split_4d_axis_1
-        SplitParams(reference_tests::Tensor({2, 8, 2, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15,
-                                                               16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
-                                                               32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
-                                                               48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63}),
-                    reference_tests::Tensor({}, element::i64, std::vector<int64_t>{1}),
-                    4,
-                    std::vector<reference_tests::Tensor>{
-                        reference_tests::Tensor({2, 2, 2, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 32, 33, 34, 35, 36, 37, 38, 39}),
-                        reference_tests::Tensor({2, 2, 2, 2}, IN_ET, std::vector<T>{8, 9, 10, 11, 12, 13, 14, 15, 40, 41, 42, 43, 44, 45, 46, 47}),
-                        reference_tests::Tensor({2, 2, 2, 2}, IN_ET, std::vector<T>{16, 17, 18, 19, 20, 21, 22, 23, 48, 49, 50, 51, 52, 53, 54, 55}),
-                        reference_tests::Tensor({2, 2, 2, 2}, IN_ET, std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31, 56, 57, 58, 59, 60, 61, 62, 63})},
-                    "split_4d_axis_1"),
+        SplitParams(
+            reference_tests::Tensor(
+                {2, 8, 2, 2},
+                IN_ET,
+                std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
+                               22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,
+                               44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63}),
+            reference_tests::Tensor({}, element::i64, std::vector<int64_t>{1}),
+            4,
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor({2, 2, 2, 2},
+                                        IN_ET,
+                                        std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 32, 33, 34, 35, 36, 37, 38, 39}),
+                reference_tests::Tensor({2, 2, 2, 2},
+                                        IN_ET,
+                                        std::vector<T>{8, 9, 10, 11, 12, 13, 14, 15, 40, 41, 42, 43, 44, 45, 46, 47}),
+                reference_tests::Tensor({2, 2, 2, 2},
+                                        IN_ET,
+                                        std::vector<T>{16, 17, 18, 19, 20, 21, 22, 23, 48, 49, 50, 51, 52, 53, 54, 55}),
+                reference_tests::Tensor(
+                    {2, 2, 2, 2},
+                    IN_ET,
+                    std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31, 56, 57, 58, 59, 60, 61, 62, 63})},
+            "split_4d_axis_1"),
         // split_4d_axis_2
-        SplitParams(reference_tests::Tensor({2, 1, 6, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
-                                                               12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+        SplitParams(reference_tests::Tensor({2, 1, 6, 2}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,
+                                                                                8,  9,  10, 11, 12, 13, 14, 15,
+                                                                                16, 17, 18, 19, 20, 21, 22, 23}),
                     reference_tests::Tensor({}, element::i64, std::vector<int64_t>{2}),
                     3,
-                    std::vector<reference_tests::Tensor>{reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 12, 13, 14, 15}),
-                                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{4, 5, 6, 7, 16, 17, 18, 19}),
-                                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{8, 9, 10, 11, 20, 21, 22, 23})},
+                    std::vector<reference_tests::Tensor>{
+                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{0, 1, 2, 3, 12, 13, 14, 15}),
+                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{4, 5, 6, 7, 16, 17, 18, 19}),
+                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{8, 9, 10, 11, 20, 21, 22, 23})},
                     "split_4d_axis_2"),
         // split_4d_axis_3
-        SplitParams(reference_tests::Tensor({2, 1, 2, 6}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
-                                                               12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+        SplitParams(reference_tests::Tensor({2, 1, 2, 6}, IN_ET, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,
+                                                                                8,  9,  10, 11, 12, 13, 14, 15,
+                                                                                16, 17, 18, 19, 20, 21, 22, 23}),
                     reference_tests::Tensor({}, element::i64, std::vector<int64_t>{3}),
                     3,
-                    std::vector<reference_tests::Tensor>{reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{0, 1, 6, 7, 12, 13, 18, 19}),
-                                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{2, 3, 8, 9, 14, 15, 20, 21}),
-                                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{4, 5, 10, 11, 16, 17, 22, 23})},
+                    std::vector<reference_tests::Tensor>{
+                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{0, 1, 6, 7, 12, 13, 18, 19}),
+                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{2, 3, 8, 9, 14, 15, 20, 21}),
+                        reference_tests::Tensor({2, 1, 2, 2}, IN_ET, std::vector<T>{4, 5, 10, 11, 16, 17, 22, 23})},
                     "split_4d_axis_3"),
         // split_4d_axis_negative_2
         SplitParams(reference_tests::Tensor({2, 1, 4, 1}, IN_ET, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7}),
@@ -168,7 +201,7 @@ std::vector<SplitParams> generateSplitParams() {
 }
 
 std::vector<SplitParams> generateSplitCombinedParams() {
-    const std::vector<std::vector<SplitParams>> splitTypeParams {
+    const std::vector<std::vector<SplitParams>> splitTypeParams{
         generateSplitParams<element::Type_t::boolean>(),
         generateSplitParams<element::Type_t::i8>(),
         generateSplitParams<element::Type_t::i16>(),
@@ -189,6 +222,8 @@ std::vector<SplitParams> generateSplitCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Split_With_Hardcoded_Refs, ReferenceSplitTest,
-    testing::ValuesIn(generateSplitCombinedParams()), ReferenceSplitTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Split_With_Hardcoded_Refs,
+                         ReferenceSplitTest,
+                         testing::ValuesIn(generateSplitCombinedParams()),
+                         ReferenceSplitTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/squared_difference.cpp b/src/plugins/template/tests/functional/op_reference/squared_difference.cpp
index 747f52e5bd75ad..230798b927fcd8 100644
--- a/src/plugins/template/tests/functional/op_reference/squared_difference.cpp
+++ b/src/plugins/template/tests/functional/op_reference/squared_difference.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/squared_difference.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/squared_difference.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,11 +16,11 @@ namespace {
 struct SquaredDifferenceParams {
     template <class IT>
     SquaredDifferenceParams(const PartialShape& iShape1,
-              const PartialShape& iShape2,
-              const element::Type& iType,
-              const std::vector<IT>& iValues1,
-              const std::vector<IT>& iValues2,
-              const std::vector<IT>& oValues)
+                            const PartialShape& iShape2,
+                            const element::Type& iType,
+                            const std::vector<IT>& iValues1,
+                            const std::vector<IT>& iValues2,
+                            const std::vector<IT>& oValues)
         : pshape1(iShape1),
           pshape2(iShape2),
           inType(iType),
@@ -36,7 +38,8 @@ struct SquaredDifferenceParams {
     ov::Tensor refData;
 };
 
-class ReferenceSquaredDifferenceLayerTest : public testing::TestWithParam<SquaredDifferenceParams>, public CommonReferenceTest {
+class ReferenceSquaredDifferenceLayerTest : public testing::TestWithParam<SquaredDifferenceParams>,
+                                            public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -57,9 +60,9 @@ class ReferenceSquaredDifferenceLayerTest : public testing::TestWithParam<Square
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto squared_difference = std::make_shared<op::v0::SquaredDifference>(in1, in2);
@@ -69,7 +72,7 @@ class ReferenceSquaredDifferenceLayerTest : public testing::TestWithParam<Square
 };
 
 class ReferenceSquaredDifferenceInPlaceLayerTest : public testing::TestWithParam<SquaredDifferenceParams>,
-                                            public CommonReferenceTest {
+                                                   public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -90,9 +93,9 @@ class ReferenceSquaredDifferenceInPlaceLayerTest : public testing::TestWithParam
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         auto squared_difference = std::make_shared<op::v0::SquaredDifference>(in1, in2);
@@ -116,36 +119,35 @@ std::vector<SquaredDifferenceParams> generateParamsForSquaredDifference() {
 
     std::vector<SquaredDifferenceParams> params{
         SquaredDifferenceParams(ov::PartialShape{1, 2},
-                       ov::PartialShape{1, 2},
-                       IN_ET,
-                       std::vector<T>{256, 56},
-                       std::vector<T>{256, 56},
-                       std::vector<T>{0, 0}),
+                                ov::PartialShape{1, 2},
+                                IN_ET,
+                                std::vector<T>{256, 56},
+                                std::vector<T>{256, 56},
+                                std::vector<T>{0, 0}),
         SquaredDifferenceParams(ov::PartialShape{2, 2},
-                       ov::PartialShape{2, 2},
-                       IN_ET,
-                       std::vector<T>{256, 56, -21, -14},
-                       std::vector<T>{-112, 56, 6, -8},
-                       std::vector<T>{135424, 0, 729, 36}),
+                                ov::PartialShape{2, 2},
+                                IN_ET,
+                                std::vector<T>{256, 56, -21, -14},
+                                std::vector<T>{-112, 56, 6, -8},
+                                std::vector<T>{135424, 0, 729, 36}),
         SquaredDifferenceParams(ov::PartialShape{1, 2},
-                       ov::PartialShape{3, 2, 2},
-                       IN_ET,
-                       std::vector<T>{1, 2},
-                       std::vector<T>{5, 6, 7, 8, 2, 3, 1, 5, 6, 7, 1, 3},
-                       std::vector<T>{16, 16, 36, 36, 1, 1, 0, 9, 25, 25, 0, 1}),
+                                ov::PartialShape{3, 2, 2},
+                                IN_ET,
+                                std::vector<T>{1, 2},
+                                std::vector<T>{5, 6, 7, 8, 2, 3, 1, 5, 6, 7, 1, 3},
+                                std::vector<T>{16, 16, 36, 36, 1, 1, 0, 9, 25, 25, 0, 1}),
         SquaredDifferenceParams(ov::PartialShape{1},
-                    ov::PartialShape{1},
-                    IN_ET,
-                    std::vector<T>{57},
-                    std::vector<T>{13},
-                    std::vector<T>{1936}),
+                                ov::PartialShape{1},
+                                IN_ET,
+                                std::vector<T>{57},
+                                std::vector<T>{13},
+                                std::vector<T>{1936}),
         SquaredDifferenceParams(ov::PartialShape{2, 2},
                                 ov::PartialShape{1},
                                 IN_ET,
                                 std::vector<T>{2, 4, 7, 8},
                                 std::vector<T>{8},
-                                std::vector<T>{36, 16, 1, 0})
-    };
+                                std::vector<T>{36, 16, 1, 0})};
     return params;
 }
 
@@ -153,14 +155,12 @@ template <element::Type_t IN_ET>
 std::vector<SquaredDifferenceParams> generateParamsForSquaredDifferenceInPlace() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<SquaredDifferenceParams> params{
-        SquaredDifferenceParams(ov::PartialShape{2, 2},
-                                ov::PartialShape{2, 2},
-                                IN_ET,
-                                std::vector<T>{1, 2, 3, 4},
-                                std::vector<T>{5, 6, 7, 8},
-                                std::vector<T>{0, 0, 0, 0})
-    };
+    std::vector<SquaredDifferenceParams> params{SquaredDifferenceParams(ov::PartialShape{2, 2},
+                                                                        ov::PartialShape{2, 2},
+                                                                        IN_ET,
+                                                                        std::vector<T>{1, 2, 3, 4},
+                                                                        std::vector<T>{5, 6, 7, 8},
+                                                                        std::vector<T>{0, 0, 0, 0})};
     return params;
 }
 
@@ -169,8 +169,7 @@ std::vector<SquaredDifferenceParams> generateCombinedParamsForSquaredDifference(
         generateParamsForSquaredDifference<element::Type_t::f32>(),
         generateParamsForSquaredDifference<element::Type_t::f16>(),
         generateParamsForSquaredDifference<element::Type_t::i64>(),
-        generateParamsForSquaredDifference<element::Type_t::i32>()
-    };
+        generateParamsForSquaredDifference<element::Type_t::i32>()};
 
     std::vector<SquaredDifferenceParams> combinedParams;
 
@@ -197,16 +196,14 @@ std::vector<SquaredDifferenceParams> generateCombinedParamsForSquaredDifferenceI
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_SquaredDifference_With_Hardcoded_Refs,
-    ReferenceSquaredDifferenceLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForSquaredDifference()),
-    ReferenceSquaredDifferenceLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_SquaredDifferenceInPlace_With_Hardcoded_Refs,
-    ReferenceSquaredDifferenceInPlaceLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForSquaredDifferenceInPlace()),
-    ReferenceSquaredDifferenceInPlaceLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_SquaredDifference_With_Hardcoded_Refs,
+                         ReferenceSquaredDifferenceLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForSquaredDifference()),
+                         ReferenceSquaredDifferenceLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_SquaredDifferenceInPlace_With_Hardcoded_Refs,
+                         ReferenceSquaredDifferenceInPlaceLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForSquaredDifferenceInPlace()),
+                         ReferenceSquaredDifferenceInPlaceLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/squeeze.cpp b/src/plugins/template/tests/functional/op_reference/squeeze.cpp
index 60639bfc54d4f8..0a1504de880d6d 100644
--- a/src/plugins/template/tests/functional/op_reference/squeeze.cpp
+++ b/src/plugins/template/tests/functional/op_reference/squeeze.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/squeeze.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/squeeze.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -94,7 +95,8 @@ class ReferenceSqueezeLayerTest : public testing::TestWithParam<SqueezeParams>,
         std::shared_ptr<op::v0::Constant> axes_node = NULL;
         std::shared_ptr<op::v0::Squeeze> squeeze = NULL;
         if (params.m_axes_node) {
-            axes_node = std::make_shared<op::v0::Constant>(params.m_axes_type, params.m_axes_shape, params.m_axes_value.data());
+            axes_node =
+                std::make_shared<op::v0::Constant>(params.m_axes_type, params.m_axes_shape, params.m_axes_value.data());
             squeeze = std::make_shared<op::v0::Squeeze>(in, axes_node);
         } else {
             squeeze = std::make_shared<op::v0::Squeeze>(in);
@@ -120,7 +122,7 @@ std::vector<SqueezeParams> generateParamsForSqueeze() {
                       IO_T,
                       std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
                       std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
-                      Shape {2},
+                      Shape{2},
                       Axes_T,
                       std::vector<T2>{0, 2}),
         SqueezeParams(Shape{1, 4, 1, 1, 2},
@@ -153,8 +155,7 @@ std::vector<SqueezeParams> generateCombinedParamsForSqueeze() {
         generateParamsForSqueeze<element::Type_t::u64, element::Type_t::i64>(),
         generateParamsForSqueeze<element::Type_t::u32, element::Type_t::i64>(),
         generateParamsForSqueeze<element::Type_t::u16, element::Type_t::i64>(),
-        generateParamsForSqueeze<element::Type_t::u8, element::Type_t::i64>()
-    };
+        generateParamsForSqueeze<element::Type_t::u8, element::Type_t::i64>()};
 
     std::vector<SqueezeParams> combinedParams;
 
@@ -165,10 +166,9 @@ std::vector<SqueezeParams> generateCombinedParamsForSqueeze() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Squeeze_With_Hardcoded_Refs,
-    ReferenceSqueezeLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForSqueeze()),
-    ReferenceSqueezeLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Squeeze_With_Hardcoded_Refs,
+                         ReferenceSqueezeLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForSqueeze()),
+                         ReferenceSqueezeLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/strided_slice.cpp b/src/plugins/template/tests/functional/op_reference/strided_slice.cpp
index 423397a85a983a..54ae9bb8ed35bf 100644
--- a/src/plugins/template/tests/functional/op_reference/strided_slice.cpp
+++ b/src/plugins/template/tests/functional/op_reference/strided_slice.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/strided_slice.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/strided_slice.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -24,12 +25,19 @@ struct StridedSliceParams {
                        const std::vector<int64_t>& shrinkAxisMask,
                        const std::vector<int64_t>& ellipsisMask,
                        const reference_tests::Tensor& expectedTensor,
-                       const std::string& testcaseName = "") :
-        dynamicDataShape(dynamicDataShape), dataTensor(dataTensor),
-        beginTensor(beginTensor), endTensor(endTensor),
-        stridesTensor(stridesTensor), beginMask(beginMask), endMask(endMask),
-        newAxisMask(newAxisMask), shrinkAxisMask(shrinkAxisMask), ellipsisMask(ellipsisMask),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+                       const std::string& testcaseName = "")
+        : dynamicDataShape(dynamicDataShape),
+          dataTensor(dataTensor),
+          beginTensor(beginTensor),
+          endTensor(endTensor),
+          stridesTensor(stridesTensor),
+          beginMask(beginMask),
+          endMask(endMask),
+          newAxisMask(newAxisMask),
+          shrinkAxisMask(shrinkAxisMask),
+          ellipsisMask(ellipsisMask),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     PartialShape dynamicDataShape;
     reference_tests::Tensor dataTensor;
@@ -47,21 +55,27 @@ struct StridedSliceParams {
 
 struct StridedSliceStrideOptionalParams {
     StridedSliceStrideOptionalParams(const PartialShape& dynamicDataShape,
-                       const reference_tests::Tensor& dataTensor,
-                       const reference_tests::Tensor& beginTensor,
-                       const reference_tests::Tensor& endTensor,
-                       const std::vector<int64_t>& beginMask,
-                       const std::vector<int64_t>& endMask,
-                       const std::vector<int64_t>& newAxisMask,
-                       const std::vector<int64_t>& shrinkAxisMask,
-                       const std::vector<int64_t>& ellipsisMask,
-                       const reference_tests::Tensor& expectedTensor,
-                       const std::string& testcaseName = "") :
-        dynamicDataShape(dynamicDataShape), dataTensor(dataTensor),
-        beginTensor(beginTensor), endTensor(endTensor),
-        beginMask(beginMask), endMask(endMask),
-        newAxisMask(newAxisMask), shrinkAxisMask(shrinkAxisMask), ellipsisMask(ellipsisMask),
-        expectedTensor(expectedTensor), testcaseName(testcaseName) {}
+                                     const reference_tests::Tensor& dataTensor,
+                                     const reference_tests::Tensor& beginTensor,
+                                     const reference_tests::Tensor& endTensor,
+                                     const std::vector<int64_t>& beginMask,
+                                     const std::vector<int64_t>& endMask,
+                                     const std::vector<int64_t>& newAxisMask,
+                                     const std::vector<int64_t>& shrinkAxisMask,
+                                     const std::vector<int64_t>& ellipsisMask,
+                                     const reference_tests::Tensor& expectedTensor,
+                                     const std::string& testcaseName = "")
+        : dynamicDataShape(dynamicDataShape),
+          dataTensor(dataTensor),
+          beginTensor(beginTensor),
+          endTensor(endTensor),
+          beginMask(beginMask),
+          endMask(endMask),
+          newAxisMask(newAxisMask),
+          shrinkAxisMask(shrinkAxisMask),
+          ellipsisMask(ellipsisMask),
+          expectedTensor(expectedTensor),
+          testcaseName(testcaseName) {}
 
     PartialShape dynamicDataShape;
     reference_tests::Tensor dataTensor;
@@ -84,7 +98,10 @@ class ReferenceStridedSliceLayerTest : public testing::TestWithParam<StridedSlic
         if (params.dynamicDataShape.is_static()) {
             inputData = {params.dataTensor.data};
         } else {
-            inputData = {params.dataTensor.data, params.beginTensor.data, params.endTensor.data, params.stridesTensor.data};
+            inputData = {params.dataTensor.data,
+                         params.beginTensor.data,
+                         params.endTensor.data,
+                         params.stridesTensor.data};
         }
         refOutData = {params.expectedTensor.data};
     }
@@ -116,31 +133,49 @@ class ReferenceStridedSliceLayerTest : public testing::TestWithParam<StridedSlic
         std::shared_ptr<Model> function;
         if (params.dynamicDataShape.is_static()) {
             const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, params.dataTensor.shape);
-            const auto beginOp = std::make_shared<op::v0::Constant>(params.beginTensor.type, params.beginTensor.shape,
+            const auto beginOp = std::make_shared<op::v0::Constant>(params.beginTensor.type,
+                                                                    params.beginTensor.shape,
                                                                     params.beginTensor.data.data());
-            const auto endOp = std::make_shared<op::v0::Constant>(params.endTensor.type, params.endTensor.shape,
+            const auto endOp = std::make_shared<op::v0::Constant>(params.endTensor.type,
+                                                                  params.endTensor.shape,
                                                                   params.endTensor.data.data());
-            const auto stridesOp = std::make_shared<op::v0::Constant>(params.stridesTensor.type, params.stridesTensor.shape,
+            const auto stridesOp = std::make_shared<op::v0::Constant>(params.stridesTensor.type,
+                                                                      params.stridesTensor.shape,
                                                                       params.stridesTensor.data.data());
-            const auto StridedSlice = std::make_shared<op::v1::StridedSlice>(data, beginOp, endOp, stridesOp,
-                                                                             params.beginMask, params.endMask, params.newAxisMask,
-                                                                             params.shrinkAxisMask, params.ellipsisMask);
+            const auto StridedSlice = std::make_shared<op::v1::StridedSlice>(data,
+                                                                             beginOp,
+                                                                             endOp,
+                                                                             stridesOp,
+                                                                             params.beginMask,
+                                                                             params.endMask,
+                                                                             params.newAxisMask,
+                                                                             params.shrinkAxisMask,
+                                                                             params.ellipsisMask);
             function = std::make_shared<ov::Model>(NodeVector{StridedSlice}, ParameterVector{data});
         } else {
             const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, PartialShape::dynamic());
             const auto beginOp = std::make_shared<op::v0::Parameter>(params.beginTensor.type, params.beginTensor.shape);
             const auto endOp = std::make_shared<op::v0::Parameter>(params.endTensor.type, params.endTensor.shape);
-            const auto stridesOp = std::make_shared<op::v0::Parameter>(params.stridesTensor.type, params.stridesTensor.shape);
-            const auto StridedSlice = std::make_shared<op::v1::StridedSlice>(data, beginOp, endOp, stridesOp,
-                                                                             params.beginMask, params.endMask, params.newAxisMask,
-                                                                             params.shrinkAxisMask, params.ellipsisMask);
-            function = std::make_shared<ov::Model>(NodeVector{StridedSlice}, ParameterVector{data, beginOp, endOp, stridesOp});
+            const auto stridesOp =
+                std::make_shared<op::v0::Parameter>(params.stridesTensor.type, params.stridesTensor.shape);
+            const auto StridedSlice = std::make_shared<op::v1::StridedSlice>(data,
+                                                                             beginOp,
+                                                                             endOp,
+                                                                             stridesOp,
+                                                                             params.beginMask,
+                                                                             params.endMask,
+                                                                             params.newAxisMask,
+                                                                             params.shrinkAxisMask,
+                                                                             params.ellipsisMask);
+            function =
+                std::make_shared<ov::Model>(NodeVector{StridedSlice}, ParameterVector{data, beginOp, endOp, stridesOp});
         }
         return function;
     }
 };
 
-class ReferenceStridedSliceLayerTestStrideOptional : public testing::TestWithParam<StridedSliceStrideOptionalParams>, public CommonReferenceTest {
+class ReferenceStridedSliceLayerTestStrideOptional : public testing::TestWithParam<StridedSliceStrideOptionalParams>,
+                                                     public CommonReferenceTest {
 public:
     void SetUp() override {
         auto params = GetParam();
@@ -178,21 +213,33 @@ class ReferenceStridedSliceLayerTestStrideOptional : public testing::TestWithPar
         std::shared_ptr<Model> function;
         if (params.dynamicDataShape.is_static()) {
             const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, params.dataTensor.shape);
-            const auto beginOp = std::make_shared<op::v0::Constant>(params.beginTensor.type, params.beginTensor.shape,
+            const auto beginOp = std::make_shared<op::v0::Constant>(params.beginTensor.type,
+                                                                    params.beginTensor.shape,
                                                                     params.beginTensor.data.data());
-            const auto endOp = std::make_shared<op::v0::Constant>(params.endTensor.type, params.endTensor.shape,
+            const auto endOp = std::make_shared<op::v0::Constant>(params.endTensor.type,
+                                                                  params.endTensor.shape,
                                                                   params.endTensor.data.data());
-            const auto StridedSlice = std::make_shared<op::v1::StridedSlice>(data, beginOp, endOp,
-                                                                             params.beginMask, params.endMask, params.newAxisMask,
-                                                                             params.shrinkAxisMask, params.ellipsisMask);
+            const auto StridedSlice = std::make_shared<op::v1::StridedSlice>(data,
+                                                                             beginOp,
+                                                                             endOp,
+                                                                             params.beginMask,
+                                                                             params.endMask,
+                                                                             params.newAxisMask,
+                                                                             params.shrinkAxisMask,
+                                                                             params.ellipsisMask);
             function = std::make_shared<ov::Model>(NodeVector{StridedSlice}, ParameterVector{data});
         } else {
             const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, PartialShape::dynamic());
             const auto beginOp = std::make_shared<op::v0::Parameter>(params.beginTensor.type, params.beginTensor.shape);
             const auto endOp = std::make_shared<op::v0::Parameter>(params.endTensor.type, params.endTensor.shape);
-            const auto StridedSlice = std::make_shared<op::v1::StridedSlice>(data, beginOp, endOp,
-                                                                             params.beginMask, params.endMask, params.newAxisMask,
-                                                                             params.shrinkAxisMask, params.ellipsisMask);
+            const auto StridedSlice = std::make_shared<op::v1::StridedSlice>(data,
+                                                                             beginOp,
+                                                                             endOp,
+                                                                             params.beginMask,
+                                                                             params.endMask,
+                                                                             params.newAxisMask,
+                                                                             params.shrinkAxisMask,
+                                                                             params.ellipsisMask);
             function = std::make_shared<ov::Model>(NodeVector{StridedSlice}, ParameterVector{data, beginOp, endOp});
         }
         return function;
@@ -207,7 +254,7 @@ TEST_P(ReferenceStridedSliceLayerTestStrideOptional, CompareWithRefs) {
     Exec();
 }
 
-template<typename T>
+template <typename T>
 std::vector<T> generateInputValues(const Shape& input_shape, T initial) {
     std::vector<T> input_values(shape_size(input_shape));
     std::iota(input_values.begin(), input_values.end(), static_cast<T>(initial));
@@ -217,12 +264,12 @@ std::vector<T> generateInputValues(const Shape& input_shape, T initial) {
 template <element::Type_t IN_ET>
 std::vector<StridedSliceParams> generateSmallParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<StridedSliceParams> params {
+    std::vector<StridedSliceParams> params{
         // strided_slice_0
         StridedSliceParams(
             {},
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                    12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+                                                                     12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 1}),
@@ -237,7 +284,7 @@ std::vector<StridedSliceParams> generateSmallParams() {
         StridedSliceParams(
             PartialShape::dynamic(),
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                    12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+                                                                     12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 1}),
@@ -255,12 +302,12 @@ std::vector<StridedSliceParams> generateSmallParams() {
 template <element::Type_t IN_ET>
 std::vector<StridedSliceParams> generateParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<StridedSliceParams> params {
+    std::vector<StridedSliceParams> params{
         // strided_slice_0
         StridedSliceParams(
             {},
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                    12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+                                                                     12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 1}),
@@ -275,7 +322,7 @@ std::vector<StridedSliceParams> generateParams() {
         StridedSliceParams(
             PartialShape::dynamic(),
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                    12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+                                                                     12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 1}),
@@ -298,16 +345,18 @@ std::vector<StridedSliceParams> generateParams() {
             std::vector<int64_t>{0, 0, 0, 0, 1, 0, 0},
             std::vector<int64_t>{0, 0, 0, 0, 0, 0, 1},
             std::vector<int64_t>{0, 0, 0, 0, 0, 1, 0},
-            reference_tests::Tensor(IN_ET, {2, 4, 2, 2, 1, 2, 2}, std::vector<T>{
-                185,  187,  189,  191,  169,  171,  173,  175,  313,  315,  317,  319,  297,  299,  301,
-                303,  569,  571,  573,  575,  553,  555,  557,  559,  697,  699,  701,  703,  681,  683,
-                685,  687,  953,  955,  957,  959,  937,  939,  941,  943,  1081, 1083, 1085, 1087, 1065,
-                1067, 1069, 1071, 1337, 1339, 1341, 1343, 1321, 1323, 1325, 1327, 1465, 1467, 1469, 1471,
-                1449, 1451, 1453, 1455, 1721, 1723, 1725, 1727, 1705, 1707, 1709, 1711, 1849, 1851, 1853,
-                1855, 1833, 1835, 1837, 1839, 2105, 2107, 2109, 2111, 2089, 2091, 2093, 2095, 2233, 2235,
-                2237, 2239, 2217, 2219, 2221, 2223, 2489, 2491, 2493, 2495, 2473, 2475, 2477, 2479, 2617,
-                2619, 2621, 2623, 2601, 2603, 2605, 2607, 2873, 2875, 2877, 2879, 2857, 2859, 2861, 2863,
-                3001, 3003, 3005, 3007, 2985, 2987, 2989, 2991}),
+            reference_tests::Tensor(
+                IN_ET,
+                {2, 4, 2, 2, 1, 2, 2},
+                std::vector<T>{185,  187,  189,  191,  169,  171,  173,  175,  313,  315,  317,  319,  297,  299,  301,
+                               303,  569,  571,  573,  575,  553,  555,  557,  559,  697,  699,  701,  703,  681,  683,
+                               685,  687,  953,  955,  957,  959,  937,  939,  941,  943,  1081, 1083, 1085, 1087, 1065,
+                               1067, 1069, 1071, 1337, 1339, 1341, 1343, 1321, 1323, 1325, 1327, 1465, 1467, 1469, 1471,
+                               1449, 1451, 1453, 1455, 1721, 1723, 1725, 1727, 1705, 1707, 1709, 1711, 1849, 1851, 1853,
+                               1855, 1833, 1835, 1837, 1839, 2105, 2107, 2109, 2111, 2089, 2091, 2093, 2095, 2233, 2235,
+                               2237, 2239, 2217, 2219, 2221, 2223, 2489, 2491, 2493, 2495, 2473, 2475, 2477, 2479, 2617,
+                               2619, 2621, 2623, 2601, 2603, 2605, 2607, 2873, 2875, 2877, 2879, 2857, 2859, 2861, 2863,
+                               3001, 3003, 3005, 3007, 2985, 2987, 2989, 2991}),
             "strided_slice_1"),
         // strided_slice_1_dynamic
         StridedSliceParams(
@@ -321,16 +370,18 @@ std::vector<StridedSliceParams> generateParams() {
             std::vector<int64_t>{0, 0, 0, 0, 1, 0, 0},
             std::vector<int64_t>{0, 0, 0, 0, 0, 0, 1},
             std::vector<int64_t>{0, 0, 0, 0, 0, 1, 0},
-            reference_tests::Tensor(IN_ET, {2, 4, 2, 2, 1, 2, 2}, std::vector<T>{
-                185,  187,  189,  191,  169,  171,  173,  175,  313,  315,  317,  319,  297,  299,  301,
-                303,  569,  571,  573,  575,  553,  555,  557,  559,  697,  699,  701,  703,  681,  683,
-                685,  687,  953,  955,  957,  959,  937,  939,  941,  943,  1081, 1083, 1085, 1087, 1065,
-                1067, 1069, 1071, 1337, 1339, 1341, 1343, 1321, 1323, 1325, 1327, 1465, 1467, 1469, 1471,
-                1449, 1451, 1453, 1455, 1721, 1723, 1725, 1727, 1705, 1707, 1709, 1711, 1849, 1851, 1853,
-                1855, 1833, 1835, 1837, 1839, 2105, 2107, 2109, 2111, 2089, 2091, 2093, 2095, 2233, 2235,
-                2237, 2239, 2217, 2219, 2221, 2223, 2489, 2491, 2493, 2495, 2473, 2475, 2477, 2479, 2617,
-                2619, 2621, 2623, 2601, 2603, 2605, 2607, 2873, 2875, 2877, 2879, 2857, 2859, 2861, 2863,
-                3001, 3003, 3005, 3007, 2985, 2987, 2989, 2991}),
+            reference_tests::Tensor(
+                IN_ET,
+                {2, 4, 2, 2, 1, 2, 2},
+                std::vector<T>{185,  187,  189,  191,  169,  171,  173,  175,  313,  315,  317,  319,  297,  299,  301,
+                               303,  569,  571,  573,  575,  553,  555,  557,  559,  697,  699,  701,  703,  681,  683,
+                               685,  687,  953,  955,  957,  959,  937,  939,  941,  943,  1081, 1083, 1085, 1087, 1065,
+                               1067, 1069, 1071, 1337, 1339, 1341, 1343, 1321, 1323, 1325, 1327, 1465, 1467, 1469, 1471,
+                               1449, 1451, 1453, 1455, 1721, 1723, 1725, 1727, 1705, 1707, 1709, 1711, 1849, 1851, 1853,
+                               1855, 1833, 1835, 1837, 1839, 2105, 2107, 2109, 2111, 2089, 2091, 2093, 2095, 2233, 2235,
+                               2237, 2239, 2217, 2219, 2221, 2223, 2489, 2491, 2493, 2495, 2473, 2475, 2477, 2479, 2617,
+                               2619, 2621, 2623, 2601, 2603, 2605, 2607, 2873, 2875, 2877, 2879, 2857, 2859, 2861, 2863,
+                               3001, 3003, 3005, 3007, 2985, 2987, 2989, 2991}),
             "strided_slice_1_dynamic"),
     };
     return params;
@@ -339,12 +390,12 @@ std::vector<StridedSliceParams> generateParams() {
 template <element::Type_t IN_ET>
 std::vector<StridedSliceStrideOptionalParams> generateStrideOptionalParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<StridedSliceStrideOptionalParams> params {
+    std::vector<StridedSliceStrideOptionalParams> params{
         // strided_slice_stride_optional
         StridedSliceStrideOptionalParams(
             {},
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                    12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+                                                                     12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
             reference_tests::Tensor(element::i64, {3}, std::vector<int64_t>{-1, -1, 0}),
             reference_tests::Tensor(element::i64, {3}, std::vector<int64_t>{0, 0, 0}),
             std::vector<int64_t>{0, 0, 0},
@@ -358,7 +409,7 @@ std::vector<StridedSliceStrideOptionalParams> generateStrideOptionalParams() {
         StridedSliceStrideOptionalParams(
             PartialShape::dynamic(),
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                    12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+                                                                     12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
             reference_tests::Tensor(element::i64, {3}, std::vector<int64_t>{-1, -1, 0}),
             reference_tests::Tensor(element::i64, {3}, std::vector<int64_t>{0, 0, 0}),
             std::vector<int64_t>{0, 0, 0},
@@ -372,7 +423,7 @@ std::vector<StridedSliceStrideOptionalParams> generateStrideOptionalParams() {
         StridedSliceStrideOptionalParams(
             PartialShape::dynamic(),
             reference_tests::Tensor(IN_ET, {2, 3, 4}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11,
-                                                    12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
+                                                                     12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{0, 0}),
             reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{-1, 0}),
             std::vector<int64_t>{1, 0},
@@ -387,7 +438,7 @@ std::vector<StridedSliceStrideOptionalParams> generateStrideOptionalParams() {
 }
 
 std::vector<StridedSliceParams> generateCombinedParams() {
-    const std::vector<std::vector<StridedSliceParams>> generatedParams {
+    const std::vector<std::vector<StridedSliceParams>> generatedParams{
         generateSmallParams<element::Type_t::i8>(),
         generateParams<element::Type_t::i16>(),
         generateParams<element::Type_t::i32>(),
@@ -410,7 +461,7 @@ std::vector<StridedSliceParams> generateCombinedParams() {
 }
 
 std::vector<StridedSliceStrideOptionalParams> generateCombinedStrideOptionalParams() {
-    const std::vector<std::vector<StridedSliceStrideOptionalParams>> generatedParams {
+    const std::vector<std::vector<StridedSliceStrideOptionalParams>> generatedParams{
         generateStrideOptionalParams<element::Type_t::i8>(),
         generateStrideOptionalParams<element::Type_t::i16>(),
         generateStrideOptionalParams<element::Type_t::i32>(),
@@ -430,9 +481,13 @@ std::vector<StridedSliceStrideOptionalParams> generateCombinedStrideOptionalPara
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_StridedSlice_With_Hardcoded_Refs, ReferenceStridedSliceLayerTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceStridedSliceLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_StridedSlice_With_Hardcoded_Refs,
+                         ReferenceStridedSliceLayerTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceStridedSliceLayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_StridedSlice_With_Hardcoded_Refs, ReferenceStridedSliceLayerTestStrideOptional,
-    testing::ValuesIn(generateCombinedStrideOptionalParams()), ReferenceStridedSliceLayerTestStrideOptional::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_StridedSlice_With_Hardcoded_Refs,
+                         ReferenceStridedSliceLayerTestStrideOptional,
+                         testing::ValuesIn(generateCombinedStrideOptionalParams()),
+                         ReferenceStridedSliceLayerTestStrideOptional::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/subtract.cpp b/src/plugins/template/tests/functional/op_reference/subtract.cpp
index 5eb145d12d6dfe..12bc8c888cbed5 100644
--- a/src/plugins/template/tests/functional/op_reference/subtract.cpp
+++ b/src/plugins/template/tests/functional/op_reference/subtract.cpp
@@ -2,9 +2,11 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/subtract.hpp"
+
 #include <gtest/gtest.h>
+
 #include "base_reference_test.hpp"
-#include "openvino/op/subtract.hpp"
 
 using namespace ov;
 using namespace reference_tests;
@@ -14,11 +16,11 @@ namespace {
 struct SubtractParams {
     template <class IT>
     SubtractParams(const PartialShape& iShape1,
-              const PartialShape& iShape2,
-              const element::Type& iType,
-              const std::vector<IT>& iValues1,
-              const std::vector<IT>& iValues2,
-              const std::vector<IT>& oValues)
+                   const PartialShape& iShape2,
+                   const element::Type& iType,
+                   const std::vector<IT>& iValues1,
+                   const std::vector<IT>& iValues2,
+                   const std::vector<IT>& oValues)
         : pshape1(iShape1),
           pshape2(iShape2),
           inType(iType),
@@ -57,9 +59,9 @@ class ReferenceSubtractLayerTest : public testing::TestWithParam<SubtractParams>
 
 private:
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape1,
-                                                    const PartialShape& input_shape2,
-                                                    const element::Type& input_type,
-                                                    const element::Type& expected_output_type) {
+                                                 const PartialShape& input_shape2,
+                                                 const element::Type& input_type,
+                                                 const element::Type& expected_output_type) {
         const auto in1 = std::make_shared<op::v0::Parameter>(input_type, input_shape1);
         const auto in2 = std::make_shared<op::v0::Parameter>(input_type, input_shape2);
         const auto subtract = std::make_shared<op::v1::Subtract>(in1, in2);
@@ -88,19 +90,14 @@ std::vector<SubtractParams> generateParamsForSubtract() {
                        IN_ET,
                        std::vector<T>{12, 24, 36, 48, 60, 72},
                        std::vector<T>{1, 2, 3, 4, 6, 1},
-                       std::vector<T>{11, 10,  9,  8,  6, 11,
-                                      23, 22, 21, 20, 18, 23,
-                                      35, 34, 33, 32, 30, 35,
-                                      47, 46, 45, 44, 42, 47,
-                                      59, 58, 57, 56, 54, 59,
-                                      71, 70, 69, 68, 66, 71}),
+                       std::vector<T>{11, 10, 9,  8,  6,  11, 23, 22, 21, 20, 18, 23, 35, 34, 33, 32, 30, 35,
+                                      47, 46, 45, 44, 42, 47, 59, 58, 57, 56, 54, 59, 71, 70, 69, 68, 66, 71}),
         SubtractParams(ov::PartialShape{1},
                        ov::PartialShape{1},
                        IN_ET,
                        std::vector<T>{8},
                        std::vector<T>{2},
-                       std::vector<T>{6})
-    };
+                       std::vector<T>{6})};
     return params;
 }
 
@@ -108,27 +105,23 @@ template <element::Type_t IN_ET>
 std::vector<SubtractParams> generateParamsForSubtractFloat() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<SubtractParams> params{
-        SubtractParams(ov::PartialShape{1},
-                       ov::PartialShape{1},
-                       IN_ET,
-                       std::vector<T>{3.1},
-                       std::vector<T>{8},
-                       std::vector<T>{-4.9})
-    };
+    std::vector<SubtractParams> params{SubtractParams(ov::PartialShape{1},
+                                                      ov::PartialShape{1},
+                                                      IN_ET,
+                                                      std::vector<T>{3.1},
+                                                      std::vector<T>{8},
+                                                      std::vector<T>{-4.9})};
     return params;
 }
 
 std::vector<SubtractParams> generateCombinedParamsForSubtract() {
-    const std::vector<std::vector<SubtractParams>> allTypeParams{
-        generateParamsForSubtract<element::Type_t::f32>(),
-        generateParamsForSubtract<element::Type_t::f16>(),
-        generateParamsForSubtract<element::Type_t::bf16>(),
-        generateParamsForSubtract<element::Type_t::i64>(),
-        generateParamsForSubtract<element::Type_t::i32>(),
-        generateParamsForSubtract<element::Type_t::u64>(),
-        generateParamsForSubtract<element::Type_t::u32>()
-    };
+    const std::vector<std::vector<SubtractParams>> allTypeParams{generateParamsForSubtract<element::Type_t::f32>(),
+                                                                 generateParamsForSubtract<element::Type_t::f16>(),
+                                                                 generateParamsForSubtract<element::Type_t::bf16>(),
+                                                                 generateParamsForSubtract<element::Type_t::i64>(),
+                                                                 generateParamsForSubtract<element::Type_t::i32>(),
+                                                                 generateParamsForSubtract<element::Type_t::u64>(),
+                                                                 generateParamsForSubtract<element::Type_t::u32>()};
 
     std::vector<SubtractParams> combinedParams;
 
@@ -142,8 +135,7 @@ std::vector<SubtractParams> generateCombinedParamsForSubtract() {
 std::vector<SubtractParams> generateCombinedParamsForSubtractFloat() {
     const std::vector<std::vector<SubtractParams>> allTypeParams{
         generateParamsForSubtractFloat<element::Type_t::f32>(),
-        generateParamsForSubtractFloat<element::Type_t::f16>()
-    };
+        generateParamsForSubtractFloat<element::Type_t::f16>()};
 
     std::vector<SubtractParams> combinedParams;
 
@@ -154,16 +146,14 @@ std::vector<SubtractParams> generateCombinedParamsForSubtractFloat() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Subtract_With_Hardcoded_Refs,
-    ReferenceSubtractLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForSubtract()),
-    ReferenceSubtractLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Subtract_Float_With_Hardcoded_Refs,
-    ReferenceSubtractLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForSubtractFloat()),
-    ReferenceSubtractLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Subtract_With_Hardcoded_Refs,
+                         ReferenceSubtractLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForSubtract()),
+                         ReferenceSubtractLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Subtract_Float_With_Hardcoded_Refs,
+                         ReferenceSubtractLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForSubtractFloat()),
+                         ReferenceSubtractLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/swish.cpp b/src/plugins/template/tests/functional/op_reference/swish.cpp
index d609e2b1a84e8b..5c551902f7c9a4 100644
--- a/src/plugins/template/tests/functional/op_reference/swish.cpp
+++ b/src/plugins/template/tests/functional/op_reference/swish.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/swish.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/swish.hpp"
 #include "base_reference_test.hpp"
 
 using namespace reference_tests;
@@ -13,31 +14,33 @@ using namespace ov;
 namespace {
 struct SwishParams {
     template <class IT>
-    SwishParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues,
+    SwishParams(const ov::PartialShape& shape,
+                const ov::element::Type& iType,
+                const std::vector<IT>& iValues,
                 const float beta = 1)
         : pshape(shape),
           inType(iType),
           outType(iType),
           inputData(CreateTensor(iType, iValues)),
           beta(beta) {
-              std::vector<IT> oValues;
-              std::vector<float> output;
-              std::vector<IT> betaVector;
+        std::vector<IT> oValues;
+        std::vector<float> output;
+        std::vector<IT> betaVector;
 
-              for (auto element : iValues)
-                  output.push_back(static_cast<float>(element));
+        for (auto element : iValues)
+            output.push_back(static_cast<float>(element));
 
-              std::transform(output.begin(), output.end(), output.begin(), [&beta](float x) -> float {
-                  return (x / (1.0f + std::exp(x * beta * -1.0f)));
-              });
+        std::transform(output.begin(), output.end(), output.begin(), [&beta](float x) -> float {
+            return (x / (1.0f + std::exp(x * beta * -1.0f)));
+        });
 
-              for (auto element : output)
-                  oValues.push_back(static_cast<IT>(element));
-              refData = CreateTensor(outType, oValues);
+        for (auto element : output)
+            oValues.push_back(static_cast<IT>(element));
+        refData = CreateTensor(outType, oValues);
 
-              betaVector.push_back(static_cast<IT>(beta));
-              betaBlob = CreateTensor(inType, betaVector);
-          }
+        betaVector.push_back(static_cast<IT>(beta));
+        betaBlob = CreateTensor(inType, betaVector);
+    }
 
     ov::PartialShape pshape;
     ov::element::Type inType;
@@ -52,7 +55,7 @@ struct SwishParams {
 class ReferenceSwishLayerTest : public testing::TestWithParam<SwishParams>, public CommonReferenceTest {
 public:
     void SetUp() override {
-        threshold = 0.06; // 0.01 failed in fp32 test
+        threshold = 0.06;  // 0.01 failed in fp32 test
 
         auto params = GetParam();
         function = CreateFunction(params.pshape, params.inType, params.outType, params.beta);
@@ -76,16 +79,18 @@ class ReferenceSwishLayerTest : public testing::TestWithParam<SwishParams>, publ
     }
 
 private:
-    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type,
-                                                    const element::Type& Swishected_output_type, const float beta) {
+    static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape,
+                                                 const element::Type& input_type,
+                                                 const element::Type& Swishected_output_type,
+                                                 const float beta) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         if (beta != 1) {
-            const auto BETA = std::make_shared<op::v0::Parameter>(input_type, Shape {});
+            const auto BETA = std::make_shared<op::v0::Parameter>(input_type, Shape{});
             const auto Swish = std::make_shared<op::v4::Swish>(in, BETA);
-            return std::make_shared<Model>(NodeVector {Swish}, ParameterVector {in, BETA});
+            return std::make_shared<Model>(NodeVector{Swish}, ParameterVector{in, BETA});
         } else {
             const auto Swish = std::make_shared<op::v4::Swish>(in);
-            return std::make_shared<ov::Model>(NodeVector {Swish}, ParameterVector {in});
+            return std::make_shared<ov::Model>(NodeVector{Swish}, ParameterVector{in});
         }
     }
 };
@@ -98,27 +103,16 @@ template <element::Type_t IN_ET>
 std::vector<SwishParams> generateSwishFloatParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
 
-    std::vector<SwishParams> swishParams {
-        SwishParams(ov::PartialShape {2, 4},
-                    IN_ET,
-                    std::vector<T>{0.4, -5.7, -6, 3, -0.9, 23, 5, 3.3},
-                    0.6f),
-        SwishParams(ov::PartialShape {2, 3},
-                    IN_ET,
-                    std::vector<T>{1, 8, -8, 17, -0.5, -1}),
-        SwishParams(ov::PartialShape {2, 2, 1, 2},
-                    IN_ET,
-                    std::vector<T>{0.1, 0.6, 20, -7, -5.3, 3.5, -9, 11},
-                    0.33f)
-    };
+    std::vector<SwishParams> swishParams{
+        SwishParams(ov::PartialShape{2, 4}, IN_ET, std::vector<T>{0.4, -5.7, -6, 3, -0.9, 23, 5, 3.3}, 0.6f),
+        SwishParams(ov::PartialShape{2, 3}, IN_ET, std::vector<T>{1, 8, -8, 17, -0.5, -1}),
+        SwishParams(ov::PartialShape{2, 2, 1, 2}, IN_ET, std::vector<T>{0.1, 0.6, 20, -7, -5.3, 3.5, -9, 11}, 0.33f)};
     return swishParams;
 }
 
 std::vector<SwishParams> generateSwishCombinedParams() {
-    const std::vector<std::vector<SwishParams>> swishTypeParams {
-        generateSwishFloatParams<element::Type_t::f32>(),
-        generateSwishFloatParams<element::Type_t::f16>()
-        };
+    const std::vector<std::vector<SwishParams>> swishTypeParams{generateSwishFloatParams<element::Type_t::f32>(),
+                                                                generateSwishFloatParams<element::Type_t::f16>()};
     std::vector<SwishParams> combinedParams;
 
     for (const auto& params : swishTypeParams) {
@@ -127,7 +121,9 @@ std::vector<SwishParams> generateSwishCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Swish_With_Hardcoded_Refs, ReferenceSwishLayerTest,
-    testing::ValuesIn(generateSwishCombinedParams()), ReferenceSwishLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Swish_With_Hardcoded_Refs,
+                         ReferenceSwishLayerTest,
+                         testing::ValuesIn(generateSwishCombinedParams()),
+                         ReferenceSwishLayerTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/tan.cpp b/src/plugins/template/tests/functional/op_reference/tan.cpp
index 705c53e78cc415..6bb9983461778a 100644
--- a/src/plugins/template/tests/functional/op_reference/tan.cpp
+++ b/src/plugins/template/tests/functional/op_reference/tan.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/tan.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/tan.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -13,9 +14,15 @@ using namespace reference_tests;
 namespace {
 struct TanParams {
     template <class IT>
-    TanParams(const ov::PartialShape& shape, const ov::element::Type& iType, const std::vector<IT>& iValues,
+    TanParams(const ov::PartialShape& shape,
+              const ov::element::Type& iType,
+              const std::vector<IT>& iValues,
               const std::vector<IT>& oValues)
-        :pshape(shape), inType(iType), outType(iType), inputData(CreateTensor(iType, iValues)), refData(CreateTensor(iType, oValues)) {}
+        : pshape(shape),
+          inType(iType),
+          outType(iType),
+          inputData(CreateTensor(iType, iValues)),
+          refData(CreateTensor(iType, oValues)) {}
     ov::PartialShape pshape;
     ov::element::Type inType;
     ov::element::Type outType;
@@ -44,7 +51,7 @@ class ReferenceTanLayerTest : public testing::TestWithParam<TanParams>, public C
     static std::shared_ptr<Model> CreateFunction(const PartialShape& input_shape, const element::Type& input_type) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto tan = std::make_shared<op::v0::Tan>(in);
-        return std::make_shared<ov::Model>(tan, ParameterVector {in});
+        return std::make_shared<ov::Model>(tan, ParameterVector{in});
     }
 };
 
@@ -53,27 +60,56 @@ TEST_P(ReferenceTanLayerTest, CompareWithHardcodedRefs) {
 }
 
 std::vector<TanParams> generateTanCombinedParams() {
-    std::vector<TanParams> combinedParams {
-        TanParams(ov::PartialShape {5}, ov::element::i32, std::vector<int32_t> {-2, -1, 0, 1, 2},
-                  std::vector<int32_t> {2, -2, 0, 2, -2}),
-        TanParams(ov::PartialShape {5}, ov::element::i64, std::vector<int64_t> {-2, -1, 0, 1, 2},
-                  std::vector<int64_t> {2, -2, 0, 2, -2}),
-        TanParams(ov::PartialShape {5}, ov::element::u32, std::vector<uint32_t> {1, 2, 3, 4, 5},
-                  std::vector<uint32_t> {2, 0xFFFFFFFF - 1, 0, 1, 0xFFFFFFFF - 2}),
-        TanParams(ov::PartialShape {5}, ov::element::u64, std::vector<uint64_t> {1, 2, 3, 4, 5},
-                  std::vector<uint64_t> {2, 0xFFFFFFFFFFFFFFFF - 1, 0, 1, 0xFFFFFFFFFFFFFFFF - 2}),
-        TanParams(ov::PartialShape {11}, ov::element::f32, std::vector<float> {0.f, 0.25f,
-                      -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f},
-                  std::vector<float> {0.00000000f, 0.25534192f, -0.25534192f, 0.54630249f, -0.54630249f,
-                       1.55740772f, -1.55740772f, -2.18503986f, 2.18503986f, 1.15782128f, -1.15782128f}),
-        TanParams(ov::PartialShape {11}, ov::element::f16, std::vector<float16> {0.f, 0.25f,
-                      -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f},
-                  std::vector<float16> {0.00000000f, 0.25534192f, -0.25534192f, 0.54630249f, -0.54630249f,
-                       1.55740772f, -1.55740772f, -2.18503986f, 2.18503986f, 1.15782128f, -1.15782128f})
-    };
+    std::vector<TanParams> combinedParams{
+        TanParams(ov::PartialShape{5},
+                  ov::element::i32,
+                  std::vector<int32_t>{-2, -1, 0, 1, 2},
+                  std::vector<int32_t>{2, -2, 0, 2, -2}),
+        TanParams(ov::PartialShape{5},
+                  ov::element::i64,
+                  std::vector<int64_t>{-2, -1, 0, 1, 2},
+                  std::vector<int64_t>{2, -2, 0, 2, -2}),
+        TanParams(ov::PartialShape{5},
+                  ov::element::u32,
+                  std::vector<uint32_t>{1, 2, 3, 4, 5},
+                  std::vector<uint32_t>{2, 0xFFFFFFFF - 1, 0, 1, 0xFFFFFFFF - 2}),
+        TanParams(ov::PartialShape{5},
+                  ov::element::u64,
+                  std::vector<uint64_t>{1, 2, 3, 4, 5},
+                  std::vector<uint64_t>{2, 0xFFFFFFFFFFFFFFFF - 1, 0, 1, 0xFFFFFFFFFFFFFFFF - 2}),
+        TanParams(ov::PartialShape{11},
+                  ov::element::f32,
+                  std::vector<float>{0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f},
+                  std::vector<float>{0.00000000f,
+                                     0.25534192f,
+                                     -0.25534192f,
+                                     0.54630249f,
+                                     -0.54630249f,
+                                     1.55740772f,
+                                     -1.55740772f,
+                                     -2.18503986f,
+                                     2.18503986f,
+                                     1.15782128f,
+                                     -1.15782128f}),
+        TanParams(ov::PartialShape{11},
+                  ov::element::f16,
+                  std::vector<float16>{0.f, 0.25f, -0.25f, 0.5f, -0.5f, 1.f, -1.f, 2.f, -2.f, 4.f, -4.f},
+                  std::vector<float16>{0.00000000f,
+                                       0.25534192f,
+                                       -0.25534192f,
+                                       0.54630249f,
+                                       -0.54630249f,
+                                       1.55740772f,
+                                       -1.55740772f,
+                                       -2.18503986f,
+                                       2.18503986f,
+                                       1.15782128f,
+                                       -1.15782128f})};
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TAN_With_Hardcoded_Refs, ReferenceTanLayerTest, ::testing::ValuesIn(generateTanCombinedParams()),
+INSTANTIATE_TEST_SUITE_P(smoke_TAN_With_Hardcoded_Refs,
+                         ReferenceTanLayerTest,
+                         ::testing::ValuesIn(generateTanCombinedParams()),
                          ReferenceTanLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/tanh.cpp b/src/plugins/template/tests/functional/op_reference/tanh.cpp
index da0f8303d4c77e..43765f9145afb2 100644
--- a/src/plugins/template/tests/functional/op_reference/tanh.cpp
+++ b/src/plugins/template/tests/functional/op_reference/tanh.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/tanh.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/tanh.hpp"
 #include "base_reference_test.hpp"
 
 using namespace ov;
@@ -42,7 +43,7 @@ class ReferenceTanhLayerTest : public testing::TestWithParam<TanhParams>, public
     static std::shared_ptr<Model> CreateFunction(const Shape& shape, const element::Type& type) {
         const auto in = std::make_shared<op::v0::Parameter>(type, shape);
         const auto Tanh = std::make_shared<op::v0::Tanh>(in);
-        return std::make_shared<ov::Model>(NodeVector {Tanh}, ParameterVector {in});
+        return std::make_shared<ov::Model>(NodeVector{Tanh}, ParameterVector{in});
     }
 };
 
@@ -53,46 +54,55 @@ TEST_P(ReferenceTanhLayerTest, TanhWithHardcodedRefs) {
 }  // namespace
 
 INSTANTIATE_TEST_SUITE_P(
-    smoke_Tanh_With_Hardcoded_Refs, ReferenceTanhLayerTest,
+    smoke_Tanh_With_Hardcoded_Refs,
+    ReferenceTanhLayerTest,
     ::testing::Values(
-        Builder {}
-            .input({{11}, element::f16, std::vector<ov::float16> {-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
-            .expected({{11}, element::f16, std::vector<ov::float16> {-0.99932930f,
-                            -0.96402758f,
-                            -0.76159416f,
-                            -0.46211716f,
-                            -0.24491866f,
-                            0.00000000f,
-                            0.24491866f,
-                            0.46211716f,
-                            0.76159416f,
-                            0.96402758f,
-                            0.99932930f}}),
-        Builder {}
-            .input({{11}, element::f32, std::vector<float> {-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
-            .expected({{11}, element::f32, std::vector<float> {-0.99932930f,
-                            -0.96402758f,
-                            -0.76159416f,
-                            -0.46211716f,
-                            -0.24491866f,
-                            0.00000000f,
-                            0.24491866f,
-                            0.46211716f,
-                            0.76159416f,
-                            0.96402758f,
-                            0.99932930f}}),
-        Builder {}
-            .input({{7}, element::i32, std::vector<int32_t> {-4, -2, -1, 0, 1, 2, 4}})
-            .expected({{7}, element::i32, std::vector<int32_t> {-1, -1, -1, 0, 1, 1, 1}}),
-        Builder {}
-            .input({{7}, element::i64, std::vector<int64_t> {-4, -2, -1, 0, 1, 2, 4}})
-            .expected({{7}, element::i64, std::vector<int64_t> {-1, -1, -1, 0, 1, 1, 1}}),
-        Builder {}
-            .input({{4}, element::u32, std::vector<uint32_t> {0, 1, 2, 4}})
-            .expected({{4}, element::u32, std::vector<uint32_t> {0, 1, 1, 1}}),
-        Builder {}
-            .input({{4}, element::u64, std::vector<uint64_t> {0, 1, 2, 4}})
-            .expected({{4}, element::u64, std::vector<uint64_t> {0, 1, 1, 1}})),
+        Builder{}
+            .input({{11},
+                    element::f16,
+                    std::vector<ov::float16>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
+            .expected({{11},
+                       element::f16,
+                       std::vector<ov::float16>{-0.99932930f,
+                                                -0.96402758f,
+                                                -0.76159416f,
+                                                -0.46211716f,
+                                                -0.24491866f,
+                                                0.00000000f,
+                                                0.24491866f,
+                                                0.46211716f,
+                                                0.76159416f,
+                                                0.96402758f,
+                                                0.99932930f}}),
+        Builder{}
+            .input({{11},
+                    element::f32,
+                    std::vector<float>{-4.f, -2.f, -1.f, -0.5f, -0.25f, 0.f, 0.25f, 0.5f, 1.f, 2.f, 4.f}})
+            .expected({{11},
+                       element::f32,
+                       std::vector<float>{-0.99932930f,
+                                          -0.96402758f,
+                                          -0.76159416f,
+                                          -0.46211716f,
+                                          -0.24491866f,
+                                          0.00000000f,
+                                          0.24491866f,
+                                          0.46211716f,
+                                          0.76159416f,
+                                          0.96402758f,
+                                          0.99932930f}}),
+        Builder{}
+            .input({{7}, element::i32, std::vector<int32_t>{-4, -2, -1, 0, 1, 2, 4}})
+            .expected({{7}, element::i32, std::vector<int32_t>{-1, -1, -1, 0, 1, 1, 1}}),
+        Builder{}
+            .input({{7}, element::i64, std::vector<int64_t>{-4, -2, -1, 0, 1, 2, 4}})
+            .expected({{7}, element::i64, std::vector<int64_t>{-1, -1, -1, 0, 1, 1, 1}}),
+        Builder{}
+            .input({{4}, element::u32, std::vector<uint32_t>{0, 1, 2, 4}})
+            .expected({{4}, element::u32, std::vector<uint32_t>{0, 1, 1, 1}}),
+        Builder{}
+            .input({{4}, element::u64, std::vector<uint64_t>{0, 1, 2, 4}})
+            .expected({{4}, element::u64, std::vector<uint64_t>{0, 1, 1, 1}})),
 
     ReferenceTanhLayerTest::getTestCaseName);
 }  // namespace reference_tests
diff --git a/src/plugins/template/tests/functional/op_reference/tensor_iterator.cpp b/src/plugins/template/tests/functional/op_reference/tensor_iterator.cpp
index 1caa12dff5c9b9..5c53422b0dad64 100644
--- a/src/plugins/template/tests/functional/op_reference/tensor_iterator.cpp
+++ b/src/plugins/template/tests/functional/op_reference/tensor_iterator.cpp
@@ -12,8 +12,8 @@
 
 namespace {
 struct TIFunctionalBase {
-    virtual std::shared_ptr<ov::Model> create_function(const std::vector<reference_tests::Tensor> &ti_inputs,
-                                                        const std::vector<reference_tests::Tensor> &results) = 0;
+    virtual std::shared_ptr<ov::Model> create_function(const std::vector<reference_tests::Tensor>& ti_inputs,
+                                                       const std::vector<reference_tests::Tensor>& results) = 0;
 
     TIFunctionalBase() = default;
 
@@ -21,8 +21,8 @@ struct TIFunctionalBase {
 };
 
 struct TIDynamicInputs : public TIFunctionalBase {
-    std::shared_ptr<ov::Model> create_function(const std::vector<reference_tests::Tensor> &ti_inputs,
-                                                const std::vector<reference_tests::Tensor> &results) override {
+    std::shared_ptr<ov::Model> create_function(const std::vector<reference_tests::Tensor>& ti_inputs,
+                                               const std::vector<reference_tests::Tensor>& results) override {
         auto X = std::make_shared<ov::opset8::Parameter>(ov::element::f32, ov::PartialShape::dynamic());
         auto Y = std::make_shared<ov::opset8::Parameter>(ov::element::f32, ov::PartialShape::dynamic());
         auto M = std::make_shared<ov::opset8::Parameter>(ov::element::f32, ov::PartialShape::dynamic());
@@ -39,8 +39,8 @@ struct TIDynamicInputs : public TIFunctionalBase {
         // Body
         auto sum = std::make_shared<ov::opset8::Add>(Xi, Yi);
         auto Zo = std::make_shared<ov::opset8::Multiply>(sum, M_body);
-        auto body = std::make_shared<ov::Model>(ov::OutputVector{body_condition, Zo},
-                                                ov::ParameterVector{Xi, Yi, M_body});
+        auto body =
+            std::make_shared<ov::Model>(ov::OutputVector{body_condition, Zo}, ov::ParameterVector{Xi, Yi, M_body});
 
         auto tensor_iterator = std::make_shared<ov::opset8::TensorIterator>();
         tensor_iterator->set_function(body);
@@ -56,14 +56,14 @@ struct TIDynamicInputs : public TIFunctionalBase {
 };
 
 struct TensorIteratorParams {
-    TensorIteratorParams(const std::shared_ptr<TIFunctionalBase> &functional,
-                            const std::vector<reference_tests::Tensor> &ti_inputs,
-                            const std::vector<reference_tests::Tensor> &expected_results,
-                            const std::string &test_case_name)
+    TensorIteratorParams(const std::shared_ptr<TIFunctionalBase>& functional,
+                         const std::vector<reference_tests::Tensor>& ti_inputs,
+                         const std::vector<reference_tests::Tensor>& expected_results,
+                         const std::string& test_case_name)
         : function(functional),
-            inputs(ti_inputs),
-            expected_results(expected_results),
-            test_case_name(test_case_name) {}
+          inputs(ti_inputs),
+          expected_results(expected_results),
+          test_case_name(test_case_name) {}
 
     std::shared_ptr<TIFunctionalBase> function;
     std::vector<reference_tests::Tensor> inputs;
@@ -72,7 +72,7 @@ struct TensorIteratorParams {
 };
 
 class ReferenceTILayerTest : public testing::TestWithParam<TensorIteratorParams>,
-                                public reference_tests::CommonReferenceTest {
+                             public reference_tests::CommonReferenceTest {
 public:
     void SetUp() override {
         SKIP_IF_CURRENT_TEST_IS_DISABLED()
@@ -80,15 +80,15 @@ class ReferenceTILayerTest : public testing::TestWithParam<TensorIteratorParams>
         function = params.function->create_function(params.inputs, params.expected_results);
         inputData.reserve(params.inputs.size());
         refOutData.reserve(params.expected_results.size());
-        for (auto &input_tensor: params.inputs) {
+        for (auto& input_tensor : params.inputs) {
             inputData.push_back(input_tensor.data);
         }
-        for (auto &expected_tensor: params.expected_results) {
+        for (auto& expected_tensor : params.expected_results) {
             refOutData.push_back(expected_tensor.data);
         }
     }
 
-    static std::string getTestCaseName(const testing::TestParamInfo<TensorIteratorParams> &obj) {
+    static std::string getTestCaseName(const testing::TestParamInfo<TensorIteratorParams>& obj) {
         auto param = obj.param;
         return param.test_case_name;
     }
@@ -98,20 +98,18 @@ TEST_P(ReferenceTILayerTest, TensorIteratorWithHardcodedRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_TensorIterator_With_Hardcoded_Refs,
-    ReferenceTILayerTest,
-    ::testing::Values(
-        TensorIteratorParams(
-            std::make_shared<TIDynamicInputs>(),
-            std::vector<reference_tests::Tensor>{
-                reference_tests::Tensor(ov::element::f32, ov::Shape{1, 2}, std::vector<float>{2, 3}),
-                reference_tests::Tensor(ov::element::f32, ov::Shape{2, 1}, std::vector<float>{4, 5}),
-                reference_tests::Tensor(ov::element::f32, ov::Shape{1, 1}, std::vector<float>{5})},
-            std::vector<reference_tests::Tensor>{
-                reference_tests::Tensor(ov::element::f32, ov::Shape{1, 1}, std::vector<float>{240})},
-            "tensor_iterator_dynamic_inputs")),
-    ReferenceTILayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TensorIterator_With_Hardcoded_Refs,
+                         ReferenceTILayerTest,
+                         ::testing::Values(TensorIteratorParams(
+                             std::make_shared<TIDynamicInputs>(),
+                             std::vector<reference_tests::Tensor>{
+                                 reference_tests::Tensor(ov::element::f32, ov::Shape{1, 2}, std::vector<float>{2, 3}),
+                                 reference_tests::Tensor(ov::element::f32, ov::Shape{2, 1}, std::vector<float>{4, 5}),
+                                 reference_tests::Tensor(ov::element::f32, ov::Shape{1, 1}, std::vector<float>{5})},
+                             std::vector<reference_tests::Tensor>{
+                                 reference_tests::Tensor(ov::element::f32, ov::Shape{1, 1}, std::vector<float>{240})},
+                             "tensor_iterator_dynamic_inputs")),
+                         ReferenceTILayerTest::getTestCaseName);
 
 enum TensorIteratorBodyType {
     RNN,
@@ -129,87 +127,104 @@ struct TIStaticFunctionalBase {
 
 struct TensorIteratorStaticParams {
     template <class T>
-    TensorIteratorStaticParams(
-        const std::shared_ptr<TIStaticFunctionalBase>& functional,
-        const size_t batchSize, const size_t inputSize, const size_t hiddenSize, const size_t seqLength,
-        const float clip, const ov::op::RecurrentSequenceDirection& direction,
-        const TensorIteratorBodyType& body_type,
-        const ov::element::Type_t& iType,
-        const std::vector<T>& XValues, const std::vector<T>& H_tValues,  const std::vector<T>& C_tValues, const std::vector<int64_t>& S_tValues,
-        const std::vector<T>& WValues, const std::vector<T>& RValues, const std::vector<T>& BValues,
-        const std::vector<T>& YValues, const std::vector<T>& HoValues, const std::vector<T>& CoValues,
-        const std::string& testcaseName = "") :
-        function(functional),
-        batchSize(batchSize), inputSize(inputSize), hiddenSize(hiddenSize), seqLength(seqLength),
-        clip(clip), body_type(body_type), direction(direction), iType(iType), oType(iType),
-        testcaseName(testcaseName) {
-            switch (body_type) {
-                case TensorIteratorBodyType::LSTM: {
-                    ov::Shape XShape = ov::Shape{batchSize, seqLength, inputSize};
-                    ov::Shape H_tShape = ov::Shape{batchSize, hiddenSize};
-                    ov::Shape C_tShape = ov::Shape{batchSize, hiddenSize};
-                    ov::Shape S_tShape = ov::Shape{batchSize};
-                    ov::Shape WShape = ov::Shape{4 * hiddenSize, inputSize};
-                    ov::Shape RShape = ov::Shape{4 * hiddenSize, hiddenSize};
-                    ov::Shape BShape = ov::Shape{4 * hiddenSize};
-                    ov::Shape YShape = ov::Shape{batchSize, seqLength, hiddenSize};
-                    ov::Shape HoShape = ov::Shape{batchSize, hiddenSize};
-                    ov::Shape CoShape = ov::Shape{batchSize, hiddenSize};
+    TensorIteratorStaticParams(const std::shared_ptr<TIStaticFunctionalBase>& functional,
+                               const size_t batchSize,
+                               const size_t inputSize,
+                               const size_t hiddenSize,
+                               const size_t seqLength,
+                               const float clip,
+                               const ov::op::RecurrentSequenceDirection& direction,
+                               const TensorIteratorBodyType& body_type,
+                               const ov::element::Type_t& iType,
+                               const std::vector<T>& XValues,
+                               const std::vector<T>& H_tValues,
+                               const std::vector<T>& C_tValues,
+                               const std::vector<int64_t>& S_tValues,
+                               const std::vector<T>& WValues,
+                               const std::vector<T>& RValues,
+                               const std::vector<T>& BValues,
+                               const std::vector<T>& YValues,
+                               const std::vector<T>& HoValues,
+                               const std::vector<T>& CoValues,
+                               const std::string& testcaseName = "")
+        : function(functional),
+          batchSize(batchSize),
+          inputSize(inputSize),
+          hiddenSize(hiddenSize),
+          seqLength(seqLength),
+          clip(clip),
+          body_type(body_type),
+          direction(direction),
+          iType(iType),
+          oType(iType),
+          testcaseName(testcaseName) {
+        switch (body_type) {
+        case TensorIteratorBodyType::LSTM: {
+            ov::Shape XShape = ov::Shape{batchSize, seqLength, inputSize};
+            ov::Shape H_tShape = ov::Shape{batchSize, hiddenSize};
+            ov::Shape C_tShape = ov::Shape{batchSize, hiddenSize};
+            ov::Shape S_tShape = ov::Shape{batchSize};
+            ov::Shape WShape = ov::Shape{4 * hiddenSize, inputSize};
+            ov::Shape RShape = ov::Shape{4 * hiddenSize, hiddenSize};
+            ov::Shape BShape = ov::Shape{4 * hiddenSize};
+            ov::Shape YShape = ov::Shape{batchSize, seqLength, hiddenSize};
+            ov::Shape HoShape = ov::Shape{batchSize, hiddenSize};
+            ov::Shape CoShape = ov::Shape{batchSize, hiddenSize};
 
-                    X = reference_tests::Tensor(XShape, iType, XValues);
-                    H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
-                    C_t = reference_tests::Tensor(C_tShape, iType, C_tValues);
-                    S_t = reference_tests::Tensor(S_tShape, ov::element::Type_t::i64, S_tValues);
-                    W = reference_tests::Tensor(WShape, iType, WValues);
-                    R = reference_tests::Tensor(RShape, iType, RValues);
-                    B = reference_tests::Tensor(BShape, iType, BValues);
-                    Y = reference_tests::Tensor(YShape, oType, YValues);
-                    Ho = reference_tests::Tensor(HoShape, oType, HoValues);
-                    Co = reference_tests::Tensor(CoShape, oType, CoValues);
-                    break;
-                }
-                case TensorIteratorBodyType::GRU: {
-                    ov::Shape XShape = ov::Shape{batchSize, seqLength, inputSize};
-                    ov::Shape H_tShape = ov::Shape{batchSize, hiddenSize};
-                    ov::Shape S_tShape = ov::Shape{batchSize};
-                    ov::Shape WShape = ov::Shape{3 * hiddenSize, inputSize};
-                    ov::Shape RShape = ov::Shape{3 * hiddenSize, hiddenSize};
-                    ov::Shape BShape = ov::Shape{3 * hiddenSize};
-                    ov::Shape YShape = ov::Shape{batchSize, seqLength, hiddenSize};
-                    ov::Shape HoShape = ov::Shape{batchSize, hiddenSize};
+            X = reference_tests::Tensor(XShape, iType, XValues);
+            H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
+            C_t = reference_tests::Tensor(C_tShape, iType, C_tValues);
+            S_t = reference_tests::Tensor(S_tShape, ov::element::Type_t::i64, S_tValues);
+            W = reference_tests::Tensor(WShape, iType, WValues);
+            R = reference_tests::Tensor(RShape, iType, RValues);
+            B = reference_tests::Tensor(BShape, iType, BValues);
+            Y = reference_tests::Tensor(YShape, oType, YValues);
+            Ho = reference_tests::Tensor(HoShape, oType, HoValues);
+            Co = reference_tests::Tensor(CoShape, oType, CoValues);
+            break;
+        }
+        case TensorIteratorBodyType::GRU: {
+            ov::Shape XShape = ov::Shape{batchSize, seqLength, inputSize};
+            ov::Shape H_tShape = ov::Shape{batchSize, hiddenSize};
+            ov::Shape S_tShape = ov::Shape{batchSize};
+            ov::Shape WShape = ov::Shape{3 * hiddenSize, inputSize};
+            ov::Shape RShape = ov::Shape{3 * hiddenSize, hiddenSize};
+            ov::Shape BShape = ov::Shape{3 * hiddenSize};
+            ov::Shape YShape = ov::Shape{batchSize, seqLength, hiddenSize};
+            ov::Shape HoShape = ov::Shape{batchSize, hiddenSize};
 
-                    X = reference_tests::Tensor(XShape, iType, XValues);
-                    H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
-                    S_t = reference_tests::Tensor(S_tShape, ov::element::Type_t::i64, S_tValues);
-                    W = reference_tests::Tensor(WShape, iType, WValues);
-                    R = reference_tests::Tensor(RShape, iType, RValues);
-                    B = reference_tests::Tensor(BShape, iType, BValues);
-                    Y = reference_tests::Tensor(YShape, oType, YValues);
-                    Ho = reference_tests::Tensor(HoShape, oType, HoValues);
-                    break;
-                }
-                case TensorIteratorBodyType::RNN: {
-                    ov::Shape XShape = ov::Shape{batchSize, seqLength, inputSize};
-                    ov::Shape H_tShape = ov::Shape{batchSize, hiddenSize};
-                    ov::Shape S_tShape = ov::Shape{batchSize};
-                    ov::Shape WShape = ov::Shape{hiddenSize, inputSize};
-                    ov::Shape RShape = ov::Shape{hiddenSize, hiddenSize};
-                    ov::Shape BShape = ov::Shape{hiddenSize};
-                    ov::Shape YShape = ov::Shape{batchSize, seqLength, hiddenSize};
-                    ov::Shape HoShape = ov::Shape{batchSize, hiddenSize};
+            X = reference_tests::Tensor(XShape, iType, XValues);
+            H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
+            S_t = reference_tests::Tensor(S_tShape, ov::element::Type_t::i64, S_tValues);
+            W = reference_tests::Tensor(WShape, iType, WValues);
+            R = reference_tests::Tensor(RShape, iType, RValues);
+            B = reference_tests::Tensor(BShape, iType, BValues);
+            Y = reference_tests::Tensor(YShape, oType, YValues);
+            Ho = reference_tests::Tensor(HoShape, oType, HoValues);
+            break;
+        }
+        case TensorIteratorBodyType::RNN: {
+            ov::Shape XShape = ov::Shape{batchSize, seqLength, inputSize};
+            ov::Shape H_tShape = ov::Shape{batchSize, hiddenSize};
+            ov::Shape S_tShape = ov::Shape{batchSize};
+            ov::Shape WShape = ov::Shape{hiddenSize, inputSize};
+            ov::Shape RShape = ov::Shape{hiddenSize, hiddenSize};
+            ov::Shape BShape = ov::Shape{hiddenSize};
+            ov::Shape YShape = ov::Shape{batchSize, seqLength, hiddenSize};
+            ov::Shape HoShape = ov::Shape{batchSize, hiddenSize};
 
-                    X = reference_tests::Tensor(XShape, iType, XValues);
-                    H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
-                    S_t = reference_tests::Tensor(S_tShape, ov::element::Type_t::i64, S_tValues);
-                    W = reference_tests::Tensor(WShape, iType, WValues);
-                    R = reference_tests::Tensor(RShape, iType, RValues);
-                    B = reference_tests::Tensor(BShape, iType, BValues);
-                    Y = reference_tests::Tensor(YShape, oType, YValues);
-                    Ho = reference_tests::Tensor(HoShape, oType, HoValues);
-                    break;
-                }
-            }
+            X = reference_tests::Tensor(XShape, iType, XValues);
+            H_t = reference_tests::Tensor(H_tShape, iType, H_tValues);
+            S_t = reference_tests::Tensor(S_tShape, ov::element::Type_t::i64, S_tValues);
+            W = reference_tests::Tensor(WShape, iType, WValues);
+            R = reference_tests::Tensor(RShape, iType, RValues);
+            B = reference_tests::Tensor(BShape, iType, BValues);
+            Y = reference_tests::Tensor(YShape, oType, YValues);
+            Ho = reference_tests::Tensor(HoShape, oType, HoValues);
+            break;
+        }
         }
+    }
 
     std::shared_ptr<TIStaticFunctionalBase> function;
 
@@ -248,206 +263,213 @@ struct TIStaticInputs : public TIStaticFunctionalBase {
         // 1. Create TensorIterator body.
         // 2. Set PortMap
         // 3. Create outer function
-        auto axis = std::make_shared<ov::opset8::Constant>(ov::element::i64, ov::Shape{1},
-                                                               std::vector<int64_t>{static_cast<int64_t>(params.sequenceAxis)});
+        auto axis =
+            std::make_shared<ov::opset8::Constant>(ov::element::i64,
+                                                   ov::Shape{1},
+                                                   std::vector<int64_t>{static_cast<int64_t>(params.sequenceAxis)});
         switch (params.body_type) {
-            case TensorIteratorBodyType::LSTM: {
-                inputShapes = {
-                        {{params.batchSize, params.seqLength, params.inputSize}, // X
-                         {params.batchSize, params.hiddenSize},                  // H_i
-                         {params.batchSize, params.hiddenSize},                  // C_i
-                         {4 * params.hiddenSize, params.inputSize},              // W
-                         {4 * params.hiddenSize, params.inputSize},              // R
-                         {4 * params.inputSize}},                                // B
-                };
-                if (params.sequenceAxis == 0) {
-                    // swap params.batchSize and params.seqLength
-                    std::swap(inputShapes[0][0], inputShapes[0][1]);
-                }
-                ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
-                                                 std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1]),
-                                                 std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[2])};
+        case TensorIteratorBodyType::LSTM: {
+            inputShapes = {
+                {{params.batchSize, params.seqLength, params.inputSize},  // X
+                 {params.batchSize, params.hiddenSize},                   // H_i
+                 {params.batchSize, params.hiddenSize},                   // C_i
+                 {4 * params.hiddenSize, params.inputSize},               // W
+                 {4 * params.hiddenSize, params.inputSize},               // R
+                 {4 * params.inputSize}},                                 // B
+            };
+            if (params.sequenceAxis == 0) {
+                // swap params.batchSize and params.seqLength
+                std::swap(inputShapes[0][0], inputShapes[0][1]);
+            }
+            ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
+                                             std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1]),
+                                             std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[2])};
 
-                // 1. Create TensorIterator body.
-                inputShapes[0][params.sequenceAxis] = 1; // sliced dimension
-                ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
-                                                std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1]),
-                                                std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[2])};
-                auto squeeze = std::make_shared<ov::opset8::Squeeze>(body_params[0], axis);
-                ov::OutputVector out_vector = {squeeze, body_params[1], body_params[2]};
+            // 1. Create TensorIterator body.
+            inputShapes[0][params.sequenceAxis] = 1;  // sliced dimension
+            ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
+                                            std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1]),
+                                            std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[2])};
+            auto squeeze = std::make_shared<ov::opset8::Squeeze>(body_params[0], axis);
+            ov::OutputVector out_vector = {squeeze, body_params[1], body_params[2]};
 
-                auto W = std::make_shared<ov::opset8::Constant>(params.W.type, params.W.shape, params.W.data.data());
-                auto R = std::make_shared<ov::opset8::Constant>(params.R.type, params.R.shape, params.R.data.data());
-                auto B = std::make_shared<ov::opset8::Constant>(params.B.type, params.B.shape, params.B.data.data());
-                auto lstm_cell = std::make_shared<ov::opset8::LSTMCell>(out_vector[0],
-                                                                            out_vector[1],
-                                                                            out_vector[2],
-                                                                            W,
-                                                                            R,
-                                                                            B,
-                                                                            params.hiddenSize,
-                                                                            std::vector<std::string>{"sigmoid", "tanh", "tanh"},
-                                                                            std::vector<float>{},
-                                                                            std::vector<float>{},
-                                                                            params.clip);
+            auto W = std::make_shared<ov::opset8::Constant>(params.W.type, params.W.shape, params.W.data.data());
+            auto R = std::make_shared<ov::opset8::Constant>(params.R.type, params.R.shape, params.R.data.data());
+            auto B = std::make_shared<ov::opset8::Constant>(params.B.type, params.B.shape, params.B.data.data());
+            auto lstm_cell = std::make_shared<ov::opset8::LSTMCell>(out_vector[0],
+                                                                    out_vector[1],
+                                                                    out_vector[2],
+                                                                    W,
+                                                                    R,
+                                                                    B,
+                                                                    params.hiddenSize,
+                                                                    std::vector<std::string>{"sigmoid", "tanh", "tanh"},
+                                                                    std::vector<float>{},
+                                                                    std::vector<float>{},
+                                                                    params.clip);
 
-                auto unsqueeze = std::make_shared<ov::opset8::Unsqueeze>(lstm_cell->output(0), axis);
-                ov::ResultVector results{std::make_shared<ov::opset8::Result>(unsqueeze),
-                                             std::make_shared<ov::opset8::Result>(lstm_cell->output(0)),
-                                             std::make_shared<ov::opset8::Result>(lstm_cell->output(1))};
-                auto body = std::make_shared<ov::Model>(results, body_params, "lstm_cell");
-                tensor_iterator->set_function(body);
+            auto unsqueeze = std::make_shared<ov::opset8::Unsqueeze>(lstm_cell->output(0), axis);
+            ov::ResultVector results{std::make_shared<ov::opset8::Result>(unsqueeze),
+                                     std::make_shared<ov::opset8::Result>(lstm_cell->output(0)),
+                                     std::make_shared<ov::opset8::Result>(lstm_cell->output(1))};
+            auto body = std::make_shared<ov::Model>(results, body_params, "lstm_cell");
+            tensor_iterator->set_function(body);
 
-                // 2. Set PortMap
-                if (params.direction == ov::op::RecurrentSequenceDirection::FORWARD) {
-                    tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, params.sequenceAxis);
-                    tensor_iterator->get_concatenated_slices(results[0], 0, 1, 1, -1, params.sequenceAxis);
-                } else if (params.direction == ov::op::RecurrentSequenceDirection::REVERSE) {
-                    tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, params.sequenceAxis);
-                    tensor_iterator->get_concatenated_slices(results[0], -1, -1, 1, 0, params.sequenceAxis);
-                } else {
-                    OPENVINO_ASSERT(false, "Bidirectional case is not supported.");
-                }
+            // 2. Set PortMap
+            if (params.direction == ov::op::RecurrentSequenceDirection::FORWARD) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, params.sequenceAxis);
+                tensor_iterator->get_concatenated_slices(results[0], 0, 1, 1, -1, params.sequenceAxis);
+            } else if (params.direction == ov::op::RecurrentSequenceDirection::REVERSE) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, params.sequenceAxis);
+                tensor_iterator->get_concatenated_slices(results[0], -1, -1, 1, 0, params.sequenceAxis);
+            } else {
+                OPENVINO_ASSERT(false, "Bidirectional case is not supported.");
+            }
 
-                tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[1]);
-                tensor_iterator->set_merged_input(body_params[2], outer_params[2], results[2]);
-                tensor_iterator->get_iter_value(results[1]);
-                tensor_iterator->get_iter_value(results[2]);
+            tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[1]);
+            tensor_iterator->set_merged_input(body_params[2], outer_params[2], results[2]);
+            tensor_iterator->get_iter_value(results[1]);
+            tensor_iterator->get_iter_value(results[2]);
 
-                // 3. Outer function
-                function = std::make_shared<ov::Model>(ov::OutputVector{tensor_iterator->output(0), tensor_iterator->output(1),
-                                                                                   tensor_iterator->output(2)}, outer_params);
-                break;
+            // 3. Outer function
+            function = std::make_shared<ov::Model>(
+                ov::OutputVector{tensor_iterator->output(0), tensor_iterator->output(1), tensor_iterator->output(2)},
+                outer_params);
+            break;
+        }
+        case TensorIteratorBodyType::GRU: {
+            inputShapes = {
+                {{params.batchSize, params.seqLength, params.inputSize},  // X
+                 {params.batchSize, params.inputSize},                    // H_i
+                 {3 * params.hiddenSize, params.inputSize},               // W
+                 {3 * params.hiddenSize, params.hiddenSize},              // R
+                 {3 * params.hiddenSize}},                                // B
+            };
+            if (params.sequenceAxis == 0) {
+                // swap params.batchSize and params.seqLength
+                std::swap(inputShapes[0][0], inputShapes[0][1]);
             }
-            case TensorIteratorBodyType::GRU: {
-                inputShapes = {
-                        {{params.batchSize, params.seqLength, params.inputSize}, // X
-                         {params.batchSize, params.inputSize},                   // H_i
-                         {3 * params.hiddenSize, params.inputSize},              // W
-                         {3 * params.hiddenSize, params.hiddenSize},             // R
-                         {3 * params.hiddenSize}},                               // B
-                };
-                if (params.sequenceAxis == 0) {
-                    // swap params.batchSize and params.seqLength
-                    std::swap(inputShapes[0][0], inputShapes[0][1]);
-                }
-                ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
-                                                 std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1])};
+            ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
+                                             std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1])};
 
-                // 1. Create TensorIterator body.
-                inputShapes[0][params.sequenceAxis] = 1; // sliced dimension
-                ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
-                                                std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1])};
+            // 1. Create TensorIterator body.
+            inputShapes[0][params.sequenceAxis] = 1;  // sliced dimension
+            ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
+                                            std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1])};
 
-                auto squeeze = std::make_shared<ov::opset8::Squeeze>(body_params[0], axis);
-                ov::OutputVector out_vector = {squeeze, body_params[1]};
+            auto squeeze = std::make_shared<ov::opset8::Squeeze>(body_params[0], axis);
+            ov::OutputVector out_vector = {squeeze, body_params[1]};
 
-                auto W = std::make_shared<ov::opset8::Constant>(params.W.type, params.W.shape, params.W.data.data());
-                auto R = std::make_shared<ov::opset8::Constant>(params.R.type, params.R.shape, params.R.data.data());
-                auto B = std::make_shared<ov::opset8::Constant>(params.B.type, params.B.shape, params.B.data.data());
-                auto gru_cell = std::make_shared<ov::opset8::GRUCell>(out_vector[0],
-                                                                          out_vector[1],
-                                                                          W,
-                                                                          R,
-                                                                          B,
-                                                                          params.hiddenSize,
-                                                                          std::vector<std::string>{"sigmoid", "tanh"},
-                                                                          std::vector<float>{},
-                                                                          std::vector<float>{},
-                                                                          params.clip,
-                                                                          false);
+            auto W = std::make_shared<ov::opset8::Constant>(params.W.type, params.W.shape, params.W.data.data());
+            auto R = std::make_shared<ov::opset8::Constant>(params.R.type, params.R.shape, params.R.data.data());
+            auto B = std::make_shared<ov::opset8::Constant>(params.B.type, params.B.shape, params.B.data.data());
+            auto gru_cell = std::make_shared<ov::opset8::GRUCell>(out_vector[0],
+                                                                  out_vector[1],
+                                                                  W,
+                                                                  R,
+                                                                  B,
+                                                                  params.hiddenSize,
+                                                                  std::vector<std::string>{"sigmoid", "tanh"},
+                                                                  std::vector<float>{},
+                                                                  std::vector<float>{},
+                                                                  params.clip,
+                                                                  false);
 
-                auto unsqueeze = std::make_shared<ov::opset8::Unsqueeze>(gru_cell->output(0), axis);
-                ov::ResultVector results{std::make_shared<ov::opset8::Result>(gru_cell->output(0)),
-                                             std::make_shared<ov::opset8::Result>(unsqueeze)};
-                auto body = std::make_shared<ov::Model>(results, body_params, "gru_cell");
-                tensor_iterator->set_function(body);
+            auto unsqueeze = std::make_shared<ov::opset8::Unsqueeze>(gru_cell->output(0), axis);
+            ov::ResultVector results{std::make_shared<ov::opset8::Result>(gru_cell->output(0)),
+                                     std::make_shared<ov::opset8::Result>(unsqueeze)};
+            auto body = std::make_shared<ov::Model>(results, body_params, "gru_cell");
+            tensor_iterator->set_function(body);
 
-                // 2. Set PortMap
-                if (params.direction == ov::op::RecurrentSequenceDirection::FORWARD) {
-                    tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, params.sequenceAxis);
-                    tensor_iterator->get_concatenated_slices(results[1], 0, 1, 1, -1, params.sequenceAxis);
-                } else if (params.direction == ov::op::RecurrentSequenceDirection::REVERSE) {
-                    tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, params.sequenceAxis);
-                    tensor_iterator->get_concatenated_slices(results[1], -1, -1, 1, 0, params.sequenceAxis);
-                } else {
-                    OPENVINO_ASSERT(false, "Bidirectional case is not supported.");
-                }
+            // 2. Set PortMap
+            if (params.direction == ov::op::RecurrentSequenceDirection::FORWARD) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, params.sequenceAxis);
+                tensor_iterator->get_concatenated_slices(results[1], 0, 1, 1, -1, params.sequenceAxis);
+            } else if (params.direction == ov::op::RecurrentSequenceDirection::REVERSE) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, params.sequenceAxis);
+                tensor_iterator->get_concatenated_slices(results[1], -1, -1, 1, 0, params.sequenceAxis);
+            } else {
+                OPENVINO_ASSERT(false, "Bidirectional case is not supported.");
+            }
 
-                tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[0]);
-                tensor_iterator->get_iter_value(results[0]);
+            tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[0]);
+            tensor_iterator->get_iter_value(results[0]);
 
-                // 3. Outer function
-                function = std::make_shared<ov::Model>(ov::OutputVector{tensor_iterator->output(0), tensor_iterator->output(1)}, outer_params);
-                break;
+            // 3. Outer function
+            function =
+                std::make_shared<ov::Model>(ov::OutputVector{tensor_iterator->output(0), tensor_iterator->output(1)},
+                                            outer_params);
+            break;
+        }
+        case TensorIteratorBodyType::RNN: {
+            inputShapes = {
+                {{params.batchSize, params.seqLength, params.inputSize},  // X
+                 {params.batchSize, params.inputSize},                    // H_i
+                 {params.hiddenSize, params.inputSize},                   // W
+                 {params.hiddenSize, params.hiddenSize},                  // R
+                 {params.hiddenSize}},                                    // B
+            };
+            if (params.sequenceAxis == 0) {
+                // swap params.batchSize and params.seqLength
+                std::swap(inputShapes[0][0], inputShapes[0][1]);
             }
-            case TensorIteratorBodyType::RNN: {
-                inputShapes = {
-                        {{params.batchSize, params.seqLength, params.inputSize}, // X
-                         {params.batchSize, params.inputSize},                   // H_i
-                         {params.hiddenSize, params.inputSize},                  // W
-                         {params.hiddenSize, params.hiddenSize},                 // R
-                         {params.hiddenSize}},                                   // B
-                };
-                if (params.sequenceAxis == 0) {
-                    // swap params.batchSize and params.seqLength
-                    std::swap(inputShapes[0][0], inputShapes[0][1]);
-                }
-                ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
-                                                 std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1])};
+            ov::ParameterVector outer_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
+                                             std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1])};
 
-                // 1. Create TensorIterator body.
-                inputShapes[0][params.sequenceAxis] = 1; // sliced dimension
-                ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
-                                                std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1])};
-                auto squeeze = std::make_shared<ov::opset8::Squeeze>(body_params[0], axis);
-                ov::OutputVector out_vector = {squeeze, body_params[1]};
+            // 1. Create TensorIterator body.
+            inputShapes[0][params.sequenceAxis] = 1;  // sliced dimension
+            ov::ParameterVector body_params{std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[0]),
+                                            std::make_shared<ov::op::v0::Parameter>(params.iType, inputShapes[1])};
+            auto squeeze = std::make_shared<ov::opset8::Squeeze>(body_params[0], axis);
+            ov::OutputVector out_vector = {squeeze, body_params[1]};
 
-                auto W = std::make_shared<ov::opset8::Constant>(params.W.type, params.W.shape, params.W.data.data());
-                auto R = std::make_shared<ov::opset8::Constant>(params.R.type, params.R.shape, params.R.data.data());
-                auto B = std::make_shared<ov::opset8::Constant>(params.B.type, params.B.shape, params.B.data.data());
-                auto rnn_cell = std::make_shared<ov::opset8::RNNCell>(out_vector[0],
-                                                                          out_vector[1],
-                                                                          W,
-                                                                          R,
-                                                                          B,
-                                                                          params.hiddenSize,
-                                                                          std::vector<std::string>{"tanh"},
-                                                                          std::vector<float>{},
-                                                                          std::vector<float>{},
-                                                                          params.clip);
+            auto W = std::make_shared<ov::opset8::Constant>(params.W.type, params.W.shape, params.W.data.data());
+            auto R = std::make_shared<ov::opset8::Constant>(params.R.type, params.R.shape, params.R.data.data());
+            auto B = std::make_shared<ov::opset8::Constant>(params.B.type, params.B.shape, params.B.data.data());
+            auto rnn_cell = std::make_shared<ov::opset8::RNNCell>(out_vector[0],
+                                                                  out_vector[1],
+                                                                  W,
+                                                                  R,
+                                                                  B,
+                                                                  params.hiddenSize,
+                                                                  std::vector<std::string>{"tanh"},
+                                                                  std::vector<float>{},
+                                                                  std::vector<float>{},
+                                                                  params.clip);
 
-                auto unsqueeze = std::make_shared<ov::opset8::Unsqueeze>(rnn_cell->output(0), axis);
-                ov::ResultVector results{std::make_shared<ov::opset8::Result>(rnn_cell),
-                                             std::make_shared<ov::opset8::Result>(unsqueeze)};
-                auto body = std::make_shared<ov::Model>(results, body_params, "rnn_cell");
-                tensor_iterator->set_function(body);
+            auto unsqueeze = std::make_shared<ov::opset8::Unsqueeze>(rnn_cell->output(0), axis);
+            ov::ResultVector results{std::make_shared<ov::opset8::Result>(rnn_cell),
+                                     std::make_shared<ov::opset8::Result>(unsqueeze)};
+            auto body = std::make_shared<ov::Model>(results, body_params, "rnn_cell");
+            tensor_iterator->set_function(body);
 
-                // 2. Set PortMap
-                if (params.direction == ov::op::RecurrentSequenceDirection::FORWARD) {
-                    tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, params.sequenceAxis);
-                    tensor_iterator->get_concatenated_slices(results[1], 0, 1, 1, -1, params.sequenceAxis);
-                } else if (params.direction == ov::op::RecurrentSequenceDirection::REVERSE) {
-                    tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, params.sequenceAxis);
-                    tensor_iterator->get_concatenated_slices(results[1], -1, -1, 1, 0, params.sequenceAxis);
-                } else {
-                    OPENVINO_ASSERT(false, "Bidirectional case is not supported.");
-                }
+            // 2. Set PortMap
+            if (params.direction == ov::op::RecurrentSequenceDirection::FORWARD) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], 0, 1, 1, -1, params.sequenceAxis);
+                tensor_iterator->get_concatenated_slices(results[1], 0, 1, 1, -1, params.sequenceAxis);
+            } else if (params.direction == ov::op::RecurrentSequenceDirection::REVERSE) {
+                tensor_iterator->set_sliced_input(body_params[0], outer_params[0], -1, -1, 1, 0, params.sequenceAxis);
+                tensor_iterator->get_concatenated_slices(results[1], -1, -1, 1, 0, params.sequenceAxis);
+            } else {
+                OPENVINO_ASSERT(false, "Bidirectional case is not supported.");
+            }
 
-                tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[0]);
-                tensor_iterator->get_iter_value(results[0]);
+            tensor_iterator->set_merged_input(body_params[1], outer_params[1], results[0]);
+            tensor_iterator->get_iter_value(results[0]);
 
-                // 3. Outer function
-                function = std::make_shared<ov::Model>(ov::OutputVector{tensor_iterator->output(0), tensor_iterator->output(1)}, outer_params);
-                break;
-            }
+            // 3. Outer function
+            function =
+                std::make_shared<ov::Model>(ov::OutputVector{tensor_iterator->output(0), tensor_iterator->output(1)},
+                                            outer_params);
+            break;
+        }
         }
         return function;
     }
 };
 
 class ReferenceTILayerStaticTest : public testing::TestWithParam<TensorIteratorStaticParams>,
-        public reference_tests::CommonReferenceTest {
+                                   public reference_tests::CommonReferenceTest {
 public:
     void SetUp() override {
         SKIP_IF_CURRENT_TEST_IS_DISABLED()
@@ -491,1112 +513,1172 @@ template <ov::element::Type_t ET>
 std::vector<TensorIteratorStaticParams> generateParams() {
     using T = typename ov::element_type_traits<ET>::value_type;
 
-    std::vector<TensorIteratorStaticParams> params {
+    std::vector<TensorIteratorStaticParams> params{
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.7f, ov::op::RecurrentSequenceDirection::FORWARD, TensorIteratorBodyType::LSTM,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            ov::op::RecurrentSequenceDirection::FORWARD,
+            TensorIteratorBodyType::LSTM,
             ET,
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
-                1.82401, 6.1306, 4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686,
-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 4.59474,
-                6.19214, 8.80766, 8.07546, 3.29232, 1.74029, 2.4198, 2.88544, 4.75644, 4.12921, 7.29896,
-                7.27759, 1.67252, 1.32823, 8.1046, 9.10476, 1.04197, 3.37783, 5.2064, 4.23835, 3.16196,
-                1.20852, 5.78501, 2.17175, 6.05313, 2.51048, 4.78967, 7.16219, 3.4651, 1.09, 2.9788,
-                1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892, 5.86648, 8.73895, 2.66603, 1.75192,
-                1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565, 7.35114, 3.1439, 1.39976,
-                3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637, 8.6232, 8.54902,
-                2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225, 3.99956, 1.08021, 5.54918, 7.05833,
-                1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
-                5.59325, 9.89258, 2.30223, 1.4347, 9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909,
-                1.00912, 6.62167, 2.80244, 6.626, 3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902,
-                6.26823, 9.72608, 3.73491, 3.8238, 3.03815, 7.05101, 8.0103, 5.61396, 6.53738, 1.41095,
-                5.0149, 9.71211, 4.23604, 5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328, 8.2817,
-                5.12336, 8.98577, 5.80541, 6.19552, 9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817,
-                8.57269, 5.99975, 3.42893, 5.38068, 3.48261, 3.02851, 6.82079, 9.2902, 2.80427, 8.91868,
-                5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755, 2.49121, 5.52697, 8.08823, 9.13242,
-                2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457, 5.55154, 7.24966, 5.1128,
-                4.25147, 8.34407, 1.4123, 4.49045, 5.12671, 7.62159, 9.18673, 3.49665, 8.35992, 6.90684,
-                1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283, 9.88249, 4.48422,
-                8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155, 9.94928, 6.88321, 1.33685,
-                7.4718, 7.19305, 6.47932, 1.9559, 3.52616, 7.98593, 9.0115, 5.59539, 7.44137, 1.70001,
-                6.53774, 8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153,
-                5.4073, 9.00437, 8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473,
-                7.95084, 2.11852, 9.28916, 1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549,
-                3.75218, 8.98228, 8.98158, 5.63695, 3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035,
-                8.37644, 8.54954, 5.70516, 2.45744, 9.54079, 1.53504, 8.9785, 6.1691, 4.40962, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
+                1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 8.6168,
+                3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.0055,  7.44373,
+                8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 7.03475, 6.33759, 7.04489,
+                4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 6.61627, 6.94572, 3.68646, 5.01521,
+                2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937,
+                1.40811, 2.2597,  8.13163, 1.26821, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069,
+                4.25135, 6.13908, 6.74053, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208,
+                1.10502, 5.48298, 1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224,
+                7.95465, 2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
+                1.63073, 5.25228, 7.68488, 2.7276,  5.1788,  3.07327, 5.57423, 2.87711, 1.44374, 5.66976, 2.55051,
+                4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,  1.82401, 6.1306,
+                4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686, 4.85031, 4.85544, 4.25714,
+                2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891, 2.16793, 3.64924, 4.24733, 3.47181,
+                1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016, 7.6686,  3.68812, 2.83922, 9.83581, 9.03719,
+                7.83414, 6.86009, 1.35715, 8.32489, 7.86316, 5.09754, 5.78644, 1.98402, 2.31429, 5.5791,  2.94085,
+                9.24799, 5.15937, 2.19041, 7.87817, 2.9146,  1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937,
+                9.37912, 6.18926, 8.55681, 6.60963, 3.92066, 7.5521,  5.70463, 7.6313,  2.48866, 7.18352, 4.8413,
+                7.55702, 7.80702, 4.5785,  9.3268,  2.83159, 1.07202, 9.33716, 3.6506,  2.50256, 1.21691, 5.06801,
+                8.27505, 4.31539, 6.48286, 1.31363, 4.1912,  1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
+                5.24875, 1.94852, 5.52768, 8.97121, 5.8094,  3.53329, 4.19126, 9.06652, 3.1734,  1.21496, 9.69154,
+                4.86971, 4.1166,  6.19361, 2.13874, 9.55039, 3.8225,  9.57548, 2.96554, 3.2383,  8.77422, 3.11741,
+                8.3359,  5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474,  4.59474, 6.19214, 8.80766, 8.07546,
+                3.29232, 1.74029, 2.4198,  2.88544, 4.75644, 4.12921, 7.29896, 7.27759, 1.67252, 1.32823, 8.1046,
+                9.10476, 1.04197, 3.37783, 5.2064,  4.23835, 3.16196, 1.20852, 5.78501, 2.17175, 6.05313, 2.51048,
+                4.78967, 7.16219, 3.4651,  1.09,    2.9788,  1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892,
+                5.86648, 8.73895, 2.66603, 1.75192, 1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565,
+                7.35114, 3.1439,  1.39976, 3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637,
+                8.6232,  8.54902, 2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225,  3.99956, 1.08021, 5.54918,
+                7.05833, 1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
+                5.59325, 9.89258, 2.30223, 1.4347,  9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909, 1.00912,
+                6.62167, 2.80244, 6.626,   3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902, 6.26823, 9.72608,
+                3.73491, 3.8238,  3.03815, 7.05101, 8.0103,  5.61396, 6.53738, 1.41095, 5.0149,  9.71211, 4.23604,
+                5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328,  8.2817,  5.12336, 8.98577, 5.80541, 6.19552,
+                9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817, 8.57269, 5.99975, 3.42893, 5.38068, 3.48261,
+                3.02851, 6.82079, 9.2902,  2.80427, 8.91868, 5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755,
+                2.49121, 5.52697, 8.08823, 9.13242, 2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457,
+                5.55154, 7.24966, 5.1128,  4.25147, 8.34407, 1.4123,  4.49045, 5.12671, 7.62159, 9.18673, 3.49665,
+                8.35992, 6.90684, 1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283,  9.88249,
+                4.48422, 8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155,  9.94928, 6.88321, 1.33685,
+                7.4718,  7.19305, 6.47932, 1.9559,  3.52616, 7.98593, 9.0115,  5.59539, 7.44137, 1.70001, 6.53774,
+                8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153, 5.4073,  9.00437,
+                8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473, 7.95084, 2.11852, 9.28916,
+                1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549, 3.75218, 8.98228, 8.98158, 5.63695,
+                3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035, 8.37644, 8.54954, 5.70516, 2.45744, 9.54079,
+                1.53504, 8.9785,  6.1691,  4.40962, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
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+                2.49121, 5.52697, 8.08823, 10},
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-            std::vector<T>{
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-                1.31284, 1.31868, 1.26086, 1.28443, 1.24866, 1.22491, 1.28812, 1.22855, 1.35744, 1.37287}),
+                0.585658, 0.587002, 0.572757, 0.578824, 0.569471, 0.562771, 0.57974,  0.563825, 0.59541,  0.598524,
+                0.577977, 0.578955, 0.568828, 0.573079, 0.566562, 0.562011, 0.573728, 0.56272,  0.585197, 0.587567},
+            std::vector<T>{0.559698, 0.587499, 0.58592,  0.563707, 0.587544, 0.56698,  0.571671, 0.571423, 0.579197,
+                           0.585993, 0.583768, 0.569262, 0.575267, 0.573003, 0.566785, 0.575539, 0.58546,  0.57339,
+                           0.572642, 0.586082, 0.582036, 0.580415, 0.582661, 0.562616, 0.57509,  0.584239, 0.583333,
+                           0.583345, 0.568079, 0.561569, 0.579218, 0.577141, 0.579248, 0.572105, 0.565823, 0.568568,
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+                           0.562011, 0.573728, 0.56272,  0.585197, 0.587567},
+            std::vector<T>{1.2132,  1.37242, 1.3621,  1.23365, 1.37271, 1.25089, 1.27652, 1.27513, 1.32014, 1.36258,
+                           1.34833, 1.26322, 1.29695, 1.284,   1.24985, 1.29853, 1.35913, 1.2862,  1.28197, 1.36315,
+                           1.33748, 1.32752, 1.34137, 1.22801, 1.29593, 1.35132, 1.34559, 1.34566, 1.25679, 1.22266,
+                           1.32026, 1.30789, 1.32044, 1.27895, 1.24474, 1.25944, 1.23589, 1.33827, 1.27907, 1.21865,
+                           1.31284, 1.31868, 1.26086, 1.28443, 1.24866, 1.22491, 1.28812, 1.22855, 1.35744, 1.37287}),
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.7f, ov::op::RecurrentSequenceDirection::REVERSE, TensorIteratorBodyType::LSTM,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            ov::op::RecurrentSequenceDirection::REVERSE,
+            TensorIteratorBodyType::LSTM,
             ET,
             std::vector<T>{
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+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
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+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
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+                0.585658, 0.587002, 0.572757, 0.578824, 0.569471, 0.562771, 0.57974,  0.563825, 0.59541,  0.598524,
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-                0.624826, 0.62722, 0.59673, 0.611138, 0.587988, 0.568023, 0.613126, 0.571356, 0.640142, 0.644091,
-                0.640947, 0.643193, 0.610134, 0.626905, 0.599072, 0.571593, 0.629065, 0.57638, 0.654104, 0.656992,
-                0.654712, 0.656356, 0.625799, 0.642901, 0.612988, 0.576717, 0.644878, 0.583449, 0.66321, 0.664664,
-                0.663529, 0.664358, 0.641868, 0.656146, 0.628916, 0.583917, 0.65754, 0.593086, 0.667146, 0.667567,
-                0.667244, 0.667485, 0.655394, 0.664256, 0.644744, 0.59371, 0.664921, 0.6056, 0.668088, 0.668142,
-                0.668102, 0.668132, 0.66388, 0.667456, 0.657447, 0.606385, 0.667634, 0.620685, 0.668185, 0.668187},
-            std::vector<T>{
-                0.559698, 0.587499, 0.58592, 0.563707, 0.587544, 0.56698, 0.571671, 0.571423, 0.579197, 0.585993,
-                0.583768, 0.569262, 0.575267, 0.573003, 0.566785, 0.575539, 0.58546, 0.57339, 0.572642, 0.586082,
-                0.582036, 0.580415, 0.582661, 0.562616, 0.57509, 0.584239, 0.583333, 0.583345, 0.568079, 0.561569,
-                0.579218, 0.577141, 0.579248, 0.572105, 0.565823, 0.568568, 0.564137, 0.582163, 0.572127, 0.560781,
-                0.577977, 0.578955, 0.568828, 0.573079, 0.566562, 0.562011, 0.573728, 0.56272, 0.585197, 0.587567},
-            std::vector<T>{
-                1.2132, 1.37242, 1.3621, 1.23365, 1.37271, 1.25089, 1.27652, 1.27513, 1.32014, 1.36258,
-                1.34833, 1.26322, 1.29695, 1.284, 1.24985, 1.29853, 1.35913, 1.2862, 1.28197, 1.36315,
-                1.33748, 1.32752, 1.34137, 1.22801, 1.29593, 1.35132, 1.34559, 1.34566, 1.25679, 1.22266,
-                1.32026, 1.30789, 1.32044, 1.27895, 1.24474, 1.25944, 1.23589, 1.33827, 1.27907, 1.21865,
-                1.31284, 1.31868, 1.26086, 1.28443, 1.24866, 1.22491, 1.28812, 1.22855, 1.35744, 1.37287}),
+                0.609258, 0.611426, 0.586197, 0.59755,  0.579676, 0.56557,  0.599186, 0.567859, 0.623984, 0.628198,
+                0.624826, 0.62722,  0.59673,  0.611138, 0.587988, 0.568023, 0.613126, 0.571356, 0.640142, 0.644091,
+                0.640947, 0.643193, 0.610134, 0.626905, 0.599072, 0.571593, 0.629065, 0.57638,  0.654104, 0.656992,
+                0.654712, 0.656356, 0.625799, 0.642901, 0.612988, 0.576717, 0.644878, 0.583449, 0.66321,  0.664664,
+                0.663529, 0.664358, 0.641868, 0.656146, 0.628916, 0.583917, 0.65754,  0.593086, 0.667146, 0.667567,
+                0.667244, 0.667485, 0.655394, 0.664256, 0.644744, 0.59371,  0.664921, 0.6056,   0.668088, 0.668142,
+                0.668102, 0.668132, 0.66388,  0.667456, 0.657447, 0.606385, 0.667634, 0.620685, 0.668185, 0.668187},
+            std::vector<T>{0.559698, 0.587499, 0.58592,  0.563707, 0.587544, 0.56698,  0.571671, 0.571423, 0.579197,
+                           0.585993, 0.583768, 0.569262, 0.575267, 0.573003, 0.566785, 0.575539, 0.58546,  0.57339,
+                           0.572642, 0.586082, 0.582036, 0.580415, 0.582661, 0.562616, 0.57509,  0.584239, 0.583333,
+                           0.583345, 0.568079, 0.561569, 0.579218, 0.577141, 0.579248, 0.572105, 0.565823, 0.568568,
+                           0.564137, 0.582163, 0.572127, 0.560781, 0.577977, 0.578955, 0.568828, 0.573079, 0.566562,
+                           0.562011, 0.573728, 0.56272,  0.585197, 0.587567},
+            std::vector<T>{1.2132,  1.37242, 1.3621,  1.23365, 1.37271, 1.25089, 1.27652, 1.27513, 1.32014, 1.36258,
+                           1.34833, 1.26322, 1.29695, 1.284,   1.24985, 1.29853, 1.35913, 1.2862,  1.28197, 1.36315,
+                           1.33748, 1.32752, 1.34137, 1.22801, 1.29593, 1.35132, 1.34559, 1.34566, 1.25679, 1.22266,
+                           1.32026, 1.30789, 1.32044, 1.27895, 1.24474, 1.25944, 1.23589, 1.33827, 1.27907, 1.21865,
+                           1.31284, 1.31868, 1.26086, 1.28443, 1.24866, 1.22491, 1.28812, 1.22855, 1.35744, 1.37287}),
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.7f, ov::op::RecurrentSequenceDirection::FORWARD, TensorIteratorBodyType::GRU,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            ov::op::RecurrentSequenceDirection::FORWARD,
+            TensorIteratorBodyType::GRU,
             ET,
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
-                1.82401, 6.1306, 4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686,
-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 4.59474,
-                6.19214, 8.80766, 8.07546, 3.29232, 1.74029, 2.4198, 2.88544, 4.75644, 4.12921, 7.29896,
-                7.27759, 1.67252, 1.32823, 8.1046, 9.10476, 1.04197, 3.37783, 5.2064, 4.23835, 3.16196,
-                1.20852, 5.78501, 2.17175, 6.05313, 2.51048, 4.78967, 7.16219, 3.4651, 1.09, 2.9788,
-                1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892, 5.86648, 8.73895, 2.66603, 1.75192,
-                1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565, 7.35114, 3.1439, 1.39976,
-                3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637, 8.6232, 8.54902,
-                2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225, 3.99956, 1.08021, 5.54918, 7.05833,
-                1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
-                5.59325, 9.89258, 2.30223, 1.4347, 9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909,
-                1.00912, 6.62167, 2.80244, 6.626, 3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902,
-                6.26823, 9.72608, 3.73491, 3.8238, 3.03815, 7.05101, 8.0103, 5.61396, 6.53738, 1.41095,
-                5.0149, 9.71211, 4.23604, 5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328, 8.2817,
-                5.12336, 8.98577, 5.80541, 6.19552, 9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817,
-                8.57269, 5.99975, 3.42893, 5.38068, 3.48261, 3.02851, 6.82079, 9.2902, 2.80427, 8.91868,
-                5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755, 2.49121, 5.52697, 8.08823, 9.13242,
-                2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457, 5.55154, 7.24966, 5.1128,
-                4.25147, 8.34407, 1.4123, 4.49045, 5.12671, 7.62159, 9.18673, 3.49665, 8.35992, 6.90684,
-                1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283, 9.88249, 4.48422,
-                8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155, 9.94928, 6.88321, 1.33685,
-                7.4718, 7.19305, 6.47932, 1.9559, 3.52616, 7.98593, 9.0115, 5.59539, 7.44137, 1.70001,
-                6.53774, 8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153,
-                5.4073, 9.00437, 8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473,
-                7.95084, 2.11852, 9.28916, 1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549,
-                3.75218, 8.98228, 8.98158, 5.63695, 3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035,
-                8.37644, 8.54954, 5.70516, 2.45744, 9.54079, 1.53504, 8.9785, 6.1691, 4.40962, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
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-                0.711027, 0.716871, 0.659048, 0.682622, 0.646854, 0.623101, 0.686311, 0.626743, 0.755629, 0.771058},
+            std::vector<T>{0.611387, 0.770609, 0.76029,  0.631845, 0.770905, 0.649083, 0.674709, 0.673325, 0.718326,
+                           0.760766, 0.746518, 0.661408, 0.695142, 0.682194, 0.648044, 0.696717, 0.75732,  0.684389,
+                           0.680157, 0.761339, 0.735673, 0.725707, 0.739564, 0.626204, 0.694121, 0.749506, 0.743778,
+                           0.743851, 0.654985, 0.620846, 0.718451, 0.706082, 0.718631, 0.677138, 0.64293,  0.657632,
+                           0.634079, 0.73646,  0.677257, 0.616843, 0.711027, 0.716871, 0.659048, 0.682622, 0.646854,
+                           0.623101, 0.686311, 0.626743, 0.755629, 0.771058},
             std::vector<T>{0}),
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.7f, ov::op::RecurrentSequenceDirection::REVERSE, TensorIteratorBodyType::GRU,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            ov::op::RecurrentSequenceDirection::REVERSE,
+            TensorIteratorBodyType::GRU,
             ET,
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
-                2.55051, 4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,
-                1.82401, 6.1306, 4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686,
-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 4.59474,
-                6.19214, 8.80766, 8.07546, 3.29232, 1.74029, 2.4198, 2.88544, 4.75644, 4.12921, 7.29896,
-                7.27759, 1.67252, 1.32823, 8.1046, 9.10476, 1.04197, 3.37783, 5.2064, 4.23835, 3.16196,
-                1.20852, 5.78501, 2.17175, 6.05313, 2.51048, 4.78967, 7.16219, 3.4651, 1.09, 2.9788,
-                1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892, 5.86648, 8.73895, 2.66603, 1.75192,
-                1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565, 7.35114, 3.1439, 1.39976,
-                3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637, 8.6232, 8.54902,
-                2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225, 3.99956, 1.08021, 5.54918, 7.05833,
-                1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
-                5.59325, 9.89258, 2.30223, 1.4347, 9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909,
-                1.00912, 6.62167, 2.80244, 6.626, 3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902,
-                6.26823, 9.72608, 3.73491, 3.8238, 3.03815, 7.05101, 8.0103, 5.61396, 6.53738, 1.41095,
-                5.0149, 9.71211, 4.23604, 5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328, 8.2817,
-                5.12336, 8.98577, 5.80541, 6.19552, 9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817,
-                8.57269, 5.99975, 3.42893, 5.38068, 3.48261, 3.02851, 6.82079, 9.2902, 2.80427, 8.91868,
-                5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755, 2.49121, 5.52697, 8.08823, 9.13242,
-                2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457, 5.55154, 7.24966, 5.1128,
-                4.25147, 8.34407, 1.4123, 4.49045, 5.12671, 7.62159, 9.18673, 3.49665, 8.35992, 6.90684,
-                1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283, 9.88249, 4.48422,
-                8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155, 9.94928, 6.88321, 1.33685,
-                7.4718, 7.19305, 6.47932, 1.9559, 3.52616, 7.98593, 9.0115, 5.59539, 7.44137, 1.70001,
-                6.53774, 8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153,
-                5.4073, 9.00437, 8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473,
-                7.95084, 2.11852, 9.28916, 1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549,
-                3.75218, 8.98228, 8.98158, 5.63695, 3.40379, 8.92309, 5.48185, 4.00095, 9.05227, 2.84035,
-                8.37644, 8.54954, 5.70516, 2.45744, 9.54079, 1.53504, 8.9785, 6.1691, 4.40962, 10},
-            std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
+                1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985, 8.6168,
+                3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215, 8.0055,  7.44373,
+                8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319, 7.03475, 6.33759, 7.04489,
+                4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754, 6.61627, 6.94572, 3.68646, 5.01521,
+                2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541, 5.72319, 1.75261, 9.25175, 9.19404, 3.69037,
+                6.2595,  6.09321, 6.52544, 9.60882, 3.34881, 3.07914, 5.80104, 9.54944, 5.43754, 5.8654,  7.88937,
+                1.40811, 2.2597,  8.13163, 1.26821, 8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069,
+                4.25135, 6.13908, 6.74053, 2.13683, 7.21184, 6.82974, 4.18545, 7.8691,  4.20879, 7.77509, 8.93208,
+                1.10502, 5.48298, 1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224,
+                7.95465, 2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
+                1.63073, 5.25228, 7.68488, 2.7276,  5.1788,  3.07327, 5.57423, 2.87711, 1.44374, 5.66976, 2.55051,
+                4.56682, 1.96629, 5.58829, 1.91922, 3.59846, 3.08583, 9.70901, 3.50487, 3.1026,  1.82401, 6.1306,
+                4.76134, 4.31059, 8.31695, 3.60784, 7.45652, 6.51653, 4.84219, 7.76686, 4.85031, 4.85544, 4.25714,
+                2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891, 2.16793, 3.64924, 4.24733, 3.47181,
+                1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016, 7.6686,  3.68812, 2.83922, 9.83581, 9.03719,
+                7.83414, 6.86009, 1.35715, 8.32489, 7.86316, 5.09754, 5.78644, 1.98402, 2.31429, 5.5791,  2.94085,
+                9.24799, 5.15937, 2.19041, 7.87817, 2.9146,  1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937,
+                9.37912, 6.18926, 8.55681, 6.60963, 3.92066, 7.5521,  5.70463, 7.6313,  2.48866, 7.18352, 4.8413,
+                7.55702, 7.80702, 4.5785,  9.3268,  2.83159, 1.07202, 9.33716, 3.6506,  2.50256, 1.21691, 5.06801,
+                8.27505, 4.31539, 6.48286, 1.31363, 4.1912,  1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
+                5.24875, 1.94852, 5.52768, 8.97121, 5.8094,  3.53329, 4.19126, 9.06652, 3.1734,  1.21496, 9.69154,
+                4.86971, 4.1166,  6.19361, 2.13874, 9.55039, 3.8225,  9.57548, 2.96554, 3.2383,  8.77422, 3.11741,
+                8.3359,  5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474,  4.59474, 6.19214, 8.80766, 8.07546,
+                3.29232, 1.74029, 2.4198,  2.88544, 4.75644, 4.12921, 7.29896, 7.27759, 1.67252, 1.32823, 8.1046,
+                9.10476, 1.04197, 3.37783, 5.2064,  4.23835, 3.16196, 1.20852, 5.78501, 2.17175, 6.05313, 2.51048,
+                4.78967, 7.16219, 3.4651,  1.09,    2.9788,  1.28761, 9.41385, 8.03883, 5.65835, 1.14816, 3.6892,
+                5.86648, 8.73895, 2.66603, 1.75192, 1.39845, 4.99427, 1.17387, 1.60329, 8.30594, 6.72662, 7.95565,
+                7.35114, 3.1439,  1.39976, 3.53095, 8.78581, 1.65811, 6.94299, 2.68641, 5.70058, 9.13491, 5.27637,
+                8.6232,  8.54902, 2.25352, 5.86274, 5.20377, 2.96815, 4.96745, 5.3225,  3.99956, 1.08021, 5.54918,
+                7.05833, 1.49913, 2.41822, 6.44593, 3.87301, 9.01465, 8.11336, 2.95749, 2.80188, 7.12396, 2.40595,
+                5.59325, 9.89258, 2.30223, 1.4347,  9.09158, 7.43797, 3.79295, 4.53646, 1.72705, 4.16909, 1.00912,
+                6.62167, 2.80244, 6.626,   3.89307, 1.42586, 7.51028, 7.83327, 4.65674, 7.33902, 6.26823, 9.72608,
+                3.73491, 3.8238,  3.03815, 7.05101, 8.0103,  5.61396, 6.53738, 1.41095, 5.0149,  9.71211, 4.23604,
+                5.98629, 4.70219, 9.69442, 2.82752, 9.93544, 6.9328,  8.2817,  5.12336, 8.98577, 5.80541, 6.19552,
+                9.25748, 3.82732, 7.53525, 8.24712, 5.32057, 5.38817, 8.57269, 5.99975, 3.42893, 5.38068, 3.48261,
+                3.02851, 6.82079, 9.2902,  2.80427, 8.91868, 5.19227, 7.52482, 3.72584, 5.40107, 2.83307, 1.79755,
+                2.49121, 5.52697, 8.08823, 9.13242, 2.97572, 7.64318, 3.32023, 6.07788, 2.19187, 4.34879, 1.7457,
+                5.55154, 7.24966, 5.1128,  4.25147, 8.34407, 1.4123,  4.49045, 5.12671, 7.62159, 9.18673, 3.49665,
+                8.35992, 6.90684, 1.10152, 7.61818, 6.43145, 7.12017, 6.25564, 6.16169, 4.24916, 9.6283,  9.88249,
+                4.48422, 8.52562, 9.83928, 6.26818, 7.03839, 1.77631, 9.92305, 8.0155,  9.94928, 6.88321, 1.33685,
+                7.4718,  7.19305, 6.47932, 1.9559,  3.52616, 7.98593, 9.0115,  5.59539, 7.44137, 1.70001, 6.53774,
+                8.54023, 7.26405, 5.99553, 8.75071, 7.70789, 3.38094, 9.99792, 6.16359, 6.75153, 5.4073,  9.00437,
+                8.87059, 8.63011, 6.82951, 6.27021, 3.53425, 9.92489, 8.19695, 5.51473, 7.95084, 2.11852, 9.28916,
+                1.40353, 3.05744, 8.58238, 3.75014, 5.35889, 6.85048, 2.29549, 3.75218, 8.98228, 8.98158, 5.63695,
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+                1.53504, 8.9785,  6.1691,  4.40962, 10},
+            std::vector<T>{1,       9.97466, 9.39302, 2.15312, 9.99136, 3.1248,  4.56923, 4.4912,  7.02771, 9.41985,
+                           8.6168,  3.81946, 5.72093, 4.99108, 3.0662,  5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
+                           8.0055,  7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
+                           7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
+                           6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 10},
             std::vector<T>{0},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 9.97466, 9.39302, 2.15312, 9.99136, 3.1248, 4.56923, 4.4912, 7.02771, 9.41985,
-                8.6168, 3.81946, 5.72093, 4.99108, 3.0662, 5.80973, 9.22566, 5.11484, 4.87629, 9.45215,
-                8.0055, 7.44373, 8.22482, 1.83521, 5.66337, 8.78518, 8.46232, 8.46643, 3.45745, 1.53319,
-                7.03475, 6.33759, 7.04489, 4.70609, 2.77796, 3.60667, 2.27908, 8.04983, 4.71285, 1.30754,
-                6.61627, 6.94572, 3.68646, 5.01521, 2.99912, 1.66028, 5.22315, 1.86555, 9.13033, 2.07541,
-                5.72319, 1.75261, 9.25175, 9.19404, 3.69037, 6.2595, 6.09321, 6.52544, 9.60882, 3.34881,
-                3.07914, 5.80104, 9.54944, 5.43754, 5.8654, 7.88937, 1.40811, 2.2597, 8.13163, 1.26821,
-                8.94813, 5.86709, 5.03182, 9.02922, 4.39826, 5.84582, 6.87069, 4.25135, 6.13908, 6.74053,
-                2.13683, 7.21184, 6.82974, 4.18545, 7.8691, 4.20879, 7.77509, 8.93208, 1.10502, 5.48298,
-                1.66413, 8.08256, 1.57661, 4.19779, 9.47653, 4.41823, 7.86628, 7.94436, 3.71224, 7.95465,
-                2.37637, 6.20771, 1.08107, 7.38138, 5.23577, 7.88133, 5.20653, 3.42101, 8.48523, 5.96192,
-                1.63073, 5.25228, 7.68488, 2.7276, 5.1788, 3.07327, 5.57423, 2.87711, 1.44374, 5.66976,
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-                4.85031, 4.85544, 4.25714, 2.38005, 9.43471, 9.24769, 8.03763, 6.54696, 1.32399, 6.88891,
-                2.16793, 3.64924, 4.24733, 3.47181, 1.66572, 2.36923, 2.45457, 9.44841, 4.34021, 1.45016,
-                7.6686, 3.68812, 2.83922, 9.83581, 9.03719, 7.83414, 6.86009, 1.35715, 8.32489, 7.86316,
-                5.09754, 5.78644, 1.98402, 2.31429, 5.5791, 2.94085, 9.24799, 5.15937, 2.19041, 7.87817,
-                2.9146, 1.66833, 1.85877, 2.45985, 4.20817, 1.85777, 2.28937, 9.37912, 6.18926, 8.55681,
-                6.60963, 3.92066, 7.5521, 5.70463, 7.6313, 2.48866, 7.18352, 4.8413, 7.55702, 7.80702,
-                4.5785, 9.3268, 2.83159, 1.07202, 9.33716, 3.6506, 2.50256, 1.21691, 5.06801, 8.27505,
-                4.31539, 6.48286, 1.31363, 4.1912, 1.70668, 7.23867, 1.11441, 5.13591, 9.65186, 4.00767,
-                5.24875, 1.94852, 5.52768, 8.97121, 5.8094, 3.53329, 4.19126, 9.06652, 3.1734, 1.21496,
-                9.69154, 4.86971, 4.1166, 6.19361, 2.13874, 9.55039, 3.8225, 9.57548, 2.96554, 3.2383,
-                8.77422, 3.11741, 8.3359, 5.89508, 2.72134, 6.29956, 1.43323, 1.14286, 1.4474, 4.59474,
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-                4.62145, 4.84158, 2.66378, 3.55164, 2.20451, 1.30991, 3.69058, 1.44707, 6.30131, 6.88241},
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+                4.62145,  4.84158,  2.66378,  3.55164,  2.20451,  1.30991,  3.69058,  1.44707,  6.30131,  6.88241},
+            std::vector<T>{0.611387, 0.770609, 0.76029,  0.631845, 0.770905, 0.649083, 0.674709, 0.673325, 0.718326,
+                           0.760766, 0.746518, 0.661408, 0.695142, 0.682194, 0.648044, 0.696717, 0.75732,  0.684389,
+                           0.680157, 0.761339, 0.735673, 0.725707, 0.739564, 0.626204, 0.694121, 0.749506, 0.743778,
+                           0.743851, 0.654985, 0.620846, 0.718451, 0.706082, 0.718631, 0.677138, 0.64293,  0.657632,
+                           0.634079, 0.73646,  0.677257, 0.616843, 0.711027, 0.716871, 0.659048, 0.682622, 0.646854,
+                           0.623101, 0.686311, 0.626743, 0.755629, 0.771058},
             std::vector<T>{0}),
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.f, ov::op::RecurrentSequenceDirection::FORWARD, TensorIteratorBodyType::RNN,
+            5,
+            10,
+            10,
+            10,
+            0.f,
+            ov::op::RecurrentSequenceDirection::FORWARD,
+            TensorIteratorBodyType::RNN,
             ET,
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-                -0.213783, -0.0673415, -0.791954, -0.618463, 0.345361, -0.0507364, 0.603086, -0.504686, 0.482923, 1},
+            std::vector<T>{-1,           0.780309,   -0.738585,  -0.920481,  0.652872,    0.0641558,  0.91262,
+                           -0.0761474,   0.847476,   -0.252158,  -0.690053,  0.784687,    -0.946421,  -0.416995,
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+                           0.61247,      0.861631,   -0.271941,  0.381896,   -0.741371,   0.665373,   -0.363293,
+                           0.474405,     0.193539,   -0.272586,  0.589941,   0.396962,    0.643758,   0.798932,
+                           0.663799,     0.819915,   0.949827,   0.312239,   0.623979,    -0.794512,  -0.524943,
+                           -0.24131,     0.398472,   -0.0301095, -0.169556,  0.277324,    0.51858,    0.115046,
+                           0.386911,     0.826518,   -0.950774,  0.674757,   -0.23359,    -0.402458,  -0.987406,
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+                           -0.547825, 0.689601},
             std::vector<T>{0}),
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.f, ov::op::RecurrentSequenceDirection::REVERSE, TensorIteratorBodyType::RNN,
+            5,
+            10,
+            10,
+            10,
+            0.f,
+            ov::op::RecurrentSequenceDirection::REVERSE,
+            TensorIteratorBodyType::RNN,
             ET,
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+                           0.363935,  -0.0884402, -0.888573, 0.608715,  -0.999921, 0.828499,  -0.150879,  -0.301067,
+                           -0.976568, 0.999748,   0.284666,  0.983777,  -0.979617, 0.971752,  -0.698165,  -0.513943,
+                           0.855178,  -0.725843,  -0.954888, 0.940128,  0.956929,  0.996744,  -0.851224,  -0.910939,
+                           0.657066,  0.603613,   0.504114,  -0.988843, 0.968051,  0.487372,  -0.996597,  -0.349508,
+                           0.105549,  0.799733,   0.118137,  0.89021,   -0.160378, -0.831619, -0.0241198, 0.723485,
+                           0.984892,  0.21006},
             std::vector<T>{0}),
     };
     return params;
@@ -1606,827 +1688,799 @@ template <ov::element::Type_t ET>
 std::vector<TensorIteratorStaticParams> generateParamsBF16() {
     using T = typename ov::element_type_traits<ET>::value_type;
 
-    std::vector<TensorIteratorStaticParams> params {
+    std::vector<TensorIteratorStaticParams> params{
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.7f, ov::op::RecurrentSequenceDirection::FORWARD, TensorIteratorBodyType::LSTM,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            ov::op::RecurrentSequenceDirection::FORWARD,
+            TensorIteratorBodyType::LSTM,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  10},
+            std::vector<T>{
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,     2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,  5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625, 1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375, 10},
             std::vector<T>{
                 0.523438, 0.667969, 0.667969, 0.667969, 0.667969, 0.523438, 0.632812, 0.664062, 0.667969, 0.640625,
-                0.539062, 0.664062, 0.667969, 0.667969, 0.667969, 0.539062, 0.617188, 0.65625, 0.667969, 0.625,
+                0.539062, 0.664062, 0.667969, 0.667969, 0.667969, 0.539062, 0.617188, 0.65625,  0.667969, 0.625,
                 0.546875, 0.648438, 0.667969, 0.664062, 0.667969, 0.546875, 0.601562, 0.640625, 0.667969, 0.609375,
-                0.546875, 0.632812, 0.664062, 0.65625, 0.664062, 0.546875, 0.585938, 0.625, 0.664062, 0.59375,
-                0.554688, 0.617188, 0.65625, 0.640625, 0.648438, 0.554688, 0.578125, 0.609375, 0.65625, 0.585938,
-                0.554688, 0.601562, 0.640625, 0.625, 0.640625, 0.554688, 0.570312, 0.59375, 0.640625, 0.578125,
-                0.554688, 0.59375, 0.625, 0.609375, 0.625, 0.554688, 0.570312, 0.585938, 0.625, 0.570312,
-                0.554688, 0.585938, 0.609375, 0.59375, 0.609375, 0.554688, 0.5625, 0.578125, 0.609375, 0.570312,
-                0.554688, 0.570312, 0.59375, 0.585938, 0.59375, 0.554688, 0.5625, 0.570312, 0.59375, 0.5625,
-                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625, 0.570312, 0.585938, 0.5625,
-                0.65625, 0.617188, 0.664062, 0.648438, 0.664062, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969,
-                0.648438, 0.601562, 0.664062, 0.632812, 0.664062, 0.65625, 0.667969, 0.664062, 0.667969, 0.664062,
+                0.546875, 0.632812, 0.664062, 0.65625,  0.664062, 0.546875, 0.585938, 0.625,    0.664062, 0.59375,
+                0.554688, 0.617188, 0.65625,  0.640625, 0.648438, 0.554688, 0.578125, 0.609375, 0.65625,  0.585938,
+                0.554688, 0.601562, 0.640625, 0.625,    0.640625, 0.554688, 0.570312, 0.59375,  0.640625, 0.578125,
+                0.554688, 0.59375,  0.625,    0.609375, 0.625,    0.554688, 0.570312, 0.585938, 0.625,    0.570312,
+                0.554688, 0.585938, 0.609375, 0.59375,  0.609375, 0.554688, 0.5625,   0.578125, 0.609375, 0.570312,
+                0.554688, 0.570312, 0.59375,  0.585938, 0.59375,  0.554688, 0.5625,   0.570312, 0.59375,  0.5625,
+                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625,   0.570312, 0.585938, 0.5625,
+                0.65625,  0.617188, 0.664062, 0.648438, 0.664062, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969,
+                0.648438, 0.601562, 0.664062, 0.632812, 0.664062, 0.65625,  0.667969, 0.664062, 0.667969, 0.664062,
                 0.632812, 0.585938, 0.648438, 0.617188, 0.648438, 0.648438, 0.664062, 0.648438, 0.667969, 0.65625,
-                0.617188, 0.578125, 0.632812, 0.601562, 0.632812, 0.632812, 0.65625, 0.632812, 0.664062, 0.648438,
+                0.617188, 0.578125, 0.632812, 0.601562, 0.632812, 0.632812, 0.65625,  0.632812, 0.664062, 0.648438,
                 0.601562, 0.570312, 0.617188, 0.585938, 0.617188, 0.617188, 0.640625, 0.617188, 0.648438, 0.632812,
-                0.585938, 0.570312, 0.601562, 0.578125, 0.601562, 0.601562, 0.625, 0.601562, 0.640625, 0.617188,
-                0.578125, 0.5625, 0.585938, 0.570312, 0.585938, 0.585938, 0.609375, 0.585938, 0.625, 0.601562,
-                0.570312, 0.5625, 0.578125, 0.570312, 0.578125, 0.578125, 0.59375, 0.578125, 0.609375, 0.585938,
-                0.570312, 0.5625, 0.570312, 0.5625, 0.570312, 0.570312, 0.585938, 0.570312, 0.59375, 0.578125,
-                0.5625, 0.554688, 0.570312, 0.5625, 0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
-                0.667969, 0.667969, 0.664062, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969, 0.65625, 0.5625,
-                0.667969, 0.664062, 0.65625, 0.667969, 0.664062, 0.640625, 0.664062, 0.667969, 0.640625, 0.5625,
-                0.664062, 0.648438, 0.640625, 0.664062, 0.65625, 0.625, 0.65625, 0.664062, 0.625, 0.554688,
-                0.65625, 0.632812, 0.625, 0.65625, 0.648438, 0.609375, 0.640625, 0.664062, 0.609375, 0.554688,
-                0.648438, 0.617188, 0.609375, 0.640625, 0.632812, 0.59375, 0.625, 0.648438, 0.59375, 0.554688,
-                0.632812, 0.601562, 0.59375, 0.625, 0.617188, 0.585938, 0.609375, 0.632812, 0.585938, 0.554688,
-                0.617188, 0.59375, 0.585938, 0.609375, 0.601562, 0.578125, 0.59375, 0.617188, 0.578125, 0.554688,
-                0.601562, 0.585938, 0.578125, 0.59375, 0.585938, 0.570312, 0.585938, 0.601562, 0.570312, 0.554688,
+                0.585938, 0.570312, 0.601562, 0.578125, 0.601562, 0.601562, 0.625,    0.601562, 0.640625, 0.617188,
+                0.578125, 0.5625,   0.585938, 0.570312, 0.585938, 0.585938, 0.609375, 0.585938, 0.625,    0.601562,
+                0.570312, 0.5625,   0.578125, 0.570312, 0.578125, 0.578125, 0.59375,  0.578125, 0.609375, 0.585938,
+                0.570312, 0.5625,   0.570312, 0.5625,   0.570312, 0.570312, 0.585938, 0.570312, 0.59375,  0.578125,
+                0.5625,   0.554688, 0.570312, 0.5625,   0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
+                0.667969, 0.667969, 0.664062, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969, 0.65625,  0.5625,
+                0.667969, 0.664062, 0.65625,  0.667969, 0.664062, 0.640625, 0.664062, 0.667969, 0.640625, 0.5625,
+                0.664062, 0.648438, 0.640625, 0.664062, 0.65625,  0.625,    0.65625,  0.664062, 0.625,    0.554688,
+                0.65625,  0.632812, 0.625,    0.65625,  0.648438, 0.609375, 0.640625, 0.664062, 0.609375, 0.554688,
+                0.648438, 0.617188, 0.609375, 0.640625, 0.632812, 0.59375,  0.625,    0.648438, 0.59375,  0.554688,
+                0.632812, 0.601562, 0.59375,  0.625,    0.617188, 0.585938, 0.609375, 0.632812, 0.585938, 0.554688,
+                0.617188, 0.59375,  0.585938, 0.609375, 0.601562, 0.578125, 0.59375,  0.617188, 0.578125, 0.554688,
+                0.601562, 0.585938, 0.578125, 0.59375,  0.585938, 0.570312, 0.585938, 0.601562, 0.570312, 0.554688,
                 0.585938, 0.570312, 0.570312, 0.585938, 0.578125, 0.570312, 0.578125, 0.585938, 0.570312, 0.554688,
-                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625, 0.570312, 0.578125, 0.5625, 0.554688,
+                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625,   0.570312, 0.578125, 0.5625,   0.554688,
                 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.632812, 0.667969, 0.648438,
                 0.664062, 0.667969, 0.667969, 0.664062, 0.664062, 0.664062, 0.664062, 0.617188, 0.667969, 0.632812,
-                0.65625, 0.664062, 0.667969, 0.648438, 0.65625, 0.65625, 0.648438, 0.601562, 0.667969, 0.617188,
-                0.648438, 0.65625, 0.664062, 0.632812, 0.640625, 0.648438, 0.640625, 0.59375, 0.664062, 0.601562,
-                0.632812, 0.640625, 0.648438, 0.617188, 0.625, 0.632812, 0.625, 0.585938, 0.648438, 0.59375,
-                0.617188, 0.625, 0.632812, 0.601562, 0.609375, 0.617188, 0.609375, 0.570312, 0.640625, 0.585938,
-                0.601562, 0.609375, 0.617188, 0.59375, 0.59375, 0.601562, 0.59375, 0.570312, 0.625, 0.570312,
-                0.585938, 0.59375, 0.601562, 0.585938, 0.585938, 0.585938, 0.585938, 0.5625, 0.609375, 0.570312,
-                0.578125, 0.585938, 0.59375, 0.570312, 0.578125, 0.578125, 0.578125, 0.5625, 0.59375, 0.5625,
-                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625, 0.585938, 0.5625,
+                0.65625,  0.664062, 0.667969, 0.648438, 0.65625,  0.65625,  0.648438, 0.601562, 0.667969, 0.617188,
+                0.648438, 0.65625,  0.664062, 0.632812, 0.640625, 0.648438, 0.640625, 0.59375,  0.664062, 0.601562,
+                0.632812, 0.640625, 0.648438, 0.617188, 0.625,    0.632812, 0.625,    0.585938, 0.648438, 0.59375,
+                0.617188, 0.625,    0.632812, 0.601562, 0.609375, 0.617188, 0.609375, 0.570312, 0.640625, 0.585938,
+                0.601562, 0.609375, 0.617188, 0.59375,  0.59375,  0.601562, 0.59375,  0.570312, 0.625,    0.570312,
+                0.585938, 0.59375,  0.601562, 0.585938, 0.585938, 0.585938, 0.585938, 0.5625,   0.609375, 0.570312,
+                0.578125, 0.585938, 0.59375,  0.570312, 0.578125, 0.578125, 0.578125, 0.5625,   0.59375,  0.5625,
+                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625,   0.585938, 0.5625,
                 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.664062, 0.617188, 0.667969, 0.667969, 0.667969,
-                0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625, 0.601562, 0.667969, 0.664062, 0.667969,
-                0.664062, 0.664062, 0.664062, 0.667969, 0.664062, 0.640625, 0.585938, 0.664062, 0.65625, 0.667969,
-                0.65625, 0.65625, 0.65625, 0.664062, 0.65625, 0.625, 0.578125, 0.65625, 0.648438, 0.664062,
-                0.648438, 0.648438, 0.640625, 0.65625, 0.648438, 0.609375, 0.570312, 0.640625, 0.632812, 0.65625,
-                0.632812, 0.632812, 0.625, 0.640625, 0.632812, 0.59375, 0.570312, 0.625, 0.617188, 0.640625,
-                0.617188, 0.617188, 0.609375, 0.625, 0.617188, 0.585938, 0.5625, 0.609375, 0.601562, 0.625,
-                0.601562, 0.601562, 0.59375, 0.609375, 0.601562, 0.578125, 0.5625, 0.59375, 0.585938, 0.609375,
-                0.585938, 0.585938, 0.585938, 0.59375, 0.585938, 0.570312, 0.5625, 0.585938, 0.578125, 0.59375,
-                0.578125, 0.578125, 0.578125, 0.585938, 0.578125, 0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
-            std::vector<T>{
-                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625, 0.570312, 0.585938, 0.5625,
-                0.5625, 0.554688, 0.570312, 0.5625, 0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
-                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625, 0.570312, 0.578125, 0.5625, 0.554688,
-                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625, 0.585938, 0.5625,
+                0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625,  0.601562, 0.667969, 0.664062, 0.667969,
+                0.664062, 0.664062, 0.664062, 0.667969, 0.664062, 0.640625, 0.585938, 0.664062, 0.65625,  0.667969,
+                0.65625,  0.65625,  0.65625,  0.664062, 0.65625,  0.625,    0.578125, 0.65625,  0.648438, 0.664062,
+                0.648438, 0.648438, 0.640625, 0.65625,  0.648438, 0.609375, 0.570312, 0.640625, 0.632812, 0.65625,
+                0.632812, 0.632812, 0.625,    0.640625, 0.632812, 0.59375,  0.570312, 0.625,    0.617188, 0.640625,
+                0.617188, 0.617188, 0.609375, 0.625,    0.617188, 0.585938, 0.5625,   0.609375, 0.601562, 0.625,
+                0.601562, 0.601562, 0.59375,  0.609375, 0.601562, 0.578125, 0.5625,   0.59375,  0.585938, 0.609375,
+                0.585938, 0.585938, 0.585938, 0.59375,  0.585938, 0.570312, 0.5625,   0.585938, 0.578125, 0.59375,
                 0.578125, 0.578125, 0.578125, 0.585938, 0.578125, 0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
-            std::vector<T>{
-                1.20312, 1.27344, 1.375, 1.32031, 1.35156, 1.20312, 1.22656, 1.25781, 1.375, 1.23438,
-                1.25, 1.21875, 1.26562, 1.23438, 1.26562, 1.26562, 1.32031, 1.26562, 1.35156, 1.28906,
-                1.34375, 1.27344, 1.25781, 1.32031, 1.28906, 1.24219, 1.28125, 1.34375, 1.24219, 1.21875,
-                1.28906, 1.32031, 1.35156, 1.27344, 1.28125, 1.29688, 1.28125, 1.22656, 1.35156, 1.23438,
-                1.32812, 1.32812, 1.32031, 1.35938, 1.32812, 1.25781, 1.21875, 1.32031, 1.28906, 1.375}),
+            std::vector<T>{0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625,   0.570312, 0.585938,
+                           0.5625,   0.5625,   0.554688, 0.570312, 0.5625,   0.570312, 0.570312, 0.578125, 0.570312,
+                           0.585938, 0.570312, 0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625,   0.570312,
+                           0.578125, 0.5625,   0.554688, 0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312,
+                           0.570312, 0.5625,   0.585938, 0.5625,   0.578125, 0.578125, 0.578125, 0.585938, 0.578125,
+                           0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
+            std::vector<T>{1.20312, 1.27344, 1.375,   1.32031, 1.35156, 1.20312, 1.22656, 1.25781, 1.375,   1.23438,
+                           1.25,    1.21875, 1.26562, 1.23438, 1.26562, 1.26562, 1.32031, 1.26562, 1.35156, 1.28906,
+                           1.34375, 1.27344, 1.25781, 1.32031, 1.28906, 1.24219, 1.28125, 1.34375, 1.24219, 1.21875,
+                           1.28906, 1.32031, 1.35156, 1.27344, 1.28125, 1.29688, 1.28125, 1.22656, 1.35156, 1.23438,
+                           1.32812, 1.32812, 1.32031, 1.35938, 1.32812, 1.25781, 1.21875, 1.32031, 1.28906, 1.375}),
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.7f, ov::op::RecurrentSequenceDirection::REVERSE, TensorIteratorBodyType::LSTM,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            ov::op::RecurrentSequenceDirection::REVERSE,
+            TensorIteratorBodyType::LSTM,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 10},
-            std::vector<T>{
-                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625, 0.570312, 0.585938, 0.5625,
-                0.554688, 0.570312, 0.59375, 0.585938, 0.59375, 0.554688, 0.5625, 0.570312, 0.59375, 0.5625,
-                0.554688, 0.585938, 0.609375, 0.59375, 0.609375, 0.554688, 0.5625, 0.578125, 0.609375, 0.570312,
-                0.554688, 0.59375, 0.625, 0.609375, 0.625, 0.554688, 0.570312, 0.585938, 0.625, 0.570312,
-                0.554688, 0.601562, 0.640625, 0.625, 0.640625, 0.554688, 0.570312, 0.59375, 0.640625, 0.578125,
-                0.554688, 0.617188, 0.65625, 0.640625, 0.648438, 0.554688, 0.578125, 0.609375, 0.65625, 0.585938,
-                0.546875, 0.632812, 0.664062, 0.65625, 0.664062, 0.546875, 0.585938, 0.625, 0.664062, 0.59375,
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  10},
+            std::vector<T>{
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,     2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,  5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625, 1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375, 10},
+            std::vector<T>{
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+                0.554688, 0.570312, 0.59375,  0.585938, 0.59375,  0.554688, 0.5625,   0.570312, 0.59375,  0.5625,
+                0.554688, 0.585938, 0.609375, 0.59375,  0.609375, 0.554688, 0.5625,   0.578125, 0.609375, 0.570312,
+                0.554688, 0.59375,  0.625,    0.609375, 0.625,    0.554688, 0.570312, 0.585938, 0.625,    0.570312,
+                0.554688, 0.601562, 0.640625, 0.625,    0.640625, 0.554688, 0.570312, 0.59375,  0.640625, 0.578125,
+                0.554688, 0.617188, 0.65625,  0.640625, 0.648438, 0.554688, 0.578125, 0.609375, 0.65625,  0.585938,
+                0.546875, 0.632812, 0.664062, 0.65625,  0.664062, 0.546875, 0.585938, 0.625,    0.664062, 0.59375,
                 0.546875, 0.648438, 0.667969, 0.664062, 0.667969, 0.546875, 0.601562, 0.640625, 0.667969, 0.609375,
-                0.539062, 0.664062, 0.667969, 0.667969, 0.667969, 0.539062, 0.617188, 0.65625, 0.667969, 0.625,
+                0.539062, 0.664062, 0.667969, 0.667969, 0.667969, 0.539062, 0.617188, 0.65625,  0.667969, 0.625,
                 0.523438, 0.667969, 0.667969, 0.667969, 0.667969, 0.523438, 0.632812, 0.664062, 0.667969, 0.640625,
-                0.5625, 0.554688, 0.570312, 0.5625, 0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
-                0.570312, 0.5625, 0.570312, 0.5625, 0.570312, 0.570312, 0.585938, 0.570312, 0.59375, 0.578125,
-                0.570312, 0.5625, 0.578125, 0.570312, 0.578125, 0.578125, 0.59375, 0.578125, 0.609375, 0.585938,
-                0.578125, 0.5625, 0.585938, 0.570312, 0.585938, 0.585938, 0.609375, 0.585938, 0.625, 0.601562,
-                0.585938, 0.570312, 0.601562, 0.578125, 0.601562, 0.601562, 0.625, 0.601562, 0.640625, 0.617188,
+                0.5625,   0.554688, 0.570312, 0.5625,   0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
+                0.570312, 0.5625,   0.570312, 0.5625,   0.570312, 0.570312, 0.585938, 0.570312, 0.59375,  0.578125,
+                0.570312, 0.5625,   0.578125, 0.570312, 0.578125, 0.578125, 0.59375,  0.578125, 0.609375, 0.585938,
+                0.578125, 0.5625,   0.585938, 0.570312, 0.585938, 0.585938, 0.609375, 0.585938, 0.625,    0.601562,
+                0.585938, 0.570312, 0.601562, 0.578125, 0.601562, 0.601562, 0.625,    0.601562, 0.640625, 0.617188,
                 0.601562, 0.570312, 0.617188, 0.585938, 0.617188, 0.617188, 0.640625, 0.617188, 0.648438, 0.632812,
-                0.617188, 0.578125, 0.632812, 0.601562, 0.632812, 0.632812, 0.65625, 0.632812, 0.664062, 0.648438,
+                0.617188, 0.578125, 0.632812, 0.601562, 0.632812, 0.632812, 0.65625,  0.632812, 0.664062, 0.648438,
                 0.632812, 0.585938, 0.648438, 0.617188, 0.648438, 0.648438, 0.664062, 0.648438, 0.667969, 0.65625,
-                0.648438, 0.601562, 0.664062, 0.632812, 0.664062, 0.65625, 0.667969, 0.664062, 0.667969, 0.664062,
-                0.65625, 0.617188, 0.664062, 0.648438, 0.664062, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969,
-                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625, 0.570312, 0.578125, 0.5625, 0.554688,
+                0.648438, 0.601562, 0.664062, 0.632812, 0.664062, 0.65625,  0.667969, 0.664062, 0.667969, 0.664062,
+                0.65625,  0.617188, 0.664062, 0.648438, 0.664062, 0.664062, 0.667969, 0.664062, 0.667969, 0.667969,
+                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625,   0.570312, 0.578125, 0.5625,   0.554688,
                 0.585938, 0.570312, 0.570312, 0.585938, 0.578125, 0.570312, 0.578125, 0.585938, 0.570312, 0.554688,
-                0.601562, 0.585938, 0.578125, 0.59375, 0.585938, 0.570312, 0.585938, 0.601562, 0.570312, 0.554688,
-                0.617188, 0.59375, 0.585938, 0.609375, 0.601562, 0.578125, 0.59375, 0.617188, 0.578125, 0.554688,
-                0.632812, 0.601562, 0.59375, 0.625, 0.617188, 0.585938, 0.609375, 0.632812, 0.585938, 0.554688,
-                0.648438, 0.617188, 0.609375, 0.640625, 0.632812, 0.59375, 0.625, 0.648438, 0.59375, 0.554688,
-                0.65625, 0.632812, 0.625, 0.65625, 0.648438, 0.609375, 0.640625, 0.664062, 0.609375, 0.554688,
-                0.664062, 0.648438, 0.640625, 0.664062, 0.65625, 0.625, 0.65625, 0.664062, 0.625, 0.554688,
-                0.667969, 0.664062, 0.65625, 0.667969, 0.664062, 0.640625, 0.664062, 0.667969, 0.640625, 0.5625,
-                0.667969, 0.667969, 0.664062, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969, 0.65625, 0.5625,
-                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625, 0.585938, 0.5625,
-                0.578125, 0.585938, 0.59375, 0.570312, 0.578125, 0.578125, 0.578125, 0.5625, 0.59375, 0.5625,
-                0.585938, 0.59375, 0.601562, 0.585938, 0.585938, 0.585938, 0.585938, 0.5625, 0.609375, 0.570312,
-                0.601562, 0.609375, 0.617188, 0.59375, 0.59375, 0.601562, 0.59375, 0.570312, 0.625, 0.570312,
-                0.617188, 0.625, 0.632812, 0.601562, 0.609375, 0.617188, 0.609375, 0.570312, 0.640625, 0.585938,
-                0.632812, 0.640625, 0.648438, 0.617188, 0.625, 0.632812, 0.625, 0.585938, 0.648438, 0.59375,
-                0.648438, 0.65625, 0.664062, 0.632812, 0.640625, 0.648438, 0.640625, 0.59375, 0.664062, 0.601562,
-                0.65625, 0.664062, 0.667969, 0.648438, 0.65625, 0.65625, 0.648438, 0.601562, 0.667969, 0.617188,
+                0.601562, 0.585938, 0.578125, 0.59375,  0.585938, 0.570312, 0.585938, 0.601562, 0.570312, 0.554688,
+                0.617188, 0.59375,  0.585938, 0.609375, 0.601562, 0.578125, 0.59375,  0.617188, 0.578125, 0.554688,
+                0.632812, 0.601562, 0.59375,  0.625,    0.617188, 0.585938, 0.609375, 0.632812, 0.585938, 0.554688,
+                0.648438, 0.617188, 0.609375, 0.640625, 0.632812, 0.59375,  0.625,    0.648438, 0.59375,  0.554688,
+                0.65625,  0.632812, 0.625,    0.65625,  0.648438, 0.609375, 0.640625, 0.664062, 0.609375, 0.554688,
+                0.664062, 0.648438, 0.640625, 0.664062, 0.65625,  0.625,    0.65625,  0.664062, 0.625,    0.554688,
+                0.667969, 0.664062, 0.65625,  0.667969, 0.664062, 0.640625, 0.664062, 0.667969, 0.640625, 0.5625,
+                0.667969, 0.667969, 0.664062, 0.667969, 0.667969, 0.648438, 0.667969, 0.667969, 0.65625,  0.5625,
+                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625,   0.585938, 0.5625,
+                0.578125, 0.585938, 0.59375,  0.570312, 0.578125, 0.578125, 0.578125, 0.5625,   0.59375,  0.5625,
+                0.585938, 0.59375,  0.601562, 0.585938, 0.585938, 0.585938, 0.585938, 0.5625,   0.609375, 0.570312,
+                0.601562, 0.609375, 0.617188, 0.59375,  0.59375,  0.601562, 0.59375,  0.570312, 0.625,    0.570312,
+                0.617188, 0.625,    0.632812, 0.601562, 0.609375, 0.617188, 0.609375, 0.570312, 0.640625, 0.585938,
+                0.632812, 0.640625, 0.648438, 0.617188, 0.625,    0.632812, 0.625,    0.585938, 0.648438, 0.59375,
+                0.648438, 0.65625,  0.664062, 0.632812, 0.640625, 0.648438, 0.640625, 0.59375,  0.664062, 0.601562,
+                0.65625,  0.664062, 0.667969, 0.648438, 0.65625,  0.65625,  0.648438, 0.601562, 0.667969, 0.617188,
                 0.664062, 0.667969, 0.667969, 0.664062, 0.664062, 0.664062, 0.664062, 0.617188, 0.667969, 0.632812,
                 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.632812, 0.667969, 0.648438,
                 0.578125, 0.578125, 0.578125, 0.585938, 0.578125, 0.570312, 0.554688, 0.578125, 0.570312, 0.585938,
-                0.585938, 0.585938, 0.585938, 0.59375, 0.585938, 0.570312, 0.5625, 0.585938, 0.578125, 0.59375,
-                0.601562, 0.601562, 0.59375, 0.609375, 0.601562, 0.578125, 0.5625, 0.59375, 0.585938, 0.609375,
-                0.617188, 0.617188, 0.609375, 0.625, 0.617188, 0.585938, 0.5625, 0.609375, 0.601562, 0.625,
-                0.632812, 0.632812, 0.625, 0.640625, 0.632812, 0.59375, 0.570312, 0.625, 0.617188, 0.640625,
-                0.648438, 0.648438, 0.640625, 0.65625, 0.648438, 0.609375, 0.570312, 0.640625, 0.632812, 0.65625,
-                0.65625, 0.65625, 0.65625, 0.664062, 0.65625, 0.625, 0.578125, 0.65625, 0.648438, 0.664062,
-                0.664062, 0.664062, 0.664062, 0.667969, 0.664062, 0.640625, 0.585938, 0.664062, 0.65625, 0.667969,
-                0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625, 0.601562, 0.667969, 0.664062, 0.667969,
+                0.585938, 0.585938, 0.585938, 0.59375,  0.585938, 0.570312, 0.5625,   0.585938, 0.578125, 0.59375,
+                0.601562, 0.601562, 0.59375,  0.609375, 0.601562, 0.578125, 0.5625,   0.59375,  0.585938, 0.609375,
+                0.617188, 0.617188, 0.609375, 0.625,    0.617188, 0.585938, 0.5625,   0.609375, 0.601562, 0.625,
+                0.632812, 0.632812, 0.625,    0.640625, 0.632812, 0.59375,  0.570312, 0.625,    0.617188, 0.640625,
+                0.648438, 0.648438, 0.640625, 0.65625,  0.648438, 0.609375, 0.570312, 0.640625, 0.632812, 0.65625,
+                0.65625,  0.65625,  0.65625,  0.664062, 0.65625,  0.625,    0.578125, 0.65625,  0.648438, 0.664062,
+                0.664062, 0.664062, 0.664062, 0.667969, 0.664062, 0.640625, 0.585938, 0.664062, 0.65625,  0.667969,
+                0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.65625,  0.601562, 0.667969, 0.664062, 0.667969,
                 0.667969, 0.667969, 0.667969, 0.667969, 0.667969, 0.664062, 0.617188, 0.667969, 0.667969, 0.667969},
-            std::vector<T>{
-                0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625, 0.570312, 0.585938, 0.5625,
-                0.5625, 0.554688, 0.570312, 0.5625, 0.570312, 0.570312, 0.578125, 0.570312, 0.585938, 0.570312,
-                0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625, 0.570312, 0.578125, 0.5625, 0.554688,
-                0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312, 0.570312, 0.5625, 0.585938, 0.5625,
-                0.578125, 0.578125, 0.578125, 0.585938, 0.578125, 0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
-            std::vector<T>{
-                1.20312, 1.27344, 1.375, 1.32031, 1.35156, 1.20312, 1.22656, 1.25781, 1.375, 1.23438,
-                1.25, 1.21875, 1.26562, 1.23438, 1.26562, 1.26562, 1.32031, 1.26562, 1.35156, 1.28906,
-                1.34375, 1.27344, 1.25781, 1.32031, 1.28906, 1.24219, 1.28125, 1.34375, 1.24219, 1.21875,
-                1.28906, 1.32031, 1.35156, 1.27344, 1.28125, 1.29688, 1.28125, 1.22656, 1.35156, 1.23438,
-                1.32812, 1.32812, 1.32031, 1.35938, 1.32812, 1.25781, 1.21875, 1.32031, 1.28906, 1.375}),
+            std::vector<T>{0.554688, 0.570312, 0.585938, 0.578125, 0.585938, 0.554688, 0.5625,   0.570312, 0.585938,
+                           0.5625,   0.5625,   0.554688, 0.570312, 0.5625,   0.570312, 0.570312, 0.578125, 0.570312,
+                           0.585938, 0.570312, 0.578125, 0.570312, 0.570312, 0.578125, 0.570312, 0.5625,   0.570312,
+                           0.578125, 0.5625,   0.554688, 0.570312, 0.578125, 0.585938, 0.570312, 0.570312, 0.570312,
+                           0.570312, 0.5625,   0.585938, 0.5625,   0.578125, 0.578125, 0.578125, 0.585938, 0.578125,
+                           0.570312, 0.554688, 0.578125, 0.570312, 0.585938},
+            std::vector<T>{1.20312, 1.27344, 1.375,   1.32031, 1.35156, 1.20312, 1.22656, 1.25781, 1.375,   1.23438,
+                           1.25,    1.21875, 1.26562, 1.23438, 1.26562, 1.26562, 1.32031, 1.26562, 1.35156, 1.28906,
+                           1.34375, 1.27344, 1.25781, 1.32031, 1.28906, 1.24219, 1.28125, 1.34375, 1.24219, 1.21875,
+                           1.28906, 1.32031, 1.35156, 1.27344, 1.28125, 1.29688, 1.28125, 1.22656, 1.35156, 1.23438,
+                           1.32812, 1.32812, 1.32031, 1.35938, 1.32812, 1.25781, 1.21875, 1.32031, 1.28906, 1.375}),
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.7f, ov::op::RecurrentSequenceDirection::FORWARD, TensorIteratorBodyType::GRU,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            ov::op::RecurrentSequenceDirection::FORWARD,
+            TensorIteratorBodyType::GRU,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
             std::vector<T>{0},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 10},
-            std::vector<T>{
-                0.867188, 3.375, 6.875, 5.1875, 6.4375, 0.867188, 1.64062, 2.65625, 6.875, 1.75,
-                0.777344, 2.4375, 4.75, 3.65625, 4.5, 0.777344, 1.29688, 1.96875, 4.75, 1.375,
-                0.714844, 1.82812, 3.375, 2.625, 3.1875, 0.714844, 1.0625, 1.51562, 3.375, 1.11719,
-                0.675781, 1.42188, 2.4375, 1.95312, 2.3125, 0.675781, 0.910156, 1.21875, 2.4375, 0.945312,
-                0.648438, 1.14844, 1.82812, 1.5, 1.75, 0.648438, 0.808594, 1.01562, 1.82812, 0.832031,
-                0.632812, 0.964844, 1.42188, 1.20312, 1.375, 0.632812, 0.738281, 0.878906, 1.42188, 0.753906,
-                0.621094, 0.839844, 1.14844, 1, 1.11719, 0.621094, 0.691406, 0.785156, 1.14844, 0.699219,
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   10},
+            std::vector<T>{
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   10},
+            std::vector<T>{1,     4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,     2.3125,
+                           3.125, 1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,  5.84375,
+                           8.625, 4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625, 10},
+            std::vector<T>{
+                0.867188, 3.375,    6.875,    5.1875,   6.4375,   0.867188, 1.64062,  2.65625,  6.875,    1.75,
+                0.777344, 2.4375,   4.75,     3.65625,  4.5,      0.777344, 1.29688,  1.96875,  4.75,     1.375,
+                0.714844, 1.82812,  3.375,    2.625,    3.1875,   0.714844, 1.0625,   1.51562,  3.375,    1.11719,
+                0.675781, 1.42188,  2.4375,   1.95312,  2.3125,   0.675781, 0.910156, 1.21875,  2.4375,   0.945312,
+                0.648438, 1.14844,  1.82812,  1.5,      1.75,     0.648438, 0.808594, 1.01562,  1.82812,  0.832031,
+                0.632812, 0.964844, 1.42188,  1.20312,  1.375,    0.632812, 0.738281, 0.878906, 1.42188,  0.753906,
+                0.621094, 0.839844, 1.14844,  1,        1.11719,  0.621094, 0.691406, 0.785156, 1.14844,  0.699219,
                 0.613281, 0.761719, 0.964844, 0.867188, 0.945312, 0.613281, 0.660156, 0.722656, 0.964844, 0.664062,
                 0.609375, 0.707031, 0.839844, 0.777344, 0.832031, 0.609375, 0.640625, 0.679688, 0.839844, 0.640625,
-                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625, 0.652344, 0.761719, 0.625,
-                2.28125, 1.42188, 3.25, 1.98438, 3.1875, 2.9375, 4.875, 3.25, 6.4375, 4.09375,
-                1.71875, 1.14844, 2.34375, 1.53125, 2.3125, 2.15625, 3.4375, 2.34375, 4.5, 2.9375,
-                1.34375, 0.964844, 1.76562, 1.21875, 1.75, 1.64062, 2.46875, 1.76562, 3.1875, 2.15625,
-                1.09375, 0.839844, 1.375, 1.01562, 1.375, 1.29688, 1.84375, 1.375, 2.3125, 1.64062,
-                0.929688, 0.761719, 1.11719, 0.878906, 1.11719, 1.0625, 1.4375, 1.11719, 1.75, 1.29688,
-                0.816406, 0.707031, 0.945312, 0.785156, 0.945312, 0.910156, 1.15625, 0.945312, 1.375, 1.0625,
-                0.746094, 0.671875, 0.832031, 0.722656, 0.832031, 0.808594, 0.972656, 0.832031, 1.11719, 0.910156,
+                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625,    0.652344, 0.761719, 0.625,
+                2.28125,  1.42188,  3.25,     1.98438,  3.1875,   2.9375,   4.875,    3.25,     6.4375,   4.09375,
+                1.71875,  1.14844,  2.34375,  1.53125,  2.3125,   2.15625,  3.4375,   2.34375,  4.5,      2.9375,
+                1.34375,  0.964844, 1.76562,  1.21875,  1.75,     1.64062,  2.46875,  1.76562,  3.1875,   2.15625,
+                1.09375,  0.839844, 1.375,    1.01562,  1.375,    1.29688,  1.84375,  1.375,    2.3125,   1.64062,
+                0.929688, 0.761719, 1.11719,  0.878906, 1.11719,  1.0625,   1.4375,   1.11719,  1.75,     1.29688,
+                0.816406, 0.707031, 0.945312, 0.785156, 0.945312, 0.910156, 1.15625,  0.945312, 1.375,    1.0625,
+                0.746094, 0.671875, 0.832031, 0.722656, 0.832031, 0.808594, 0.972656, 0.832031, 1.11719,  0.910156,
                 0.695312, 0.648438, 0.753906, 0.679688, 0.753906, 0.738281, 0.847656, 0.753906, 0.945312, 0.808594,
                 0.664062, 0.632812, 0.699219, 0.652344, 0.699219, 0.691406, 0.761719, 0.699219, 0.832031, 0.738281,
                 0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062, 0.753906, 0.691406,
-                5.9375, 3.375, 2.71875, 4.9375, 4, 2.09375, 3.53125, 6.125, 2.21875, 1.03125,
-                4.15625, 2.4375, 2, 3.5, 2.875, 1.59375, 2.53125, 4.25, 1.6875, 0.886719,
-                2.96875, 1.82812, 1.53125, 2.53125, 2.125, 1.26562, 1.89062, 3.03125, 1.32812, 0.792969,
-                2.1875, 1.42188, 1.21875, 1.89062, 1.625, 1.04688, 1.46875, 2.21875, 1.08594, 0.730469,
-                1.65625, 1.14844, 1.01562, 1.46875, 1.28125, 0.898438, 1.17969, 1.6875, 0.925781, 0.6875,
-                1.3125, 0.964844, 0.878906, 1.17969, 1.05469, 0.800781, 0.988281, 1.32812, 0.816406, 0.65625,
-                1.07812, 0.839844, 0.785156, 0.988281, 0.902344, 0.730469, 0.855469, 1.08594, 0.746094, 0.636719,
-                0.917969, 0.761719, 0.722656, 0.855469, 0.800781, 0.6875, 0.769531, 0.925781, 0.695312, 0.625,
-                0.808594, 0.707031, 0.679688, 0.769531, 0.730469, 0.65625, 0.714844, 0.816406, 0.664062, 0.617188,
-                0.738281, 0.671875, 0.652344, 0.714844, 0.6875, 0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
-                4.0625, 4.875, 6.375, 3.375, 3.625, 4.1875, 3.4375, 1.70312, 6.5, 2.0625,
-                2.90625, 3.4375, 4.4375, 2.4375, 2.59375, 3, 2.46875, 1.34375, 4.5, 1.57812,
-                2.125, 2.46875, 3.15625, 1.82812, 1.9375, 2.1875, 1.84375, 1.09375, 3.1875, 1.25,
-                1.625, 1.84375, 2.28125, 1.42188, 1.5, 1.65625, 1.4375, 0.929688, 2.3125, 1.03125,
-                1.28125, 1.4375, 1.71875, 1.14844, 1.20312, 1.3125, 1.15625, 0.816406, 1.75, 0.886719,
-                1.05469, 1.15625, 1.34375, 0.964844, 1, 1.07812, 0.972656, 0.746094, 1.375, 0.792969,
-                0.902344, 0.972656, 1.09375, 0.839844, 0.867188, 0.917969, 0.847656, 0.695312, 1.11719, 0.730469,
+                5.9375,   3.375,    2.71875,  4.9375,   4,        2.09375,  3.53125,  6.125,    2.21875,  1.03125,
+                4.15625,  2.4375,   2,        3.5,      2.875,    1.59375,  2.53125,  4.25,     1.6875,   0.886719,
+                2.96875,  1.82812,  1.53125,  2.53125,  2.125,    1.26562,  1.89062,  3.03125,  1.32812,  0.792969,
+                2.1875,   1.42188,  1.21875,  1.89062,  1.625,    1.04688,  1.46875,  2.21875,  1.08594,  0.730469,
+                1.65625,  1.14844,  1.01562,  1.46875,  1.28125,  0.898438, 1.17969,  1.6875,   0.925781, 0.6875,
+                1.3125,   0.964844, 0.878906, 1.17969,  1.05469,  0.800781, 0.988281, 1.32812,  0.816406, 0.65625,
+                1.07812,  0.839844, 0.785156, 0.988281, 0.902344, 0.730469, 0.855469, 1.08594,  0.746094, 0.636719,
+                0.917969, 0.761719, 0.722656, 0.855469, 0.800781, 0.6875,   0.769531, 0.925781, 0.695312, 0.625,
+                0.808594, 0.707031, 0.679688, 0.769531, 0.730469, 0.65625,  0.714844, 0.816406, 0.664062, 0.617188,
+                0.738281, 0.671875, 0.652344, 0.714844, 0.6875,   0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
+                4.0625,   4.875,    6.375,    3.375,    3.625,    4.1875,   3.4375,   1.70312,  6.5,      2.0625,
+                2.90625,  3.4375,   4.4375,   2.4375,   2.59375,  3,        2.46875,  1.34375,  4.5,      1.57812,
+                2.125,    2.46875,  3.15625,  1.82812,  1.9375,   2.1875,   1.84375,  1.09375,  3.1875,   1.25,
+                1.625,    1.84375,  2.28125,  1.42188,  1.5,      1.65625,  1.4375,   0.929688, 2.3125,   1.03125,
+                1.28125,  1.4375,   1.71875,  1.14844,  1.20312,  1.3125,   1.15625,  0.816406, 1.75,     0.886719,
+                1.05469,  1.15625,  1.34375,  0.964844, 1,        1.07812,  0.972656, 0.746094, 1.375,    0.792969,
+                0.902344, 0.972656, 1.09375,  0.839844, 0.867188, 0.917969, 0.847656, 0.695312, 1.11719,  0.730469,
                 0.800781, 0.847656, 0.929688, 0.761719, 0.777344, 0.808594, 0.761719, 0.664062, 0.945312, 0.6875,
                 0.730469, 0.761719, 0.816406, 0.707031, 0.714844, 0.738281, 0.707031, 0.640625, 0.832031, 0.65625,
-                0.6875, 0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625, 0.753906, 0.636719,
-                5.53125, 5.65625, 5.125, 6.65625, 5.6875, 2.71875, 1.42188, 5, 3.96875, 6.875,
-                3.875, 3.96875, 3.625, 4.625, 4, 2, 1.14844, 3.53125, 2.84375, 4.75,
-                2.78125, 2.84375, 2.59375, 3.28125, 2.875, 1.53125, 0.964844, 2.53125, 2.09375, 3.375,
-                2.0625, 2.09375, 1.9375, 2.375, 2.125, 1.21875, 0.839844, 1.89062, 1.59375, 2.4375,
-                1.57812, 1.59375, 1.5, 1.78125, 1.625, 1.01562, 0.761719, 1.46875, 1.26562, 1.82812,
-                1.25, 1.26562, 1.20312, 1.39062, 1.28125, 0.878906, 0.707031, 1.17969, 1.04688, 1.42188,
-                1.03125, 1.04688, 1, 1.125, 1.05469, 0.785156, 0.671875, 0.988281, 0.898438, 1.14844,
+                0.6875,   0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625,    0.753906, 0.636719,
+                5.53125,  5.65625,  5.125,    6.65625,  5.6875,   2.71875,  1.42188,  5,        3.96875,  6.875,
+                3.875,    3.96875,  3.625,    4.625,    4,        2,        1.14844,  3.53125,  2.84375,  4.75,
+                2.78125,  2.84375,  2.59375,  3.28125,  2.875,    1.53125,  0.964844, 2.53125,  2.09375,  3.375,
+                2.0625,   2.09375,  1.9375,   2.375,    2.125,    1.21875,  0.839844, 1.89062,  1.59375,  2.4375,
+                1.57812,  1.59375,  1.5,      1.78125,  1.625,    1.01562,  0.761719, 1.46875,  1.26562,  1.82812,
+                1.25,     1.26562,  1.20312,  1.39062,  1.28125,  0.878906, 0.707031, 1.17969,  1.04688,  1.42188,
+                1.03125,  1.04688,  1,        1.125,    1.05469,  0.785156, 0.671875, 0.988281, 0.898438, 1.14844,
                 0.886719, 0.898438, 0.867188, 0.949219, 0.902344, 0.722656, 0.648438, 0.855469, 0.800781, 0.964844,
                 0.792969, 0.800781, 0.777344, 0.832031, 0.800781, 0.679688, 0.632812, 0.769531, 0.730469, 0.839844,
-                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875, 0.761719},
-            std::vector<T>{
-                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625, 0.652344, 0.761719, 0.625,
-                0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062, 0.753906, 0.691406,
-                0.738281, 0.671875, 0.652344, 0.714844, 0.6875, 0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
-                0.6875, 0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625, 0.753906, 0.636719,
-                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875, 0.761719},
+                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875,   0.761719},
+            std::vector<T>{0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625,    0.652344, 0.761719,
+                           0.625,    0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062,
+                           0.753906, 0.691406, 0.738281, 0.671875, 0.652344, 0.714844, 0.6875,   0.636719, 0.675781,
+                           0.746094, 0.640625, 0.609375, 0.6875,   0.707031, 0.746094, 0.671875, 0.675781, 0.691406,
+                           0.671875, 0.625,    0.753906, 0.636719, 0.730469, 0.730469, 0.714844, 0.753906, 0.730469,
+                           0.652344, 0.621094, 0.714844, 0.6875,   0.761719},
             std::vector<T>{0}),
         TensorIteratorStaticParams(
             std::make_shared<TIStaticInputs>(),
-            5, 10, 10, 10,
-            0.7f, ov::op::RecurrentSequenceDirection::REVERSE, TensorIteratorBodyType::GRU,
+            5,
+            10,
+            10,
+            10,
+            0.7f,
+            ov::op::RecurrentSequenceDirection::REVERSE,
+            TensorIteratorBodyType::GRU,
             ET,
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 1.10938,
-                2.15625, 1.64062, 3.65625, 9.6875, 4.25, 6.125, 3.46875, 2.82812, 1.66406, 3.26562,
-                2.375, 7.6875, 2.45312, 2.75, 9.4375, 6.21875, 4.3125, 9.75, 1.45312, 8.625,
-                7.65625, 3.15625, 3.6875, 5.4375, 2.84375, 6.5625, 9.8125, 8.4375, 9, 2.40625,
-                7.8125, 1.16406, 6.875, 1.625, 1.35938, 5.375, 8.3125, 6.4375, 7.875, 6.125,
-                5.09375, 3.84375, 5.78125, 9.875, 1.98438, 6.1875, 2.3125, 4.40625, 5.5625, 5.9375,
-                2.9375, 7.6875, 9.25, 7, 5.15625, 3.375, 2.1875, 1.59375, 7.875, 4.3125,
-                2.90625, 6.65625, 1.67188, 2.89062, 1.85938, 7.75, 2.45312, 1.59375, 4.1875, 3.34375,
-                1.85938, 8.25, 2.28125, 2.73438, 9.375, 6.75, 6.1875, 5.71875, 8.5, 9.3125,
-                6.625, 3.375, 3.90625, 1.59375, 7.5625, 7.625, 5.6875, 7.9375, 7.625, 9.125,
-                2.48438, 9.375, 7.1875, 1.125, 4.8125, 3.09375, 7.5625, 6.5625, 7.8125, 9.5,
-                4.5625, 9.5, 9.3125, 6, 2.82812, 9.25, 1.07031, 6.75, 9.3125, 4.5,
-                3.65625, 5.375, 2.5, 6.4375, 1.21875, 5.9375, 5.0625, 9.3125, 8.25, 9.25,
-                4.3125, 4.5625, 6.46875, 9.625, 1.3125, 2.5625, 4.1875, 2.125, 1.70312, 2.21875,
-                7.25, 5.5625, 1.10938, 1.1875, 5.125, 9.5, 9.625, 8.4375, 4, 1.13281,
-                5.25, 2.57812, 1.94531, 3.98438, 5.5, 2.17188, 9, 8.25, 5.8125, 4.09375,
-                3.53125, 9.4375, 4.1875, 6.25, 9.0625, 8.875, 3.17188, 8.625, 1.21875, 9.125,
-                9.6875, 5.125, 4.875, 5.90625, 4.125, 8.125, 6.1875, 3.5625, 2.125, 5.40625,
-                9.5, 6.375, 3.8125, 1.14062, 9.5625, 6.3125, 2.96875, 4.875, 3.23438, 8.25,
-                8.75, 3.84375, 3.125, 9, 8.3125, 6.1875, 5.875, 2.65625, 2.71875, 8.0625,
-                6.3125, 6.5, 1.42969, 1.48438, 1.14062, 4.78125, 1.44531, 7.125, 4.59375, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 10},
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   1.10938, 2.15625, 1.64062, 3.65625, 9.6875,  4.25,    6.125,   3.46875, 2.82812,
+                1.66406, 3.26562, 2.375,   7.6875,  2.45312, 2.75,    9.4375,  6.21875, 4.3125,  9.75,    1.45312,
+                8.625,   7.65625, 3.15625, 3.6875,  5.4375,  2.84375, 6.5625,  9.8125,  8.4375,  9,       2.40625,
+                7.8125,  1.16406, 6.875,   1.625,   1.35938, 5.375,   8.3125,  6.4375,  7.875,   6.125,   5.09375,
+                3.84375, 5.78125, 9.875,   1.98438, 6.1875,  2.3125,  4.40625, 5.5625,  5.9375,  2.9375,  7.6875,
+                9.25,    7,       5.15625, 3.375,   2.1875,  1.59375, 7.875,   4.3125,  2.90625, 6.65625, 1.67188,
+                2.89062, 1.85938, 7.75,    2.45312, 1.59375, 4.1875,  3.34375, 1.85938, 8.25,    2.28125, 2.73438,
+                9.375,   6.75,    6.1875,  5.71875, 8.5,     9.3125,  6.625,   3.375,   3.90625, 1.59375, 7.5625,
+                7.625,   5.6875,  7.9375,  7.625,   9.125,   2.48438, 9.375,   7.1875,  1.125,   4.8125,  3.09375,
+                7.5625,  6.5625,  7.8125,  9.5,     4.5625,  9.5,     9.3125,  6,       2.82812, 9.25,    1.07031,
+                6.75,    9.3125,  4.5,     3.65625, 5.375,   2.5,     6.4375,  1.21875, 5.9375,  5.0625,  9.3125,
+                8.25,    9.25,    4.3125,  4.5625,  6.46875, 9.625,   1.3125,  2.5625,  4.1875,  2.125,   1.70312,
+                2.21875, 7.25,    5.5625,  1.10938, 1.1875,  5.125,   9.5,     9.625,   8.4375,  4,       1.13281,
+                5.25,    2.57812, 1.94531, 3.98438, 5.5,     2.17188, 9,       8.25,    5.8125,  4.09375, 3.53125,
+                9.4375,  4.1875,  6.25,    9.0625,  8.875,   3.17188, 8.625,   1.21875, 9.125,   9.6875,  5.125,
+                4.875,   5.90625, 4.125,   8.125,   6.1875,  3.5625,  2.125,   5.40625, 9.5,     6.375,   3.8125,
+                1.14062, 9.5625,  6.3125,  2.96875, 4.875,   3.23438, 8.25,    8.75,    3.84375, 3.125,   9,
+                8.3125,  6.1875,  5.875,   2.65625, 2.71875, 8.0625,  6.3125,  6.5,     1.42969, 1.48438, 1.14062,
+                4.78125, 1.44531, 7.125,   4.59375, 10},
+            std::vector<T>{1,      4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,
+                           3.125,  1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375,
+                           8.625,  4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,
+                           5.8125, 7.03125, 9.25,   4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125,
+                           8,      8.1875,  7.4375, 9.6875,  8.25,    3.8125,  1.82812, 7.21875, 5.65625, 10},
             std::vector<T>{0},
             std::vector<int64_t>{10, 10, 10, 10, 10},
             std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 1.25,
-                5.8125, 7.03125, 9.25, 4.75, 5.125, 6, 4.875, 2.25, 9.4375, 2.78125,
-                8, 8.1875, 7.4375, 9.6875, 8.25, 3.8125, 1.82812, 7.21875, 5.65625, 8.875,
-                8.75, 9, 8.4375, 1.76562, 8.4375, 1.34375, 3.45312, 2.53125, 1.53125, 8.875,
-                7.03125, 1.88281, 6.3125, 4.78125, 7.03125, 9.625, 4.6875, 5.8125, 2.78125, 7.21875,
-                3.59375, 3.84375, 2.28125, 7.1875, 8, 8.5, 4.6875, 1.16406, 1.30469, 7.75,
-                6.625, 9.875, 6.9375, 7.71875, 3.6875, 3.53125, 5, 8.125, 3, 1.92188,
-                1.65625, 5, 5.21875, 9.125, 1.85938, 3.64062, 9.125, 3.59375, 2.0625, 2.15625,
-                5.71875, 1.17188, 1.75, 7.125, 9.25, 2.90625, 9.1875, 3.375, 3.6875, 5.4375,
-                6.25, 1.47656, 6.0625, 6.15625, 6.5, 2.3125, 9.625, 6.3125, 3.34375, 7.3125,
-                3.07812, 1.92188, 5.8125, 4.71875, 9.5, 7.25, 5.4375, 4.71875, 5.875, 1.45312,
-                7.875, 5.8125, 1.40625, 6.96875, 2.25, 5.625, 8.125, 9.5, 1.26562, 6.25,
-                8.9375, 9.125, 5.875, 2.23438, 5.03125, 2.25, 9, 8.25, 4.375, 4.5625,
-                5.84375, 2.48438, 6.875, 9.375, 4.25, 4.125, 6.125, 7.75, 6.75, 7.53125,
-                2.125, 8.9375, 7.1875, 6.625, 6.8125, 7.75, 4.1875, 4.125, 7.875, 3.42188,
-                4.1875, 9.0625, 7.75, 4.84375, 8.875, 9.625, 1.10156, 6.96875, 5.46875, 6.59375,
-                1.66406, 2.03125, 8.0625, 9.5, 1.57812, 5.0625, 4.1875, 6.1875, 9.5, 4.6875,
-                4.40625, 3.125, 7.875, 9.125, 7.9375, 6.15625, 3.71875, 1.02344, 7.9375, 6.5625,
-                2.375, 3.9375, 6.1875, 5.75, 1.07812, 9, 7.375, 4.1875, 5.25, 9.125,
-                7.875, 6.625, 5.1875, 1.14062, 3.40625, 9.375, 8.5, 7.1875, 5.9375, 10,
-                1.625, 2.54688, 5.25, 2.21875, 7.6875, 9.375, 2.71875, 7.25, 5.1875, 1.59375,
-                3.0625, 7.8125, 5.5625, 7.78125, 2.875, 9.25, 1.4375, 7.375, 5.65625, 2.125,
-                2.54688, 1.17188, 4.5625, 1.23438, 1.96875, 1.25, 5.5625, 3.21875, 1.92188, 8.75,
-                3.59375, 5.84375, 3.07812, 5.96875, 9.6875, 8.5625, 3.5, 2.125, 3.09375, 3.5,
-                1.82031, 6.25, 6.125, 9.75, 4.75, 6.0625, 4.3125, 1.16406, 8.3125, 8.1875,
-                3.59375, 3.09375, 7.4375, 8.25, 6.5, 4.5, 4.8125, 8.75, 7.75, 7.71875,
-                4.84375, 6, 4.84375, 2.21875, 4.25, 1.53906, 2.375, 2.09375, 9.375, 1.39844,
-                9.25, 1.96875, 8, 3.03125, 6.5625, 7.40625, 1.32031, 6.03125, 6.875, 10},
-            std::vector<T>{
-                1, 4.75, 10, 7.46875, 9.375, 1, 2.15625, 3.71875, 10, 2.3125,
-                3.125, 1.82812, 4.5625, 2.67188, 4.5, 4.125, 7, 4.5625, 9.375, 5.84375,
-                8.625, 4.75, 3.8125, 7.15625, 5.71875, 2.84375, 5, 8.875, 3.0625, 10},
-            std::vector<T>{
-                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625, 0.652344, 0.761719, 0.625,
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   10},
+            std::vector<T>{
+                1,       4.75,    10,      7.46875, 9.375,   1,       2.15625, 3.71875, 10,      2.3125,  3.125,
+                1.82812, 4.5625,  2.67188, 4.5,     4.125,   7,       4.5625,  9.375,   5.84375, 8.625,   4.75,
+                3.8125,  7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625,  1.25,    5.8125,  7.03125, 9.25,
+                4.75,    5.125,   6,       4.875,   2.25,    9.4375,  2.78125, 8,       8.1875,  7.4375,  9.6875,
+                8.25,    3.8125,  1.82812, 7.21875, 5.65625, 8.875,   8.75,    9,       8.4375,  1.76562, 8.4375,
+                1.34375, 3.45312, 2.53125, 1.53125, 8.875,   7.03125, 1.88281, 6.3125,  4.78125, 7.03125, 9.625,
+                4.6875,  5.8125,  2.78125, 7.21875, 3.59375, 3.84375, 2.28125, 7.1875,  8,       8.5,     4.6875,
+                1.16406, 1.30469, 7.75,    6.625,   9.875,   6.9375,  7.71875, 3.6875,  3.53125, 5,       8.125,
+                3,       1.92188, 1.65625, 5,       5.21875, 9.125,   1.85938, 3.64062, 9.125,   3.59375, 2.0625,
+                2.15625, 5.71875, 1.17188, 1.75,    7.125,   9.25,    2.90625, 9.1875,  3.375,   3.6875,  5.4375,
+                6.25,    1.47656, 6.0625,  6.15625, 6.5,     2.3125,  9.625,   6.3125,  3.34375, 7.3125,  3.07812,
+                1.92188, 5.8125,  4.71875, 9.5,     7.25,    5.4375,  4.71875, 5.875,   1.45312, 7.875,   5.8125,
+                1.40625, 6.96875, 2.25,    5.625,   8.125,   9.5,     1.26562, 6.25,    8.9375,  9.125,   5.875,
+                2.23438, 5.03125, 2.25,    9,       8.25,    4.375,   4.5625,  5.84375, 2.48438, 6.875,   9.375,
+                4.25,    4.125,   6.125,   7.75,    6.75,    7.53125, 2.125,   8.9375,  7.1875,  6.625,   6.8125,
+                7.75,    4.1875,  4.125,   7.875,   3.42188, 4.1875,  9.0625,  7.75,    4.84375, 8.875,   9.625,
+                1.10156, 6.96875, 5.46875, 6.59375, 1.66406, 2.03125, 8.0625,  9.5,     1.57812, 5.0625,  4.1875,
+                6.1875,  9.5,     4.6875,  4.40625, 3.125,   7.875,   9.125,   7.9375,  6.15625, 3.71875, 1.02344,
+                7.9375,  6.5625,  2.375,   3.9375,  6.1875,  5.75,    1.07812, 9,       7.375,   4.1875,  5.25,
+                9.125,   7.875,   6.625,   5.1875,  1.14062, 3.40625, 9.375,   8.5,     7.1875,  5.9375,  10,
+                1.625,   2.54688, 5.25,    2.21875, 7.6875,  9.375,   2.71875, 7.25,    5.1875,  1.59375, 3.0625,
+                7.8125,  5.5625,  7.78125, 2.875,   9.25,    1.4375,  7.375,   5.65625, 2.125,   2.54688, 1.17188,
+                4.5625,  1.23438, 1.96875, 1.25,    5.5625,  3.21875, 1.92188, 8.75,    3.59375, 5.84375, 3.07812,
+                5.96875, 9.6875,  8.5625,  3.5,     2.125,   3.09375, 3.5,     1.82031, 6.25,    6.125,   9.75,
+                4.75,    6.0625,  4.3125,  1.16406, 8.3125,  8.1875,  3.59375, 3.09375, 7.4375,  8.25,    6.5,
+                4.5,     4.8125,  8.75,    7.75,    7.71875, 4.84375, 6,       4.84375, 2.21875, 4.25,    1.53906,
+                2.375,   2.09375, 9.375,   1.39844, 9.25,    1.96875, 8,       3.03125, 6.5625,  7.40625, 1.32031,
+                6.03125, 6.875,   10},
+            std::vector<T>{1,     4.75,    10,     7.46875, 9.375,   1,       2.15625, 3.71875, 10,     2.3125,
+                           3.125, 1.82812, 4.5625, 2.67188, 4.5,     4.125,   7,       4.5625,  9.375,  5.84375,
+                           8.625, 4.75,    3.8125, 7.15625, 5.71875, 2.84375, 5,       8.875,   3.0625, 10},
+            std::vector<T>{
+                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625,    0.652344, 0.761719, 0.625,
                 0.609375, 0.707031, 0.839844, 0.777344, 0.832031, 0.609375, 0.640625, 0.679688, 0.839844, 0.640625,
                 0.613281, 0.761719, 0.964844, 0.867188, 0.945312, 0.613281, 0.660156, 0.722656, 0.964844, 0.664062,
-                0.621094, 0.839844, 1.14844, 1, 1.11719, 0.621094, 0.691406, 0.785156, 1.14844, 0.699219,
-                0.632812, 0.964844, 1.42188, 1.20312, 1.375, 0.632812, 0.738281, 0.878906, 1.42188, 0.753906,
-                0.648438, 1.14844, 1.82812, 1.5, 1.75, 0.648438, 0.808594, 1.01562, 1.82812, 0.832031,
-                0.675781, 1.42188, 2.4375, 1.95312, 2.3125, 0.675781, 0.910156, 1.21875, 2.4375, 0.945312,
-                0.714844, 1.82812, 3.375, 2.625, 3.1875, 0.714844, 1.0625, 1.51562, 3.375, 1.11719,
-                0.777344, 2.4375, 4.75, 3.65625, 4.5, 0.777344, 1.29688, 1.96875, 4.75, 1.375,
-                0.867188, 3.375, 6.875, 5.1875, 6.4375, 0.867188, 1.64062, 2.65625, 6.875, 1.75,
+                0.621094, 0.839844, 1.14844,  1,        1.11719,  0.621094, 0.691406, 0.785156, 1.14844,  0.699219,
+                0.632812, 0.964844, 1.42188,  1.20312,  1.375,    0.632812, 0.738281, 0.878906, 1.42188,  0.753906,
+                0.648438, 1.14844,  1.82812,  1.5,      1.75,     0.648438, 0.808594, 1.01562,  1.82812,  0.832031,
+                0.675781, 1.42188,  2.4375,   1.95312,  2.3125,   0.675781, 0.910156, 1.21875,  2.4375,   0.945312,
+                0.714844, 1.82812,  3.375,    2.625,    3.1875,   0.714844, 1.0625,   1.51562,  3.375,    1.11719,
+                0.777344, 2.4375,   4.75,     3.65625,  4.5,      0.777344, 1.29688,  1.96875,  4.75,     1.375,
+                0.867188, 3.375,    6.875,    5.1875,   6.4375,   0.867188, 1.64062,  2.65625,  6.875,    1.75,
                 0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062, 0.753906, 0.691406,
                 0.664062, 0.632812, 0.699219, 0.652344, 0.699219, 0.691406, 0.761719, 0.699219, 0.832031, 0.738281,
                 0.695312, 0.648438, 0.753906, 0.679688, 0.753906, 0.738281, 0.847656, 0.753906, 0.945312, 0.808594,
-                0.746094, 0.671875, 0.832031, 0.722656, 0.832031, 0.808594, 0.972656, 0.832031, 1.11719, 0.910156,
-                0.816406, 0.707031, 0.945312, 0.785156, 0.945312, 0.910156, 1.15625, 0.945312, 1.375, 1.0625,
-                0.929688, 0.761719, 1.11719, 0.878906, 1.11719, 1.0625, 1.4375, 1.11719, 1.75, 1.29688,
-                1.09375, 0.839844, 1.375, 1.01562, 1.375, 1.29688, 1.84375, 1.375, 2.3125, 1.64062,
-                1.34375, 0.964844, 1.76562, 1.21875, 1.75, 1.64062, 2.46875, 1.76562, 3.1875, 2.15625,
-                1.71875, 1.14844, 2.34375, 1.53125, 2.3125, 2.15625, 3.4375, 2.34375, 4.5, 2.9375,
-                2.28125, 1.42188, 3.25, 1.98438, 3.1875, 2.9375, 4.875, 3.25, 6.4375, 4.09375,
-                0.738281, 0.671875, 0.652344, 0.714844, 0.6875, 0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
-                0.808594, 0.707031, 0.679688, 0.769531, 0.730469, 0.65625, 0.714844, 0.816406, 0.664062, 0.617188,
-                0.917969, 0.761719, 0.722656, 0.855469, 0.800781, 0.6875, 0.769531, 0.925781, 0.695312, 0.625,
-                1.07812, 0.839844, 0.785156, 0.988281, 0.902344, 0.730469, 0.855469, 1.08594, 0.746094, 0.636719,
-                1.3125, 0.964844, 0.878906, 1.17969, 1.05469, 0.800781, 0.988281, 1.32812, 0.816406, 0.65625,
-                1.65625, 1.14844, 1.01562, 1.46875, 1.28125, 0.898438, 1.17969, 1.6875, 0.925781, 0.6875,
-                2.1875, 1.42188, 1.21875, 1.89062, 1.625, 1.04688, 1.46875, 2.21875, 1.08594, 0.730469,
-                2.96875, 1.82812, 1.53125, 2.53125, 2.125, 1.26562, 1.89062, 3.03125, 1.32812, 0.792969,
-                4.15625, 2.4375, 2, 3.5, 2.875, 1.59375, 2.53125, 4.25, 1.6875, 0.886719,
-                5.9375, 3.375, 2.71875, 4.9375, 4, 2.09375, 3.53125, 6.125, 2.21875, 1.03125,
-                0.6875, 0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625, 0.753906, 0.636719,
+                0.746094, 0.671875, 0.832031, 0.722656, 0.832031, 0.808594, 0.972656, 0.832031, 1.11719,  0.910156,
+                0.816406, 0.707031, 0.945312, 0.785156, 0.945312, 0.910156, 1.15625,  0.945312, 1.375,    1.0625,
+                0.929688, 0.761719, 1.11719,  0.878906, 1.11719,  1.0625,   1.4375,   1.11719,  1.75,     1.29688,
+                1.09375,  0.839844, 1.375,    1.01562,  1.375,    1.29688,  1.84375,  1.375,    2.3125,   1.64062,
+                1.34375,  0.964844, 1.76562,  1.21875,  1.75,     1.64062,  2.46875,  1.76562,  3.1875,   2.15625,
+                1.71875,  1.14844,  2.34375,  1.53125,  2.3125,   2.15625,  3.4375,   2.34375,  4.5,      2.9375,
+                2.28125,  1.42188,  3.25,     1.98438,  3.1875,   2.9375,   4.875,    3.25,     6.4375,   4.09375,
+                0.738281, 0.671875, 0.652344, 0.714844, 0.6875,   0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
+                0.808594, 0.707031, 0.679688, 0.769531, 0.730469, 0.65625,  0.714844, 0.816406, 0.664062, 0.617188,
+                0.917969, 0.761719, 0.722656, 0.855469, 0.800781, 0.6875,   0.769531, 0.925781, 0.695312, 0.625,
+                1.07812,  0.839844, 0.785156, 0.988281, 0.902344, 0.730469, 0.855469, 1.08594,  0.746094, 0.636719,
+                1.3125,   0.964844, 0.878906, 1.17969,  1.05469,  0.800781, 0.988281, 1.32812,  0.816406, 0.65625,
+                1.65625,  1.14844,  1.01562,  1.46875,  1.28125,  0.898438, 1.17969,  1.6875,   0.925781, 0.6875,
+                2.1875,   1.42188,  1.21875,  1.89062,  1.625,    1.04688,  1.46875,  2.21875,  1.08594,  0.730469,
+                2.96875,  1.82812,  1.53125,  2.53125,  2.125,    1.26562,  1.89062,  3.03125,  1.32812,  0.792969,
+                4.15625,  2.4375,   2,        3.5,      2.875,    1.59375,  2.53125,  4.25,     1.6875,   0.886719,
+                5.9375,   3.375,    2.71875,  4.9375,   4,        2.09375,  3.53125,  6.125,    2.21875,  1.03125,
+                0.6875,   0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625,    0.753906, 0.636719,
                 0.730469, 0.761719, 0.816406, 0.707031, 0.714844, 0.738281, 0.707031, 0.640625, 0.832031, 0.65625,
                 0.800781, 0.847656, 0.929688, 0.761719, 0.777344, 0.808594, 0.761719, 0.664062, 0.945312, 0.6875,
-                0.902344, 0.972656, 1.09375, 0.839844, 0.867188, 0.917969, 0.847656, 0.695312, 1.11719, 0.730469,
-                1.05469, 1.15625, 1.34375, 0.964844, 1, 1.07812, 0.972656, 0.746094, 1.375, 0.792969,
-                1.28125, 1.4375, 1.71875, 1.14844, 1.20312, 1.3125, 1.15625, 0.816406, 1.75, 0.886719,
-                1.625, 1.84375, 2.28125, 1.42188, 1.5, 1.65625, 1.4375, 0.929688, 2.3125, 1.03125,
-                2.125, 2.46875, 3.15625, 1.82812, 1.9375, 2.1875, 1.84375, 1.09375, 3.1875, 1.25,
-                2.90625, 3.4375, 4.4375, 2.4375, 2.59375, 3, 2.46875, 1.34375, 4.5, 1.57812,
-                4.0625, 4.875, 6.375, 3.375, 3.625, 4.1875, 3.4375, 1.70312, 6.5, 2.0625,
-                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875, 0.761719,
+                0.902344, 0.972656, 1.09375,  0.839844, 0.867188, 0.917969, 0.847656, 0.695312, 1.11719,  0.730469,
+                1.05469,  1.15625,  1.34375,  0.964844, 1,        1.07812,  0.972656, 0.746094, 1.375,    0.792969,
+                1.28125,  1.4375,   1.71875,  1.14844,  1.20312,  1.3125,   1.15625,  0.816406, 1.75,     0.886719,
+                1.625,    1.84375,  2.28125,  1.42188,  1.5,      1.65625,  1.4375,   0.929688, 2.3125,   1.03125,
+                2.125,    2.46875,  3.15625,  1.82812,  1.9375,   2.1875,   1.84375,  1.09375,  3.1875,   1.25,
+                2.90625,  3.4375,   4.4375,   2.4375,   2.59375,  3,        2.46875,  1.34375,  4.5,      1.57812,
+                4.0625,   4.875,    6.375,    3.375,    3.625,    4.1875,   3.4375,   1.70312,  6.5,      2.0625,
+                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875,   0.761719,
                 0.792969, 0.800781, 0.777344, 0.832031, 0.800781, 0.679688, 0.632812, 0.769531, 0.730469, 0.839844,
                 0.886719, 0.898438, 0.867188, 0.949219, 0.902344, 0.722656, 0.648438, 0.855469, 0.800781, 0.964844,
-                1.03125, 1.04688, 1, 1.125, 1.05469, 0.785156, 0.671875, 0.988281, 0.898438, 1.14844,
-                1.25, 1.26562, 1.20312, 1.39062, 1.28125, 0.878906, 0.707031, 1.17969, 1.04688, 1.42188,
-                1.57812, 1.59375, 1.5, 1.78125, 1.625, 1.01562, 0.761719, 1.46875, 1.26562, 1.82812,
-                2.0625, 2.09375, 1.9375, 2.375, 2.125, 1.21875, 0.839844, 1.89062, 1.59375, 2.4375,
-                2.78125, 2.84375, 2.59375, 3.28125, 2.875, 1.53125, 0.964844, 2.53125, 2.09375, 3.375,
-                3.875, 3.96875, 3.625, 4.625, 4, 2, 1.14844, 3.53125, 2.84375, 4.75,
-                5.53125, 5.65625, 5.125, 6.65625, 5.6875, 2.71875, 1.42188, 5, 3.96875, 6.875},
-            std::vector<T>{
-                0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625, 0.652344, 0.761719, 0.625,
-                0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062, 0.753906, 0.691406,
-                0.738281, 0.671875, 0.652344, 0.714844, 0.6875, 0.636719, 0.675781, 0.746094, 0.640625, 0.609375,
-                0.6875, 0.707031, 0.746094, 0.671875, 0.675781, 0.691406, 0.671875, 0.625, 0.753906, 0.636719,
-                0.730469, 0.730469, 0.714844, 0.753906, 0.730469, 0.652344, 0.621094, 0.714844, 0.6875, 0.761719},
+                1.03125,  1.04688,  1,        1.125,    1.05469,  0.785156, 0.671875, 0.988281, 0.898438, 1.14844,
+                1.25,     1.26562,  1.20312,  1.39062,  1.28125,  0.878906, 0.707031, 1.17969,  1.04688,  1.42188,
+                1.57812,  1.59375,  1.5,      1.78125,  1.625,    1.01562,  0.761719, 1.46875,  1.26562,  1.82812,
+                2.0625,   2.09375,  1.9375,   2.375,    2.125,    1.21875,  0.839844, 1.89062,  1.59375,  2.4375,
+                2.78125,  2.84375,  2.59375,  3.28125,  2.875,    1.53125,  0.964844, 2.53125,  2.09375,  3.375,
+                3.875,    3.96875,  3.625,    4.625,    4,        2,        1.14844,  3.53125,  2.84375,  4.75,
+                5.53125,  5.65625,  5.125,    6.65625,  5.6875,   2.71875,  1.42188,  5,        3.96875,  6.875},
+            std::vector<T>{0.605469, 0.671875, 0.761719, 0.714844, 0.753906, 0.605469, 0.625,    0.652344, 0.761719,
+                           0.625,    0.640625, 0.621094, 0.664062, 0.632812, 0.664062, 0.660156, 0.707031, 0.664062,
+                           0.753906, 0.691406, 0.738281, 0.671875, 0.652344, 0.714844, 0.6875,   0.636719, 0.675781,
+                           0.746094, 0.640625, 0.609375, 0.6875,   0.707031, 0.746094, 0.671875, 0.675781, 0.691406,
+                           0.671875, 0.625,    0.753906, 0.636719, 0.730469, 0.730469, 0.714844, 0.753906, 0.730469,
+                           0.652344, 0.621094, 0.714844, 0.6875,   0.761719},
             std::vector<T>{0}),
     };
     return params;
 }
 
 std::vector<TensorIteratorStaticParams> generateCombinedParams() {
-    const std::vector<std::vector<TensorIteratorStaticParams>> generatedParams {
+    const std::vector<std::vector<TensorIteratorStaticParams>> generatedParams{
         generateParams<ov::element::Type_t::f64>(),
         generateParams<ov::element::Type_t::f32>(),
         generateParams<ov::element::Type_t::f16>(),
@@ -2440,6 +2494,8 @@ std::vector<TensorIteratorStaticParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TensorIterator_With_Hardcoded_Refs, ReferenceTILayerStaticTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceTILayerStaticTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_TensorIterator_With_Hardcoded_Refs,
+                         ReferenceTILayerStaticTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceTILayerStaticTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/tile.cpp b/src/plugins/template/tests/functional/op_reference/tile.cpp
index f07d7c2198d34a..2a99ee45b11cb4 100644
--- a/src/plugins/template/tests/functional/op_reference/tile.cpp
+++ b/src/plugins/template/tests/functional/op_reference/tile.cpp
@@ -4,18 +4,22 @@
 
 #include <gtest/gtest.h>
 
-#include "openvino/opsets/opset1.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/opsets/opset1.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct TileParams {
-    TileParams(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& repeats,
-        const reference_tests::Tensor& expected, const std::string& testcaseName = "") :
-        A(A), repeats(repeats), expected(expected), testcaseName(testcaseName) {}
+    TileParams(const reference_tests::Tensor& A,
+               const reference_tests::Tensor& repeats,
+               const reference_tests::Tensor& expected,
+               const std::string& testcaseName = "")
+        : A(A),
+          repeats(repeats),
+          expected(expected),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor repeats;
@@ -52,8 +56,8 @@ class ReferenceTileTest : public testing::TestWithParam<TileParams>, public Comm
 private:
     static std::shared_ptr<Model> CreateFunction(const TileParams& params) {
         const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
-        const auto repeats = std::make_shared<opset1::Constant>(params.repeats.type, params.repeats.shape,
-                                                                params.repeats.data.data());
+        const auto repeats =
+            std::make_shared<opset1::Constant>(params.repeats.type, params.repeats.shape, params.repeats.data.data());
         const auto tile = std::make_shared<opset1::Tile>(A, repeats);
         const auto f = std::make_shared<Model>(NodeVector{tile}, ParameterVector{A});
         return f;
@@ -68,46 +72,33 @@ template <element::Type_t ET, element::Type_t ET_INT>
 std::vector<TileParams> generateParams() {
     using T = typename element_type_traits<ET>::value_type;
     using T_INT = typename element_type_traits<ET_INT>::value_type;
-    std::vector<TileParams> params {
-        TileParams(
-            reference_tests::Tensor(ET, {}, std::vector<T>{
-                1
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
-            reference_tests::Tensor(ET, {2}, std::vector<T>{
-                1, 1
-            }),
-            "tile_0d_to_1d_data_broadcast"),
-        TileParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-            }),
-            reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
-            reference_tests::Tensor(ET, {24}, std::vector<T>{
-                1, 2, 3, 4, 5, 6,
-                1, 2, 3, 4, 5, 6,
-                1, 2, 3, 4, 5, 6,
-                1, 2, 3, 4, 5, 6
-            }),
-            "tile_1d_to_1d_no_broadcast"),
-        TileParams(
-            reference_tests::Tensor(ET, {3}, std::vector<T>{
-                1, 2, 3
-            }),
-            reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{2, 2, 1}),
-            reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{
-                1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3
-            }),
-            "tile_1d_to_3d_data_broadcast"),
-        TileParams(
-            reference_tests::Tensor(ET, {2, 1, 3}, std::vector<T>{
-                1, 2, 3, 4, 5, 6
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
-            reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{
-                1, 2, 3, 1, 2, 3, 4, 5, 6, 4, 5, 6
-            }),
-            "tile_3d_to_3d_repeats_broadcast"),
+    std::vector<TileParams> params{
+        TileParams(reference_tests::Tensor(ET, {}, std::vector<T>{1}),
+                   reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{2}),
+                   reference_tests::Tensor(ET, {2}, std::vector<T>{1, 1}),
+                   "tile_0d_to_1d_data_broadcast"),
+        TileParams(reference_tests::Tensor(ET,
+                                           {6},
+                                           std::vector<T>{
+                                               1,
+                                               2,
+                                               3,
+                                               4,
+                                               5,
+                                               6,
+                                           }),
+                   reference_tests::Tensor(ET_INT, {1}, std::vector<T_INT>{4}),
+                   reference_tests::Tensor(ET, {24}, std::vector<T>{1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6,
+                                                                    1, 2, 3, 4, 5, 6, 1, 2, 3, 4, 5, 6}),
+                   "tile_1d_to_1d_no_broadcast"),
+        TileParams(reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
+                   reference_tests::Tensor(ET_INT, {3}, std::vector<T_INT>{2, 2, 1}),
+                   reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3}),
+                   "tile_1d_to_3d_data_broadcast"),
+        TileParams(reference_tests::Tensor(ET, {2, 1, 3}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
+                   reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{1, 2, 3, 1, 2, 3, 4, 5, 6, 4, 5, 6}),
+                   "tile_3d_to_3d_repeats_broadcast"),
     };
     return params;
 }
@@ -116,22 +107,20 @@ template <element::Type_t ET, element::Type_t ET_INT>
 std::vector<TileParams> generateParamsFloatValue() {
     using T = typename element_type_traits<ET>::value_type;
     using T_INT = typename element_type_traits<ET_INT>::value_type;
-    std::vector<TileParams> params {
-        TileParams(
-            reference_tests::Tensor(ET, {2, 1, 3}, std::vector<T>{
-                1.1f, 2.2f, 3.3f, 4.4f, 5.5f, 6.6f
-            }),
-            reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
-            reference_tests::Tensor(ET, {2, 2, 3}, std::vector<T>{
-                1.1f, 2.2f, 3.3f, 1.1f, 2.2f, 3.3f, 4.4f, 5.5f, 6.6f, 4.4f, 5.5f, 6.6f
-            }),
-            "tile_3d_to_3d_repeats_broadcast_float_val"),
+    std::vector<TileParams> params{
+        TileParams(reference_tests::Tensor(ET, {2, 1, 3}, std::vector<T>{1.1f, 2.2f, 3.3f, 4.4f, 5.5f, 6.6f}),
+                   reference_tests::Tensor(ET_INT, {2}, std::vector<T_INT>{2, 1}),
+                   reference_tests::Tensor(
+                       ET,
+                       {2, 2, 3},
+                       std::vector<T>{1.1f, 2.2f, 3.3f, 1.1f, 2.2f, 3.3f, 4.4f, 5.5f, 6.6f, 4.4f, 5.5f, 6.6f}),
+                   "tile_3d_to_3d_repeats_broadcast_float_val"),
     };
     return params;
 }
 
 std::vector<TileParams> generateCombinedParams() {
-    const std::vector<std::vector<TileParams>> generatedParams {
+    const std::vector<std::vector<TileParams>> generatedParams{
         // test each data type for each repeats type
         // CVS-73511 - commented here due segmentation fault
         // generateParams<element::Type_t::i4, element::Type_t::i4>(),
@@ -315,8 +304,7 @@ std::vector<TileParams> generateCombinedParams() {
         generateParamsFloatValue<element::Type_t::bf16, element::Type_t::u8>(),
         generateParamsFloatValue<element::Type_t::bf16, element::Type_t::u16>(),
         generateParamsFloatValue<element::Type_t::bf16, element::Type_t::u32>(),
-        generateParamsFloatValue<element::Type_t::bf16, element::Type_t::u64>()
-    };
+        generateParamsFloatValue<element::Type_t::bf16, element::Type_t::u64>()};
     std::vector<TileParams> combinedParams;
 
     for (const auto& params : generatedParams) {
@@ -325,6 +313,8 @@ std::vector<TileParams> generateCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Tile_With_Hardcoded_Refs, ReferenceTileTest,
-    testing::ValuesIn(generateCombinedParams()), ReferenceTileTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Tile_With_Hardcoded_Refs,
+                         ReferenceTileTest,
+                         testing::ValuesIn(generateCombinedParams()),
+                         ReferenceTileTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/topk.cpp b/src/plugins/template/tests/functional/op_reference/topk.cpp
index 74291ea086fa48..f3fac57bd2acf1 100644
--- a/src/plugins/template/tests/functional/op_reference/topk.cpp
+++ b/src/plugins/template/tests/functional/op_reference/topk.cpp
@@ -14,14 +14,24 @@ using namespace ov;
 
 namespace {
 struct TopKParams {
-    TopKParams(
-        const reference_tests::Tensor& A, const reference_tests::Tensor& k, const int64_t axis,
-        const opset1::TopK::Mode mode, const opset1::TopK::SortType sort,
-        const reference_tests::Tensor& result0, const reference_tests::Tensor& result1, const size_t outIdx,
-        const std::string& testcaseName = "") :
-        A(A), k(k), axis(axis), mode(mode), sort(sort),
-        result0(result0), result1(result1), outIdx(outIdx),
-        testcaseName(testcaseName) {}
+    TopKParams(const reference_tests::Tensor& A,
+               const reference_tests::Tensor& k,
+               const int64_t axis,
+               const opset1::TopK::Mode mode,
+               const opset1::TopK::SortType sort,
+               const reference_tests::Tensor& result0,
+               const reference_tests::Tensor& result1,
+               const size_t outIdx,
+               const std::string& testcaseName = "")
+        : A(A),
+          k(k),
+          axis(axis),
+          mode(mode),
+          sort(sort),
+          result0(result0),
+          result1(result1),
+          outIdx(outIdx),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor k;
@@ -54,15 +64,18 @@ class ReferenceTopKTest : public testing::TestWithParam<TopKParams>, public Comm
 };
 
 struct TopKParamsResnet50 {
-    TopKParamsResnet50(
-        const reference_tests::Tensor& A,
-        const reference_tests::Tensor& result5Value, const reference_tests::Tensor& result5Index,
-        const reference_tests::Tensor& result1Value, const reference_tests::Tensor& result1Index,
-        const std::string& testcaseName = "") :
-        A(A),
-        result5Value(result5Value), result5Index(result5Index),
-        result1Value(result1Value), result1Index(result1Index),
-        testcaseName(testcaseName) {}
+    TopKParamsResnet50(const reference_tests::Tensor& A,
+                       const reference_tests::Tensor& result5Value,
+                       const reference_tests::Tensor& result5Index,
+                       const reference_tests::Tensor& result1Value,
+                       const reference_tests::Tensor& result1Index,
+                       const std::string& testcaseName = "")
+        : A(A),
+          result5Value(result5Value),
+          result5Index(result5Index),
+          result1Value(result1Value),
+          result1Index(result1Index),
+          testcaseName(testcaseName) {}
 
     reference_tests::Tensor A;
     reference_tests::Tensor result5Value;
@@ -78,8 +91,10 @@ class ReferenceTopKTestResnet50 : public testing::TestWithParam<TopKParamsResnet
         const auto& params = GetParam();
         function = CreateFunction(params);
         inputData = {params.A.data};
-        refOutData = {params.result5Value.data, params.result5Index.data,
-                      params.result1Value.data, params.result1Index.data};
+        refOutData = {params.result5Value.data,
+                      params.result5Index.data,
+                      params.result1Value.data,
+                      params.result1Index.data};
     }
 
     static std::string getTestCaseName(const testing::TestParamInfo<TopKParamsResnet50>& obj) {
@@ -101,8 +116,7 @@ class ReferenceTopKTestResnet50 : public testing::TestWithParam<TopKParamsResnet
 
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParamsResnet50& params) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
         const auto B = std::make_shared<opset1::TopK>(A,
                                                       opset1::Constant::create(element::i64, {}, {5}),
                                                       1,
@@ -118,7 +132,8 @@ class ReferenceTopKTestResnet50 : public testing::TestWithParam<TopKParamsResnet
         const auto out5_index = B->output(1);
         const auto out1_value = C->output(0);
         const auto out1_index = C->output(1);
-        const auto f = std::make_shared<Model>(OutputVector{out5_value, out5_index, out1_value, out1_index}, ParameterVector{A});
+        const auto f =
+            std::make_shared<Model>(OutputVector{out5_value, out5_index, out1_value, out1_index}, ParameterVector{A});
         return f;
     }
 };
@@ -131,60 +146,70 @@ template <element::Type_t ET, element::Type_t ET_OUT>
 std::vector<TopKParamsResnet50> generateParamsResnet50() {
     using T = typename element_type_traits<ET>::value_type;
     using T_OUT = typename element_type_traits<ET_OUT>::value_type;
-    std::vector<TopKParamsResnet50> params {
+    std::vector<TopKParamsResnet50> params{
         TopKParamsResnet50(
-            reference_tests::Tensor(ET, {128, 1000}, [](std::vector<size_t> shape) -> std::vector<T> {
-                std::vector<T> data;
-                for (size_t i = 0; i < shape[0]; i++) {
-                    for (size_t j = 0; j < shape[1]; j++) {
-                        data.push_back(static_cast<T>(j));
-                    }
-                }
-                return data;
-            }({128, 1000})),
-            reference_tests::Tensor(ET, {128, 5}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T>{
-                std::vector<T> expected_value;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_value.push_back(static_cast<T>(shape[1] - j - 1));
-                    }
-                }
-                return expected_value;
-            }({128, 5}, {128, 1000})),
-            reference_tests::Tensor(ET_OUT, {128, 5}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT>{
-                std::vector<T_OUT> expected_index;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_index.push_back(static_cast<T_OUT>(shape[1] - j - 1));
-                    }
-                }
-                return expected_index;
-            }({128, 5}, {128, 1000})),
-            reference_tests::Tensor(ET, {128, 1}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T>{
-                std::vector<T> expected_value;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_value.push_back(static_cast<T>(shape[1] - j - 1));
-                    }
-                }
-                return expected_value;
-            }({128, 1}, {128, 1000})),
-            reference_tests::Tensor(ET_OUT, {128, 1}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT>{
-                std::vector<T_OUT> expected_index;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_index.push_back(static_cast<T_OUT>(shape[1] - j - 1));
-                    }
-                }
-                return expected_index;
-            }({128, 1}, {128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 1000},
+                                    [](std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> data;
+                                        for (size_t i = 0; i < shape[0]; i++) {
+                                            for (size_t j = 0; j < shape[1]; j++) {
+                                                data.push_back(static_cast<T>(j));
+                                            }
+                                        }
+                                        return data;
+                                    }({128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 5},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> expected_value;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            for (size_t j = 0; j < rshape[1]; j++) {
+                                                expected_value.push_back(static_cast<T>(shape[1] - j - 1));
+                                            }
+                                        }
+                                        return expected_value;
+                                    }({128, 5}, {128, 1000})),
+            reference_tests::Tensor(ET_OUT,
+                                    {128, 5},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT> {
+                                        std::vector<T_OUT> expected_index;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            for (size_t j = 0; j < rshape[1]; j++) {
+                                                expected_index.push_back(static_cast<T_OUT>(shape[1] - j - 1));
+                                            }
+                                        }
+                                        return expected_index;
+                                    }({128, 5}, {128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 1},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> expected_value;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            for (size_t j = 0; j < rshape[1]; j++) {
+                                                expected_value.push_back(static_cast<T>(shape[1] - j - 1));
+                                            }
+                                        }
+                                        return expected_value;
+                                    }({128, 1}, {128, 1000})),
+            reference_tests::Tensor(ET_OUT,
+                                    {128, 1},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT> {
+                                        std::vector<T_OUT> expected_index;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            for (size_t j = 0; j < rshape[1]; j++) {
+                                                expected_index.push_back(static_cast<T_OUT>(shape[1] - j - 1));
+                                            }
+                                        }
+                                        return expected_index;
+                                    }({128, 1}, {128, 1000})),
             "topk_resnet50"),
     };
     return params;
 }
 
 std::vector<TopKParamsResnet50> generateCombinedParamsResnet50() {
-    const std::vector<std::vector<TopKParamsResnet50>> generatedParams {
+    const std::vector<std::vector<TopKParamsResnet50>> generatedParams{
         generateParamsResnet50<element::Type_t::i8, element::Type_t::i32>(),
         generateParamsResnet50<element::Type_t::i16, element::Type_t::i32>(),
         generateParamsResnet50<element::Type_t::i32, element::Type_t::i32>(),
@@ -206,8 +231,10 @@ std::vector<TopKParamsResnet50> generateCombinedParamsResnet50() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestResnet50,
-    testing::ValuesIn(generateCombinedParamsResnet50()), ReferenceTopKTestResnet50::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestResnet50,
+                         testing::ValuesIn(generateCombinedParamsResnet50()),
+                         ReferenceTopKTestResnet50::getTestCaseName);
 
 class ReferenceTopKTestMaxMinSort : public ReferenceTopKTest {
 public:
@@ -220,11 +247,8 @@ class ReferenceTopKTestMaxMinSort : public ReferenceTopKTest {
 
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
         const auto B = std::make_shared<opset1::TopK>(A, k, params.axis, params.mode, params.sort);
         const auto f = std::make_shared<Model>(B->outputs(), ParameterVector{A});
         return f;
@@ -240,278 +264,307 @@ std::vector<TopKParams> generateParamsMaxMinSort() {
     using T = typename element_type_traits<ET>::value_type;
     using T2 = typename element_type_traits<ET2>::value_type;
     using T_OUT = typename element_type_traits<ET_OUT>::value_type;
-    std::vector<TopKParams> params {
+    std::vector<TopKParams> params{
         TopKParams(
-            reference_tests::Tensor(ET, {128, 1000}, [](std::vector<size_t> shape) -> std::vector<T> {
-                std::vector<T> data;
-                for (size_t i = 0; i < shape[0]; i++) {
-                    for (size_t j = 0; j < shape[1]; j++) {
-                        data.push_back(static_cast<T>(j));
-                    }
-                }
-                return data;
-            }({128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 1000},
+                                    [](std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> data;
+                                        for (size_t i = 0; i < shape[0]; i++) {
+                                            for (size_t j = 0; j < shape[1]; j++) {
+                                                data.push_back(static_cast<T>(j));
+                                            }
+                                        }
+                                        return data;
+                                    }({128, 1000})),
             reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
             1,
             opset1::TopK::Mode::MAX,
             opset1::TopK::SortType::NONE,
-            reference_tests::Tensor(ET, {128, 5}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T>{
-                std::vector<T> expected_value;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    expected_value.push_back(static_cast<T>(shape[1] - 3));
-                    expected_value.push_back(static_cast<T>(shape[1] - 1));
-                    expected_value.push_back(static_cast<T>(shape[1] - 2));
-                    expected_value.push_back(static_cast<T>(shape[1] - 5));
-                    expected_value.push_back(static_cast<T>(shape[1] - 4));
-                }
-                return expected_value;
-            }({128, 5}, {128, 1000})),
-            reference_tests::Tensor(ET_OUT, {128, 5}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT>{
-                std::vector<T_OUT> expected_index;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 3));
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 1));
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 2));
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 5));
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 4));
-                }
-                return expected_index;
-            }({128, 5}, {128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 5},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> expected_value;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            expected_value.push_back(static_cast<T>(shape[1] - 3));
+                                            expected_value.push_back(static_cast<T>(shape[1] - 1));
+                                            expected_value.push_back(static_cast<T>(shape[1] - 2));
+                                            expected_value.push_back(static_cast<T>(shape[1] - 5));
+                                            expected_value.push_back(static_cast<T>(shape[1] - 4));
+                                        }
+                                        return expected_value;
+                                    }({128, 5}, {128, 1000})),
+            reference_tests::Tensor(ET_OUT,
+                                    {128, 5},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT> {
+                                        std::vector<T_OUT> expected_index;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 3));
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 1));
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 2));
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 5));
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 4));
+                                        }
+                                        return expected_index;
+                                    }({128, 5}, {128, 1000})),
             0,
             "topk_max_sort_none"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {128, 1000}, [](std::vector<size_t> shape) -> std::vector<T> {
-                std::vector<T> data;
-                for (size_t i = 0; i < shape[0]; i++) {
-                    for (size_t j = 0; j < shape[1]; j++) {
-                        data.push_back(static_cast<T>(j));
-                    }
-                }
-                return data;
-            }({128, 1000})),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::NONE,
-            reference_tests::Tensor(ET, {128, 5}, [](std::vector<size_t> rshape) -> std::vector<T>{
-                std::vector<T> expected_value;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    expected_value.push_back(1);
-                    expected_value.push_back(0);
-                    expected_value.push_back(3);
-                    expected_value.push_back(2);
-                    expected_value.push_back(4);
-                }
-                return expected_value;
-            }({128, 5})),
-            reference_tests::Tensor(ET_OUT, {128, 5}, [](std::vector<size_t> rshape) -> std::vector<T_OUT>{
-                std::vector<T_OUT> expected_index;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    expected_index.push_back(1);
-                    expected_index.push_back(0);
-                    expected_index.push_back(3);
-                    expected_index.push_back(2);
-                    expected_index.push_back(4);
-                }
-                return expected_index;
-            }({128, 5})),
-            0,
-            "topk_min_sort_none"),
+        TopKParams(reference_tests::Tensor(ET,
+                                           {128, 1000},
+                                           [](std::vector<size_t> shape) -> std::vector<T> {
+                                               std::vector<T> data;
+                                               for (size_t i = 0; i < shape[0]; i++) {
+                                                   for (size_t j = 0; j < shape[1]; j++) {
+                                                       data.push_back(static_cast<T>(j));
+                                                   }
+                                               }
+                                               return data;
+                                           }({128, 1000})),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::NONE,
+                   reference_tests::Tensor(ET,
+                                           {128, 5},
+                                           [](std::vector<size_t> rshape) -> std::vector<T> {
+                                               std::vector<T> expected_value;
+                                               for (size_t i = 0; i < rshape[0]; i++) {
+                                                   expected_value.push_back(1);
+                                                   expected_value.push_back(0);
+                                                   expected_value.push_back(3);
+                                                   expected_value.push_back(2);
+                                                   expected_value.push_back(4);
+                                               }
+                                               return expected_value;
+                                           }({128, 5})),
+                   reference_tests::Tensor(ET_OUT,
+                                           {128, 5},
+                                           [](std::vector<size_t> rshape) -> std::vector<T_OUT> {
+                                               std::vector<T_OUT> expected_index;
+                                               for (size_t i = 0; i < rshape[0]; i++) {
+                                                   expected_index.push_back(1);
+                                                   expected_index.push_back(0);
+                                                   expected_index.push_back(3);
+                                                   expected_index.push_back(2);
+                                                   expected_index.push_back(4);
+                                               }
+                                               return expected_index;
+                                           }({128, 5})),
+                   0,
+                   "topk_min_sort_none"),
 
         TopKParams(
-            reference_tests::Tensor(ET, {128, 1000}, [](std::vector<size_t> shape) -> std::vector<T> {
-                std::vector<T> data;
-                for (size_t i = 0; i < shape[0]; i++) {
-                    for (size_t j = 0; j < shape[1]; j++) {
-                        data.push_back(static_cast<T>(j));
-                    }
-                }
-                return data;
-            }({128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 1000},
+                                    [](std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> data;
+                                        for (size_t i = 0; i < shape[0]; i++) {
+                                            for (size_t j = 0; j < shape[1]; j++) {
+                                                data.push_back(static_cast<T>(j));
+                                            }
+                                        }
+                                        return data;
+                                    }({128, 1000})),
             reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
             1,
             opset1::TopK::Mode::MAX,
             opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {128, 5}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T>{
-                std::vector<T> expected_value;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_value.push_back(static_cast<T>((shape[1] - j - 1)));
-                    }
-                }
-                return expected_value;
-            }({128, 5}, {128, 1000})),
-            reference_tests::Tensor(ET_OUT, {128, 5}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT>{
-                std::vector<T_OUT> expected_index;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_index.push_back(static_cast<T_OUT>(shape[1] - j - 1));
-                    }
-                }
-                return expected_index;
-            }({128, 5}, {128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 5},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> expected_value;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            for (size_t j = 0; j < rshape[1]; j++) {
+                                                expected_value.push_back(static_cast<T>((shape[1] - j - 1)));
+                                            }
+                                        }
+                                        return expected_value;
+                                    }({128, 5}, {128, 1000})),
+            reference_tests::Tensor(ET_OUT,
+                                    {128, 5},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT> {
+                                        std::vector<T_OUT> expected_index;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            for (size_t j = 0; j < rshape[1]; j++) {
+                                                expected_index.push_back(static_cast<T_OUT>(shape[1] - j - 1));
+                                            }
+                                        }
+                                        return expected_index;
+                                    }({128, 5}, {128, 1000})),
             0,
             "topk_max_sort_value"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {128, 1000}, [](std::vector<size_t> shape) -> std::vector<T> {
-                std::vector<T> data;
-                for (size_t i = 0; i < shape[0]; i++) {
-                    for (size_t j = 0; j < shape[1]; j++) {
-                        data.push_back(static_cast<T>(j));
-                    }
-                }
-                return data;
-            }({128, 1000})),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {128, 5}, [](std::vector<size_t> rshape) -> std::vector<T>{
-                std::vector<T> expected_value;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_value.push_back(static_cast<T>(j));
-                    }
-                }
-                return expected_value;
-            }({128, 5})),
-            reference_tests::Tensor(ET_OUT, {128, 5}, [](std::vector<size_t> rshape) -> std::vector<T_OUT>{
-                std::vector<T_OUT> expected_index;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_index.push_back(static_cast<T_OUT>(j));
-                    }
-                }
-                return expected_index;
-            }({128, 5})),
-            0,
-            "topk_min_sort_value"),
+        TopKParams(reference_tests::Tensor(ET,
+                                           {128, 1000},
+                                           [](std::vector<size_t> shape) -> std::vector<T> {
+                                               std::vector<T> data;
+                                               for (size_t i = 0; i < shape[0]; i++) {
+                                                   for (size_t j = 0; j < shape[1]; j++) {
+                                                       data.push_back(static_cast<T>(j));
+                                                   }
+                                               }
+                                               return data;
+                                           }({128, 1000})),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET,
+                                           {128, 5},
+                                           [](std::vector<size_t> rshape) -> std::vector<T> {
+                                               std::vector<T> expected_value;
+                                               for (size_t i = 0; i < rshape[0]; i++) {
+                                                   for (size_t j = 0; j < rshape[1]; j++) {
+                                                       expected_value.push_back(static_cast<T>(j));
+                                                   }
+                                               }
+                                               return expected_value;
+                                           }({128, 5})),
+                   reference_tests::Tensor(ET_OUT,
+                                           {128, 5},
+                                           [](std::vector<size_t> rshape) -> std::vector<T_OUT> {
+                                               std::vector<T_OUT> expected_index;
+                                               for (size_t i = 0; i < rshape[0]; i++) {
+                                                   for (size_t j = 0; j < rshape[1]; j++) {
+                                                       expected_index.push_back(static_cast<T_OUT>(j));
+                                                   }
+                                               }
+                                               return expected_index;
+                                           }({128, 5})),
+                   0,
+                   "topk_min_sort_value"),
 
         TopKParams(
-            reference_tests::Tensor(ET, {128, 1000}, [](std::vector<size_t> shape) -> std::vector<T> {
-                std::vector<T> data;
-                for (size_t i = 0; i < shape[0]; i++) {
-                    for (size_t j = 0; j < shape[1]; j++) {
-                        data.push_back(static_cast<T>(j));
-                    }
-                }
-                return data;
-            }({128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 1000},
+                                    [](std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> data;
+                                        for (size_t i = 0; i < shape[0]; i++) {
+                                            for (size_t j = 0; j < shape[1]; j++) {
+                                                data.push_back(static_cast<T>(j));
+                                            }
+                                        }
+                                        return data;
+                                    }({128, 1000})),
             reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
             1,
             opset1::TopK::Mode::MAX,
             opset1::TopK::SortType::SORT_INDICES,
-            reference_tests::Tensor(ET, {128, 5}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T>{
-                std::vector<T> expected_value;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    expected_value.push_back(static_cast<T>(shape[1] - 5));
-                    expected_value.push_back(static_cast<T>(shape[1] - 4));
-                    expected_value.push_back(static_cast<T>(shape[1] - 3));
-                    expected_value.push_back(static_cast<T>(shape[1] - 2));
-                    expected_value.push_back(static_cast<T>(shape[1] - 1));
-                }
-                return expected_value;
-            }({128, 5}, {128, 1000})),
-            reference_tests::Tensor(ET_OUT, {128, 5}, [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT>{
-                std::vector<T_OUT> expected_index;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 5));
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 4));
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 3));
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 2));
-                    expected_index.push_back(static_cast<T_OUT>(shape[1] - 1));
-                }
-                return expected_index;
-            }({128, 5}, {128, 1000})),
+            reference_tests::Tensor(ET,
+                                    {128, 5},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T> {
+                                        std::vector<T> expected_value;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            expected_value.push_back(static_cast<T>(shape[1] - 5));
+                                            expected_value.push_back(static_cast<T>(shape[1] - 4));
+                                            expected_value.push_back(static_cast<T>(shape[1] - 3));
+                                            expected_value.push_back(static_cast<T>(shape[1] - 2));
+                                            expected_value.push_back(static_cast<T>(shape[1] - 1));
+                                        }
+                                        return expected_value;
+                                    }({128, 5}, {128, 1000})),
+            reference_tests::Tensor(ET_OUT,
+                                    {128, 5},
+                                    [](std::vector<size_t> rshape, std::vector<size_t> shape) -> std::vector<T_OUT> {
+                                        std::vector<T_OUT> expected_index;
+                                        for (size_t i = 0; i < rshape[0]; i++) {
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 5));
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 4));
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 3));
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 2));
+                                            expected_index.push_back(static_cast<T_OUT>(shape[1] - 1));
+                                        }
+                                        return expected_index;
+                                    }({128, 5}, {128, 1000})),
             0,
             "topk_max_sort_index"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {128, 1000}, [](std::vector<size_t> shape) -> std::vector<T> {
-                std::vector<T> data;
-                for (size_t i = 0; i < shape[0]; i++) {
-                    for (size_t j = 0; j < shape[1]; j++) {
-                        data.push_back(static_cast<T>(j));
-                    }
-                }
-                return data;
-            }({128, 1000})),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_INDICES,
-            reference_tests::Tensor(ET, {128, 5}, [](std::vector<size_t> rshape) -> std::vector<T>{
-                std::vector<T> expected_value;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_value.push_back(static_cast<T>(j));
-                    }
-                }
-                return expected_value;
-            }({128, 5})),
-            reference_tests::Tensor(ET_OUT, {128, 5}, [](std::vector<size_t> rshape) -> std::vector<T_OUT>{
-                std::vector<T_OUT> expected_index;
-                for (size_t i = 0; i < rshape[0]; i++) {
-                    for (size_t j = 0; j < rshape[1]; j++) {
-                        expected_index.push_back(static_cast<T_OUT>(j));
-                    }
-                }
-                return expected_index;
-            }({128, 5})),
-            0,
-            "topk_min_sort_index"),
+        TopKParams(reference_tests::Tensor(ET,
+                                           {128, 1000},
+                                           [](std::vector<size_t> shape) -> std::vector<T> {
+                                               std::vector<T> data;
+                                               for (size_t i = 0; i < shape[0]; i++) {
+                                                   for (size_t j = 0; j < shape[1]; j++) {
+                                                       data.push_back(static_cast<T>(j));
+                                                   }
+                                               }
+                                               return data;
+                                           }({128, 1000})),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{5}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_INDICES,
+                   reference_tests::Tensor(ET,
+                                           {128, 5},
+                                           [](std::vector<size_t> rshape) -> std::vector<T> {
+                                               std::vector<T> expected_value;
+                                               for (size_t i = 0; i < rshape[0]; i++) {
+                                                   for (size_t j = 0; j < rshape[1]; j++) {
+                                                       expected_value.push_back(static_cast<T>(j));
+                                                   }
+                                               }
+                                               return expected_value;
+                                           }({128, 5})),
+                   reference_tests::Tensor(ET_OUT,
+                                           {128, 5},
+                                           [](std::vector<size_t> rshape) -> std::vector<T_OUT> {
+                                               std::vector<T_OUT> expected_index;
+                                               for (size_t i = 0; i < rshape[0]; i++) {
+                                                   for (size_t j = 0; j < rshape[1]; j++) {
+                                                       expected_index.push_back(static_cast<T_OUT>(j));
+                                                   }
+                                               }
+                                               return expected_index;
+                                           }({128, 5})),
+                   0,
+                   "topk_min_sort_index"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {5}, std::vector<T>{3, 1, 2, 5, 4}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{5, 4, 3}),
-            reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{3, 4, 0}),
-            0,
-            "topk_mode_sort_order"),
+        TopKParams(reference_tests::Tensor(ET, {5}, std::vector<T>{3, 1, 2, 5, 4}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {3}, std::vector<T>{5, 4, 3}),
+                   reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{3, 4, 0}),
+                   0,
+                   "topk_mode_sort_order"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {5}, std::vector<T>{3, 1, 2, 5, 4}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_INDICES,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{3, 5, 4}),
-            reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{0, 3, 4}),
-            0,
-            "topk_mode_sort_order_1"),
+        TopKParams(reference_tests::Tensor(ET, {5}, std::vector<T>{3, 1, 2, 5, 4}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_INDICES,
+                   reference_tests::Tensor(ET, {3}, std::vector<T>{3, 5, 4}),
+                   reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{0, 3, 4}),
+                   0,
+                   "topk_mode_sort_order_1"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {5}, std::vector<T>{3, 1, 2, 5, 4}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
-            reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{1, 2, 0}),
-            0,
-            "topk_mode_sort_order_2"),
+        TopKParams(reference_tests::Tensor(ET, {5}, std::vector<T>{3, 1, 2, 5, 4}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
+                   reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{1, 2, 0}),
+                   0,
+                   "topk_mode_sort_order_2"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {5}, std::vector<T>{3, 1, 2, 5, 4}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_INDICES,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{3, 1, 2}),
-            reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{0, 1, 2}),
-            0,
-            "topk_mode_sort_order_3"),
+        TopKParams(reference_tests::Tensor(ET, {5}, std::vector<T>{3, 1, 2, 5, 4}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_INDICES,
+                   reference_tests::Tensor(ET, {3}, std::vector<T>{3, 1, 2}),
+                   reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{0, 1, 2}),
+                   0,
+                   "topk_mode_sort_order_3"),
     };
     return params;
 }
 
 std::vector<TopKParams> generateCombinedParamsMaxMinSort() {
-    const std::vector<std::vector<TopKParams>> generatedParams {
+    const std::vector<std::vector<TopKParams>> generatedParams{
         generateParamsMaxMinSort<element::Type_t::i8, element::Type_t::i64, element::Type_t::i32>(),
         generateParamsMaxMinSort<element::Type_t::i16, element::Type_t::i64, element::Type_t::i32>(),
         generateParamsMaxMinSort<element::Type_t::i32, element::Type_t::i64, element::Type_t::i32>(),
@@ -533,8 +586,10 @@ std::vector<TopKParams> generateCombinedParamsMaxMinSort() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestMaxMinSort,
-    testing::ValuesIn(generateCombinedParamsMaxMinSort()), ReferenceTopKTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestMaxMinSort,
+                         testing::ValuesIn(generateCombinedParamsMaxMinSort()),
+                         ReferenceTopKTest::getTestCaseName);
 
 class ReferenceTopKTestBackend : public ReferenceTopKTest {
 public:
@@ -547,11 +602,8 @@ class ReferenceTopKTestBackend : public ReferenceTopKTest {
 
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
         const auto B = std::make_shared<opset1::TopK>(A, k, params.axis, params.mode, params.sort);
         const auto f = std::make_shared<Model>(B->outputs(), ParameterVector{A});
         return f;
@@ -563,7 +615,7 @@ TEST_P(ReferenceTopKTestBackend, CompareWithRefs) {
 }
 
 std::vector<TopKParams> generateCombinedParamsBackend() {
-    const std::vector<std::vector<TopKParams>> generatedParams {
+    const std::vector<std::vector<TopKParams>> generatedParams{
         generateParamsMaxMinSort<element::Type_t::i8, element::Type_t::i64, element::Type_t::i32>(),
         generateParamsMaxMinSort<element::Type_t::i16, element::Type_t::i64, element::Type_t::i32>(),
         generateParamsMaxMinSort<element::Type_t::i32, element::Type_t::i64, element::Type_t::i32>(),
@@ -585,8 +637,10 @@ std::vector<TopKParams> generateCombinedParamsBackend() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestBackend,
-    testing::ValuesIn(generateCombinedParamsBackend()), ReferenceTopKTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestBackend,
+                         testing::ValuesIn(generateCombinedParamsBackend()),
+                         ReferenceTopKTest::getTestCaseName);
 
 class ReferenceTopKTest1dMaxMin : public ReferenceTopKTest {
 public:
@@ -620,11 +674,8 @@ class ReferenceTopKTest1dMaxMin : public ReferenceTopKTest {
 
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params, size_t out_idx) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
         const auto B = std::make_shared<opset1::TopK>(A, k, params.axis, params.mode, params.sort);
         const auto f = std::make_shared<Model>(OutputVector{B->output(out_idx)}, ParameterVector{A});
         return f;
@@ -640,668 +691,478 @@ std::vector<TopKParams> generateParams1dMaxMin() {
     using T = typename element_type_traits<ET>::value_type;
     using T2 = typename element_type_traits<ET2>::value_type;
     using T_OUT = typename element_type_traits<ET_OUT>::value_type;
-    std::vector<TopKParams> params {
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{6}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
-            reference_tests::Tensor(ET_OUT, {6}, std::vector<T_OUT>{5, 4, 3, 2, 1, 0}),
-            0,
-            "topk_1d_max_all"),
+    std::vector<TopKParams> params{
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{6}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
+                   reference_tests::Tensor(ET_OUT, {6}, std::vector<T_OUT>{5, 4, 3, 2, 1, 0}),
+                   0,
+                   "topk_1d_max_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{6}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
-            reference_tests::Tensor(ET_OUT, {6}, std::vector<T_OUT>{5, 4, 3, 2, 1, 0}),
-            1,
-            "topk_1d_max_all"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{6}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
+                   reference_tests::Tensor(ET_OUT, {6}, std::vector<T_OUT>{5, 4, 3, 2, 1, 0}),
+                   1,
+                   "topk_1d_max_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{6, 5, 4}),
-            reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{5, 4, 3}),
-            0,
-            "topk_1d_max_partial"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {3}, std::vector<T>{6, 5, 4}),
+                   reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{5, 4, 3}),
+                   0,
+                   "topk_1d_max_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{6, 5, 4}),
-            reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{5, 4, 3}),
-            1,
-            "topk_1d_max_partial"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {3}, std::vector<T>{6, 5, 4}),
+                   reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{5, 4, 3}),
+                   1,
+                   "topk_1d_max_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {1}, std::vector<T>{6}),
-            reference_tests::Tensor(ET_OUT, {1}, std::vector<T_OUT>{5}),
-            0,
-            "topk_1d_max_one"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {1}, std::vector<T>{6}),
+                   reference_tests::Tensor(ET_OUT, {1}, std::vector<T_OUT>{5}),
+                   0,
+                   "topk_1d_max_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {1}, std::vector<T>{6}),
-            reference_tests::Tensor(ET_OUT, {1}, std::vector<T_OUT>{5}),
-            1,
-            "topk_1d_max_one"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {1}, std::vector<T>{6}),
+                   reference_tests::Tensor(ET_OUT, {1}, std::vector<T_OUT>{5}),
+                   1,
+                   "topk_1d_max_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{6}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
-            reference_tests::Tensor(ET_OUT, {6}, std::vector<T_OUT>{5, 4, 3, 2, 1, 0}),
-            0,
-            "topk_1d_min_all"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{6}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET_OUT, {6}, std::vector<T_OUT>{5, 4, 3, 2, 1, 0}),
+                   0,
+                   "topk_1d_min_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{6}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
-            reference_tests::Tensor(ET_OUT, {6}, std::vector<T_OUT>{5, 4, 3, 2, 1, 0}),
-            1,
-            "topk_1d_min_all"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{6}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {6}, std::vector<T>{1, 2, 3, 4, 5, 6}),
+                   reference_tests::Tensor(ET_OUT, {6}, std::vector<T_OUT>{5, 4, 3, 2, 1, 0}),
+                   1,
+                   "topk_1d_min_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
-            reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{5, 4, 3}),
-            0,
-            "topk_1d_min_partial"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
+                   reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{5, 4, 3}),
+                   0,
+                   "topk_1d_min_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
-            reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{5, 4, 3}),
-            1,
-            "topk_1d_min_partial"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {3}, std::vector<T>{1, 2, 3}),
+                   reference_tests::Tensor(ET_OUT, {3}, std::vector<T_OUT>{5, 4, 3}),
+                   1,
+                   "topk_1d_min_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {1}, std::vector<T>{1}),
-            reference_tests::Tensor(ET_OUT, {1}, std::vector<T_OUT>{5}),
-            0,
-            "topk_1d_min_one"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {1}, std::vector<T>{1}),
+                   reference_tests::Tensor(ET_OUT, {1}, std::vector<T_OUT>{5}),
+                   0,
+                   "topk_1d_min_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {1}, std::vector<T>{1}),
-            reference_tests::Tensor(ET_OUT, {1}, std::vector<T_OUT>{5}),
-            1,
-            "topk_1d_min_one"),
+        TopKParams(reference_tests::Tensor(ET, {6}, std::vector<T>{6, 5, 4, 3, 2, 1}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {1}, std::vector<T>{1}),
+                   reference_tests::Tensor(ET_OUT, {1}, std::vector<T_OUT>{5}),
+                   1,
+                   "topk_1d_min_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                10, 12, 9, 4, 8, 2, 11, 7, 6, 3, 5, 1
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{
-                1, 1, 0, 2, 2, 0, 2, 2, 0, 1, 1, 0
-            }),
-            0,
-            "topk_3d_max_all"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{10, 12, 9, 4, 8, 2, 11, 7, 6, 3, 5, 1}),
+                   reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{1, 1, 0, 2, 2, 0, 2, 2, 0, 1, 1, 0}),
+                   0,
+                   "topk_3d_max_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                10, 12, 9, 4, 8, 2, 11, 7, 6, 3, 5, 1
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{
-                1, 1, 0, 2, 2, 0, 2, 2, 0, 1, 1, 0
-            }),
-            1,
-            "topk_3d_max_all"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{10, 12, 9, 4, 8, 2, 11, 7, 6, 3, 5, 1}),
+                   reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{1, 1, 0, 2, 2, 0, 2, 2, 0, 1, 1, 0}),
+                   1,
+                   "topk_3d_max_all"),
 
         TopKParams(
-            reference_tests::Tensor(ET, {2, 6, 3, 2, 4}, std::vector<T>{
-                  1,   73,  9,   81,  17,  89,  2,   74,  10,  82,  18,  90,  3,   75,  11,  83,  19,
-                  91,  4,   76,  12,  84,  20,  92,  145, 217, 153, 225, 161, 233, 146, 218, 154, 226,
-                  162, 234, 147, 219, 155, 227, 163, 235, 148, 220, 156, 228, 164, 236, 5,   77,  13,
-                  85,  21,  93,  6,   78,  14,  86,  22,  94,  7,   79,  15,  87,  23,  95,  8,   80,
-                  16,  88,  24,  96,  149, 221, 157, 229, 165, 27,  150, 222, 158, 230, 166, 23,  151,
-                  223, 159, 231, 17,  39,  2,   224, 160, 232, 168, 240, 25,  97,  33,  105, 41,  113,
-                  26,  98,  34,  106, 42,  114, 27,  99,  35,  107, 43,  115, 28,  100, 36,  108, 44,
-                  116, 169, 241, 177, 249, 185, 25,  170, 242, 178, 250, 186, 258, 171, 243, 179, 251,
-                  187, 259, 172, 24,  180, 252, 188, 260, 29,  101, 37,  109, 45,  117, 30,  102, 38,
-                  10,  46,  118, 31,  103, 39,  111, 47,  119, 32,  104, 40,  112, 48,  20,  173, 245,
-                  181, 253, 189, 261, 174, 246, 182, 254, 190, 262, 175, 27,  183, 255, 191, 263, 176,
-                  248, 184, 256, 192, 264, 49,  121, 57,  129, 65,  137, 50,  122, 58,  130, 66,  138,
-                  51,  123, 59,  131, 67,  139, 52,  124, 60,  132, 68,  140, 193, 265, 201, 273, 209,
-                  281, 194, 266, 202, 274, 210, 43,  115, 28,  100, 36,  108, 44,  116, 169, 241, 177,
-                  212, 284, 53,  125, 61,  133, 69,  141, 54,  126, 62,  134, 70,  142, 55,  127, 63,
-                  135, 71,  143, 56,  128, 64,  136, 72,  144, 197, 269, 205, 277, 213, 285, 198, 270,
-                  206, 278, 214, 286, 199, 271, 207, 279, 215, 287, 200, 272, 208, 280, 216, 288
-            }),
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 3, 2, 4},
+                std::vector<T>{
+                    1,   73,  9,   81,  17,  89,  2,   74,  10,  82,  18,  90,  3,   75,  11,  83,  19,  91,  4,   76,
+                    12,  84,  20,  92,  145, 217, 153, 225, 161, 233, 146, 218, 154, 226, 162, 234, 147, 219, 155, 227,
+                    163, 235, 148, 220, 156, 228, 164, 236, 5,   77,  13,  85,  21,  93,  6,   78,  14,  86,  22,  94,
+                    7,   79,  15,  87,  23,  95,  8,   80,  16,  88,  24,  96,  149, 221, 157, 229, 165, 27,  150, 222,
+                    158, 230, 166, 23,  151, 223, 159, 231, 17,  39,  2,   224, 160, 232, 168, 240, 25,  97,  33,  105,
+                    41,  113, 26,  98,  34,  106, 42,  114, 27,  99,  35,  107, 43,  115, 28,  100, 36,  108, 44,  116,
+                    169, 241, 177, 249, 185, 25,  170, 242, 178, 250, 186, 258, 171, 243, 179, 251, 187, 259, 172, 24,
+                    180, 252, 188, 260, 29,  101, 37,  109, 45,  117, 30,  102, 38,  10,  46,  118, 31,  103, 39,  111,
+                    47,  119, 32,  104, 40,  112, 48,  20,  173, 245, 181, 253, 189, 261, 174, 246, 182, 254, 190, 262,
+                    175, 27,  183, 255, 191, 263, 176, 248, 184, 256, 192, 264, 49,  121, 57,  129, 65,  137, 50,  122,
+                    58,  130, 66,  138, 51,  123, 59,  131, 67,  139, 52,  124, 60,  132, 68,  140, 193, 265, 201, 273,
+                    209, 281, 194, 266, 202, 274, 210, 43,  115, 28,  100, 36,  108, 44,  116, 169, 241, 177, 212, 284,
+                    53,  125, 61,  133, 69,  141, 54,  126, 62,  134, 70,  142, 55,  127, 63,  135, 71,  143, 56,  128,
+                    64,  136, 72,  144, 197, 269, 205, 277, 213, 285, 198, 270, 206, 278, 214, 286, 199, 271, 207, 279,
+                    215, 287, 200, 272, 208, 280, 216, 288}),
             reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
             1,
             opset1::TopK::Mode::MAX,
             opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 2, 3, 2, 4}, std::vector<T>{
-                169, 241, 177, 249, 185, 233, 170, 242, 178, 250, 186, 258, 171, 243, 179, 251,
-                187, 259, 172, 224, 180, 252, 188, 260, 149, 221, 157, 229, 165, 113, 150, 222,
-                158, 230, 166, 234, 151, 223, 159, 231, 163, 235, 148, 220, 160, 232, 168, 240,
-                197, 269, 205, 277, 213, 285, 198, 270, 206, 278, 214, 286, 199, 271, 207, 279,
-                215, 287, 200, 272, 241, 280, 216, 288, 193, 265, 201, 273, 209, 281, 194, 266,
-                202, 274, 210, 262, 175, 127, 183, 255, 191, 263, 176, 248, 208, 256, 212, 284
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 2, 3, 2, 4}, std::vector<T_OUT>{
-                5, 5, 5, 5, 5, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 5, 5, 5, 5,
-                3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3,
-                5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 5, 5, 5,
-                3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 4, 1, 1, 1, 1, 1, 1, 5, 1, 3, 3
-            }),
+            reference_tests::Tensor(
+                ET,
+                {2, 2, 3, 2, 4},
+                std::vector<T>{169, 241, 177, 249, 185, 233, 170, 242, 178, 250, 186, 258, 171, 243, 179, 251,
+                               187, 259, 172, 224, 180, 252, 188, 260, 149, 221, 157, 229, 165, 113, 150, 222,
+                               158, 230, 166, 234, 151, 223, 159, 231, 163, 235, 148, 220, 160, 232, 168, 240,
+                               197, 269, 205, 277, 213, 285, 198, 270, 206, 278, 214, 286, 199, 271, 207, 279,
+                               215, 287, 200, 272, 241, 280, 216, 288, 193, 265, 201, 273, 209, 281, 194, 266,
+                               202, 274, 210, 262, 175, 127, 183, 255, 191, 263, 176, 248, 208, 256, 212, 284}),
+            reference_tests::Tensor(
+                ET_OUT,
+                {2, 2, 3, 2, 4},
+                std::vector<T_OUT>{5, 5, 5, 5, 5, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 5, 5, 5, 5,
+                                   3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3,
+                                   5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 5, 5, 5,
+                                   3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 4, 1, 1, 1, 1, 1, 1, 5, 1, 3, 3}),
             0,
             "topk_5d_max_partial"),
 
         TopKParams(
-            reference_tests::Tensor(ET, {2, 6, 3, 2, 4}, std::vector<T>{
-                  1,   73,  9,   81,  17,  89,  2,   74,  10,  82,  18,  90,  3,   75,  11,  83,  19,
-                  91,  4,   76,  12,  84,  20,  92,  145, 217, 153, 225, 161, 233, 146, 218, 154, 226,
-                  162, 234, 147, 219, 155, 227, 163, 235, 148, 220, 156, 228, 164, 236, 5,   77,  13,
-                  85,  21,  93,  6,   78,  14,  86,  22,  94,  7,   79,  15,  87,  23,  95,  8,   80,
-                  16,  88,  24,  96,  149, 221, 157, 229, 165, 27,  150, 222, 158, 230, 166, 23,  151,
-                  223, 159, 231, 17,  39,  2,   224, 160, 232, 168, 240, 25,  97,  33,  105, 41,  113,
-                  26,  98,  34,  106, 42,  114, 27,  99,  35,  107, 43,  115, 28,  100, 36,  108, 44,
-                  116, 169, 241, 177, 249, 185, 25,  170, 242, 178, 250, 186, 258, 171, 243, 179, 251,
-                  187, 259, 172, 24,  180, 252, 188, 260, 29,  101, 37,  109, 45,  117, 30,  102, 38,
-                  10,  46,  118, 31,  103, 39,  111, 47,  119, 32,  104, 40,  112, 48,  20,  173, 245,
-                  181, 253, 189, 261, 174, 246, 182, 254, 190, 262, 175, 27,  183, 255, 191, 263, 176,
-                  248, 184, 256, 192, 264, 49,  121, 57,  129, 65,  137, 50,  122, 58,  130, 66,  138,
-                  51,  123, 59,  131, 67,  139, 52,  124, 60,  132, 68,  140, 193, 265, 201, 273, 209,
-                  281, 194, 266, 202, 274, 210, 43,  115, 28,  100, 36,  108, 44,  116, 169, 241, 177,
-                  212, 284, 53,  125, 61,  133, 69,  141, 54,  126, 62,  134, 70,  142, 55,  127, 63,
-                  135, 71,  143, 56,  128, 64,  136, 72,  144, 197, 269, 205, 277, 213, 285, 198, 270,
-                  206, 278, 214, 286, 199, 271, 207, 279, 215, 287, 200, 272, 208, 280, 216, 288
-            }),
+            reference_tests::Tensor(
+                ET,
+                {2, 6, 3, 2, 4},
+                std::vector<T>{
+                    1,   73,  9,   81,  17,  89,  2,   74,  10,  82,  18,  90,  3,   75,  11,  83,  19,  91,  4,   76,
+                    12,  84,  20,  92,  145, 217, 153, 225, 161, 233, 146, 218, 154, 226, 162, 234, 147, 219, 155, 227,
+                    163, 235, 148, 220, 156, 228, 164, 236, 5,   77,  13,  85,  21,  93,  6,   78,  14,  86,  22,  94,
+                    7,   79,  15,  87,  23,  95,  8,   80,  16,  88,  24,  96,  149, 221, 157, 229, 165, 27,  150, 222,
+                    158, 230, 166, 23,  151, 223, 159, 231, 17,  39,  2,   224, 160, 232, 168, 240, 25,  97,  33,  105,
+                    41,  113, 26,  98,  34,  106, 42,  114, 27,  99,  35,  107, 43,  115, 28,  100, 36,  108, 44,  116,
+                    169, 241, 177, 249, 185, 25,  170, 242, 178, 250, 186, 258, 171, 243, 179, 251, 187, 259, 172, 24,
+                    180, 252, 188, 260, 29,  101, 37,  109, 45,  117, 30,  102, 38,  10,  46,  118, 31,  103, 39,  111,
+                    47,  119, 32,  104, 40,  112, 48,  20,  173, 245, 181, 253, 189, 261, 174, 246, 182, 254, 190, 262,
+                    175, 27,  183, 255, 191, 263, 176, 248, 184, 256, 192, 264, 49,  121, 57,  129, 65,  137, 50,  122,
+                    58,  130, 66,  138, 51,  123, 59,  131, 67,  139, 52,  124, 60,  132, 68,  140, 193, 265, 201, 273,
+                    209, 281, 194, 266, 202, 274, 210, 43,  115, 28,  100, 36,  108, 44,  116, 169, 241, 177, 212, 284,
+                    53,  125, 61,  133, 69,  141, 54,  126, 62,  134, 70,  142, 55,  127, 63,  135, 71,  143, 56,  128,
+                    64,  136, 72,  144, 197, 269, 205, 277, 213, 285, 198, 270, 206, 278, 214, 286, 199, 271, 207, 279,
+                    215, 287, 200, 272, 208, 280, 216, 288}),
             reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
             1,
             opset1::TopK::Mode::MAX,
             opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 2, 3, 2, 4}, std::vector<T>{
-                169, 241, 177, 249, 185, 233, 170, 242, 178, 250, 186, 258, 171, 243, 179, 251,
-                187, 259, 172, 224, 180, 252, 188, 260, 149, 221, 157, 229, 165, 113, 150, 222,
-                158, 230, 166, 234, 151, 223, 159, 231, 163, 235, 148, 220, 160, 232, 168, 240,
-                197, 269, 205, 277, 213, 285, 198, 270, 206, 278, 214, 286, 199, 271, 207, 279,
-                215, 287, 200, 272, 241, 280, 216, 288, 193, 265, 201, 273, 209, 281, 194, 266,
-                202, 274, 210, 262, 175, 127, 183, 255, 191, 263, 176, 248, 208, 256, 212, 284
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 2, 3, 2, 4}, std::vector<T_OUT>{
-                5, 5, 5, 5, 5, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 5, 5, 5, 5,
-                3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3,
-                5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 5, 5, 5,
-                3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 4, 1, 1, 1, 1, 1, 1, 5, 1, 3, 3
-            }),
+            reference_tests::Tensor(
+                ET,
+                {2, 2, 3, 2, 4},
+                std::vector<T>{169, 241, 177, 249, 185, 233, 170, 242, 178, 250, 186, 258, 171, 243, 179, 251,
+                               187, 259, 172, 224, 180, 252, 188, 260, 149, 221, 157, 229, 165, 113, 150, 222,
+                               158, 230, 166, 234, 151, 223, 159, 231, 163, 235, 148, 220, 160, 232, 168, 240,
+                               197, 269, 205, 277, 213, 285, 198, 270, 206, 278, 214, 286, 199, 271, 207, 279,
+                               215, 287, 200, 272, 241, 280, 216, 288, 193, 265, 201, 273, 209, 281, 194, 266,
+                               202, 274, 210, 262, 175, 127, 183, 255, 191, 263, 176, 248, 208, 256, 212, 284}),
+            reference_tests::Tensor(
+                ET_OUT,
+                {2, 2, 3, 2, 4},
+                std::vector<T_OUT>{5, 5, 5, 5, 5, 1, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 5, 5, 5, 5,
+                                   3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3,
+                                   5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 5, 5, 5,
+                                   3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 1, 4, 1, 1, 1, 1, 1, 1, 5, 1, 3, 3}),
             1,
             "topk_5d_max_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                10, 12, 9, 4, 11, 7, 6, 3
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{
-                1, 1, 0, 2, 2, 2, 0, 1
-            }),
-            0,
-            "topk_3d_max_partial"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{10, 12, 9, 4, 11, 7, 6, 3}),
+                   reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{1, 1, 0, 2, 2, 2, 0, 1}),
+                   0,
+                   "topk_3d_max_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                10, 12, 9, 4, 11, 7, 6, 3
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{
-                1, 1, 0, 2, 2, 2, 0, 1
-            }),
-            1,
-            "topk_3d_max_partial"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{10, 12, 9, 4, 11, 7, 6, 3}),
+                   reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{1, 1, 0, 2, 2, 2, 0, 1}),
+                   1,
+                   "topk_3d_max_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 1, 2}, std::vector<T>{
-                10, 12, 11, 7
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 1, 2}, std::vector<T_OUT>{
-                1, 1, 2, 2
-            }),
-            0,
-            "topk_3d_max_one"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 1, 2}, std::vector<T>{10, 12, 11, 7}),
+                   reference_tests::Tensor(ET_OUT, {2, 1, 2}, std::vector<T_OUT>{1, 1, 2, 2}),
+                   0,
+                   "topk_3d_max_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 1, 2}, std::vector<T>{
-                10, 12, 11, 7
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 1, 2}, std::vector<T_OUT>{
-                1, 1, 2, 2
-            }),
-            1,
-            "topk_3d_max_one"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 1, 2}, std::vector<T>{10, 12, 11, 7}),
+                   reference_tests::Tensor(ET_OUT, {2, 1, 2}, std::vector<T_OUT>{1, 1, 2, 2}),
+                   1,
+                   "topk_3d_max_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                8, 2, 10, 4, 12, 9, 5, 1, 6, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{
-                2, 0, 1, 2, 0, 1, 1, 0, 0, 1, 2, 2
-            }),
-            0,
-            "topk_3d_min_all"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{8, 2, 10, 4, 12, 9, 5, 1, 6, 3, 11, 7}),
+                   reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{2, 0, 1, 2, 0, 1, 1, 0, 0, 1, 2, 2}),
+                   0,
+                   "topk_3d_min_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                8, 2, 10, 4, 12, 9, 5, 1, 6, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{
-                2, 0, 1, 2, 0, 1, 1, 0, 0, 1, 2, 2
-            }),
-            1,
-            "topk_3d_min_all"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{8, 2, 10, 4, 12, 9, 5, 1, 6, 3, 11, 7}),
+                   reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{2, 0, 1, 2, 0, 1, 1, 0, 0, 1, 2, 2}),
+                   1,
+                   "topk_3d_min_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                8, 2, 10, 4, 5, 1, 6, 3
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{
-                2, 0, 1, 2, 1, 0, 0, 1
-            }),
-            0,
-            "topk_3d_min_partial"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{8, 2, 10, 4, 5, 1, 6, 3}),
+                   reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{2, 0, 1, 2, 1, 0, 0, 1}),
+                   0,
+                   "topk_3d_min_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{
-                8, 2, 10, 4, 5, 1, 6, 3
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{
-                2, 0, 1, 2, 1, 0, 0, 1
-            }),
-            1,
-            "topk_3d_min_partial"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{8, 2, 10, 4, 5, 1, 6, 3}),
+                   reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{2, 0, 1, 2, 1, 0, 0, 1}),
+                   1,
+                   "topk_3d_min_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 1, 2}, std::vector<T>{
-                8, 2, 5, 1
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 1, 2}, std::vector<T_OUT>{
-                2, 0, 1, 0
-            }),
-            0,
-            "topk_3d_min_one"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 1, 2}, std::vector<T>{8, 2, 5, 1}),
+                   reference_tests::Tensor(ET_OUT, {2, 1, 2}, std::vector<T_OUT>{2, 0, 1, 0}),
+                   0,
+                   "topk_3d_min_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 1, 2}, std::vector<T>{
-                8, 2, 5, 1
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 1, 2}, std::vector<T_OUT>{
-                2, 0, 1, 0
-            }),
-            1,
-            "topk_3d_min_one"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 1, 2}, std::vector<T>{8, 2, 5, 1}),
+                   reference_tests::Tensor(ET_OUT, {2, 1, 2}, std::vector<T_OUT>{2, 0, 1, 0}),
+                   1,
+                   "topk_3d_min_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{4}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                12, 11, 10, 9, 8, 7, 6, 2, 5, 3, 1, 4
-            }),
-            reference_tests::Tensor(ET_OUT, {4, 3}, std::vector<T_OUT>{
-                1, 3, 0, 0, 1, 3, 2, 0, 2, 3, 2, 1
-            }),
-            0,
-            "topk_2d_max_all"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{4}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {4, 3}, std::vector<T>{12, 11, 10, 9, 8, 7, 6, 2, 5, 3, 1, 4}),
+                   reference_tests::Tensor(ET_OUT, {4, 3}, std::vector<T_OUT>{1, 3, 0, 0, 1, 3, 2, 0, 2, 3, 2, 1}),
+                   0,
+                   "topk_2d_max_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{4}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                12, 11, 10, 9, 8, 7, 6, 2, 5, 3, 1, 4
-            }),
-            reference_tests::Tensor(ET_OUT, {4, 3}, std::vector<T_OUT>{
-                1, 3, 0, 0, 1, 3, 2, 0, 2, 3, 2, 1
-            }),
-            1,
-            "topk_2d_max_all"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{4}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {4, 3}, std::vector<T>{12, 11, 10, 9, 8, 7, 6, 2, 5, 3, 1, 4}),
+                   reference_tests::Tensor(ET_OUT, {4, 3}, std::vector<T_OUT>{1, 3, 0, 0, 1, 3, 2, 0, 2, 3, 2, 1}),
+                   1,
+                   "topk_2d_max_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                12, 11, 10, 9, 8, 7
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3}, std::vector<T_OUT>{
-                1, 3, 0, 0, 1, 3
-            }),
-            0,
-            "topk_2d_max_partial"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3}, std::vector<T>{12, 11, 10, 9, 8, 7}),
+                   reference_tests::Tensor(ET_OUT, {2, 3}, std::vector<T_OUT>{1, 3, 0, 0, 1, 3}),
+                   0,
+                   "topk_2d_max_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                12, 11, 10, 9, 8, 7
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3}, std::vector<T_OUT>{
-                1, 3, 0, 0, 1, 3
-            }),
-            1,
-            "topk_2d_max_partial"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3}, std::vector<T>{12, 11, 10, 9, 8, 7}),
+                   reference_tests::Tensor(ET_OUT, {2, 3}, std::vector<T_OUT>{1, 3, 0, 0, 1, 3}),
+                   1,
+                   "topk_2d_max_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {1, 3}, std::vector<T>{
-                12, 11, 10
-            }),
-            reference_tests::Tensor(ET_OUT, {1, 3}, std::vector<T_OUT>{
-                1, 3, 0
-            }),
-            0,
-            "topk_2d_max_one"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {1, 3}, std::vector<T>{12, 11, 10}),
+                   reference_tests::Tensor(ET_OUT, {1, 3}, std::vector<T_OUT>{1, 3, 0}),
+                   0,
+                   "topk_2d_max_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            0,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {1, 3}, std::vector<T>{
-                12, 11, 10
-            }),
-            reference_tests::Tensor(ET_OUT, {1, 3}, std::vector<T_OUT>{
-                1, 3, 0
-            }),
-            1,
-            "topk_2d_max_one"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   0,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {1, 3}, std::vector<T>{12, 11, 10}),
+                   reference_tests::Tensor(ET_OUT, {1, 3}, std::vector<T_OUT>{1, 3, 0}),
+                   1,
+                   "topk_2d_max_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{
-                1, 3, 2, 4, 1, 3, 3, 2
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 1}, std::vector<T>{
-                4, 3
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 1}, std::vector<T_OUT>{
-                3, 1
-            }),
-            0,
-            "topk_2d_max_one_with_equal_values"),
+        TopKParams(reference_tests::Tensor(ET, {2, 4}, std::vector<T>{1, 3, 2, 4, 1, 3, 3, 2}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 1}, std::vector<T>{4, 3}),
+                   reference_tests::Tensor(ET_OUT, {2, 1}, std::vector<T_OUT>{3, 1}),
+                   0,
+                   "topk_2d_max_one_with_equal_values"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 4}, std::vector<T>{
-                1, 3, 2, 4, 1, 3, 3, 2
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 1}, std::vector<T>{
-                4, 3
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 1}, std::vector<T_OUT>{
-                3, 1
-            }),
-            1,
-            "topk_2d_max_one_with_equal_values"),
+        TopKParams(reference_tests::Tensor(ET, {2, 4}, std::vector<T>{1, 3, 2, 4, 1, 3, 3, 2}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 1}, std::vector<T>{4, 3}),
+                   reference_tests::Tensor(ET_OUT, {2, 1}, std::vector<T_OUT>{3, 1}),
+                   1,
+                   "topk_2d_max_one_with_equal_values"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{4}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                3, 1, 4, 6, 2, 5, 9, 8, 7, 12, 11, 10
-            }),
-            reference_tests::Tensor(ET_OUT, {4, 3}, std::vector<T_OUT>{
-                3, 2, 1, 2, 0, 2, 1, 1, 3, 0, 3, 0
-            }),
-            0,
-            "topk_2d_min_all"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{4}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {4, 3}, std::vector<T>{3, 1, 4, 6, 2, 5, 9, 8, 7, 12, 11, 10}),
+                   reference_tests::Tensor(ET_OUT, {4, 3}, std::vector<T_OUT>{3, 2, 1, 2, 0, 2, 1, 1, 3, 0, 3, 0}),
+                   0,
+                   "topk_2d_min_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{4}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                3, 1, 4, 6, 2, 5, 9, 8, 7, 12, 11, 10
-            }),
-            reference_tests::Tensor(ET_OUT, {4, 3}, std::vector<T_OUT>{
-                3, 2, 1, 2, 0, 2, 1, 1, 3, 0, 3, 0
-            }),
-            1,
-            "topk_2d_min_all"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{4}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {4, 3}, std::vector<T>{3, 1, 4, 6, 2, 5, 9, 8, 7, 12, 11, 10}),
+                   reference_tests::Tensor(ET_OUT, {4, 3}, std::vector<T_OUT>{3, 2, 1, 2, 0, 2, 1, 1, 3, 0, 3, 0}),
+                   1,
+                   "topk_2d_min_all"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                3, 1, 4, 6, 2, 5
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3}, std::vector<T_OUT>{
-                3, 2, 1, 2, 0, 2
-            }),
-            0,
-            "topk_2d_min_partial"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3}, std::vector<T>{3, 1, 4, 6, 2, 5}),
+                   reference_tests::Tensor(ET_OUT, {2, 3}, std::vector<T_OUT>{3, 2, 1, 2, 0, 2}),
+                   0,
+                   "topk_2d_min_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3}, std::vector<T>{
-                3, 1, 4, 6, 2, 5
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3}, std::vector<T_OUT>{
-                3, 2, 1, 2, 0, 2
-            }),
-            1,
-            "topk_2d_min_partial"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3}, std::vector<T>{3, 1, 4, 6, 2, 5}),
+                   reference_tests::Tensor(ET_OUT, {2, 3}, std::vector<T_OUT>{3, 2, 1, 2, 0, 2}),
+                   1,
+                   "topk_2d_min_partial"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::NONE,
-            reference_tests::Tensor(ET, {1, 3}, std::vector<T>{
-                3, 1, 4
-            }),
-            reference_tests::Tensor(ET_OUT, {1, 3}, std::vector<T_OUT>{
-                3, 2, 1
-            }),
-            0,
-            "topk_2d_min_one"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::NONE,
+                   reference_tests::Tensor(ET, {1, 3}, std::vector<T>{3, 1, 4}),
+                   reference_tests::Tensor(ET_OUT, {1, 3}, std::vector<T_OUT>{3, 2, 1}),
+                   0,
+                   "topk_2d_min_one"),
 
-        TopKParams(
-            reference_tests::Tensor(ET, {4, 3}, std::vector<T>{
-                12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
-            0,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::NONE,
-            reference_tests::Tensor(ET, {1, 3}, std::vector<T>{
-                3, 1, 4
-            }),
-            reference_tests::Tensor(ET_OUT, {1, 3}, std::vector<T_OUT>{
-                3, 2, 1
-            }),
-            1,
-            "topk_2d_min_one"),
+        TopKParams(reference_tests::Tensor(ET, {4, 3}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{1}),
+                   0,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::NONE,
+                   reference_tests::Tensor(ET, {1, 3}, std::vector<T>{3, 1, 4}),
+                   reference_tests::Tensor(ET_OUT, {1, 3}, std::vector<T_OUT>{3, 2, 1}),
+                   1,
+                   "topk_2d_min_one"),
     };
     return params;
 }
 
 std::vector<TopKParams> generateCombinedParams1dMaxMin() {
-    const std::vector<std::vector<TopKParams>> generatedParams {
+    const std::vector<std::vector<TopKParams>> generatedParams{
         generateParams1dMaxMin<element::Type_t::i16, element::Type_t::i64, element::Type_t::i32>(),
         generateParams1dMaxMin<element::Type_t::i32, element::Type_t::i64, element::Type_t::i32>(),
         generateParams1dMaxMin<element::Type_t::i64, element::Type_t::i64, element::Type_t::i32>(),
@@ -1321,23 +1182,17 @@ std::vector<TopKParams> generateCombinedParams1dMaxMin() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTest1dMaxMin,
-    testing::ValuesIn(generateCombinedParams1dMaxMin()), ReferenceTopKTest1dMaxMin::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTest1dMaxMin,
+                         testing::ValuesIn(generateCombinedParams1dMaxMin()),
+                         ReferenceTopKTest1dMaxMin::getTestCaseName);
 
 class ReferenceTopKTestInt64 : public ReferenceTopKTest1dMaxMin {
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params, size_t out_idx) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
-        const auto B = std::make_shared<opset1::TopK>(A,
-                                                      k,
-                                                      params.axis,
-                                                      params.mode,
-                                                      params.sort,
-                                                      element::i64);
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
+        const auto B = std::make_shared<opset1::TopK>(A, k, params.axis, params.mode, params.sort, element::i64);
         const auto f = std::make_shared<Model>(OutputVector{B->output(out_idx)}, ParameterVector{A});
         return f;
     }
@@ -1352,45 +1207,31 @@ std::vector<TopKParams> generateParamsInt64() {
     using T = typename element_type_traits<ET>::value_type;
     using T2 = typename element_type_traits<ET2>::value_type;
     using T_OUT = typename element_type_traits<ET_OUT>::value_type;
-    std::vector<TopKParams> params {
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                10, 12, 9, 4, 8, 2, 11, 7, 6, 3, 5, 1
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{
-                1, 1, 0, 2, 2, 0, 2, 2, 0, 1, 1, 0
-            }),
-            0,
-            "topk_int64"),
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7
-            }),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
-            1,
-            opset1::TopK::Mode::MAX,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{
-                10, 12, 9, 4, 8, 2, 11, 7, 6, 3, 5, 1
-            }),
-            reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{
-                1, 1, 0, 2, 2, 0, 2, 2, 0, 1, 1, 0
-            }),
-            1,
-            "topk_int64"),
+    std::vector<TopKParams> params{
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{10, 12, 9, 4, 8, 2, 11, 7, 6, 3, 5, 1}),
+                   reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{1, 1, 0, 2, 2, 0, 2, 2, 0, 1, 1, 0}),
+                   0,
+                   "topk_int64"),
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{9, 2, 10, 12, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{3}),
+                   1,
+                   opset1::TopK::Mode::MAX,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{10, 12, 9, 4, 8, 2, 11, 7, 6, 3, 5, 1}),
+                   reference_tests::Tensor(ET_OUT, {2, 3, 2}, std::vector<T_OUT>{1, 1, 0, 2, 2, 0, 2, 2, 0, 1, 1, 0}),
+                   1,
+                   "topk_int64"),
     };
     return params;
 }
 
 std::vector<TopKParams> generateCombinedParamsInt64() {
-    const std::vector<std::vector<TopKParams>> generatedParams {
+    const std::vector<std::vector<TopKParams>> generatedParams{
         generateParamsInt64<element::Type_t::f32, element::Type_t::i64, element::Type_t::i32>(),
     };
     std::vector<TopKParams> combinedParams;
@@ -1401,8 +1242,10 @@ std::vector<TopKParams> generateCombinedParamsInt64() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestInt64,
-    testing::ValuesIn(generateCombinedParamsInt64()), ReferenceTopKTest1dMaxMin::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestInt64,
+                         testing::ValuesIn(generateCombinedParamsInt64()),
+                         ReferenceTopKTest1dMaxMin::getTestCaseName);
 
 class ReferenceTopKTestSingleOutput : public ReferenceTopKTest {
 public:
@@ -1415,11 +1258,8 @@ class ReferenceTopKTestSingleOutput : public ReferenceTopKTest {
 
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
         const auto B = std::make_shared<opset1::TopK>(A, k, params.axis, params.mode, params.sort);
         const auto f = std::make_shared<Model>(OutputVector{B->output(1)}, ParameterVector{A});
         return f;
@@ -1435,23 +1275,22 @@ std::vector<TopKParams> generateParamsSingleOutput() {
     using T = typename element_type_traits<ET>::value_type;
     using T2 = typename element_type_traits<ET2>::value_type;
     using T_OUT = typename element_type_traits<ET_OUT>::value_type;
-    std::vector<TopKParams> params {
-        TopKParams(
-            reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
-            reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
-            1,
-            opset1::TopK::Mode::MIN,
-            opset1::TopK::SortType::SORT_VALUES,
-            reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{}),
-            reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{2, 0, 1, 2, 1, 0, 0, 1}),
-            0,
-            "topk_3d_single_output"),
+    std::vector<TopKParams> params{
+        TopKParams(reference_tests::Tensor(ET, {2, 3, 2}, std::vector<T>{12, 2, 10, 9, 8, 4, 6, 1, 5, 3, 11, 7}),
+                   reference_tests::Tensor(ET2, {}, std::vector<T2>{2}),
+                   1,
+                   opset1::TopK::Mode::MIN,
+                   opset1::TopK::SortType::SORT_VALUES,
+                   reference_tests::Tensor(ET, {2, 2, 2}, std::vector<T>{}),
+                   reference_tests::Tensor(ET_OUT, {2, 2, 2}, std::vector<T_OUT>{2, 0, 1, 2, 1, 0, 0, 1}),
+                   0,
+                   "topk_3d_single_output"),
     };
     return params;
 }
 
 std::vector<TopKParams> generateCombinedParamsSingleOutput() {
-    const std::vector<std::vector<TopKParams>> generatedParams {
+    const std::vector<std::vector<TopKParams>> generatedParams{
         generateParamsSingleOutput<element::Type_t::i8, element::Type_t::i64, element::Type_t::i32>(),
         generateParamsSingleOutput<element::Type_t::i16, element::Type_t::i64, element::Type_t::i32>(),
         generateParamsSingleOutput<element::Type_t::i32, element::Type_t::i64, element::Type_t::i32>(),
@@ -1473,8 +1312,10 @@ std::vector<TopKParams> generateCombinedParamsSingleOutput() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestSingleOutput,
-    testing::ValuesIn(generateCombinedParamsSingleOutput()), ReferenceTopKTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestSingleOutput,
+                         testing::ValuesIn(generateCombinedParamsSingleOutput()),
+                         ReferenceTopKTest::getTestCaseName);
 
 TEST(ReferenceTopKTestInvalid, topk_v1_invalid_strings) {
     const auto data = std::make_shared<opset1::Parameter>(element::f32, Shape{1, 2, 3});
@@ -1493,14 +1334,10 @@ TEST(ReferenceTopKTestInvalid, topk_v1_invalid_k) {
     EXPECT_THROW(opset1::TopK(data, k_negative, 0, "max", "index"), ov::NodeValidationFailure);
 }
 
-
-
-
 class ReferenceTopKTestResnet50V3 : public ReferenceTopKTestResnet50 {
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParamsResnet50& params) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
         const auto B = std::make_shared<opset3::TopK>(A,
                                                       opset1::Constant::create(element::i64, {}, {5}),
                                                       1,
@@ -1516,7 +1353,8 @@ class ReferenceTopKTestResnet50V3 : public ReferenceTopKTestResnet50 {
         const auto out5_index = B->output(1);
         const auto out1_value = C->output(0);
         const auto out1_index = C->output(1);
-        const auto f = std::make_shared<Model>(OutputVector{out5_value, out5_index, out1_value, out1_index}, ParameterVector{A});
+        const auto f =
+            std::make_shared<Model>(OutputVector{out5_value, out5_index, out1_value, out1_index}, ParameterVector{A});
         return f;
     }
 };
@@ -1525,17 +1363,16 @@ TEST_P(ReferenceTopKTestResnet50V3, CompareWithRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestResnet50V3,
-    testing::ValuesIn(generateCombinedParamsResnet50()), ReferenceTopKTestResnet50V3::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestResnet50V3,
+                         testing::ValuesIn(generateCombinedParamsResnet50()),
+                         ReferenceTopKTestResnet50V3::getTestCaseName);
 
 class ReferenceTopKTestMaxMinSortV3 : public ReferenceTopKTestMaxMinSort {
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
         const auto B = std::make_shared<opset3::TopK>(A, k, params.axis, params.mode, params.sort);
         const auto f = std::make_shared<Model>(B->outputs(), ParameterVector{A});
         return f;
@@ -1546,17 +1383,16 @@ TEST_P(ReferenceTopKTestMaxMinSortV3, CompareWithRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestMaxMinSortV3,
-    testing::ValuesIn(generateCombinedParamsMaxMinSort()), ReferenceTopKTestMaxMinSortV3::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestMaxMinSortV3,
+                         testing::ValuesIn(generateCombinedParamsMaxMinSort()),
+                         ReferenceTopKTestMaxMinSortV3::getTestCaseName);
 
 class ReferenceTopKTestBackendV3 : public ReferenceTopKTestBackend {
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
         const auto B = std::make_shared<opset3::TopK>(A, k, params.axis, params.mode, params.sort);
         const auto f = std::make_shared<Model>(B->outputs(), ParameterVector{A});
         return f;
@@ -1567,17 +1403,16 @@ TEST_P(ReferenceTopKTestBackendV3, CompareWithRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestBackendV3,
-    testing::ValuesIn(generateCombinedParamsBackend()), ReferenceTopKTestBackendV3::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestBackendV3,
+                         testing::ValuesIn(generateCombinedParamsBackend()),
+                         ReferenceTopKTestBackendV3::getTestCaseName);
 
 class ReferenceTopKTest1dMaxMinV3 : public ReferenceTopKTest1dMaxMin {
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params, size_t out_idx) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
         const auto B = std::make_shared<opset3::TopK>(A, k, params.axis, params.mode, params.sort);
         const auto f = std::make_shared<Model>(OutputVector{B->output(out_idx)}, ParameterVector{A});
         return f;
@@ -1588,23 +1423,17 @@ TEST_P(ReferenceTopKTest1dMaxMinV3, CompareWithRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTest1dMaxMinV3,
-    testing::ValuesIn(generateCombinedParams1dMaxMin()), ReferenceTopKTest1dMaxMinV3::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTest1dMaxMinV3,
+                         testing::ValuesIn(generateCombinedParams1dMaxMin()),
+                         ReferenceTopKTest1dMaxMinV3::getTestCaseName);
 
 class ReferenceTopKTestInt64V3 : public ReferenceTopKTestInt64 {
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params, size_t out_idx) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
-        const auto B = std::make_shared<opset3::TopK>(A,
-                                                      k,
-                                                      params.axis,
-                                                      params.mode,
-                                                      params.sort,
-                                                      element::i64);
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
+        const auto B = std::make_shared<opset3::TopK>(A, k, params.axis, params.mode, params.sort, element::i64);
         const auto f = std::make_shared<Model>(OutputVector{B->output(out_idx)}, ParameterVector{A});
         return f;
     }
@@ -1614,17 +1443,16 @@ TEST_P(ReferenceTopKTestInt64V3, CompareWithRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestInt64V3,
-    testing::ValuesIn(generateCombinedParamsInt64()), ReferenceTopKTestInt64V3::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestInt64V3,
+                         testing::ValuesIn(generateCombinedParamsInt64()),
+                         ReferenceTopKTestInt64V3::getTestCaseName);
 
 class ReferenceTopKTestSingleOutputV3 : public ReferenceTopKTestSingleOutput {
 private:
     static std::shared_ptr<Model> CreateFunction(const TopKParams& params) {
-        const auto A = std::make_shared<opset1::Parameter>(params.A.type,
-                                                           params.A.shape);
-        const auto k = opset1::Constant::create(params.k.type,
-                                                params.k.shape,
-                                                params.k.data.data());
+        const auto A = std::make_shared<opset1::Parameter>(params.A.type, params.A.shape);
+        const auto k = opset1::Constant::create(params.k.type, params.k.shape, params.k.data.data());
         const auto B = std::make_shared<opset3::TopK>(A, k, params.axis, params.mode, params.sort);
         const auto f = std::make_shared<Model>(OutputVector{B->output(1)}, ParameterVector{A});
         return f;
@@ -1635,8 +1463,10 @@ TEST_P(ReferenceTopKTestSingleOutputV3, CompareWithRefs) {
     Exec();
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs, ReferenceTopKTestSingleOutputV3,
-    testing::ValuesIn(generateCombinedParamsSingleOutput()), ReferenceTopKTestSingleOutputV3::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
+                         ReferenceTopKTestSingleOutputV3,
+                         testing::ValuesIn(generateCombinedParamsSingleOutput()),
+                         ReferenceTopKTestSingleOutputV3::getTestCaseName);
 
 TEST(ReferenceTopKTestInvalidV3, topk_v3_invalid_strings) {
     const auto data = std::make_shared<opset1::Parameter>(element::f32, Shape{1, 2, 3});
@@ -1753,4 +1583,4 @@ INSTANTIATE_TEST_SUITE_P(smoke_TopK_With_Hardcoded_Refs,
                          testing::ValuesIn(generateCombinedParamsForStableTest()),
                          ReferenceTopKv11StableTest::getTestCaseName);
 
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/transpose.cpp b/src/plugins/template/tests/functional/op_reference/transpose.cpp
index 44d45f2710cf3d..0ebb36e781b3bf 100644
--- a/src/plugins/template/tests/functional/op_reference/transpose.cpp
+++ b/src/plugins/template/tests/functional/op_reference/transpose.cpp
@@ -2,13 +2,14 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/transpose.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/transpose.hpp"
-#include "openvino/op/constant.hpp"
-#include "openvino/op/convert.hpp"
 #include "base_reference_test.hpp"
 #include "common_test_utils/type_prop.hpp"
+#include "openvino/op/constant.hpp"
+#include "openvino/op/convert.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -33,7 +34,7 @@ struct TransposeParams {
     reference_tests::Tensor axisTensor;
     reference_tests::Tensor expectedTensor;
     std::string testcaseName;
-    std::pair<std::string,std::string> expectedException;
+    std::pair<std::string, std::string> expectedException;
 };
 
 class ReferenceTransposeLayerTest : public testing::TestWithParam<TransposeParams>, public CommonReferenceTest {
@@ -68,17 +69,19 @@ class ReferenceTransposeLayerTest : public testing::TestWithParam<TransposeParam
         std::shared_ptr<Model> function;
         if (params.dynamicDataShape.is_static()) {
             const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, params.dataTensor.shape);
-            const auto axis = std::make_shared<op::v0::Constant>(params.axisTensor.type, params.axisTensor.shape,
+            const auto axis = std::make_shared<op::v0::Constant>(params.axisTensor.type,
+                                                                 params.axisTensor.shape,
                                                                  params.axisTensor.data.data());
             const auto axisI64 = std::make_shared<op::v0::Convert>(axis, element::i64);
             const auto transpose = std::make_shared<op::v1::Transpose>(data, axisI64);
-            function = std::make_shared<ov::Model>(NodeVector {transpose}, ParameterVector {data});
+            function = std::make_shared<ov::Model>(NodeVector{transpose}, ParameterVector{data});
         } else {
             const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, PartialShape::dynamic());
-            const auto axis = std::make_shared<op::v0::Parameter>(params.axisTensor.type, PartialShape{Dimension::dynamic()});
+            const auto axis =
+                std::make_shared<op::v0::Parameter>(params.axisTensor.type, PartialShape{Dimension::dynamic()});
             const auto axisI64 = std::make_shared<op::v0::Convert>(axis, element::i64);
             const auto transpose = std::make_shared<op::v1::Transpose>(data, axisI64);
-            function = std::make_shared<ov::Model>(NodeVector {transpose}, ParameterVector {data, axis});
+            function = std::make_shared<ov::Model>(NodeVector{transpose}, ParameterVector{data, axis});
         }
         return function;
     }
@@ -105,7 +108,7 @@ TEST_P(ReferenceTransposeLayerTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<TransposeParams> generateTransposeParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<TransposeParams> transposeParams {
+    std::vector<TransposeParams> transposeParams{
         // transpose_basic
         TransposeParams(PartialShape::dynamic(),
                         reference_tests::Tensor(IN_ET, {2, 3}, std::vector<T>{1, 2, 3, 4, 5, 6}),
@@ -117,51 +120,62 @@ std::vector<TransposeParams> generateTransposeParams() {
                         reference_tests::Tensor(element::i64, {2}, std::vector<int64_t>{1, 0}),
                         reference_tests::Tensor(IN_ET, {3, 2}, std::vector<T>{1, 4, 2, 5, 3, 6}),
                         "transpose_basic_2"),
-        TransposeParams(PartialShape::dynamic(),
-                        reference_tests::Tensor(IN_ET, {2, 2, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
-                        reference_tests::Tensor(element::i64, {3}, std::vector<int64_t>{2, 1, 0}),
-                        reference_tests::Tensor(IN_ET, {3, 2, 2}, std::vector<T>{1, 7, 4, 10, 2, 8, 5, 11, 3, 9, 6, 12}),
-                        "transpose_basic_3"),
+        TransposeParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(IN_ET, {2, 2, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+            reference_tests::Tensor(element::i64, {3}, std::vector<int64_t>{2, 1, 0}),
+            reference_tests::Tensor(IN_ET, {3, 2, 2}, std::vector<T>{1, 7, 4, 10, 2, 8, 5, 11, 3, 9, 6, 12}),
+            "transpose_basic_3"),
         // transpose_axes_constant
-        TransposeParams({},
-                        reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                                   13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
-                        reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{2, 3, 0, 1}),
-                        reference_tests::Tensor(IN_ET, {3, 4, 2, 1}, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
-                                                                   7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
-                        "transpose_axes_constant"),
+        TransposeParams(
+            {},
+            reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{2, 3, 0, 1}),
+            reference_tests::Tensor(IN_ET, {3, 4, 2, 1}, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
+                                                                        7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
+            "transpose_axes_constant"),
         // transpose_axes_empty_constant
-        TransposeParams({},
-                        reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                                   13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
-                        reference_tests::Tensor(element::i64, {0}, std::vector<int64_t>{}),
-                        reference_tests::Tensor(IN_ET, {4, 3, 1, 2}, std::vector<T>{1, 13, 5, 17, 9,  21, 2, 14, 6, 18, 10, 22,
-                                                                   3, 15, 7, 19, 11, 23, 4, 16, 8, 20, 12, 24}),
-                        "transpose_axes_empty_constant"),
+        TransposeParams(
+            {},
+            reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor(element::i64, {0}, std::vector<int64_t>{}),
+            reference_tests::Tensor(IN_ET, {4, 3, 1, 2}, std::vector<T>{1, 13, 5, 17, 9,  21, 2, 14, 6, 18, 10, 22,
+                                                                        3, 15, 7, 19, 11, 23, 4, 16, 8, 20, 12, 24}),
+            "transpose_axes_empty_constant"),
         // transpose_axes_parameter_static_shapes
-        TransposeParams({},
-                        reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                                   13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
-                        reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{2, 3, 0, 1}),
-                        reference_tests::Tensor(IN_ET, {4, 3, 1, 2}, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
-                                                                   7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
-                        "transpose_axes_parameter_static_shapes"),
+        TransposeParams(
+            {},
+            reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{2, 3, 0, 1}),
+            reference_tests::Tensor(IN_ET, {4, 3, 1, 2}, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
+                                                                        7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
+            "transpose_axes_parameter_static_shapes"),
         // transpose_axes_parameter_dynamic_shapes
-        TransposeParams(PartialShape::dynamic(),
-                        reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                                   13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
-                        reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{2, 3, 0, 1}),
-                        reference_tests::Tensor(IN_ET, {4, 3, 1, 2}, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
-                                                                   7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
-                        "transpose_axes_parameter_dynamic_shapes"),
+        TransposeParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{2, 3, 0, 1}),
+            reference_tests::Tensor(IN_ET, {4, 3, 1, 2}, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
+                                                                        7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
+            "transpose_axes_parameter_dynamic_shapes"),
         // transpose_int_data_axes_constant
-        TransposeParams({},
-                        reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
-                                                                   13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
-                        reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{2, 3, 0, 1}),
-                        reference_tests::Tensor(IN_ET, {3, 4, 2, 1}, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
-                                                                   7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
-                        "transpose_int_data_axes_constant"),
+        TransposeParams(
+            {},
+            reference_tests::Tensor(IN_ET, {2, 1, 3, 4}, std::vector<T>{1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16,
+                                                                        17, 18, 19, 20, 21, 22, 23, 24}),
+            reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{2, 3, 0, 1}),
+            reference_tests::Tensor(IN_ET, {3, 4, 2, 1}, std::vector<T>{1, 13, 2, 14, 3, 15, 4,  16, 5,  17, 6,  18,
+                                                                        7, 19, 8, 20, 9, 21, 10, 22, 11, 23, 12, 24}),
+            "transpose_int_data_axes_constant"),
     };
     return transposeParams;
 }
@@ -192,7 +206,7 @@ std::vector<TransposeParams> generateThrowingTransposeParams() {
 }
 
 std::vector<TransposeParams> generateTransposeCombinedParams() {
-    const std::vector<std::vector<TransposeParams>> transposeTypeParams {
+    const std::vector<std::vector<TransposeParams>> transposeTypeParams{
         generateTransposeParams<element::Type_t::i8>(),
         generateTransposeParams<element::Type_t::i16>(),
         generateTransposeParams<element::Type_t::i32>(),
@@ -214,6 +228,8 @@ std::vector<TransposeParams> generateTransposeCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Transpose_With_Hardcoded_Refs, ReferenceTransposeLayerTest,
-    testing::ValuesIn(generateTransposeCombinedParams()), ReferenceTransposeLayerTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Transpose_With_Hardcoded_Refs,
+                         ReferenceTransposeLayerTest,
+                         testing::ValuesIn(generateTransposeCombinedParams()),
+                         ReferenceTransposeLayerTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/unsqueeze.cpp b/src/plugins/template/tests/functional/op_reference/unsqueeze.cpp
index 0fedf476e99ec3..f486035de10dd1 100644
--- a/src/plugins/template/tests/functional/op_reference/unsqueeze.cpp
+++ b/src/plugins/template/tests/functional/op_reference/unsqueeze.cpp
@@ -2,11 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/unsqueeze.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/unsqueeze.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
@@ -16,14 +17,14 @@ namespace {
 struct UnsqueezeParams {
     template <class IO_T, class Axes_T>
     UnsqueezeParams(const Shape& input_shape,
-                  const Shape& expected_shape,
-                  const element::Type& input_type,
-                  const element::Type& expected_type,
-                  const std::vector<IO_T>& input_value,
-                  const std::vector<IO_T>& expected_value,
-                  const Shape& axes_shape,
-                  const element::Type& axes_type,
-                  const std::vector<Axes_T>& axes_value)
+                    const Shape& expected_shape,
+                    const element::Type& input_type,
+                    const element::Type& expected_type,
+                    const std::vector<IO_T>& input_value,
+                    const std::vector<IO_T>& expected_value,
+                    const Shape& axes_shape,
+                    const element::Type& axes_type,
+                    const std::vector<Axes_T>& axes_value)
         : m_input_shape(input_shape),
           m_expected_shape(expected_shape),
           m_input_type(input_type),
@@ -74,10 +75,10 @@ class ReferenceUnsqueezeLayerTest : public testing::TestWithParam<UnsqueezeParam
 
 private:
     static std::shared_ptr<Model> CreateFunction(const element::Type_t& input_type,
-                                                    const Shape& input_shape,
-                                                    const element::Type& axes_type,
-                                                    const Shape& axes_shape,
-                                                    const ov::Tensor& axes_value) {
+                                                 const Shape& input_shape,
+                                                 const element::Type& axes_type,
+                                                 const Shape& axes_shape,
+                                                 const ov::Tensor& axes_value) {
         const auto in = std::make_shared<op::v0::Parameter>(input_type, input_shape);
         const auto axes = std::make_shared<op::v0::Constant>(axes_type, axes_shape, axes_value.data());
         const auto unsqueeze = std::make_shared<op::v0::Unsqueeze>(in, axes);
@@ -94,17 +95,15 @@ std::vector<UnsqueezeParams> generateParamsForUnsqueeze() {
     using T1 = typename element_type_traits<IO_T>::value_type;
     using T2 = typename element_type_traits<Axes_T>::value_type;
 
-    std::vector<UnsqueezeParams> params{
-        UnsqueezeParams(Shape{4, 2},
-                      Shape{4, 1, 1, 2},
-                      IO_T,
-                      IO_T,
-                      std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
-                      std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
-                      Shape {2},
-                      Axes_T,
-                      std::vector<T2>{1, 2})
-    };
+    std::vector<UnsqueezeParams> params{UnsqueezeParams(Shape{4, 2},
+                                                        Shape{4, 1, 1, 2},
+                                                        IO_T,
+                                                        IO_T,
+                                                        std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
+                                                        std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
+                                                        Shape{2},
+                                                        Axes_T,
+                                                        std::vector<T2>{1, 2})};
 
     return params;
 }
@@ -114,17 +113,15 @@ std::vector<UnsqueezeParams> generateParamsForUnsqueezeNegative() {
     using T1 = typename element_type_traits<IO_T>::value_type;
     using T2 = typename element_type_traits<Axes_T>::value_type;
 
-    std::vector<UnsqueezeParams> params{
-        UnsqueezeParams(Shape{4, 2},
-                      Shape{4, 1, 2, 1},
-                      IO_T,
-                      IO_T,
-                      std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
-                      std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
-                      Shape {2},
-                      Axes_T,
-                      std::vector<T2>{1, -1})
-    };
+    std::vector<UnsqueezeParams> params{UnsqueezeParams(Shape{4, 2},
+                                                        Shape{4, 1, 2, 1},
+                                                        IO_T,
+                                                        IO_T,
+                                                        std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
+                                                        std::vector<T1>{1, 2, 3, 4, 5, 6, 7, 8},
+                                                        Shape{2},
+                                                        Axes_T,
+                                                        std::vector<T2>{1, -1})};
 
     return params;
 }
@@ -162,10 +159,9 @@ std::vector<UnsqueezeParams> generateCombinedParamsForUnsqueeze() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_Unsqueeze_With_Hardcoded_Refs,
-    ReferenceUnsqueezeLayerTest,
-    ::testing::ValuesIn(generateCombinedParamsForUnsqueeze()),
-    ReferenceUnsqueezeLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Unsqueeze_With_Hardcoded_Refs,
+                         ReferenceUnsqueezeLayerTest,
+                         ::testing::ValuesIn(generateCombinedParamsForUnsqueeze()),
+                         ReferenceUnsqueezeLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/op_reference/variadic_split.cpp b/src/plugins/template/tests/functional/op_reference/variadic_split.cpp
index 68eb1267f38297..1f32da3440be1c 100644
--- a/src/plugins/template/tests/functional/op_reference/variadic_split.cpp
+++ b/src/plugins/template/tests/functional/op_reference/variadic_split.cpp
@@ -2,23 +2,30 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "openvino/op/variadic_split.hpp"
+
 #include <gtest/gtest.h>
 
-#include "openvino/op/variadic_split.hpp"
-#include "openvino/op/constant.hpp"
 #include "base_reference_test.hpp"
+#include "openvino/op/constant.hpp"
 
 using namespace reference_tests;
 using namespace ov;
 
 namespace {
 struct VariadicSplitParams {
-    VariadicSplitParams(const ov::PartialShape& dynamicDataShape, const reference_tests::Tensor& dataTensor,
-                        const reference_tests::Tensor& axisTensor, const reference_tests::Tensor& splitLengthTensor,
-                        const std::vector<reference_tests::Tensor>& expectedTensors, const std::string& testcaseName = "") :
-                        dynamicDataShape(dynamicDataShape), dataTensor(dataTensor),
-                        axisTensor(axisTensor), splitLengthTensor(splitLengthTensor),
-                        expectedTensors(expectedTensors), testcaseName(testcaseName) {}
+    VariadicSplitParams(const ov::PartialShape& dynamicDataShape,
+                        const reference_tests::Tensor& dataTensor,
+                        const reference_tests::Tensor& axisTensor,
+                        const reference_tests::Tensor& splitLengthTensor,
+                        const std::vector<reference_tests::Tensor>& expectedTensors,
+                        const std::string& testcaseName = "")
+        : dynamicDataShape(dynamicDataShape),
+          dataTensor(dataTensor),
+          axisTensor(axisTensor),
+          splitLengthTensor(splitLengthTensor),
+          expectedTensors(expectedTensors),
+          testcaseName(testcaseName) {}
 
     ov::PartialShape dynamicDataShape;
     reference_tests::Tensor dataTensor;
@@ -80,13 +87,13 @@ class ReferenceVariadicSplitTest : public testing::TestWithParam<VariadicSplitPa
     static std::shared_ptr<Model> CreateDynamicFunction(const VariadicSplitParams& params) {
         const auto data = std::make_shared<op::v0::Parameter>(params.dataTensor.type, params.dynamicDataShape);
         const auto axis = std::make_shared<op::v0::Parameter>(params.axisTensor.type, params.axisTensor.shape);
-        const auto splitLengths = std::make_shared<op::v0::Parameter>(params.splitLengthTensor.type, params.splitLengthTensor.shape);
+        const auto splitLengths =
+            std::make_shared<op::v0::Parameter>(params.splitLengthTensor.type, params.splitLengthTensor.shape);
         const auto split = std::make_shared<op::v1::VariadicSplit>(data, axis, splitLengths);
         return std::make_shared<ov::Model>(split->outputs(), ParameterVector{data, axis, splitLengths});
     }
 };
 
-
 TEST_P(ReferenceVariadicSplitTest, CompareWithRefs) {
     Exec();
 }
@@ -94,185 +101,213 @@ TEST_P(ReferenceVariadicSplitTest, CompareWithRefs) {
 template <element::Type_t IN_ET>
 std::vector<VariadicSplitParams> generateVariadicSplitParams() {
     using T = typename element_type_traits<IN_ET>::value_type;
-    std::vector<VariadicSplitParams> variadicSplitParams {
+    std::vector<VariadicSplitParams> variadicSplitParams{
         // variadic_split_1d_static
-        VariadicSplitParams({10},
-                            reference_tests::Tensor(IN_ET, {10}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}),
-                            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{0}),
-                            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{5, 3, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {5}, std::vector<T>{1, 2, 3, 4, 5}),
-                                                reference_tests::Tensor(IN_ET, {3}, std::vector<T>{6, 7, 8}),
-                                                reference_tests::Tensor(IN_ET, {2}, std::vector<T>{9, 10})},
-                            "variadic_split_1d_static"),
+        VariadicSplitParams(
+            {10},
+            reference_tests::Tensor(IN_ET, {10}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}),
+            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{0}),
+            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{5, 3, 2}),
+            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {5}, std::vector<T>{1, 2, 3, 4, 5}),
+                                                 reference_tests::Tensor(IN_ET, {3}, std::vector<T>{6, 7, 8}),
+                                                 reference_tests::Tensor(IN_ET, {2}, std::vector<T>{9, 10})},
+            "variadic_split_1d_static"),
         // variadic_split_1d_dynamic
-        VariadicSplitParams(PartialShape::dynamic(),
-                            reference_tests::Tensor(IN_ET, {10}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}),
-                            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{0}),
-                            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{5, 3, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {5}, std::vector<T>{1, 2, 3, 4, 5}),
-                                                reference_tests::Tensor(IN_ET, {3}, std::vector<T>{6, 7, 8}),
-                                                reference_tests::Tensor(IN_ET, {2}, std::vector<T>{9, 10})},
-                            "variadic_split_1d_dynamic"),
+        VariadicSplitParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(IN_ET, {10}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10}),
+            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{0}),
+            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{5, 3, 2}),
+            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {5}, std::vector<T>{1, 2, 3, 4, 5}),
+                                                 reference_tests::Tensor(IN_ET, {3}, std::vector<T>{6, 7, 8}),
+                                                 reference_tests::Tensor(IN_ET, {2}, std::vector<T>{9, 10})},
+            "variadic_split_1d_dynamic"),
         // variadic_split_2d_axis_0_static
-        VariadicSplitParams({6, 2},
-                            reference_tests::Tensor(IN_ET, {6, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
-                            reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{0}),
-                            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{4, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {4, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8}),
-                                                reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{9, 10, 11, 12})},
-                            "variadic_split_2d_axis_0_static"),
+        VariadicSplitParams(
+            {6, 2},
+            reference_tests::Tensor(IN_ET, {6, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+            reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{0}),
+            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{4, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {4, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8}),
+                reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{9, 10, 11, 12})},
+            "variadic_split_2d_axis_0_static"),
         // variadic_split_2d_axis_0_dynamic
-        VariadicSplitParams(PartialShape::dynamic(),
-                            reference_tests::Tensor(IN_ET, {6, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
-                            reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{0}),
-                            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{4, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {4, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8}),
-                                                reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{9, 10, 11, 12})},
-                            "variadic_split_2d_axis_0_dynamic"),
+        VariadicSplitParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(IN_ET, {6, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+            reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{0}),
+            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{4, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {4, 2}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8}),
+                reference_tests::Tensor(IN_ET, {2, 2}, std::vector<T>{9, 10, 11, 12})},
+            "variadic_split_2d_axis_0_dynamic"),
         // variadic_split_2d_axis_1_static
-        VariadicSplitParams({4, 3},
-                            reference_tests::Tensor(IN_ET, {4, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
-                            reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{1}),
-                            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {4, 1}, std::vector<T>{1, 4, 7, 10}),
-                                                reference_tests::Tensor(IN_ET, {4, 2}, std::vector<T>{2, 3, 5, 6, 8, 9, 11, 12})},
-                            "variadic_split_2d_axis_1_static"),
+        VariadicSplitParams(
+            {4, 3},
+            reference_tests::Tensor(IN_ET, {4, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+            reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{1}),
+            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {4, 1}, std::vector<T>{1, 4, 7, 10}),
+                reference_tests::Tensor(IN_ET, {4, 2}, std::vector<T>{2, 3, 5, 6, 8, 9, 11, 12})},
+            "variadic_split_2d_axis_1_static"),
         // variadic_split_2d_axis_1_dynamic
-        VariadicSplitParams(PartialShape::dynamic(),
-                            reference_tests::Tensor(IN_ET, {4, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
-                            reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{1}),
-                            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {4, 1}, std::vector<T>{1, 4, 7, 10}),
-                                                reference_tests::Tensor(IN_ET, {4, 2}, std::vector<T>{2, 3, 5, 6, 8, 9, 11, 12})},
-                            "variadic_split_2d_axis_1_dynamic"),
+        VariadicSplitParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(IN_ET, {4, 3}, std::vector<T>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}),
+            reference_tests::Tensor(element::i32, {}, std::vector<int32_t>{1}),
+            reference_tests::Tensor(element::i32, {2}, std::vector<int32_t>{1, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {4, 1}, std::vector<T>{1, 4, 7, 10}),
+                reference_tests::Tensor(IN_ET, {4, 2}, std::vector<T>{2, 3, 5, 6, 8, 9, 11, 12})},
+            "variadic_split_2d_axis_1_dynamic"),
         // variadic_split_4d_axis_0_static
-        VariadicSplitParams({6, 2, 3, 1},
-                            reference_tests::Tensor(IN_ET, {6, 2, 3, 1}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                       8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23,
-                                                                       24, 25, 26, 27, 28, 29, 30, 31,
-                                                                       32, 33, 34, 35}),
-                            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{0}),
-                            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{3, 1, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {3, 2, 3, 1}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                                           8, 9, 10, 11, 12, 13, 14, 15,
-                                                                                           16, 17}),
-                                                reference_tests::Tensor(IN_ET, {1, 2, 3, 1}, std::vector<T>{18, 19, 20, 21, 22, 23}),
-                                                reference_tests::Tensor(IN_ET, {2, 2, 3, 1}, std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31,
-                                                                                           32, 33, 34, 35})},
-                            "variadic_split_4d_axis_0_static"),
+        VariadicSplitParams(
+            {6, 2, 3, 1},
+            reference_tests::Tensor(IN_ET, {6, 2, 3, 1}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16, 17,
+                                                                        18, 19, 20, 21, 22, 23, 24, 25, 26,
+                                                                        27, 28, 29, 30, 31, 32, 33, 34, 35}),
+            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{0}),
+            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{3, 1, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET,
+                                        {3, 2, 3, 1},
+                                        std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17}),
+                reference_tests::Tensor(IN_ET, {1, 2, 3, 1}, std::vector<T>{18, 19, 20, 21, 22, 23}),
+                reference_tests::Tensor(IN_ET,
+                                        {2, 2, 3, 1},
+                                        std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35})},
+            "variadic_split_4d_axis_0_static"),
         // variadic_split_4d_axis_0_dynamic
-        VariadicSplitParams(PartialShape::dynamic(),
-                            reference_tests::Tensor(IN_ET, {6, 2, 3, 1}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                       8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23,
-                                                                       24, 25, 26, 27, 28, 29, 30, 31,
-                                                                       32, 33, 34, 35}),
-                            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{0}),
-                            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{3, 1, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {3, 2, 3, 1}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                                           8, 9, 10, 11, 12, 13, 14, 15,
-                                                                                           16, 17}),
-                                                reference_tests::Tensor(IN_ET, {1, 2, 3, 1}, std::vector<T>{18, 19, 20, 21, 22, 23}),
-                                                reference_tests::Tensor(IN_ET, {2, 2, 3, 1}, std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31,
-                                                                                           32, 33, 34, 35})},
-                            "variadic_split_4d_axis_0_dynamic"),
+        VariadicSplitParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(IN_ET, {6, 2, 3, 1}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,
+                                                                        9,  10, 11, 12, 13, 14, 15, 16, 17,
+                                                                        18, 19, 20, 21, 22, 23, 24, 25, 26,
+                                                                        27, 28, 29, 30, 31, 32, 33, 34, 35}),
+            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{0}),
+            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{3, 1, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET,
+                                        {3, 2, 3, 1},
+                                        std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17}),
+                reference_tests::Tensor(IN_ET, {1, 2, 3, 1}, std::vector<T>{18, 19, 20, 21, 22, 23}),
+                reference_tests::Tensor(IN_ET,
+                                        {2, 2, 3, 1},
+                                        std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35})},
+            "variadic_split_4d_axis_0_dynamic"),
         // variadic_split_4d_axis_1_static
-        VariadicSplitParams({2, 8, 2, 2},
-                            reference_tests::Tensor(IN_ET, {2, 8, 2, 2}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                       8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23,
-                                                                       24, 25, 26, 27, 28, 29, 30, 31,
-                                                                       32, 33, 34, 35, 36, 37, 38, 39,
-                                                                       40, 41, 42, 43, 44, 45, 46, 47,
-                                                                       48, 49, 50, 51, 52, 53, 54, 55,
-                                                                       56, 57, 58, 59, 60, 61, 62, 63}),
-                            reference_tests::Tensor(element::u64, {1}, std::vector<uint64_t>{1}),
-                            reference_tests::Tensor(element::u64, {4}, std::vector<uint64_t>{1, 3, 2, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{0, 1, 2, 3, 32, 33, 34, 35}),
-                                                reference_tests::Tensor(IN_ET, {2, 3, 2, 2}, std::vector<T>{4, 5, 6, 7, 8, 9, 10, 11,
-                                                                                           12, 13, 14, 15, 36, 37, 38, 39,
-                                                                                           40, 41, 42, 43, 44, 45, 46, 47}),
-                                                reference_tests::Tensor(IN_ET, {2, 2, 2, 2}, std::vector<T>{16, 17, 18, 19, 20, 21, 22, 23,
-                                                                                           48, 49, 50, 51, 52, 53, 54, 55}),
-                                                reference_tests::Tensor(IN_ET, {2, 2, 2, 2}, std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31,
-                                                                                           56, 57, 58, 59, 60, 61, 62, 63})},
-                            "variadic_split_4d_axis_1_static"),
+        VariadicSplitParams(
+            {2, 8, 2, 2},
+            reference_tests::Tensor(
+                IN_ET,
+                {2, 8, 2, 2},
+                std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
+                               22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,
+                               44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63}),
+            reference_tests::Tensor(element::u64, {1}, std::vector<uint64_t>{1}),
+            reference_tests::Tensor(element::u64, {4}, std::vector<uint64_t>{1, 3, 2, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{0, 1, 2, 3, 32, 33, 34, 35}),
+                reference_tests::Tensor(IN_ET, {2, 3, 2, 2}, std::vector<T>{4,  5,  6,  7,  8,  9,  10, 11,
+                                                                            12, 13, 14, 15, 36, 37, 38, 39,
+                                                                            40, 41, 42, 43, 44, 45, 46, 47}),
+                reference_tests::Tensor(IN_ET,
+                                        {2, 2, 2, 2},
+                                        std::vector<T>{16, 17, 18, 19, 20, 21, 22, 23, 48, 49, 50, 51, 52, 53, 54, 55}),
+                reference_tests::Tensor(
+                    IN_ET,
+                    {2, 2, 2, 2},
+                    std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31, 56, 57, 58, 59, 60, 61, 62, 63})},
+            "variadic_split_4d_axis_1_static"),
         // variadic_split_4d_axis_1_dynamic
-        VariadicSplitParams(PartialShape::dynamic(),
-                            reference_tests::Tensor(IN_ET, {2, 8, 2, 2}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                       8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23,
-                                                                       24, 25, 26, 27, 28, 29, 30, 31,
-                                                                       32, 33, 34, 35, 36, 37, 38, 39,
-                                                                       40, 41, 42, 43, 44, 45, 46, 47,
-                                                                       48, 49, 50, 51, 52, 53, 54, 55,
-                                                                       56, 57, 58, 59, 60, 61, 62, 63}),
-                            reference_tests::Tensor(element::i64, {1}, std::vector<int64_t>{1}),
-                            reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{1, 3, 2, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{0, 1, 2, 3, 32, 33, 34, 35}),
-                                                reference_tests::Tensor(IN_ET, {2, 3, 2, 2}, std::vector<T>{4, 5, 6, 7, 8, 9, 10, 11,
-                                                                                           12, 13, 14, 15, 36, 37, 38, 39,
-                                                                                           40, 41, 42, 43, 44, 45, 46, 47}),
-                                                reference_tests::Tensor(IN_ET, {2, 2, 2, 2}, std::vector<T>{16, 17, 18, 19, 20, 21, 22, 23,
-                                                                                           48, 49, 50, 51, 52, 53, 54, 55}),
-                                                reference_tests::Tensor(IN_ET, {2, 2, 2, 2}, std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31,
-                                                                                           56, 57, 58, 59, 60, 61, 62, 63})},
-                            "variadic_split_4d_axis_1_dynamic"),
+        VariadicSplitParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(
+                IN_ET,
+                {2, 8, 2, 2},
+                std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
+                               22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43,
+                               44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63}),
+            reference_tests::Tensor(element::i64, {1}, std::vector<int64_t>{1}),
+            reference_tests::Tensor(element::i64, {4}, std::vector<int64_t>{1, 3, 2, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{0, 1, 2, 3, 32, 33, 34, 35}),
+                reference_tests::Tensor(IN_ET, {2, 3, 2, 2}, std::vector<T>{4,  5,  6,  7,  8,  9,  10, 11,
+                                                                            12, 13, 14, 15, 36, 37, 38, 39,
+                                                                            40, 41, 42, 43, 44, 45, 46, 47}),
+                reference_tests::Tensor(IN_ET,
+                                        {2, 2, 2, 2},
+                                        std::vector<T>{16, 17, 18, 19, 20, 21, 22, 23, 48, 49, 50, 51, 52, 53, 54, 55}),
+                reference_tests::Tensor(
+                    IN_ET,
+                    {2, 2, 2, 2},
+                    std::vector<T>{24, 25, 26, 27, 28, 29, 30, 31, 56, 57, 58, 59, 60, 61, 62, 63})},
+            "variadic_split_4d_axis_1_dynamic"),
         // variadic_split_4d_axis_2_static
-        VariadicSplitParams({2, 1, 6, 2},
-                            reference_tests::Tensor(IN_ET, {2, 1, 6, 2}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                       8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23}),
-                            reference_tests::Tensor(element::u32, {1}, std::vector<uint32_t>{2}),
-                            reference_tests::Tensor(element::u32, {3}, std::vector<uint32_t>{3, 1, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {2, 1, 3, 2}, std::vector<T>{0, 1, 2, 3, 4, 5, 12, 13,
-                                                                                           14, 15, 16, 17}),
-                                                reference_tests::Tensor(IN_ET, {2, 1, 1, 2}, std::vector<T>{6, 7, 18, 19}),
-                                                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{8, 9, 10, 11, 20, 21, 22, 23})},
-                            "variadic_split_4d_axis_2_static"),
+        VariadicSplitParams(
+            {2, 1, 6, 2},
+            reference_tests::Tensor(IN_ET, {2, 1, 6, 2}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,
+                                                                        8,  9,  10, 11, 12, 13, 14, 15,
+                                                                        16, 17, 18, 19, 20, 21, 22, 23}),
+            reference_tests::Tensor(element::u32, {1}, std::vector<uint32_t>{2}),
+            reference_tests::Tensor(element::u32, {3}, std::vector<uint32_t>{3, 1, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {2, 1, 3, 2}, std::vector<T>{0, 1, 2, 3, 4, 5, 12, 13, 14, 15, 16, 17}),
+                reference_tests::Tensor(IN_ET, {2, 1, 1, 2}, std::vector<T>{6, 7, 18, 19}),
+                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{8, 9, 10, 11, 20, 21, 22, 23})},
+            "variadic_split_4d_axis_2_static"),
         // variadic_split_4d_axis_2_dynamic
-        VariadicSplitParams(PartialShape::dynamic(),
-                            reference_tests::Tensor(IN_ET, {2, 1, 6, 2}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                       8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23}),
-                            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{2}),
-                            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{-1, 1, 2}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {2, 1, 3, 2}, std::vector<T>{0, 1, 2, 3, 4, 5, 12, 13,
-                                                                                           14, 15, 16, 17}),
-                                                reference_tests::Tensor(IN_ET, {2, 1, 1, 2}, std::vector<T>{6, 7, 18, 19}),
-                                                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{8, 9, 10, 11, 20, 21, 22, 23})},
-                            "variadic_split_4d_axis_2_dynamic"),
+        VariadicSplitParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(IN_ET, {2, 1, 6, 2}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,
+                                                                        8,  9,  10, 11, 12, 13, 14, 15,
+                                                                        16, 17, 18, 19, 20, 21, 22, 23}),
+            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{2}),
+            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{-1, 1, 2}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {2, 1, 3, 2}, std::vector<T>{0, 1, 2, 3, 4, 5, 12, 13, 14, 15, 16, 17}),
+                reference_tests::Tensor(IN_ET, {2, 1, 1, 2}, std::vector<T>{6, 7, 18, 19}),
+                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{8, 9, 10, 11, 20, 21, 22, 23})},
+            "variadic_split_4d_axis_2_dynamic"),
         // variadic_split_4d_axis_3_static
-        VariadicSplitParams({2, 1, 2, 6},
-                            reference_tests::Tensor(IN_ET, {2, 1, 2, 6}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                       8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23}),
-                            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{3}),
-                            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{1, -1, 3}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {2, 1, 2, 1}, std::vector<T>{0, 6, 12, 18}),
-                                                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{1, 2, 7, 8, 13, 14, 19, 20}),
-                                                reference_tests::Tensor(IN_ET, {2, 1, 2, 3}, std::vector<T>{3, 4, 5, 9, 10, 11, 15, 16,
-                                                                                           17, 21, 22, 23})},
-                            "variadic_split_4d_axis_neg1_static"),
+        VariadicSplitParams(
+            {2, 1, 2, 6},
+            reference_tests::Tensor(IN_ET, {2, 1, 2, 6}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,
+                                                                        8,  9,  10, 11, 12, 13, 14, 15,
+                                                                        16, 17, 18, 19, 20, 21, 22, 23}),
+            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{3}),
+            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{1, -1, 3}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {2, 1, 2, 1}, std::vector<T>{0, 6, 12, 18}),
+                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{1, 2, 7, 8, 13, 14, 19, 20}),
+                reference_tests::Tensor(IN_ET,
+                                        {2, 1, 2, 3},
+                                        std::vector<T>{3, 4, 5, 9, 10, 11, 15, 16, 17, 21, 22, 23})},
+            "variadic_split_4d_axis_neg1_static"),
         // variadic_split_4d_axis_3_dynamic
-        VariadicSplitParams(PartialShape::dynamic(),
-                            reference_tests::Tensor(IN_ET, {2, 1, 2, 6}, std::vector<T>{0, 1, 2, 3, 4, 5, 6, 7,
-                                                                       8, 9, 10, 11, 12, 13, 14, 15,
-                                                                       16, 17, 18, 19, 20, 21, 22, 23}),
-                            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{-1}),
-                            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{1, 2, -1}),
-                            std::vector<reference_tests::Tensor>{reference_tests::Tensor(IN_ET, {2, 1, 2, 1}, std::vector<T>{0, 6, 12, 18}),
-                                                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{1, 2, 7, 8, 13, 14, 19, 20}),
-                                                reference_tests::Tensor(IN_ET, {2, 1, 2, 3}, std::vector<T>{3, 4, 5, 9, 10, 11, 15, 16,
-                                                                                           17, 21, 22, 23})},
-                            "variadic_split_4d_axis_3_dynamic"),
+        VariadicSplitParams(
+            PartialShape::dynamic(),
+            reference_tests::Tensor(IN_ET, {2, 1, 2, 6}, std::vector<T>{0,  1,  2,  3,  4,  5,  6,  7,
+                                                                        8,  9,  10, 11, 12, 13, 14, 15,
+                                                                        16, 17, 18, 19, 20, 21, 22, 23}),
+            reference_tests::Tensor(element::i32, {1}, std::vector<int32_t>{-1}),
+            reference_tests::Tensor(element::i32, {3}, std::vector<int32_t>{1, 2, -1}),
+            std::vector<reference_tests::Tensor>{
+                reference_tests::Tensor(IN_ET, {2, 1, 2, 1}, std::vector<T>{0, 6, 12, 18}),
+                reference_tests::Tensor(IN_ET, {2, 1, 2, 2}, std::vector<T>{1, 2, 7, 8, 13, 14, 19, 20}),
+                reference_tests::Tensor(IN_ET,
+                                        {2, 1, 2, 3},
+                                        std::vector<T>{3, 4, 5, 9, 10, 11, 15, 16, 17, 21, 22, 23})},
+            "variadic_split_4d_axis_3_dynamic"),
     };
     return variadicSplitParams;
 }
 
 std::vector<VariadicSplitParams> generateVariadicSplitCombinedParams() {
-    const std::vector<std::vector<VariadicSplitParams>> variadicSplitTypeParams {
+    const std::vector<std::vector<VariadicSplitParams>> variadicSplitTypeParams{
         generateVariadicSplitParams<element::Type_t::i8>(),
         generateVariadicSplitParams<element::Type_t::i16>(),
         generateVariadicSplitParams<element::Type_t::i32>(),
@@ -292,6 +327,8 @@ std::vector<VariadicSplitParams> generateVariadicSplitCombinedParams() {
     return combinedParams;
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_VariadicSplit_With_Hardcoded_Refs, ReferenceVariadicSplitTest,
-    testing::ValuesIn(generateVariadicSplitCombinedParams()), ReferenceVariadicSplitTest::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_VariadicSplit_With_Hardcoded_Refs,
+                         ReferenceVariadicSplitTest,
+                         testing::ValuesIn(generateVariadicSplitCombinedParams()),
+                         ReferenceVariadicSplitTest::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/preprocessing/yuv_to_grey_tests.cpp b/src/plugins/template/tests/functional/preprocessing/yuv_to_grey_tests.cpp
index 8ead0964c017b4..e468fde15d8053 100644
--- a/src/plugins/template/tests/functional/preprocessing/yuv_to_grey_tests.cpp
+++ b/src/plugins/template/tests/functional/preprocessing/yuv_to_grey_tests.cpp
@@ -2,10 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <gtest/gtest.h>
-
 #include "preprocessing/yuv_to_grey_tests.hpp"
 
+#include <gtest/gtest.h>
+
 using namespace ov::preprocess;
 
 INSTANTIATE_TEST_SUITE_P(smoke_Preprocessing,
diff --git a/src/plugins/template/tests/functional/set_device_name.cpp b/src/plugins/template/tests/functional/set_device_name.cpp
index 4e9d9c8f35c4a5..f2e45bd34df4b0 100644
--- a/src/plugins/template/tests/functional/set_device_name.cpp
+++ b/src/plugins/template/tests/functional/set_device_name.cpp
@@ -1,11 +1,11 @@
 // Copyright (C) 2018-2023 Intel Corporation
 // SPDX-License-Identifier: Apache-2.0
 //
-#include <string>
-#include <stdexcept>
-
 #include "set_device_name.hpp"
 
+#include <stdexcept>
+#include <string>
+
 namespace ov {
 namespace test {
 void set_device_suffix(const std::string& suffix) {
@@ -13,5 +13,5 @@ void set_device_suffix(const std::string& suffix) {
         throw std::runtime_error("The suffix can't be used for TEMPLATE device!");
     }
 }
-} // namespace test
-} // namespace ov
+}  // namespace test
+}  // namespace ov
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/executable_network/exec_network_base.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/executable_network/exec_network_base.cpp
index edf642937238bc..454c2c5844c8d0 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/executable_network/exec_network_base.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/executable_network/exec_network_base.cpp
@@ -2,33 +2,28 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/executable_network/exec_network_base.hpp"
 
+#include <vector>
+
 using namespace BehaviorTestsDefinitions;
 
 namespace {
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
-
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, ExecutableNetworkBaseTest,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        ExecutableNetworkBaseTest::getTestCaseName);
-
-
-const std::vector<InferenceEngine::Precision> netPrecisions = {
-        InferenceEngine::Precision::FP32,
-        InferenceEngine::Precision::FP16
-};
-
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, ExecNetSetPrecision,
-                         ::testing::Combine(
-                                 ::testing::ValuesIn(netPrecisions),
-                                 ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                 ::testing::ValuesIn(configs)),
+const std::vector<std::map<std::string, std::string>> configs = {{}};
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         ExecutableNetworkBaseTest,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         ExecutableNetworkBaseTest::getTestCaseName);
+
+const std::vector<InferenceEngine::Precision> netPrecisions = {InferenceEngine::Precision::FP32,
+                                                               InferenceEngine::Precision::FP16};
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         ExecNetSetPrecision,
+                         ::testing::Combine(::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
                          ExecNetSetPrecision::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/callback.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/callback.cpp
index fe7686dc590fe0..5a54f7542f609d 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/callback.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/callback.cpp
@@ -2,20 +2,18 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/infer_request/callback.hpp"
 
+#include <vector>
+
 using namespace BehaviorTestsDefinitions;
 
 namespace {
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
+const std::vector<std::map<std::string, std::string>> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, InferRequestCallbackTests,
-        ::testing::Combine(
-            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-            ::testing::ValuesIn(configs)),
-        InferRequestCallbackTests::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         InferRequestCallbackTests,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         InferRequestCallbackTests::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/config.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/config.cpp
index 492d7c9bb3b661..b822c6f94e6533 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/config.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/config.cpp
@@ -2,23 +2,21 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/infer_request/config.hpp"
 
+#include <vector>
+
 using namespace BehaviorTestsDefinitions;
 
 namespace {
 
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
+const std::vector<std::map<std::string, std::string>> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, InferRequestConfigTest,
-                        ::testing::Combine(
-                                ::testing::Values(1u),
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         InferRequestConfigTest,
+                         ::testing::Combine(::testing::Values(1u),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
                          InferRequestConfigTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/io_blob.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/io_blob.cpp
index 10d16f14da9942..b6f1f38a3bdc86 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/io_blob.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/io_blob.cpp
@@ -2,21 +2,19 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/infer_request/io_blob.hpp"
 
+#include <vector>
+
 using namespace BehaviorTestsDefinitions;
 
 namespace {
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
+const std::vector<std::map<std::string, std::string>> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, InferRequestIOBBlobTest,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        InferRequestIOBBlobTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         InferRequestIOBBlobTest,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         InferRequestIOBBlobTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/memory_states.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/memory_states.cpp
index 3a8bc33f74b521..323cdb5ac4c222 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/memory_states.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/memory_states.cpp
@@ -22,4 +22,3 @@ INSTANTIATE_TEST_SUITE_P(smoke_Template_BehaviorTests,
                          ::testing::ValuesIn(memoryStateTestCases),
                          InferRequestQueryStateExceptionTest::getTestCaseName);
 }  // namespace
-
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/multithreading.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/multithreading.cpp
index d0e2c321c530fa..d633da55e8fd8b 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/multithreading.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/multithreading.cpp
@@ -2,22 +2,20 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/infer_request/multithreading.hpp"
 
+#include <vector>
+
 using namespace BehaviorTestsDefinitions;
 
 namespace {
 
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
+const std::vector<std::map<std::string, std::string>> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, InferRequestMultithreadingTests,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        InferRequestMultithreadingTests::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         InferRequestMultithreadingTests,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         InferRequestMultithreadingTests::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/wait.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/wait.cpp
index 94e97854188bcf..8233cb87b652e7 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/wait.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/infer_request/wait.cpp
@@ -2,21 +2,19 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/infer_request/wait.hpp"
 
+#include <vector>
+
 using namespace BehaviorTestsDefinitions;
 
 namespace {
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
+const std::vector<std::map<std::string, std::string>> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, InferRequestWaitTests,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        InferRequestWaitTests::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         InferRequestWaitTests,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         InferRequestWaitTests::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/exec_network_base.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/exec_network_base.cpp
index e0a40cae32436b..f6f96b5b20f8c3 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/exec_network_base.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/exec_network_base.cpp
@@ -8,59 +8,56 @@
 using namespace ov::test::behavior;
 namespace {
 
-    const std::vector<ov::AnyMap> configs = {
-            {},
-    };
-    const std::vector<ov::AnyMap> swPluginConfigs = {
-            {ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}
-    };
-
-    INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVCompiledModelBaseTest,
-                            ::testing::Combine(
-                                    ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                    ::testing::ValuesIn(configs)),
-                            OVCompiledModelBaseTest::getTestCaseName);
-
-    INSTANTIATE_TEST_SUITE_P(smoke_Multi_BehaviorTests, OVCompiledModelBaseTest,
-                            ::testing::Combine(
-                                    ::testing::Values(ov::test::utils::DEVICE_MULTI),
-                                    ::testing::ValuesIn(swPluginConfigs)),
-                            OVCompiledModelBaseTest::getTestCaseName);
-
-    INSTANTIATE_TEST_SUITE_P(smoke_Auto_BehaviorTests, OVCompiledModelBaseTest,
-                            ::testing::Combine(
-                                    ::testing::Values(ov::test::utils::DEVICE_AUTO),
-                                    ::testing::ValuesIn(swPluginConfigs)),
-                            OVCompiledModelBaseTest::getTestCaseName);
-
-    INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests, OVCompiledModelBaseTest,
-                             ::testing::Combine(
-                                     ::testing::Values(ov::test::utils::DEVICE_HETERO),
-                                     ::testing::ValuesIn(swPluginConfigs)),
-                             OVCompiledModelBaseTest::getTestCaseName);
-
-
-    INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVCompiledModelBaseTestOptional,
-                            ::testing::Combine(
-                                    ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                    ::testing::ValuesIn(configs)),
-                            OVCompiledModelBaseTestOptional::getTestCaseName);
-
-    INSTANTIATE_TEST_SUITE_P(smoke_Multi_BehaviorTests, OVCompiledModelBaseTestOptional,
-                            ::testing::Combine(
-                                    ::testing::Values(ov::test::utils::DEVICE_MULTI),
-                                    ::testing::ValuesIn(swPluginConfigs)),
-                            OVCompiledModelBaseTestOptional::getTestCaseName);
-
-    INSTANTIATE_TEST_SUITE_P(smoke_Auto_BehaviorTests, OVCompiledModelBaseTestOptional,
-                            ::testing::Combine(
-                                    ::testing::Values(ov::test::utils::DEVICE_AUTO),
-                                    ::testing::ValuesIn(swPluginConfigs)),
-                            OVCompiledModelBaseTestOptional::getTestCaseName);
-
-    INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests, OVCompiledModelBaseTestOptional,
-                             ::testing::Combine(
-                                     ::testing::Values(ov::test::utils::DEVICE_HETERO),
-                                     ::testing::ValuesIn(swPluginConfigs)),
-                             OVCompiledModelBaseTestOptional::getTestCaseName);
+const std::vector<ov::AnyMap> configs = {
+    {},
+};
+const std::vector<ov::AnyMap> swPluginConfigs = {{ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVCompiledModelBaseTest,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVCompiledModelBaseTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Multi_BehaviorTests,
+                         OVCompiledModelBaseTest,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_MULTI),
+                                            ::testing::ValuesIn(swPluginConfigs)),
+                         OVCompiledModelBaseTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Auto_BehaviorTests,
+                         OVCompiledModelBaseTest,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_AUTO),
+                                            ::testing::ValuesIn(swPluginConfigs)),
+                         OVCompiledModelBaseTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests,
+                         OVCompiledModelBaseTest,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_HETERO),
+                                            ::testing::ValuesIn(swPluginConfigs)),
+                         OVCompiledModelBaseTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVCompiledModelBaseTestOptional,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVCompiledModelBaseTestOptional::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Multi_BehaviorTests,
+                         OVCompiledModelBaseTestOptional,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_MULTI),
+                                            ::testing::ValuesIn(swPluginConfigs)),
+                         OVCompiledModelBaseTestOptional::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Auto_BehaviorTests,
+                         OVCompiledModelBaseTestOptional,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_AUTO),
+                                            ::testing::ValuesIn(swPluginConfigs)),
+                         OVCompiledModelBaseTestOptional::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests,
+                         OVCompiledModelBaseTestOptional,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_HETERO),
+                                            ::testing::ValuesIn(swPluginConfigs)),
+                         OVCompiledModelBaseTestOptional::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/get_metric.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/get_metric.cpp
index 17ed16f162155b..6f1c98f11bc00c 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/get_metric.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/get_metric.cpp
@@ -4,7 +4,6 @@
 
 #include "behavior/compiled_model/properties.hpp"
 #include "behavior/compiled_model/properties_hetero.hpp"
-
 #include "behavior/ov_plugin/properties_tests.hpp"
 #include "openvino/runtime/core.hpp"
 
@@ -71,4 +70,3 @@ INSTANTIATE_TEST_SUITE_P(smoke_OVClassHeteroCompiledModelGetMetricTest,
 //////////////////////////////////////////////////////////////////////////////////////////
 
 }  // namespace
-
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/ov_exec_net_import_export.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/ov_exec_net_import_export.cpp
index 57c487b18b92d5..391c2919c26e74 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/ov_exec_net_import_export.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/ov_exec_net_import_export.cpp
@@ -1,59 +1,55 @@
 // Copyright (C) 2018-2023 Intel Corporation
 // SPDX-License-Identifier: Apache-2.0
 //
-#include "behavior/compiled_model/import_export.hpp"
+#include <common_test_utils/test_constants.hpp>
 
+#include "behavior/compiled_model/import_export.hpp"
 #include "ie_plugin_config.hpp"
-#include <common_test_utils/test_constants.hpp>
 
 using namespace ov::test::behavior;
 namespace {
 const std::vector<ov::element::Type_t> netPrecisions = {
-        ov::element::i8,
-        ov::element::i16,
-        ov::element::i32,
-        ov::element::i64,
-        ov::element::u8,
-        ov::element::u16,
-        ov::element::u32,
-        ov::element::u64,
-        ov::element::f16,
-        ov::element::f32,
+    ov::element::i8,
+    ov::element::i16,
+    ov::element::i32,
+    ov::element::i64,
+    ov::element::u8,
+    ov::element::u16,
+    ov::element::u32,
+    ov::element::u64,
+    ov::element::f16,
+    ov::element::f32,
 };
 const std::vector<ov::AnyMap> configs = {
-        {},
+    {},
 };
-const std::vector<ov::AnyMap> multiConfigs = {
-        {ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
+const std::vector<ov::AnyMap> multiConfigs = {{ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
 
-const std::vector<ov::AnyMap> heteroConfigs = {
-        {ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
+const std::vector<ov::AnyMap> heteroConfigs = {{ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
 
 INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
                          OVCompiledGraphImportExportTest,
-                         ::testing::Combine(
-                                 ::testing::ValuesIn(netPrecisions),
-                                 ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                 ::testing::ValuesIn(configs)),
+                         ::testing::Combine(::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
                          OVCompiledGraphImportExportTest::getTestCaseName);
 
 INSTANTIATE_TEST_SUITE_P(smoke_Auto_BehaviorTests,
-         OVCompiledGraphImportExportTest,
-        ::testing::Combine(
-                ::testing::ValuesIn(netPrecisions),
-                ::testing::Values(ov::test::utils::DEVICE_AUTO),
-                ::testing::ValuesIn(multiConfigs)),
-        OVCompiledGraphImportExportTest::getTestCaseName);
+                         OVCompiledGraphImportExportTest,
+                         ::testing::Combine(::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(ov::test::utils::DEVICE_AUTO),
+                                            ::testing::ValuesIn(multiConfigs)),
+                         OVCompiledGraphImportExportTest::getTestCaseName);
 
 INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests,
-         OVCompiledGraphImportExportTest,
-        ::testing::Combine(::testing::ValuesIn(netPrecisions),
-                           ::testing::Values(ov::test::utils::DEVICE_HETERO),
-                           ::testing::ValuesIn(heteroConfigs)),
-        OVCompiledGraphImportExportTest::getTestCaseName);
+                         OVCompiledGraphImportExportTest,
+                         ::testing::Combine(::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(ov::test::utils::DEVICE_HETERO),
+                                            ::testing::ValuesIn(heteroConfigs)),
+                         OVCompiledGraphImportExportTest::getTestCaseName);
 
 INSTANTIATE_TEST_SUITE_P(smoke_OVClassImportExportTestP,
                          OVClassCompiledModelImportExportTestP,
-                         ::testing::Values("HETERO:TEMPLATE"));   
+                         ::testing::Values("HETERO:TEMPLATE"));
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/properties.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/properties.cpp
index 64b6fc0c1722b1..5622be5f16cce5 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/properties.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_executable_network/properties.cpp
@@ -45,7 +45,8 @@ INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
                                             ::testing::ValuesIn(default_properties)),
                          OVClassCompiledModelPropertiesDefaultTests::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVCompiledModelPropertiesDefaultSupportedTests,
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVCompiledModelPropertiesDefaultSupportedTests,
                          ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
                          OVCompiledModelPropertiesDefaultSupportedTests::getTestCaseName);
 
@@ -96,15 +97,15 @@ INSTANTIATE_TEST_SUITE_P(smoke_AutoBatch_BehaviorTests,
                                             ::testing::ValuesIn(auto_batch_properties)),
                          OVClassCompiledModelPropertiesTests::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_OVClassCompiledModelEmptyPropertiesTests, OVClassCompiledModelEmptyPropertiesTests,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_OVClassCompiledModelEmptyPropertiesTests,
+                         OVClassCompiledModelEmptyPropertiesTests,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
 // OV Class Load network
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_OVCompiledModelIncorrectDevice, OVCompiledModelIncorrectDevice,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_OVCompiledModelIncorrectDevice,
+                         OVCompiledModelIncorrectDevice,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
 const std::vector<std::tuple<std::string, std::pair<ov::AnyMap, std::string>>> GetMetricTest_ExecutionDevice_TEMPLATE =
     {{ov::test::utils::DEVICE_TEMPLATE, std::make_pair(ov::AnyMap{}, "TEMPLATE.0")}};
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/batched_tensors.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/batched_tensors.cpp
index 25798f13590963..d8e9b3a6284d52 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/batched_tensors.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/batched_tensors.cpp
@@ -2,10 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/ov_infer_request/batched_tensors.hpp"
 
+#include <vector>
+
 namespace ov {
 namespace test {
 namespace behavior {
@@ -61,10 +61,12 @@ TEST_P(OVInferRequestBatchedTests, SetInputTensors_Strides) {
     tensors.push_back(tensor1_cut);
     tensors.push_back(tensor2_cut);
     auto exp_tensor = ov::Tensor(element::f32, batch_shape);
-    ASSERT_THROW({
-                     req.set_tensors("tensor_input0", tensors);
-                     req.infer();
-                 }, ov::Exception);
+    ASSERT_THROW(
+        {
+            req.set_tensors("tensor_input0", tensors);
+            req.infer();
+        },
+        ov::Exception);
 }
 
 }  // namespace behavior
@@ -76,7 +78,8 @@ namespace {
 using namespace ov::test::behavior;
 using namespace ov;
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestBatchedTests,
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferRequestBatchedTests,
                          ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
                          OVInferRequestBatchedTests::getTestCaseName);
 
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/callback.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/callback.cpp
index a54609aaa15872..64152aad1d304c 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/callback.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/callback.cpp
@@ -2,20 +2,18 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/ov_infer_request/callback.hpp"
 
+#include <vector>
+
 using namespace ov::test::behavior;
 
 namespace {
-const std::vector<ov::AnyMap> configs = {
-    {}
-};
+const std::vector<ov::AnyMap> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestCallbackTests,
-        ::testing::Combine(
-            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-            ::testing::ValuesIn(configs)),
-        OVInferRequestCallbackTests::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferRequestCallbackTests,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVInferRequestCallbackTests::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/cancellation.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/cancellation.cpp
index e31ce005428ba6..1746a4ee5b7de6 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/cancellation.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/cancellation.cpp
@@ -8,12 +8,12 @@ using namespace ov::test::behavior;
 
 namespace {
 const std::vector<ov::AnyMap> configs = {
-        {},
+    {},
 };
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestCancellationTests,
-        ::testing::Combine(
-            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-            ::testing::ValuesIn(configs)),
-        OVInferRequestCancellationTests::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferRequestCancellationTests,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVInferRequestCancellationTests::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/infer_request_dynamic.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/infer_request_dynamic.cpp
index 62f36bb55461eb..1ae1cb74130ec4 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/infer_request_dynamic.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/infer_request_dynamic.cpp
@@ -2,37 +2,38 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/ov_infer_request/infer_request_dynamic.hpp"
 
+#include <vector>
+
 using namespace ov::test::behavior;
 
 namespace {
 
-const std::vector<ov::AnyMap> configs = {
-    {}
-};
-
-const std::vector<ov::AnyMap> HeteroConfigs = {
-            {ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
-
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestDynamicTests,
-                        ::testing::Combine(
-                                ::testing::Values(ngraph::builder::subgraph::makeSplitConvConcat()),
-                                ::testing::Values(std::vector<std::pair<std::vector<size_t>, std::vector<size_t>>>{{{1, 4, 20, 20}, {1, 10, 18, 18}},
-                                                                                                                   {{2, 4, 20, 20}, {2, 10, 18, 18}}}),
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        OVInferRequestDynamicTests::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests, OVInferRequestDynamicTests,
-                            ::testing::Combine(
-                                ::testing::Values(ngraph::builder::subgraph::makeSplitConvConcat()),
-                                ::testing::Values(std::vector<std::pair<std::vector<size_t>, std::vector<size_t>>>{{{1, 4, 20, 20}, {1, 10, 18, 18}},
-                                                                                                                   {{2, 4, 20, 20}, {2, 10, 18, 18}}}),
-                                ::testing::Values(ov::test::utils::DEVICE_HETERO),
-                                ::testing::ValuesIn(HeteroConfigs)),
-                        OVInferRequestDynamicTests::getTestCaseName);
+const std::vector<ov::AnyMap> configs = {{}};
+
+const std::vector<ov::AnyMap> HeteroConfigs = {{ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
+
+INSTANTIATE_TEST_SUITE_P(
+    smoke_BehaviorTests,
+    OVInferRequestDynamicTests,
+    ::testing::Combine(::testing::Values(ngraph::builder::subgraph::makeSplitConvConcat()),
+                       ::testing::Values(std::vector<std::pair<std::vector<size_t>, std::vector<size_t>>>{
+                           {{1, 4, 20, 20}, {1, 10, 18, 18}},
+                           {{2, 4, 20, 20}, {2, 10, 18, 18}}}),
+                       ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                       ::testing::ValuesIn(configs)),
+    OVInferRequestDynamicTests::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(
+    smoke_Hetero_BehaviorTests,
+    OVInferRequestDynamicTests,
+    ::testing::Combine(::testing::Values(ngraph::builder::subgraph::makeSplitConvConcat()),
+                       ::testing::Values(std::vector<std::pair<std::vector<size_t>, std::vector<size_t>>>{
+                           {{1, 4, 20, 20}, {1, 10, 18, 18}},
+                           {{2, 4, 20, 20}, {2, 10, 18, 18}}}),
+                       ::testing::Values(ov::test::utils::DEVICE_HETERO),
+                       ::testing::ValuesIn(HeteroConfigs)),
+    OVInferRequestDynamicTests::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/inference.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/inference.cpp
index f3288d328f44f5..2490bcb1a33cc2 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/inference.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/inference.cpp
@@ -2,19 +2,19 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/ov_infer_request/inference.hpp"
 
+#include <vector>
+
 namespace {
 
 using namespace ov::test::behavior;
 using namespace ov;
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestInferenceTests,
-                         ::testing::Combine(
-                         ::testing::Values(tensor_roi::roi_nchw(), tensor_roi::roi_1d()),
-                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferRequestInferenceTests,
+                         ::testing::Combine(::testing::Values(tensor_roi::roi_nchw(), tensor_roi::roi_1d()),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
                          OVInferRequestInferenceTests::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/inference_chaining.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/inference_chaining.cpp
index 87297a4ab90024..14e51f2cfeee5e 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/inference_chaining.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/inference_chaining.cpp
@@ -3,41 +3,39 @@
 //
 
 #include "behavior/ov_infer_request/inference_chaining.hpp"
+
 #include "common_test_utils/test_constants.hpp"
 
 using namespace ov::test::behavior;
 
 namespace {
 
-const std::vector<ov::AnyMap> configs = {
-    {}
-};
-
-const std::vector<ov::AnyMap> HeteroConfigs = {
-            {ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
-
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferenceChaining,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        OVInferenceChaining::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests, OVInferenceChaining,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_HETERO),
-                                ::testing::ValuesIn(HeteroConfigs)),
-                        OVInferenceChaining::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferenceChainingStatic,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        OVInferenceChainingStatic::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests, OVInferenceChainingStatic,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_HETERO),
-                                ::testing::ValuesIn(HeteroConfigs)),
-                        OVInferenceChainingStatic::getTestCaseName);
+const std::vector<ov::AnyMap> configs = {{}};
+
+const std::vector<ov::AnyMap> HeteroConfigs = {{ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferenceChaining,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVInferenceChaining::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests,
+                         OVInferenceChaining,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_HETERO),
+                                            ::testing::ValuesIn(HeteroConfigs)),
+                         OVInferenceChaining::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferenceChainingStatic,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVInferenceChainingStatic::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests,
+                         OVInferenceChainingStatic,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_HETERO),
+                                            ::testing::ValuesIn(HeteroConfigs)),
+                         OVInferenceChainingStatic::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/io_tensor.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/io_tensor.cpp
index a6d6fc10fd635f..9949e943999239 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/io_tensor.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/io_tensor.cpp
@@ -2,22 +2,20 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/ov_infer_request/io_tensor.hpp"
 
+#include <vector>
+
 using namespace ov::test::behavior;
 
 namespace {
-const std::vector<ov::AnyMap> configs = {
-    {}
-};
+const std::vector<ov::AnyMap> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestIOTensorTest,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        OVInferRequestIOTensorTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferRequestIOTensorTest,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVInferRequestIOTensorTest::getTestCaseName);
 
 std::vector<ov::element::Type> prcs = {
     ov::element::boolean,
@@ -40,30 +38,28 @@ std::vector<ov::element::Type> prcs = {
 
 const std::vector<ov::AnyMap> emptyConfigs = {{}};
 
-const std::vector<ov::AnyMap> HeteroConfigs = {
-            {ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
+const std::vector<ov::AnyMap> HeteroConfigs = {{ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
 
-const std::vector<ov::AnyMap> Multiconfigs = {
-        {ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
+const std::vector<ov::AnyMap> Multiconfigs = {{ov::device::priorities(ov::test::utils::DEVICE_TEMPLATE)}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestCheckTensorPrecision,
-                         ::testing::Combine(
-                                 ::testing::ValuesIn(prcs),
-                                 ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                 ::testing::ValuesIn(emptyConfigs)),
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferRequestCheckTensorPrecision,
+                         ::testing::Combine(::testing::ValuesIn(prcs),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(emptyConfigs)),
                          OVInferRequestCheckTensorPrecision::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests, OVInferRequestCheckTensorPrecision,
-                         ::testing::Combine(
-                                 ::testing::ValuesIn(prcs),
-                                 ::testing::Values(ov::test::utils::DEVICE_HETERO),
-                                 ::testing::ValuesIn(HeteroConfigs)),
+INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests,
+                         OVInferRequestCheckTensorPrecision,
+                         ::testing::Combine(::testing::ValuesIn(prcs),
+                                            ::testing::Values(ov::test::utils::DEVICE_HETERO),
+                                            ::testing::ValuesIn(HeteroConfigs)),
                          OVInferRequestCheckTensorPrecision::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Multi_BehaviorTests, OVInferRequestCheckTensorPrecision,
-                         ::testing::Combine(
-                                 ::testing::ValuesIn(prcs),
-                                 ::testing::Values(ov::test::utils::DEVICE_MULTI),
-                                 ::testing::ValuesIn(Multiconfigs)),
+INSTANTIATE_TEST_SUITE_P(smoke_Multi_BehaviorTests,
+                         OVInferRequestCheckTensorPrecision,
+                         ::testing::Combine(::testing::ValuesIn(prcs),
+                                            ::testing::Values(ov::test::utils::DEVICE_MULTI),
+                                            ::testing::ValuesIn(Multiconfigs)),
                          OVInferRequestCheckTensorPrecision::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/multithreading.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/multithreading.cpp
index 98347aba2e4142..3607e851ff6db4 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/multithreading.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/multithreading.cpp
@@ -2,22 +2,20 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/ov_infer_request/multithreading.hpp"
 
+#include <vector>
+
 using namespace ov::test::behavior;
 
 namespace {
 
-const std::vector<ov::AnyMap> configs = {
-    {}
-};
+const std::vector<ov::AnyMap> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestMultithreadingTests,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        OVInferRequestMultithreadingTests::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferRequestMultithreadingTests,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVInferRequestMultithreadingTests::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/wait.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/wait.cpp
index a4914fc899b134..06733733a7b7dd 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/wait.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_infer_request/wait.cpp
@@ -2,21 +2,19 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
-
 #include "behavior/ov_infer_request/wait.hpp"
 
+#include <vector>
+
 using namespace ov::test::behavior;
 
 namespace {
-const std::vector<ov::AnyMap> configs = {
-    {}
-};
+const std::vector<ov::AnyMap> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVInferRequestWaitTests,
-                        ::testing::Combine(
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        OVInferRequestWaitTests::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVInferRequestWaitTests,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         OVInferRequestWaitTests::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/life_time.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/life_time.cpp
index ca3a5b27901ccf..a415fa490608a9 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/life_time.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/life_time.cpp
@@ -8,12 +8,14 @@ using namespace ov::test::behavior;
 
 namespace {
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVHoldersTest,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        OVHoldersTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVHoldersTest,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                         OVHoldersTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, OVHoldersTestOnImportedNetwork,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE, "HETERO:TEMPLATE"),
-        OVHoldersTestOnImportedNetwork::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         OVHoldersTestOnImportedNetwork,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE, "HETERO:TEMPLATE"),
+                         OVHoldersTestOnImportedNetwork::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/properties_tests.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/properties_tests.cpp
index 0f05a09f4da99d..bfc64eb0454962 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/properties_tests.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/properties_tests.cpp
@@ -16,8 +16,10 @@ const std::vector<ov::AnyMap> inproperties = {
 
 INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
                          OVPropertiesIncorrectTests,
-                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE, ov::test::utils::DEVICE_HETERO,
-                                                              ov::test::utils::DEVICE_MULTI, ov::test::utils::DEVICE_BATCH),
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE,
+                                                              ov::test::utils::DEVICE_HETERO,
+                                                              ov::test::utils::DEVICE_MULTI,
+                                                              ov::test::utils::DEVICE_BATCH),
                                             ::testing::ValuesIn(inproperties)),
                          OVPropertiesIncorrectTests::getTestCaseName);
 
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/caching_tests.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/caching_tests.cpp
index 03658e2e4fed81..c17f0cfca2c6ee 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/caching_tests.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/caching_tests.cpp
@@ -7,19 +7,17 @@
 using namespace LayerTestsDefinitions;
 
 namespace {
-    static const std::vector<ov::element::Type> precisionsTemplate = {
-            ov::element::f32,
-    };
+static const std::vector<ov::element::Type> precisionsTemplate = {
+    ov::element::f32,
+};
 
-    static const std::vector<std::size_t> batchSizesTemplate = {
-            1, 2
-    };
+static const std::vector<std::size_t> batchSizesTemplate = {1, 2};
 
-    INSTANTIATE_TEST_SUITE_P(smoke_Behavior_CachingSupportCase_Template, LoadNetworkCacheTestBase,
-                            ::testing::Combine(
-                                    ::testing::ValuesIn(LoadNetworkCacheTestBase::getStandardFunctions()),
-                                    ::testing::ValuesIn(precisionsTemplate),
-                                    ::testing::ValuesIn(batchSizesTemplate),
-                                    ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
-                            LoadNetworkCacheTestBase::getTestCaseName);
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_Behavior_CachingSupportCase_Template,
+                         LoadNetworkCacheTestBase,
+                         ::testing::Combine(::testing::ValuesIn(LoadNetworkCacheTestBase::getStandardFunctions()),
+                                            ::testing::ValuesIn(precisionsTemplate),
+                                            ::testing::ValuesIn(batchSizesTemplate),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
+                         LoadNetworkCacheTestBase::getTestCaseName);
+}  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/core_integration.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/core_integration.cpp
index 55be786c2a6ffa..858ba1f0d7b254 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/core_integration.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/core_integration.cpp
@@ -2,12 +2,12 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <utility>
+#include "behavior/plugin/core_integration.hpp"
+
 #include <string>
+#include <utility>
 #include <vector>
 
-#include "behavior/plugin/core_integration.hpp"
-
 using namespace BehaviorTestsDefinitions;
 
 namespace {
@@ -16,54 +16,54 @@ namespace {
 // IE Class Common tests with <pluginName, deviceName params>
 //
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassBasicTestP, IEClassBasicTestP,
-        ::testing::Values(std::make_pair("openvino_template_plugin", ov::test::utils::DEVICE_TEMPLATE)));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassBasicTestP,
+                         IEClassBasicTestP,
+                         ::testing::Values(std::make_pair("openvino_template_plugin",
+                                                          ov::test::utils::DEVICE_TEMPLATE)));
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassNetworkTestP, IEClassNetworkTestP,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassNetworkTestP,
+                         IEClassNetworkTestP,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
 //
 // IE Class GetMetric
 //
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetMetricTest, IEClassGetMetricTest_SUPPORTED_CONFIG_KEYS,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
-
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetMetricTest, IEClassGetMetricTest_SUPPORTED_METRICS,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetMetricTest,
+                         IEClassGetMetricTest_SUPPORTED_CONFIG_KEYS,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetMetricTest, IEClassGetMetricTest_AVAILABLE_DEVICES,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetMetricTest,
+                         IEClassGetMetricTest_SUPPORTED_METRICS,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetMetricTest, IEClassGetMetricTest_FULL_DEVICE_NAME,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetMetricTest,
+                         IEClassGetMetricTest_AVAILABLE_DEVICES,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetMetricTest, IEClassGetMetricTest_OPTIMIZATION_CAPABILITIES,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetMetricTest,
+                         IEClassGetMetricTest_FULL_DEVICE_NAME,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetMetricTest, IEClassGetMetricTest_RANGE_FOR_ASYNC_INFER_REQUESTS,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetMetricTest,
+                         IEClassGetMetricTest_OPTIMIZATION_CAPABILITIES,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetMetricTest, IEClassGetMetricTest_ThrowUnsupported,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetMetricTest,
+                         IEClassGetMetricTest_RANGE_FOR_ASYNC_INFER_REQUESTS,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetConfigTest, IEClassGetConfigTest_ThrowUnsupported,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetMetricTest,
+                         IEClassGetMetricTest_ThrowUnsupported,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetAvailableDevices, IEClassGetAvailableDevices,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetConfigTest,
+                         IEClassGetConfigTest_ThrowUnsupported,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetAvailableDevices,
+                         IEClassGetAvailableDevices,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
 //
 // IE Class SetConfig
@@ -117,9 +117,9 @@ TEST_F(IEClassSetConfigTestHETERO, smoke_SetConfigNoThrow) {
 // IE Class GetConfig
 //
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassGetConfigTest, IEClassGetConfigTest,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassGetConfigTest,
+                         IEClassGetConfigTest,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
 class IEClassGetConfigTestTEMPLATE : public BehaviorTestsUtils::IEClassNetworkTest,
                                      public BehaviorTestsUtils::IEPluginTestBase {
@@ -137,7 +137,7 @@ TEST_F(IEClassGetConfigTestTEMPLATE, smoke_GetConfigNoThrow) {
     ASSERT_NO_THROW(p = ie.GetMetric(deviceName, METRIC_KEY(SUPPORTED_CONFIG_KEYS)));
     auto configValues = p.as<std::vector<std::string>>();
 
-    for (auto &&confKey : configValues) {
+    for (auto&& confKey : configValues) {
         if (CONFIG_KEY(DEVICE_ID) == confKey) {
             auto defaultDeviceID = ie.GetConfig(deviceName, CONFIG_KEY(DEVICE_ID)).as<std::string>();
             std::cout << CONFIG_KEY(DEVICE_ID) << " : " << defaultDeviceID << std::endl;
@@ -153,13 +153,13 @@ TEST_F(IEClassGetConfigTestTEMPLATE, smoke_GetConfigNoThrow) {
 
 // IE Class Query network
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassQueryNetworkTest, IEClassQueryNetworkTest,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassQueryNetworkTest,
+                         IEClassQueryNetworkTest,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
 
 // IE Class Load network
 
-INSTANTIATE_TEST_SUITE_P(
-        smoke_IEClassLoadNetworkTest, IEClassLoadNetworkTest,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
-} // namespace
+INSTANTIATE_TEST_SUITE_P(smoke_IEClassLoadNetworkTest,
+                         IEClassLoadNetworkTest,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE));
+}  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/life_time.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/life_time.cpp
index 0bc6c5ca1f32a3..b505320e1e0991 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/life_time.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/life_time.cpp
@@ -8,7 +8,7 @@ using namespace BehaviorTestsDefinitions;
 
 namespace {
 
-const std::vector<std::vector<int >> orders = {
+const std::vector<std::vector<int>> orders = {
     // 0 - plugin
     // 1 - executable_network
     // 2 - infer_request
@@ -17,23 +17,23 @@ const std::vector<std::vector<int >> orders = {
     {1, 0, 2},
     {1, 2, 0},
     {2, 0, 1},
-    {2, 1, 0}
-};
-
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, HoldersTest,
-        ::testing::Combine(
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        ::testing::ValuesIn(orders)),
-        HoldersTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, HoldersTestImportNetwork,
-        ::testing::Combine(
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE, "HETERO:TEMPLATE"),
-        ::testing::ValuesIn(orders)),
-        HoldersTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, HoldersTestOnImportedNetwork,
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE, "HETERO:TEMPLATE"),
-        HoldersTestOnImportedNetwork::getTestCaseName);
+    {2, 1, 0}};
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         HoldersTest,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(orders)),
+                         HoldersTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         HoldersTestImportNetwork,
+                         ::testing::Combine(::testing::Values(ov::test::utils::DEVICE_TEMPLATE, "HETERO:TEMPLATE"),
+                                            ::testing::ValuesIn(orders)),
+                         HoldersTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         HoldersTestOnImportedNetwork,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE, "HETERO:TEMPLATE"),
+                         HoldersTestOnImportedNetwork::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/preprocessing.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/preprocessing.cpp
index adc17a6d4035d8..ea8d9a2e62217e 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/preprocessing.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/preprocessing.cpp
@@ -10,33 +10,30 @@ using namespace BehaviorTestsDefinitions;
 
 namespace {
 
-const std::vector<InferenceEngine::Precision> inputPrecisions = {
-    InferenceEngine::Precision::U8,
-    InferenceEngine::Precision::FP32
-};
-
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
-
-INSTANTIATE_TEST_SUITE_P(smoke_Behavior_PreprocessingPrecisionConvertTestsViaSetInput, PreprocessingPrecisionConvertTest,
-                        ::testing::Combine(
-                                ::testing::ValuesIn(inputPrecisions),
-                                ::testing::Values(4),               // Number of input tensor channels
-                                ::testing::Values(true),            // Use SetInput
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        PreprocessingPrecisionConvertTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Behavior_PreprocessingPrecisionConvertTestsViaGetBlob, PreprocessingPrecisionConvertTest,
-                        ::testing::Combine(
-                                ::testing::ValuesIn(inputPrecisions),
-                                ::testing::Values(4),          // Number of input tensor channels (blob_copy only supports 4d and 5d tensors)
-                                ::testing::Values(false),      // use GetBlob
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        PreprocessingPrecisionConvertTest::getTestCaseName);
+const std::vector<InferenceEngine::Precision> inputPrecisions = {InferenceEngine::Precision::U8,
+                                                                 InferenceEngine::Precision::FP32};
+
+const std::vector<std::map<std::string, std::string>> configs = {{}};
+
+INSTANTIATE_TEST_SUITE_P(smoke_Behavior_PreprocessingPrecisionConvertTestsViaSetInput,
+                         PreprocessingPrecisionConvertTest,
+                         ::testing::Combine(::testing::ValuesIn(inputPrecisions),
+                                            ::testing::Values(4),     // Number of input tensor channels
+                                            ::testing::Values(true),  // Use SetInput
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         PreprocessingPrecisionConvertTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_Behavior_PreprocessingPrecisionConvertTestsViaGetBlob,
+                         PreprocessingPrecisionConvertTest,
+                         ::testing::Combine(::testing::ValuesIn(inputPrecisions),
+                                            ::testing::Values(4),  // Number of input tensor channels (blob_copy only
+                                                                   // supports 4d and 5d tensors)
+                                            ::testing::Values(false),  // use GetBlob
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         PreprocessingPrecisionConvertTest::getTestCaseName);
 
 }  // namespace
 
-#endif // ENABLE_GAPI_PREPROCESSING
+#endif  // ENABLE_GAPI_PREPROCESSING
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/set_preprocess.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/set_preprocess.cpp
index 42f7e9fb7d929e..e570c6fc0f6d12 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/set_preprocess.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/set_preprocess.cpp
@@ -8,49 +8,40 @@ using namespace BehaviorTestsDefinitions;
 
 namespace {
 
-const std::vector<InferenceEngine::Precision> netPrecisions = {
-    InferenceEngine::Precision::FP32,
-    InferenceEngine::Precision::FP16
-};
+const std::vector<InferenceEngine::Precision> netPrecisions = {InferenceEngine::Precision::FP32,
+                                                               InferenceEngine::Precision::FP16};
 
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
+const std::vector<std::map<std::string, std::string>> configs = {{}};
 
 const std::vector<std::map<std::string, std::string>> multiConfigs = {
-        {{ InferenceEngine::MultiDeviceConfigParams::KEY_MULTI_DEVICE_PRIORITIES,
-           ov::test::utils::DEVICE_TEMPLATE }}
-};
+    {{InferenceEngine::MultiDeviceConfigParams::KEY_MULTI_DEVICE_PRIORITIES, ov::test::utils::DEVICE_TEMPLATE}}};
 
 const std::vector<std::map<std::string, std::string>> heteroConfigs = {
-        {{ "TARGET_FALLBACK", ov::test::utils::DEVICE_TEMPLATE }}
-};
+    {{"TARGET_FALLBACK", ov::test::utils::DEVICE_TEMPLATE}}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, InferRequestPreprocessTest,
-                        ::testing::Combine(
-                                ::testing::ValuesIn(netPrecisions),
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        InferRequestPreprocessTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         InferRequestPreprocessTest,
+                         ::testing::Combine(::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         InferRequestPreprocessTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Multi_BehaviorTests, InferRequestPreprocessTest,
-                        ::testing::Combine(
-                                ::testing::ValuesIn(netPrecisions),
-                                ::testing::Values(ov::test::utils::DEVICE_MULTI),
-                                ::testing::ValuesIn(multiConfigs)),
-                        InferRequestPreprocessTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Multi_BehaviorTests,
+                         InferRequestPreprocessTest,
+                         ::testing::Combine(::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(ov::test::utils::DEVICE_MULTI),
+                                            ::testing::ValuesIn(multiConfigs)),
+                         InferRequestPreprocessTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests, InferRequestPreprocessTest,
-                        ::testing::Combine(
-                                ::testing::ValuesIn(netPrecisions),
-                                ::testing::Values(ov::test::utils::DEVICE_HETERO),
-                                ::testing::ValuesIn(heteroConfigs)),
-                        InferRequestPreprocessTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_Hetero_BehaviorTests,
+                         InferRequestPreprocessTest,
+                         ::testing::Combine(::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(ov::test::utils::DEVICE_HETERO),
+                                            ::testing::ValuesIn(heteroConfigs)),
+                         InferRequestPreprocessTest::getTestCaseName);
 
-const std::vector<InferenceEngine::Precision> ioPrecisions = {
-    InferenceEngine::Precision::FP32,
-    InferenceEngine::Precision::U8
-};
+const std::vector<InferenceEngine::Precision> ioPrecisions = {InferenceEngine::Precision::FP32,
+                                                              InferenceEngine::Precision::U8};
 const std::vector<InferenceEngine::Layout> netLayouts = {
     InferenceEngine::Layout::NCHW,
 };
@@ -60,18 +51,18 @@ const std::vector<InferenceEngine::Layout> ioLayouts = {
     InferenceEngine::Layout::NHWC,
 };
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, InferRequestPreprocessConversionTest,
-                        ::testing::Combine(
-                                ::testing::ValuesIn(netPrecisions),
-                                ::testing::ValuesIn(ioPrecisions),
-                                ::testing::ValuesIn(ioPrecisions),
-                                ::testing::ValuesIn(netLayouts),
-                                ::testing::ValuesIn(ioLayouts),
-                                ::testing::ValuesIn(ioLayouts),
-                                ::testing::Bool(),
-                                ::testing::Bool(),
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                                ::testing::ValuesIn(configs)),
-                        InferRequestPreprocessConversionTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         InferRequestPreprocessConversionTest,
+                         ::testing::Combine(::testing::ValuesIn(netPrecisions),
+                                            ::testing::ValuesIn(ioPrecisions),
+                                            ::testing::ValuesIn(ioPrecisions),
+                                            ::testing::ValuesIn(netLayouts),
+                                            ::testing::ValuesIn(ioLayouts),
+                                            ::testing::ValuesIn(ioLayouts),
+                                            ::testing::Bool(),
+                                            ::testing::Bool(),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::ValuesIn(configs)),
+                         InferRequestPreprocessConversionTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/synthetic.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/synthetic.cpp
index c3e82400793055..6a152b6bdcd615 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/synthetic.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/synthetic.cpp
@@ -14,71 +14,97 @@ using namespace HeteroTests;
 // this tests load plugin by library name: this is not available during static linkage
 #ifndef OPENVINO_STATIC_LIBRARY
 
-INSTANTIATE_TEST_SUITE_P(smoke_manyTargetInputs, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::withMajorNodesFunctions(
-                                        [] {return ngraph::builder::subgraph::makeConvPool2Relu2();}, {"Conv_1"}, true))),
-                        HeteroSyntheticTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_SingleMajorNode, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::_singleMajorNodeFunctions)),
-                        HeteroSyntheticTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(nightly_RandomMajorNodes, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::_randomMajorNodeFunctions)),
-                        HeteroSyntheticTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(
+    smoke_manyTargetInputs,
+    HeteroSyntheticTest,
+    ::testing::Combine(::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                                      {"TEMPLATE1", "openvino_template_plugin"}}),
+                       ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::withMajorNodesFunctions(
+                           [] {
+                               return ngraph::builder::subgraph::makeConvPool2Relu2();
+                           },
+                           {"Conv_1"},
+                           true))),
+    HeteroSyntheticTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(
+    smoke_SingleMajorNode,
+    HeteroSyntheticTest,
+    ::testing::Combine(::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                                      {"TEMPLATE1", "openvino_template_plugin"}}),
+                       ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::_singleMajorNodeFunctions)),
+    HeteroSyntheticTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(
+    nightly_RandomMajorNodes,
+    HeteroSyntheticTest,
+    ::testing::Combine(::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                                      {"TEMPLATE1", "openvino_template_plugin"}}),
+                       ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::_randomMajorNodeFunctions)),
+    HeteroSyntheticTest::getTestCaseName);
 
 static std::vector<std::function<std::shared_ptr<ngraph::Function>()>> dynamicBuilders = {
-    [] {return ngraph::builder::subgraph::makeConvPoolReluNonZero();},
+    [] {
+        return ngraph::builder::subgraph::makeConvPoolReluNonZero();
+    },
 };
 
-INSTANTIATE_TEST_SUITE_P(smoke_NonZeroMajorNode_dynamic, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::withMajorNodesFunctions(
-                                        dynamicBuilders.front(), {"nonZero_1"}))),
-                        HeteroSyntheticTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_NonZeroMajorNode_dynamic_batch, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::withMajorNodesFunctions(
-                                        dynamicBuilders.front(), {"nonZero_1"}, true))),
-                        HeteroSyntheticTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_SingleMajorNode_dynamic, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::singleMajorNodeFunctions(
-                                        dynamicBuilders))),
-                        HeteroSyntheticTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(nightly_RandomMajorNodes_dynamic, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::randomMajorNodeFunctions(
-                                        dynamicBuilders))),
-                        HeteroSyntheticTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(smoke_SingleMajorNode_dynamic_batch, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::singleMajorNodeFunctions(
-                                        dynamicBuilders, true))),
-                        HeteroSyntheticTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(nightly_RandomMajorNodes_dynamic_batch, HeteroSyntheticTest,
-                        ::testing::Combine(
-                                ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"}, {"TEMPLATE1", "openvino_template_plugin"}}),
-                                ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::randomMajorNodeFunctions(
-                                        dynamicBuilders, true))),
-                        HeteroSyntheticTest::getTestCaseName);
-
-#endif // !OPENVINO_STATIC_LIBRARY
+INSTANTIATE_TEST_SUITE_P(
+    smoke_NonZeroMajorNode_dynamic,
+    HeteroSyntheticTest,
+    ::testing::Combine(
+        ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                       {"TEMPLATE1", "openvino_template_plugin"}}),
+        ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::withMajorNodesFunctions(dynamicBuilders.front(),
+                                                                                      {"nonZero_1"}))),
+    HeteroSyntheticTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(
+    smoke_NonZeroMajorNode_dynamic_batch,
+    HeteroSyntheticTest,
+    ::testing::Combine(
+        ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                       {"TEMPLATE1", "openvino_template_plugin"}}),
+        ::testing::ValuesIn(
+            HeteroTests::HeteroSyntheticTest::withMajorNodesFunctions(dynamicBuilders.front(), {"nonZero_1"}, true))),
+    HeteroSyntheticTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(
+    smoke_SingleMajorNode_dynamic,
+    HeteroSyntheticTest,
+    ::testing::Combine(
+        ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                       {"TEMPLATE1", "openvino_template_plugin"}}),
+        ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::singleMajorNodeFunctions(dynamicBuilders))),
+    HeteroSyntheticTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(
+    nightly_RandomMajorNodes_dynamic,
+    HeteroSyntheticTest,
+    ::testing::Combine(
+        ::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                       {"TEMPLATE1", "openvino_template_plugin"}}),
+        ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::randomMajorNodeFunctions(dynamicBuilders))),
+    HeteroSyntheticTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(
+    smoke_SingleMajorNode_dynamic_batch,
+    HeteroSyntheticTest,
+    ::testing::Combine(::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                                      {"TEMPLATE1", "openvino_template_plugin"}}),
+                       ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::singleMajorNodeFunctions(dynamicBuilders,
+                                                                                                      true))),
+    HeteroSyntheticTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(
+    nightly_RandomMajorNodes_dynamic_batch,
+    HeteroSyntheticTest,
+    ::testing::Combine(::testing::Values(std::vector<PluginParameter>{{"TEMPLATE0", "openvino_template_plugin"},
+                                                                      {"TEMPLATE1", "openvino_template_plugin"}}),
+                       ::testing::ValuesIn(HeteroTests::HeteroSyntheticTest::randomMajorNodeFunctions(dynamicBuilders,
+                                                                                                      true))),
+    HeteroSyntheticTest::getTestCaseName);
+
+#endif  // !OPENVINO_STATIC_LIBRARY
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/version.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/version.cpp
index 173c63f3d790ec..7fa154c1b86b1a 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/version.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/plugin/version.cpp
@@ -8,12 +8,11 @@ using namespace BehaviorTestsDefinitions;
 
 namespace {
 
-const std::vector<std::map<std::string, std::string>> configs = {
-    {}
-};
+const std::vector<std::map<std::string, std::string>> configs = {{}};
 
-INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests, VersionTest,
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-                        VersionTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
+                         VersionTest,
+                         ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                         VersionTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp
index d6528bd9f73f78..9aff6a6bcdfb32 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "single_layer_tests/convolution.hpp"
+
 #include <vector>
 
-#include "single_layer_tests/convolution.hpp"
 #include "common_test_utils/test_constants.hpp"
 
 using namespace LayerTestsDefinitions;
@@ -13,128 +14,108 @@ namespace {
 
 // ! [test_convolution:declare_parameters]
 const std::vector<InferenceEngine::Precision> netPrecisions = {
-        InferenceEngine::Precision::FP32,
-        InferenceEngine::Precision::FP16,
+    InferenceEngine::Precision::FP32,
+    InferenceEngine::Precision::FP16,
 };
 
 /* ============= 2D Convolution ============= */
 
-const std::vector<std::vector<size_t >> kernels = {{3, 3},
-                                                   {3, 5}};
-const std::vector<std::vector<size_t >> strides = {{1, 1},
-                                                   {1, 3}};
-const std::vector<std::vector<ptrdiff_t>> padBegins = {{0, 0},
-                                                       {0, 3}};
-const std::vector<std::vector<ptrdiff_t>> padEnds = {{0, 0},
-                                                     {0, 3}};
-const std::vector<std::vector<size_t >> dilations = {{1, 1},
-                                                     {3, 1}};
+const std::vector<std::vector<size_t>> kernels = {{3, 3}, {3, 5}};
+const std::vector<std::vector<size_t>> strides = {{1, 1}, {1, 3}};
+const std::vector<std::vector<ptrdiff_t>> padBegins = {{0, 0}, {0, 3}};
+const std::vector<std::vector<ptrdiff_t>> padEnds = {{0, 0}, {0, 3}};
+const std::vector<std::vector<size_t>> dilations = {{1, 1}, {3, 1}};
 const std::vector<size_t> numOutChannels = {1, 5};
-const std::vector<ngraph::op::PadType> padTypes = {
-        ngraph::op::PadType::EXPLICIT,
-        ngraph::op::PadType::VALID
-};
-
-const auto conv2DParams_ExplicitPadding = ::testing::Combine(
-        ::testing::ValuesIn(kernels),
-        ::testing::ValuesIn(strides),
-        ::testing::ValuesIn(padBegins),
-        ::testing::ValuesIn(padEnds),
-        ::testing::ValuesIn(dilations),
-        ::testing::ValuesIn(numOutChannels),
-        ::testing::Values(ngraph::op::PadType::EXPLICIT)
-);
+const std::vector<ngraph::op::PadType> padTypes = {ngraph::op::PadType::EXPLICIT, ngraph::op::PadType::VALID};
+
+const auto conv2DParams_ExplicitPadding = ::testing::Combine(::testing::ValuesIn(kernels),
+                                                             ::testing::ValuesIn(strides),
+                                                             ::testing::ValuesIn(padBegins),
+                                                             ::testing::ValuesIn(padEnds),
+                                                             ::testing::ValuesIn(dilations),
+                                                             ::testing::ValuesIn(numOutChannels),
+                                                             ::testing::Values(ngraph::op::PadType::EXPLICIT));
 // ! [test_convolution:declare_parameters]
 
-const auto conv2DParams_AutoPadValid = ::testing::Combine(
-        ::testing::ValuesIn(kernels),
-        ::testing::ValuesIn(strides),
-        ::testing::Values(std::vector<ptrdiff_t>({0, 0})),
-        ::testing::Values(std::vector<ptrdiff_t>({0, 0})),
-        ::testing::ValuesIn(dilations),
-        ::testing::ValuesIn(numOutChannels),
-        ::testing::Values(ngraph::op::PadType::VALID)
-);
+const auto conv2DParams_AutoPadValid = ::testing::Combine(::testing::ValuesIn(kernels),
+                                                          ::testing::ValuesIn(strides),
+                                                          ::testing::Values(std::vector<ptrdiff_t>({0, 0})),
+                                                          ::testing::Values(std::vector<ptrdiff_t>({0, 0})),
+                                                          ::testing::ValuesIn(dilations),
+                                                          ::testing::ValuesIn(numOutChannels),
+                                                          ::testing::Values(ngraph::op::PadType::VALID));
 
 // ! [test_convolution:instantiate]
-INSTANTIATE_TEST_SUITE_P(Convolution2D_ExplicitPadding, ConvolutionLayerTest,
-                         ::testing::Combine(
-                                 conv2DParams_ExplicitPadding,
-                                 ::testing::ValuesIn(netPrecisions),
-                                 ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                 ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                 ::testing::Values(InferenceEngine::Layout::ANY),
-                                 ::testing::Values(InferenceEngine::Layout::ANY),
-                                 ::testing::Values(std::vector<size_t >({1, 3, 30, 30})),
-                                 ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
+INSTANTIATE_TEST_SUITE_P(Convolution2D_ExplicitPadding,
+                         ConvolutionLayerTest,
+                         ::testing::Combine(conv2DParams_ExplicitPadding,
+                                            ::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(std::vector<size_t>({1, 3, 30, 30})),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
                          ConvolutionLayerTest::getTestCaseName);
 // ! [test_convolution:instantiate]
 
-INSTANTIATE_TEST_SUITE_P(Convolution2D_AutoPadValid, ConvolutionLayerTest,
-                         ::testing::Combine(
-                                 conv2DParams_AutoPadValid,
-                                 ::testing::ValuesIn(netPrecisions),
-                                 ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                 ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                 ::testing::Values(InferenceEngine::Layout::ANY),
-                                 ::testing::Values(InferenceEngine::Layout::ANY),
-                                 ::testing::Values(std::vector<size_t >({1, 3, 30, 30})),
-                                 ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
+INSTANTIATE_TEST_SUITE_P(Convolution2D_AutoPadValid,
+                         ConvolutionLayerTest,
+                         ::testing::Combine(conv2DParams_AutoPadValid,
+                                            ::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(std::vector<size_t>({1, 3, 30, 30})),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
                          ConvolutionLayerTest::getTestCaseName);
 
 /* ============= 3D Convolution ============= */
 
-const std::vector<std::vector<size_t >> kernels3d = {{3, 3, 3},
-                                                     {3, 5, 3}};
-const std::vector<std::vector<ptrdiff_t>> paddings3d = {{0, 0, 0},
-                                                        {0, 2, 0}};
-
-const std::vector<std::vector<size_t >> strides3d = {{1, 1, 1},
-                                                     {1, 2, 1}};
-const std::vector<std::vector<size_t >> dilations3d = {{1, 1, 1},
-                                                       {1, 2, 1}};
-
-const auto conv3DParams_ExplicitPadding = ::testing::Combine(
-        ::testing::ValuesIn(kernels3d),
-        ::testing::ValuesIn(strides3d),
-        ::testing::ValuesIn(paddings3d),
-        ::testing::ValuesIn(paddings3d),
-        ::testing::ValuesIn(dilations3d),
-        ::testing::Values(5),
-        ::testing::Values(ngraph::op::PadType::EXPLICIT)
-);
-const auto conv3DParams_AutoPadValid = ::testing::Combine(
-        ::testing::ValuesIn(kernels3d),
-        ::testing::ValuesIn(strides3d),
-        ::testing::Values(std::vector<ptrdiff_t>({0, 0, 0})),
-        ::testing::Values(std::vector<ptrdiff_t>({0, 0, 0})),
-        ::testing::ValuesIn(dilations3d),
-        ::testing::Values(5),
-        ::testing::Values(ngraph::op::PadType::VALID)
-);
-
-INSTANTIATE_TEST_SUITE_P(smoke_Convolution3D_ExplicitPadding, ConvolutionLayerTest,
-                         ::testing::Combine(
-                                 conv3DParams_ExplicitPadding,
-                                 ::testing::ValuesIn(netPrecisions),
-                                 ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                 ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                 ::testing::Values(InferenceEngine::Layout::ANY),
-                                 ::testing::Values(InferenceEngine::Layout::ANY),
-                                 ::testing::Values(std::vector<size_t >({1, 3, 10, 10, 10})),
-                                 ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
+const std::vector<std::vector<size_t>> kernels3d = {{3, 3, 3}, {3, 5, 3}};
+const std::vector<std::vector<ptrdiff_t>> paddings3d = {{0, 0, 0}, {0, 2, 0}};
+
+const std::vector<std::vector<size_t>> strides3d = {{1, 1, 1}, {1, 2, 1}};
+const std::vector<std::vector<size_t>> dilations3d = {{1, 1, 1}, {1, 2, 1}};
+
+const auto conv3DParams_ExplicitPadding = ::testing::Combine(::testing::ValuesIn(kernels3d),
+                                                             ::testing::ValuesIn(strides3d),
+                                                             ::testing::ValuesIn(paddings3d),
+                                                             ::testing::ValuesIn(paddings3d),
+                                                             ::testing::ValuesIn(dilations3d),
+                                                             ::testing::Values(5),
+                                                             ::testing::Values(ngraph::op::PadType::EXPLICIT));
+const auto conv3DParams_AutoPadValid = ::testing::Combine(::testing::ValuesIn(kernels3d),
+                                                          ::testing::ValuesIn(strides3d),
+                                                          ::testing::Values(std::vector<ptrdiff_t>({0, 0, 0})),
+                                                          ::testing::Values(std::vector<ptrdiff_t>({0, 0, 0})),
+                                                          ::testing::ValuesIn(dilations3d),
+                                                          ::testing::Values(5),
+                                                          ::testing::Values(ngraph::op::PadType::VALID));
+
+INSTANTIATE_TEST_SUITE_P(smoke_Convolution3D_ExplicitPadding,
+                         ConvolutionLayerTest,
+                         ::testing::Combine(conv3DParams_ExplicitPadding,
+                                            ::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(std::vector<size_t>({1, 3, 10, 10, 10})),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
                          ConvolutionLayerTest::getTestCaseName);
 
-INSTANTIATE_TEST_SUITE_P(nightly_Convolution3D_AutoPadValid, ConvolutionLayerTest,
-                         ::testing::Combine(
-                                 conv3DParams_AutoPadValid,
-                                 ::testing::ValuesIn(netPrecisions),
-                                 ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                 ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                 ::testing::Values(InferenceEngine::Layout::ANY),
-                                 ::testing::Values(InferenceEngine::Layout::ANY),
-                                 ::testing::Values(std::vector<size_t >({1, 3, 10, 10, 10})),
-                                 ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
+INSTANTIATE_TEST_SUITE_P(nightly_Convolution3D_AutoPadValid,
+                         ConvolutionLayerTest,
+                         ::testing::Combine(conv3DParams_AutoPadValid,
+                                            ::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(std::vector<size_t>({1, 3, 10, 10, 10})),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
                          ConvolutionLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/eltwise.cpp b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/eltwise.cpp
index d476ff03b974bc..1c2bfa338e78ed 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/eltwise.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/eltwise.cpp
@@ -2,130 +2,130 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <vector>
 #include "single_layer_tests/eltwise.hpp"
+
+#include <vector>
+
 #include "common_test_utils/test_constants.hpp"
 
 using namespace ov::test::subgraph;
 
 namespace {
 std::vector<std::vector<ov::Shape>> inShapesStatic = {
-        {{2}},
-        {{2, 200}},
-        {{10, 200}},
-        {{1, 10, 100}},
-        {{4, 4, 16}},
-        {{1, 1, 1, 3}},
-        {{2, 17, 5, 4}, {1, 17, 1, 1}},
-        {{2, 17, 5, 1}, {1, 17, 1, 4}},
-        {{1, 2, 4}},
-        {{1, 4, 4}},
-        {{1, 4, 4, 1}},
-        {{1, 1, 1, 1, 1, 1, 3}},
-        {{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}},
+    {{2}},
+    {{2, 200}},
+    {{10, 200}},
+    {{1, 10, 100}},
+    {{4, 4, 16}},
+    {{1, 1, 1, 3}},
+    {{2, 17, 5, 4}, {1, 17, 1, 1}},
+    {{2, 17, 5, 1}, {1, 17, 1, 4}},
+    {{1, 2, 4}},
+    {{1, 4, 4}},
+    {{1, 4, 4, 1}},
+    {{1, 1, 1, 1, 1, 1, 3}},
+    {{1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}},
 };
 
 std::vector<std::vector<ov::test::InputShape>> inShapesDynamic = {
-        {{{ngraph::Dimension(1, 10), 200}, {{2, 200}, {1, 200}}},
-         {{ngraph::Dimension(1, 10), 200}, {{2, 200}, {5, 200}}}},
+    {{{ngraph::Dimension(1, 10), 200}, {{2, 200}, {1, 200}}}, {{ngraph::Dimension(1, 10), 200}, {{2, 200}, {5, 200}}}},
 };
 
 std::vector<ov::test::ElementType> netPrecisions = {
-        ov::element::f32,
-        ov::element::f16,
-        ov::element::i32,
+    ov::element::f32,
+    ov::element::f16,
+    ov::element::i32,
 };
 
 std::vector<ngraph::helpers::InputLayerType> secondaryInputTypes = {
-        ngraph::helpers::InputLayerType::CONSTANT,
-        ngraph::helpers::InputLayerType::PARAMETER,
+    ngraph::helpers::InputLayerType::CONSTANT,
+    ngraph::helpers::InputLayerType::PARAMETER,
 };
 
 std::vector<ngraph::helpers::InputLayerType> secondaryInputTypesDynamic = {
-        ngraph::helpers::InputLayerType::PARAMETER,
+    ngraph::helpers::InputLayerType::PARAMETER,
 };
 
 std::vector<ov::test::utils::OpType> opTypes = {
-        ov::test::utils::OpType::SCALAR,
-        ov::test::utils::OpType::VECTOR,
+    ov::test::utils::OpType::SCALAR,
+    ov::test::utils::OpType::VECTOR,
 };
 
 std::vector<ov::test::utils::OpType> opTypesDynamic = {
-        ov::test::utils::OpType::VECTOR,
+    ov::test::utils::OpType::VECTOR,
 };
 
-std::vector<ngraph::helpers::EltwiseTypes> eltwiseOpTypes = {
-        ngraph::helpers::EltwiseTypes::ADD,
-        ngraph::helpers::EltwiseTypes::MULTIPLY,
-        ngraph::helpers::EltwiseTypes::SUBTRACT,
-        ngraph::helpers::EltwiseTypes::DIVIDE,
-        ngraph::helpers::EltwiseTypes::FLOOR_MOD,
-        ngraph::helpers::EltwiseTypes::SQUARED_DIFF,
-        ngraph::helpers::EltwiseTypes::POWER,
-        ngraph::helpers::EltwiseTypes::MOD
-};
+std::vector<ngraph::helpers::EltwiseTypes> eltwiseOpTypes = {ngraph::helpers::EltwiseTypes::ADD,
+                                                             ngraph::helpers::EltwiseTypes::MULTIPLY,
+                                                             ngraph::helpers::EltwiseTypes::SUBTRACT,
+                                                             ngraph::helpers::EltwiseTypes::DIVIDE,
+                                                             ngraph::helpers::EltwiseTypes::FLOOR_MOD,
+                                                             ngraph::helpers::EltwiseTypes::SQUARED_DIFF,
+                                                             ngraph::helpers::EltwiseTypes::POWER,
+                                                             ngraph::helpers::EltwiseTypes::MOD};
 
 std::vector<ngraph::helpers::EltwiseTypes> eltwiseOpTypesDynamic = {
-        ngraph::helpers::EltwiseTypes::ADD,
-        ngraph::helpers::EltwiseTypes::MULTIPLY,
-        ngraph::helpers::EltwiseTypes::SUBTRACT,
+    ngraph::helpers::EltwiseTypes::ADD,
+    ngraph::helpers::EltwiseTypes::MULTIPLY,
+    ngraph::helpers::EltwiseTypes::SUBTRACT,
 };
 
 ov::test::Config additional_config = {};
 
-const auto multiply_params = ::testing::Combine(
-        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(inShapesStatic)),
-        ::testing::ValuesIn(eltwiseOpTypes),
-        ::testing::ValuesIn(secondaryInputTypes),
-        ::testing::ValuesIn(opTypes),
-        ::testing::ValuesIn(netPrecisions),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        ::testing::Values(additional_config));
-
-const auto multiply_params_dynamic = ::testing::Combine(
-        ::testing::ValuesIn(inShapesDynamic),
-        ::testing::ValuesIn(eltwiseOpTypesDynamic),
-        ::testing::ValuesIn(secondaryInputTypesDynamic),
-        ::testing::ValuesIn(opTypesDynamic),
-        ::testing::ValuesIn(netPrecisions),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        ::testing::Values(additional_config));
-
-INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_static, EltwiseLayerTest, multiply_params, EltwiseLayerTest::getTestCaseName);
-INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_dynamic, EltwiseLayerTest, multiply_params_dynamic, EltwiseLayerTest::getTestCaseName);
-
+const auto multiply_params =
+    ::testing::Combine(::testing::ValuesIn(ov::test::static_shapes_to_test_representation(inShapesStatic)),
+                       ::testing::ValuesIn(eltwiseOpTypes),
+                       ::testing::ValuesIn(secondaryInputTypes),
+                       ::testing::ValuesIn(opTypes),
+                       ::testing::ValuesIn(netPrecisions),
+                       ::testing::Values(ov::element::undefined),
+                       ::testing::Values(ov::element::undefined),
+                       ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                       ::testing::Values(additional_config));
+
+const auto multiply_params_dynamic = ::testing::Combine(::testing::ValuesIn(inShapesDynamic),
+                                                        ::testing::ValuesIn(eltwiseOpTypesDynamic),
+                                                        ::testing::ValuesIn(secondaryInputTypesDynamic),
+                                                        ::testing::ValuesIn(opTypesDynamic),
+                                                        ::testing::ValuesIn(netPrecisions),
+                                                        ::testing::Values(ov::element::undefined),
+                                                        ::testing::Values(ov::element::undefined),
+                                                        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                                        ::testing::Values(additional_config));
+
+INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_static,
+                         EltwiseLayerTest,
+                         multiply_params,
+                         EltwiseLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_dynamic,
+                         EltwiseLayerTest,
+                         multiply_params_dynamic,
+                         EltwiseLayerTest::getTestCaseName);
 
 std::vector<std::vector<ov::Shape>> inShapesSingleThread = {
-        {{1, 2, 3, 4}},
-        {{2, 2, 2, 2}},
-        {{2, 1, 2, 1, 2, 2}},
+    {{1, 2, 3, 4}},
+    {{2, 2, 2, 2}},
+    {{2, 1, 2, 1, 2, 2}},
 };
 
 std::vector<ngraph::helpers::EltwiseTypes> eltwiseOpTypesSingleThread = {
-        ngraph::helpers::EltwiseTypes::ADD,
-        ngraph::helpers::EltwiseTypes::POWER,
+    ngraph::helpers::EltwiseTypes::ADD,
+    ngraph::helpers::EltwiseTypes::POWER,
 };
 
-ov::AnyMap additional_config_single_thread = {
-        {"CPU_THREADS_NUM", "1"}
-};
+ov::AnyMap additional_config_single_thread = {{"CPU_THREADS_NUM", "1"}};
 
-const auto single_thread_params = ::testing::Combine(
-        ::testing::ValuesIn(ov::test::static_shapes_to_test_representation(inShapesSingleThread)),
-        ::testing::ValuesIn(eltwiseOpTypesSingleThread),
-        ::testing::ValuesIn(secondaryInputTypes),
-        ::testing::ValuesIn(opTypes),
-        ::testing::ValuesIn(netPrecisions),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        ::testing::Values(additional_config_single_thread));
+const auto single_thread_params =
+    ::testing::Combine(::testing::ValuesIn(ov::test::static_shapes_to_test_representation(inShapesSingleThread)),
+                       ::testing::ValuesIn(eltwiseOpTypesSingleThread),
+                       ::testing::ValuesIn(secondaryInputTypes),
+                       ::testing::ValuesIn(opTypes),
+                       ::testing::ValuesIn(netPrecisions),
+                       ::testing::Values(ov::element::undefined),
+                       ::testing::Values(ov::element::undefined),
+                       ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                       ::testing::Values(additional_config_single_thread));
 
 INSTANTIATE_TEST_SUITE_P(smoke_SingleThread, EltwiseLayerTest, single_thread_params, EltwiseLayerTest::getTestCaseName);
 
-
-} // namespace
+}  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/reshape.cpp b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/reshape.cpp
index 7e2fff0a97fae2..576490fa79d8de 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/reshape.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/reshape.cpp
@@ -15,45 +15,45 @@ const std::vector<InferenceEngine::Precision> netPrecisions = {
     InferenceEngine::Precision::FP32,
 };
 
-INSTANTIATE_TEST_SUITE_P(
-    smoke_ReshapeCheckDynBatch, ReshapeLayerTest,
-    ::testing::Combine(
-        ::testing::Values(true), ::testing::ValuesIn(netPrecisions),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(std::vector<size_t>({30, 30, 30, 30})),
-        ::testing::Values(std::vector<int64_t>({30, 30, 30, 30})),
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        ::testing::Values(std::map<std::string, std::string>({}))),
-    ReshapeLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_ReshapeCheck, ReshapeLayerTest,
-    ::testing::Combine(
-        ::testing::Values(true), ::testing::ValuesIn(netPrecisions),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(std::vector<size_t>({10, 10, 10, 10})),
-        ::testing::Values(std::vector<int64_t>({10, 0, 100})),
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        ::testing::Values(std::map<std::string, std::string>({}))),
-    ReshapeLayerTest::getTestCaseName);
-
-INSTANTIATE_TEST_SUITE_P(
-    smoke_ReshapeCheckNegative, ReshapeLayerTest,
-    ::testing::Combine(
-        ::testing::Values(true), ::testing::ValuesIn(netPrecisions),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(InferenceEngine::Layout::ANY),
-        ::testing::Values(std::vector<size_t>({10, 10, 10, 10})),
-        ::testing::Values(std::vector<int64_t>({10, -1, 100})),
-        ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        ::testing::Values(std::map<std::string, std::string>({}))),
-    ReshapeLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_ReshapeCheckDynBatch,
+                         ReshapeLayerTest,
+                         ::testing::Combine(::testing::Values(true),
+                                            ::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(std::vector<size_t>({30, 30, 30, 30})),
+                                            ::testing::Values(std::vector<int64_t>({30, 30, 30, 30})),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::Values(std::map<std::string, std::string>({}))),
+                         ReshapeLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_ReshapeCheck,
+                         ReshapeLayerTest,
+                         ::testing::Combine(::testing::Values(true),
+                                            ::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(std::vector<size_t>({10, 10, 10, 10})),
+                                            ::testing::Values(std::vector<int64_t>({10, 0, 100})),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::Values(std::map<std::string, std::string>({}))),
+                         ReshapeLayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_ReshapeCheckNegative,
+                         ReshapeLayerTest,
+                         ::testing::Combine(::testing::Values(true),
+                                            ::testing::ValuesIn(netPrecisions),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(std::vector<size_t>({10, 10, 10, 10})),
+                                            ::testing::Values(std::vector<int64_t>({10, -1, 100})),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                            ::testing::Values(std::map<std::string, std::string>({}))),
+                         ReshapeLayerTest::getTestCaseName);
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/softmax.cpp b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/softmax.cpp
index bc97e14db8e0fd..83c03b7a881e3b 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/softmax.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/softmax.cpp
@@ -2,9 +2,10 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "single_layer_tests/softmax.hpp"
+
 #include <vector>
 
-#include "single_layer_tests/softmax.hpp"
 #include "common_test_utils/test_constants.hpp"
 
 using namespace ov::test::subgraph;
@@ -12,164 +13,140 @@ using namespace ov::test::subgraph;
 namespace {
 
 const std::vector<ov::test::ElementType> netPrecisions = {
-        ov::element::f32,
-        ov::element::f16,
+    ov::element::f32,
+    ov::element::f16,
 };
 
 const std::vector<ov::Shape> inputStaticShape2D = {
-        {1, 100},
-        {100, 1},
-        {10, 10},
+    {1, 100},
+    {100, 1},
+    {10, 10},
 };
 
 const std::vector<ov::test::InputShape> inputDynamicShape2D = {
-        {{ngraph::Dimension::dynamic(), 10}, {{1, 10}, {2, 10}, {10, 10}}},
-        {{ngraph::Dimension(1, 10), 10}, {{1, 10}, {2, 10}, {10, 10}}},
-        {{10, ngraph::Dimension::dynamic()}, {{10, 1}, {10, 5}, {10, 10}}},
-        {{ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic()}, {{1, 10}, {2, 10}, {10, 10}}}
-};
-
-const std::vector<int64_t> axis2D = {
-        -2, -1, 0, 1
-};
-
-const auto params2D_static = testing::Combine(
-        testing::ValuesIn(netPrecisions),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        testing::ValuesIn(ov::test::static_shapes_to_test_representation(inputStaticShape2D)),
-        testing::ValuesIn(axis2D),
-        testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        testing::Values(ov::AnyMap())
-);
-
-const auto params2D_dynamic = testing::Combine(
-        testing::ValuesIn(netPrecisions),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        testing::ValuesIn(inputDynamicShape2D),
-        testing::ValuesIn(axis2D),
-        testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        testing::Values(ov::AnyMap())
-);
-
-INSTANTIATE_TEST_SUITE_P(
-        smoke_SoftMax2D_static,
-        SoftMax8LayerTest,
-        params2D_static,
-        SoftMax8LayerTest::getTestCaseName
-);
-
-INSTANTIATE_TEST_SUITE_P(
-        smoke_SoftMax2D_dynamic,
-        SoftMax8LayerTest,
-        params2D_dynamic,
-        SoftMax8LayerTest::getTestCaseName
-);
+    {{ngraph::Dimension::dynamic(), 10}, {{1, 10}, {2, 10}, {10, 10}}},
+    {{ngraph::Dimension(1, 10), 10}, {{1, 10}, {2, 10}, {10, 10}}},
+    {{10, ngraph::Dimension::dynamic()}, {{10, 1}, {10, 5}, {10, 10}}},
+    {{ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic()}, {{1, 10}, {2, 10}, {10, 10}}}};
+
+const std::vector<int64_t> axis2D = {-2, -1, 0, 1};
+
+const auto params2D_static =
+    testing::Combine(testing::ValuesIn(netPrecisions),
+                     ::testing::Values(ov::element::undefined),
+                     ::testing::Values(ov::element::undefined),
+                     testing::ValuesIn(ov::test::static_shapes_to_test_representation(inputStaticShape2D)),
+                     testing::ValuesIn(axis2D),
+                     testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                     testing::Values(ov::AnyMap()));
+
+const auto params2D_dynamic = testing::Combine(testing::ValuesIn(netPrecisions),
+                                               ::testing::Values(ov::element::undefined),
+                                               ::testing::Values(ov::element::undefined),
+                                               testing::ValuesIn(inputDynamicShape2D),
+                                               testing::ValuesIn(axis2D),
+                                               testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                               testing::Values(ov::AnyMap()));
+
+INSTANTIATE_TEST_SUITE_P(smoke_SoftMax2D_static,
+                         SoftMax8LayerTest,
+                         params2D_static,
+                         SoftMax8LayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_SoftMax2D_dynamic,
+                         SoftMax8LayerTest,
+                         params2D_dynamic,
+                         SoftMax8LayerTest::getTestCaseName);
 
 const std::vector<ov::Shape> inputStaticShape4D = {
-        {1, 100, 1, 1},
-        {50, 100, 4, 1},
-        {2, 100, 10, 1},
+    {1, 100, 1, 1},
+    {50, 100, 4, 1},
+    {2, 100, 10, 1},
 };
 
 const std::vector<ov::test::InputShape> inputDynamicShape4D = {
-        {{ngraph::Dimension::dynamic(), 100, ngraph::Dimension(1, 10), 1}, {{1, 100, 1, 1}, {100, 100, 5, 1}}},
-        {{ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic()},
-                                                                           {{1, 100, 1, 1}, {50, 100, 4, 1}, {2, 100, 10, 1}}},
+    {{ngraph::Dimension::dynamic(), 100, ngraph::Dimension(1, 10), 1}, {{1, 100, 1, 1}, {100, 100, 5, 1}}},
+    {{ngraph::Dimension::dynamic(),
+      ngraph::Dimension::dynamic(),
+      ngraph::Dimension::dynamic(),
+      ngraph::Dimension::dynamic()},
+     {{1, 100, 1, 1}, {50, 100, 4, 1}, {2, 100, 10, 1}}},
 };
 
 const std::vector<ov::test::ElementType> netPrecisions4D = {
-        ov::element::f32,
+    ov::element::f32,
 };
 
 const std::vector<int64_t> axis4D = {0, 1, 2, 3, -1, -2, -3, -4};
 
-const auto params4Dstatic = testing::Combine(
-        testing::ValuesIn(netPrecisions4D),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        testing::ValuesIn(ov::test::static_shapes_to_test_representation(inputStaticShape4D)),
-        testing::ValuesIn(axis4D),
-        testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        testing::Values(ov::AnyMap())
-);
-
-const auto params4Ddynamic = testing::Combine(
-        testing::ValuesIn(netPrecisions4D),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        testing::ValuesIn(inputDynamicShape4D),
-        testing::ValuesIn(axis4D),
-        testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        testing::Values(ov::AnyMap())
-);
-
-INSTANTIATE_TEST_SUITE_P(
-        smoke_SoftMax4D_static,
-        SoftMax8LayerTest,
-        params4Dstatic,
-        SoftMax8LayerTest::getTestCaseName
-);
-
-INSTANTIATE_TEST_SUITE_P(
-        smoke_SoftMax4D_dynamic,
-        SoftMax8LayerTest,
-        params4Ddynamic,
-        SoftMax8LayerTest::getTestCaseName
-);
-
+const auto params4Dstatic =
+    testing::Combine(testing::ValuesIn(netPrecisions4D),
+                     ::testing::Values(ov::element::undefined),
+                     ::testing::Values(ov::element::undefined),
+                     testing::ValuesIn(ov::test::static_shapes_to_test_representation(inputStaticShape4D)),
+                     testing::ValuesIn(axis4D),
+                     testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                     testing::Values(ov::AnyMap()));
+
+const auto params4Ddynamic = testing::Combine(testing::ValuesIn(netPrecisions4D),
+                                              ::testing::Values(ov::element::undefined),
+                                              ::testing::Values(ov::element::undefined),
+                                              testing::ValuesIn(inputDynamicShape4D),
+                                              testing::ValuesIn(axis4D),
+                                              testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                              testing::Values(ov::AnyMap()));
+
+INSTANTIATE_TEST_SUITE_P(smoke_SoftMax4D_static, SoftMax8LayerTest, params4Dstatic, SoftMax8LayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_SoftMax4D_dynamic,
+                         SoftMax8LayerTest,
+                         params4Ddynamic,
+                         SoftMax8LayerTest::getTestCaseName);
 
 const std::vector<ov::Shape> inputStaticShape5D = {
-        {1, 100, 1, 1, 1},
-        {50, 100, 4, 1, 1},
-        {2, 100, 10, 1, 1},
+    {1, 100, 1, 1, 1},
+    {50, 100, 4, 1, 1},
+    {2, 100, 10, 1, 1},
 };
 
 const std::vector<ov::test::InputShape> inputDynamicShape5D = {
-        {{ngraph::Dimension::dynamic(), 100, ngraph::Dimension(1, 10), 1, 1}, {{1, 100, 1, 1, 1}, {100, 100, 5, 1, 1}}},
-        {{ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic()},
-                                                                           {{1, 100, 1, 1, 1}, {50, 100, 4, 1, 1}, {2, 100, 10, 1, 1}}},
+    {{ngraph::Dimension::dynamic(), 100, ngraph::Dimension(1, 10), 1, 1}, {{1, 100, 1, 1, 1}, {100, 100, 5, 1, 1}}},
+    {{ngraph::Dimension::dynamic(),
+      ngraph::Dimension::dynamic(),
+      ngraph::Dimension::dynamic(),
+      ngraph::Dimension::dynamic(),
+      ngraph::Dimension::dynamic()},
+     {{1, 100, 1, 1, 1}, {50, 100, 4, 1, 1}, {2, 100, 10, 1, 1}}},
 };
 
 const std::vector<ov::test::ElementType> netPrecisions5D = {
-        ov::element::f32,
+    ov::element::f32,
 };
 
 const std::vector<int64_t> axis5D = {0, 1, 2, 3, 4, -1, -2, -3, -4, -5};
 
-const auto params5Dstatic = testing::Combine(
-        testing::ValuesIn(netPrecisions5D),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        testing::ValuesIn(ov::test::static_shapes_to_test_representation(inputStaticShape5D)),
-        testing::ValuesIn(axis5D),
-        testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        testing::Values(ov::AnyMap())
-);
-
-const auto params5Ddynamic = testing::Combine(
-        testing::ValuesIn(netPrecisions5D),
-        ::testing::Values(ov::element::undefined),
-        ::testing::Values(ov::element::undefined),
-        testing::ValuesIn(inputDynamicShape5D),
-        testing::ValuesIn(axis5D),
-        testing::Values(ov::test::utils::DEVICE_TEMPLATE),
-        testing::Values(ov::AnyMap())
-);
-
-INSTANTIATE_TEST_SUITE_P(
-        smoke_SoftMax5D_static,
-        SoftMax8LayerTest,
-        params5Dstatic,
-        SoftMax8LayerTest::getTestCaseName
-);
-
-INSTANTIATE_TEST_SUITE_P(
-        smoke_SoftMax5D_dynamic,
-        SoftMax8LayerTest,
-        params5Ddynamic,
-        SoftMax8LayerTest::getTestCaseName
-);
+const auto params5Dstatic =
+    testing::Combine(testing::ValuesIn(netPrecisions5D),
+                     ::testing::Values(ov::element::undefined),
+                     ::testing::Values(ov::element::undefined),
+                     testing::ValuesIn(ov::test::static_shapes_to_test_representation(inputStaticShape5D)),
+                     testing::ValuesIn(axis5D),
+                     testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                     testing::Values(ov::AnyMap()));
+
+const auto params5Ddynamic = testing::Combine(testing::ValuesIn(netPrecisions5D),
+                                              ::testing::Values(ov::element::undefined),
+                                              ::testing::Values(ov::element::undefined),
+                                              testing::ValuesIn(inputDynamicShape5D),
+                                              testing::ValuesIn(axis5D),
+                                              testing::Values(ov::test::utils::DEVICE_TEMPLATE),
+                                              testing::Values(ov::AnyMap()));
+
+INSTANTIATE_TEST_SUITE_P(smoke_SoftMax5D_static, SoftMax8LayerTest, params5Dstatic, SoftMax8LayerTest::getTestCaseName);
+
+INSTANTIATE_TEST_SUITE_P(smoke_SoftMax5D_dynamic,
+                         SoftMax8LayerTest,
+                         params5Ddynamic,
+                         SoftMax8LayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/split.cpp b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/split.cpp
index 337138773ce74d..064f1b5150274f 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/split.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/split.cpp
@@ -2,27 +2,28 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 
+#include "single_layer_tests/split.hpp"
+
 #include <vector>
 
-#include "single_layer_tests/split.hpp"
 #include "common_test_utils/test_constants.hpp"
 
 using namespace LayerTestsDefinitions;
 
 namespace {
 
-INSTANTIATE_TEST_SUITE_P(smoke_NumSplitsCheck, SplitLayerTest,
-                        ::testing::Combine(
-                                ::testing::Values(1, 2, 3, 5, 6, 10, 30),
-                                ::testing::Values(0, 1, 2, 3),
-                                ::testing::Values(InferenceEngine::Precision::FP32),
-                                ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
-                                ::testing::Values(InferenceEngine::Layout::ANY),
-                                ::testing::Values(InferenceEngine::Layout::ANY),
-                                ::testing::Values(std::vector<size_t>({30, 30, 30, 30})),
-                                ::testing::Values(std::vector<size_t>({})),
-                                ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
-                        SplitLayerTest::getTestCaseName);
+INSTANTIATE_TEST_SUITE_P(smoke_NumSplitsCheck,
+                         SplitLayerTest,
+                         ::testing::Combine(::testing::Values(1, 2, 3, 5, 6, 10, 30),
+                                            ::testing::Values(0, 1, 2, 3),
+                                            ::testing::Values(InferenceEngine::Precision::FP32),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Precision::UNSPECIFIED),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(InferenceEngine::Layout::ANY),
+                                            ::testing::Values(std::vector<size_t>({30, 30, 30, 30})),
+                                            ::testing::Values(std::vector<size_t>({})),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE)),
+                         SplitLayerTest::getTestCaseName);
 
 }  // namespace
diff --git a/src/plugins/template/tests/functional/subgraph_reference/base_reference_cnn_test.cpp b/src/plugins/template/tests/functional/subgraph_reference/base_reference_cnn_test.cpp
index df225ad0ca1410..3086055af575ad 100644
--- a/src/plugins/template/tests/functional/subgraph_reference/base_reference_cnn_test.cpp
+++ b/src/plugins/template/tests/functional/subgraph_reference/base_reference_cnn_test.cpp
@@ -2,22 +2,22 @@
 // SPDX-License-Identifier: Apache-2.0
 //
 #include "base_reference_cnn_test.hpp"
-#include "functional_test_utils/ov_plugin_cache.hpp"
-#include "shared_test_classes/base/layer_test_utils.hpp"
 
 #include <gtest/gtest.h>
 
+#include "functional_test_utils/ov_plugin_cache.hpp"
+#include "ie_ngraph_utils.hpp"
 #include "openvino/core/type/element_type.hpp"
 #include "openvino/runtime/allocator.hpp"
 #include "openvino/runtime/tensor.hpp"
+#include "shared_test_classes/base/layer_test_utils.hpp"
 #include "transformations/utils/utils.hpp"
-#include "ie_ngraph_utils.hpp"
 
 using namespace ov;
 
 namespace reference_tests {
 
-ReferenceCNNTest::ReferenceCNNTest(): targetDevice("TEMPLATE") {
+ReferenceCNNTest::ReferenceCNNTest() : targetDevice("TEMPLATE") {
     core = test::utils::PluginCache::get().core(targetDevice);
     legacy_core = PluginCache::get().ie(targetDevice);
 }
@@ -43,22 +43,25 @@ void ReferenceCNNTest::LoadNetworkLegacy() {
     auto inputInfo = legacy_network.getInputsInfo();
     auto outputInfo = legacy_network.getOutputsInfo();
     for (const auto& param : function->get_parameters()) {
-        inputInfo[param->get_friendly_name()]->setPrecision(InferenceEngine::details::convertPrecision(param->get_element_type()));
+        inputInfo[param->get_friendly_name()]->setPrecision(
+            InferenceEngine::details::convertPrecision(param->get_element_type()));
     }
     for (const auto& result : function->get_results()) {
         outputInfo[ov::op::util::create_ie_output_name(result->input_value(0))]->setPrecision(
-                InferenceEngine::details::convertPrecision(result->get_element_type()));
+            InferenceEngine::details::convertPrecision(result->get_element_type()));
     }
     legacy_exec_network = legacy_core->LoadNetwork(legacy_network, targetDevice);
 }
 
 void ReferenceCNNTest::FillInputs() {
     const auto& params = function->get_parameters();
-    std::default_random_engine random(0); // hard-coded seed to make test results predictable
+    std::default_random_engine random(0);  // hard-coded seed to make test results predictable
     std::uniform_int_distribution<int> distrib(0, 255);
     for (const auto& param : params) {
         auto elem_count = shape_size(param->get_output_tensor(0).get_shape());
-        InferenceEngine::TensorDesc d(InferenceEngine::Precision::FP32, param->get_output_tensor(0).get_shape(), InferenceEngine::Layout::NCHW);
+        InferenceEngine::TensorDesc d(InferenceEngine::Precision::FP32,
+                                      param->get_output_tensor(0).get_shape(),
+                                      InferenceEngine::Layout::NCHW);
         auto blob = make_blob_with_precision(d);
         blob->allocate();
 
@@ -98,7 +101,6 @@ void ReferenceCNNTest::InferLegacy() {
     legacy_infer_request.Infer();
 }
 
-
 void ReferenceCNNTest::Validate() {
     for (const auto& result : function->get_results()) {
         auto name = ov::op::util::create_ie_output_name(result->input_value(0));
diff --git a/src/plugins/template/tests/functional/subgraph_reference/preprocess.cpp b/src/plugins/template/tests/functional/subgraph_reference/preprocess.cpp
index 0b58dc517d807d..ea5c3465dbb31b 100644
--- a/src/plugins/template/tests/functional/subgraph_reference/preprocess.cpp
+++ b/src/plugins/template/tests/functional/subgraph_reference/preprocess.cpp
@@ -20,7 +20,7 @@ using namespace reference_tests;
 namespace {
 
 struct RefPreprocessParams {
-    RefPreprocessParams(const std::string& val): name(val) {}
+    RefPreprocessParams(const std::string& val) : name(val) {}
     std::function<std::shared_ptr<ov::Model>()> function;
     std::vector<reference_tests::Tensor> inputs;
     std::vector<reference_tests::Tensor> expected;
@@ -52,11 +52,10 @@ class ReferencePreprocessTest : public testing::TestWithParam<RefPreprocessParam
     }
 };
 
-
 TEST_P(ReferencePreprocessTest, CompareWithHardcodedRefs) {
     Exec();
 }
-} // namespace
+}  // namespace
 
 static std::shared_ptr<Model> create_simple_function(element::Type type, const PartialShape& shape) {
     auto data1 = std::make_shared<op::v0::Parameter>(type, shape);
@@ -95,11 +94,16 @@ static RefPreprocessParams simple_mean_scale() {
     res.function = []() {
         auto f = create_simple_function(element::f32, Shape{1, 3, 2, 2});
         auto p = PrePostProcessor(f);
-        p.input().preprocess().mean(1.f).scale(2.f); p.build();
+        p.input().preprocess().mean(1.f).scale(2.f);
+        p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{1., 3., 5., 7., 9., 11., 13., 15., 17., 19., 21., 23.});
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11.});
+    res.inputs.emplace_back(Shape{1, 3, 2, 2},
+                            element::f32,
+                            std::vector<float>{1., 3., 5., 7., 9., 11., 13., 15., 17., 19., 21., 23.});
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::f32,
+                              std::vector<float>{0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10., 11.});
     return res;
 }
 
@@ -108,12 +112,17 @@ static RefPreprocessParams scale_then_mean() {
     res.function = []() {
         auto f = create_simple_function(element::f32, Shape{1, 3, 2, 2});
         auto p = PrePostProcessor(f);
-        p.input().preprocess().scale(2.0f).mean(2.0f); p.build();
+        p.input().preprocess().scale(2.0f).mean(2.0f);
+        p.build();
         return f;
     };
 
-    res.inputs.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{2., 4., 6., 8., 10., 12., 14., 16., 18., 20., 100., 200.});
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{-1., 0, 1., 2., 3., 4., 5., 6., 7., 8., 48., 98.});
+    res.inputs.emplace_back(Shape{1, 3, 2, 2},
+                            element::f32,
+                            std::vector<float>{2., 4., 6., 8., 10., 12., 14., 16., 18., 20., 100., 200.});
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::f32,
+                              std::vector<float>{-1., 0, 1., 2., 3., 4., 5., 6., 7., 8., 48., 98.});
     return res;
 }
 
@@ -122,13 +131,13 @@ static RefPreprocessParams convert_only() {
     res.function = []() {
         auto f = create_simple_function(element::f32, Shape{1, 1, 2, 2});
         auto p = PrePostProcessor(f);
+        p.input().tensor().set_element_type(element::i16);
         p.input()
-                .tensor().set_element_type(element::i16);
-        p.input().preprocess()
-                .convert_element_type(element::f32)
-                .scale(3.f)
-                .convert_element_type(element::u8)
-                .convert_element_type(element::f32);
+            .preprocess()
+            .convert_element_type(element::f32)
+            .scale(3.f)
+            .convert_element_type(element::u8)
+            .convert_element_type(element::f32);
         p.build();
         return f;
     };
@@ -142,19 +151,17 @@ static RefPreprocessParams convert_element_type_and_scale() {
     res.function = []() {
         auto f = create_simple_function(element::u8, Shape{1, 3, 2, 2});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_element_type(element::i16);
-        p.input().preprocess()
-                .convert_element_type(element::f32)
-                .scale(2.f)
-                .convert_element_type(element::u8);
+        p.input().tensor().set_element_type(element::i16);
+        p.input().preprocess().convert_element_type(element::f32).scale(2.f).convert_element_type(element::u8);
         p.build();
         return f;
     };
 
-    res.inputs.emplace_back(Shape{1, 3, 2, 2}, element::i16,
+    res.inputs.emplace_back(Shape{1, 3, 2, 2},
+                            element::i16,
                             std::vector<int16_t>{2, 3, 6, 8, 10, 12, 14, 16, 18, 20, 10000, 200});
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::u8,
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::u8,
                               std::vector<uint8_t>{1, 1, 3, 4, 5, 6, 7, 8, 9, 10, (uint8_t)5000, 100});
     return res;
 }
@@ -164,8 +171,7 @@ static RefPreprocessParams tensor_element_type_and_scale() {
     res.function = []() {
         auto f = create_simple_function(element::i8, Shape{1, 3, 1, 1});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_element_type(element::f32);
+        p.input().tensor().set_element_type(element::f32);
         p.input().preprocess().scale(2.0f).convert_element_type(element::i8);
         p.build();
         return f;
@@ -206,7 +212,7 @@ static RefPreprocessParams test_multiple() {
         p1.input().preprocess().scale(2.f);
         p1.input().preprocess().mean({1.f, 2.f, 3.f});
         p1.input().preprocess().scale({2.f, 3.f, 4.f});
-        p1.input().preprocess().custom([](const Output<Node> &node) {
+        p1.input().preprocess().custom([](const Output<Node>& node) {
             auto abs = std::make_shared<op::v0::Abs>(node);
             abs->set_friendly_name(node.get_node_shared_ptr()->get_friendly_name() + "/abs");
             return abs;
@@ -227,9 +233,7 @@ static RefPreprocessParams test_2_inputs_basic() {
         auto f = create_n_inputs(2, element::f32, Shape{1, 3, 1, 1});
         auto p = PrePostProcessor(f);
         p.input(0).preprocess().mean(1.f);
-        p.input("tensor_input2").preprocess()
-                .mean(1.f)
-                .scale(2.0f);
+        p.input("tensor_input2").preprocess().mean(1.f).scale(2.0f);
         p.build();
         return f;
     };
@@ -246,8 +250,7 @@ static RefPreprocessParams mean_scale_vector_tensor_layout() {
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 3, 2, 1});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_layout("NC??");
+        p.input().tensor().set_layout("NC??");
         p.input().preprocess().mean({1.f, 2.f, 3.f}).scale({2.f, 3.f, 4.f});
         p.build();
         return f;
@@ -263,8 +266,7 @@ static RefPreprocessParams mean_scale_dynamic_layout() {
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 2, 1, 3});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_layout("N...C");
+        p.input().tensor().set_layout("N...C");
         p.input().preprocess().mean({1.f, 2.f, 3.f}).scale({2.f, 3.f, 4.f});
         p.build();
         return f;
@@ -280,8 +282,7 @@ static RefPreprocessParams resize_to_network_height() {
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 2, 1, 1});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_spatial_dynamic_shape();
+        p.input().tensor().set_spatial_dynamic_shape();
         p.input().preprocess().resize(ResizeAlgorithm::RESIZE_LINEAR);
         p.input().model().set_layout("NHWC");
         p.build();
@@ -297,15 +298,15 @@ static RefPreprocessParams resize_to_network_width() {
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{Dimension::dynamic(), 1, 2, 2});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_spatial_dynamic_shape();
+        p.input().tensor().set_spatial_dynamic_shape();
         p.input().preprocess().resize(ResizeAlgorithm::RESIZE_LINEAR);
         p.input().model().set_layout("NCHW");
         p.build();
         return f;
     };
-    res.inputs.emplace_back(element::f32, Shape{1, 1, 2, 6}, std::vector<float>{0., 1., 2., 3., 4., 5.,
-                                                                                0., 1., 2., 3., 4., 5.});
+    res.inputs.emplace_back(element::f32,
+                            Shape{1, 1, 2, 6},
+                            std::vector<float>{0., 1., 2., 3., 4., 5., 0., 1., 2., 3., 4., 5.});
     res.expected.emplace_back(Shape{1, 1, 2, 2}, element::f32, std::vector<float>{1., 4., 1., 4.});
     return res;
 }
@@ -315,8 +316,7 @@ static RefPreprocessParams resize_from_spatial_dims() {
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{Dimension::dynamic(), 1, 1, 1});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_spatial_static_shape(1, 4);
+        p.input().tensor().set_spatial_static_shape(1, 4);
         p.input().preprocess().resize(ResizeAlgorithm::RESIZE_CUBIC);
         p.input().model().set_layout("NCHW");
         p.build();
@@ -332,17 +332,13 @@ static RefPreprocessParams resize_i8() {
     res.function = []() {
         auto f = create_simple_function(element::i8, PartialShape{1, 3, 1, 1});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor()
-                .set_spatial_dynamic_shape();
+        p.input().tensor().set_spatial_dynamic_shape();
         p.input().preprocess().resize(ResizeAlgorithm::RESIZE_LINEAR);
         p.input().model().set_layout("NCHW");
         p.build();
         return f;
     };
-    res.inputs.emplace_back(element::i8, Shape{1, 3, 2, 2}, std::vector<int8_t>{0, 0, 0, 0,
-                                                                                1, 1, 1, 1,
-                                                                                2, 2, 2, 2});
+    res.inputs.emplace_back(element::i8, Shape{1, 3, 2, 2}, std::vector<int8_t>{0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2});
     res.expected.emplace_back(Shape{1, 3, 1, 1}, element::i8, std::vector<int8_t>{0, 1, 2});
     return res;
 }
@@ -352,8 +348,7 @@ static RefPreprocessParams resize_to_network_width_height() {
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 1, 4, 4});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_spatial_static_shape(5, 5);
+        p.input().tensor().set_spatial_static_shape(5, 5);
         p.input().preprocess().resize(ResizeAlgorithm::RESIZE_NEAREST);
         p.input().model().set_layout("...HW");
         p.build();
@@ -382,8 +377,7 @@ static RefPreprocessParams resize_to_specified_width_height() {
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 1, Dimension::dynamic(), Dimension::dynamic()});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor().set_spatial_dynamic_shape();
+        p.input().tensor().set_spatial_dynamic_shape();
         p.input().preprocess().resize(ResizeAlgorithm::RESIZE_NEAREST, 4, 4);
         p.input().model().set_layout("...HW");
         p.build();
@@ -419,13 +413,34 @@ static RefPreprocessParams convert_layout_nhwc_to_nchw() {
         p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{1, 2, 2, 3}, element::u8, std::vector<uint8_t>{1,  2,  3,       // [H=0, W=0, RGB]
-                                                                                 4,  5,  6,       // [H=0, W=1]
-                                                                                 7,  8,  9,       // [H=1, W=0]
-                                                                                 10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::u8, std::vector<uint8_t>{1, 4, 7, 10,    // R
-                                                                                   2, 5, 8, 11,    // G
-                                                                                   3, 6, 9, 12});  // B
+    res.inputs.emplace_back(Shape{1, 2, 2, 3},
+                            element::u8,
+                            std::vector<uint8_t>{1,
+                                                 2,
+                                                 3,  // [H=0, W=0, RGB]
+                                                 4,
+                                                 5,
+                                                 6,  // [H=0, W=1]
+                                                 7,
+                                                 8,
+                                                 9,  // [H=1, W=0]
+                                                 10,
+                                                 11,
+                                                 12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::u8,
+                              std::vector<uint8_t>{1,
+                                                   4,
+                                                   7,
+                                                   10,  // R
+                                                   2,
+                                                   5,
+                                                   8,
+                                                   11,  // G
+                                                   3,
+                                                   6,
+                                                   9,
+                                                   12});  // B
     return res;
 }
 
@@ -441,13 +456,34 @@ static RefPreprocessParams convert_layout_nhwc_to_nchw_fully_dynamic() {
         p.build();
         return f;
     };
-    res.inputs.emplace_back(element::u8, Shape{1, 2, 2, 3}, std::vector<uint8_t>{1,  2,  3,       // [H=0, W=0, RGB]
-                                                                                 4,  5,  6,       // [H=0, W=1]
-                                                                                 7,  8,  9,       // [H=1, W=0]
-                                                                                 10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::u8, std::vector<uint8_t>{1, 4, 7, 10,    // R
-                                                                                   2, 5, 8, 11,    // G
-                                                                                   3, 6, 9, 12});  // B
+    res.inputs.emplace_back(element::u8,
+                            Shape{1, 2, 2, 3},
+                            std::vector<uint8_t>{1,
+                                                 2,
+                                                 3,  // [H=0, W=0, RGB]
+                                                 4,
+                                                 5,
+                                                 6,  // [H=0, W=1]
+                                                 7,
+                                                 8,
+                                                 9,  // [H=1, W=0]
+                                                 10,
+                                                 11,
+                                                 12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::u8,
+                              std::vector<uint8_t>{1,
+                                                   4,
+                                                   7,
+                                                   10,  // R
+                                                   2,
+                                                   5,
+                                                   8,
+                                                   11,  // G
+                                                   3,
+                                                   6,
+                                                   9,
+                                                   12});  // B
     return res;
 }
 
@@ -461,13 +497,34 @@ static RefPreprocessParams convert_layout_hwc_to_nchw() {
         p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{2, 2, 3}, element::u8, std::vector<uint8_t>{1,  2,  3,       // [H=0, W=0, RGB]
-                                                                              4,  5,  6,       // [H=0, W=1]
-                                                                              7,  8,  9,       // [H=1, W=0]
-                                                                              10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{1, 4, 7, 10,    // R
-                                                                                  2, 5, 8, 11,    // G
-                                                                                  3, 6, 9, 12});  // B
+    res.inputs.emplace_back(Shape{2, 2, 3},
+                            element::u8,
+                            std::vector<uint8_t>{1,
+                                                 2,
+                                                 3,  // [H=0, W=0, RGB]
+                                                 4,
+                                                 5,
+                                                 6,  // [H=0, W=1]
+                                                 7,
+                                                 8,
+                                                 9,  // [H=1, W=0]
+                                                 10,
+                                                 11,
+                                                 12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::f32,
+                              std::vector<float>{1,
+                                                 4,
+                                                 7,
+                                                 10,  // R
+                                                 2,
+                                                 5,
+                                                 8,
+                                                 11,  // G
+                                                 3,
+                                                 6,
+                                                 9,
+                                                 12});  // B
     return res;
 }
 
@@ -481,13 +538,34 @@ static RefPreprocessParams convert_layout_hwc_to_nchw_fully_dynamic() {
         p.build();
         return f;
     };
-    res.inputs.emplace_back(element::u8, Shape{2, 2, 3}, std::vector<uint8_t>{1,  2,  3,       // [H=0, W=0, RGB]
-                                                                              4,  5,  6,       // [H=0, W=1]
-                                                                              7,  8,  9,       // [H=1, W=0]
-                                                                              10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{1, 4, 7, 10,    // R
-                                                                                  2, 5, 8, 11,    // G
-                                                                                  3, 6, 9, 12});  // B
+    res.inputs.emplace_back(element::u8,
+                            Shape{2, 2, 3},
+                            std::vector<uint8_t>{1,
+                                                 2,
+                                                 3,  // [H=0, W=0, RGB]
+                                                 4,
+                                                 5,
+                                                 6,  // [H=0, W=1]
+                                                 7,
+                                                 8,
+                                                 9,  // [H=1, W=0]
+                                                 10,
+                                                 11,
+                                                 12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::f32,
+                              std::vector<float>{1,
+                                                 4,
+                                                 7,
+                                                 10,  // R
+                                                 2,
+                                                 5,
+                                                 8,
+                                                 11,  // G
+                                                 3,
+                                                 6,
+                                                 9,
+                                                 12});  // B
     return res;
 }
 
@@ -502,13 +580,34 @@ static RefPreprocessParams convert_layout_nhwc_to_net_no_tensor_shape() {
         p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{1, 2, 2, 3}, element::u8, std::vector<uint8_t>{1,  2,  3,       // [H=0, W=0, RGB]
-                                                                                 4,  5,  6,       // [H=0, W=1]
-                                                                                 7,  8,  9,       // [H=1, W=0]
-                                                                                 10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::u8, std::vector<uint8_t>{1, 4, 7, 10,    // R
-                                                                                   2, 5, 8, 11,    // G
-                                                                                   3, 6, 9, 12});  // B
+    res.inputs.emplace_back(Shape{1, 2, 2, 3},
+                            element::u8,
+                            std::vector<uint8_t>{1,
+                                                 2,
+                                                 3,  // [H=0, W=0, RGB]
+                                                 4,
+                                                 5,
+                                                 6,  // [H=0, W=1]
+                                                 7,
+                                                 8,
+                                                 9,  // [H=1, W=0]
+                                                 10,
+                                                 11,
+                                                 12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::u8,
+                              std::vector<uint8_t>{1,
+                                                   4,
+                                                   7,
+                                                   10,  // R
+                                                   2,
+                                                   5,
+                                                   8,
+                                                   11,  // G
+                                                   3,
+                                                   6,
+                                                   9,
+                                                   12});  // B
     return res;
 }
 
@@ -521,13 +620,34 @@ static RefPreprocessParams convert_layout_by_dims() {
         p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{1, 2, 2, 3}, element::u8, std::vector<uint8_t>{1,  2,  3,       // [H=0, W=0, RGB]
-                                                                                 4,  5,  6,       // [H=0, W=1]
-                                                                                 7,  8,  9,       // [H=1, W=0]
-                                                                                 10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::u8, std::vector<uint8_t>{1, 4, 7, 10,    // R
-                                                                                   2, 5, 8, 11,    // G
-                                                                                   3, 6, 9, 12});  // B
+    res.inputs.emplace_back(Shape{1, 2, 2, 3},
+                            element::u8,
+                            std::vector<uint8_t>{1,
+                                                 2,
+                                                 3,  // [H=0, W=0, RGB]
+                                                 4,
+                                                 5,
+                                                 6,  // [H=0, W=1]
+                                                 7,
+                                                 8,
+                                                 9,  // [H=1, W=0]
+                                                 10,
+                                                 11,
+                                                 12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::u8,
+                              std::vector<uint8_t>{1,
+                                                   4,
+                                                   7,
+                                                   10,  // R
+                                                   2,
+                                                   5,
+                                                   8,
+                                                   11,  // G
+                                                   3,
+                                                   6,
+                                                   9,
+                                                   12});  // B
     return res;
 }
 
@@ -536,18 +656,41 @@ static RefPreprocessParams convert_layout_by_dims_multi() {
     res.function = []() {
         auto f = create_simple_function(element::f32, {1, 3, 2, 2});
         auto p = PrePostProcessor(f);
-        p.input().preprocess().convert_layout({0, 1, 3, 2}) // NHWC->NHCW
-                .convert_layout({0, 2, 1, 3});                      // NHCW->NCHW
+        p.input()
+            .preprocess()
+            .convert_layout({0, 1, 3, 2})   // NHWC->NHCW
+            .convert_layout({0, 2, 1, 3});  // NHCW->NCHW
         p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{1, 2, 2, 3}, element::f32, std::vector<float>{1,  2,  3,       // [H=0, W=0]
-                                                                                4,  5,  6,       // [H=0, W=1]
-                                                                                7,  8,  9,       // [H=1, W=0]
-                                                                                10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{1, 4, 7, 10,    // R
-                                                                                  2, 5, 8, 11,    // G
-                                                                                  3, 6, 9, 12});  // B
+    res.inputs.emplace_back(Shape{1, 2, 2, 3},
+                            element::f32,
+                            std::vector<float>{1,
+                                               2,
+                                               3,  // [H=0, W=0]
+                                               4,
+                                               5,
+                                               6,  // [H=0, W=1]
+                                               7,
+                                               8,
+                                               9,  // [H=1, W=0]
+                                               10,
+                                               11,
+                                               12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::f32,
+                              std::vector<float>{1,
+                                                 4,
+                                                 7,
+                                                 10,  // R
+                                                 2,
+                                                 5,
+                                                 8,
+                                                 11,  // G
+                                                 3,
+                                                 6,
+                                                 9,
+                                                 12});  // B
     return res;
 }
 
@@ -557,19 +700,42 @@ static RefPreprocessParams convert_layout_by_dims_multi_layout() {
         auto f = create_simple_function(element::f32, {1, 3, 2, 2});
         auto p = PrePostProcessor(f);
         p.input().tensor().set_layout("N??C");
-        p.input().preprocess().convert_layout({0, 1, 3, 2}) // NHWC->NHCW
-                .mean({1, 2, 2})              // Apply means to 'C' channel
-                .convert_layout({0, 2, 1, 3}); // NHCW->NCHW
+        p.input()
+            .preprocess()
+            .convert_layout({0, 1, 3, 2})   // NHWC->NHCW
+            .mean({1, 2, 2})                // Apply means to 'C' channel
+            .convert_layout({0, 2, 1, 3});  // NHCW->NCHW
         p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{1, 2, 2, 3}, element::f32, std::vector<float>{1,  2,  3,       // [H=0, W=0, RGB]
-                                                                                4,  5,  6,       // [H=0, W=1]
-                                                                                7,  8,  9,       // [H=1, W=0]
-                                                                                10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{1-1, 4-1, 7-1, 10-1,     // R
-                                                                                  2-2, 5-2, 8-2, 11-2,    // G
-                                                                                  3-2, 6-2, 9-2, 12-2});  // B
+    res.inputs.emplace_back(Shape{1, 2, 2, 3},
+                            element::f32,
+                            std::vector<float>{1,
+                                               2,
+                                               3,  // [H=0, W=0, RGB]
+                                               4,
+                                               5,
+                                               6,  // [H=0, W=1]
+                                               7,
+                                               8,
+                                               9,  // [H=1, W=0]
+                                               10,
+                                               11,
+                                               12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::f32,
+                              std::vector<float>{1 - 1,
+                                                 4 - 1,
+                                                 7 - 1,
+                                                 10 - 1,  // R
+                                                 2 - 2,
+                                                 5 - 2,
+                                                 8 - 2,
+                                                 11 - 2,  // G
+                                                 3 - 2,
+                                                 6 - 2,
+                                                 9 - 2,
+                                                 12 - 2});  // B
     return res;
 }
 
@@ -578,13 +744,8 @@ static RefPreprocessParams resize_and_convert_layout() {
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 2, 2, 2});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor()
-                .set_layout("NCHW")
-                .set_spatial_dynamic_shape();
-        p.input().preprocess()
-                .resize(ResizeAlgorithm::RESIZE_LINEAR)
-                .convert_layout();
+        p.input().tensor().set_layout("NCHW").set_spatial_dynamic_shape();
+        p.input().preprocess().resize(ResizeAlgorithm::RESIZE_LINEAR).convert_layout();
         p.input().model().set_layout("NHWC");
         p.build();
         return f;
@@ -611,16 +772,13 @@ static RefPreprocessParams resize_and_convert_layout() {
 
 static RefPreprocessParams convert_color_nv12_to_bgr_two_planes() {
     RefPreprocessParams res("convert_color_nv12_to_bgr_two_planes");
-    res.abs_threshold = 1.f; // Allow small color conversion deviations
-    res.rel_threshold = 1.f; // Ignore relative pixel values comparison (100%)
+    res.abs_threshold = 1.f;  // Allow small color conversion deviations
+    res.rel_threshold = 1.f;  // Ignore relative pixel values comparison (100%)
     res.function = []() {
         auto f = create_simple_function(element::u8, PartialShape{1, 4, 4, 3});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor()
-                .set_color_format(ColorFormat::NV12_TWO_PLANES);
-        p.input().preprocess()
-                .convert_color(ColorFormat::BGR);
+        p.input().tensor().set_color_format(ColorFormat::NV12_TWO_PLANES);
+        p.input().preprocess().convert_color(ColorFormat::BGR);
         p.build();
         return f;
     };
@@ -650,16 +808,13 @@ static RefPreprocessParams convert_color_nv12_to_bgr_two_planes() {
 
 static RefPreprocessParams convert_color_nv12_single_plane() {
     RefPreprocessParams res("convert_color_nv12_single_plane");
-    res.abs_threshold = 1.f; // Allow small color conversion deviations
-    res.rel_threshold = 1.f; // Ignore relative pixel values comparison (100%)
+    res.abs_threshold = 1.f;  // Allow small color conversion deviations
+    res.rel_threshold = 1.f;  // Ignore relative pixel values comparison (100%)
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 4, 4, 3});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor()
-                .set_color_format(ColorFormat::NV12_SINGLE_PLANE);
-        p.input().preprocess()
-                .convert_color(ColorFormat::RGB);
+        p.input().tensor().set_color_format(ColorFormat::NV12_SINGLE_PLANE);
+        p.input().preprocess().convert_color(ColorFormat::RGB);
         p.build();
         return f;
     };
@@ -685,21 +840,22 @@ static RefPreprocessParams convert_color_nv12_single_plane() {
 
 static RefPreprocessParams convert_color_nv12_layout_resize() {
     RefPreprocessParams res("convert_color_nv12_layout_resize");
-    res.abs_threshold = 1.f; // Allow small color conversion deviations
-    res.rel_threshold = 1.f; // Ignore relative pixel values comparison (100%)
+    res.abs_threshold = 1.f;  // Allow small color conversion deviations
+    res.rel_threshold = 1.f;  // Ignore relative pixel values comparison (100%)
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 3, 2, 2});
         auto p = PrePostProcessor(f);
         p.input()
-                .tensor()
-                .set_color_format(ColorFormat::NV12_SINGLE_PLANE)
-                .set_element_type(element::u8)
-                .set_spatial_dynamic_shape();
-        p.input().preprocess()
-                .convert_color(ColorFormat::RGB)
-                .convert_layout()
-                .convert_element_type(element::f32)
-                .resize(ResizeAlgorithm::RESIZE_NEAREST);
+            .tensor()
+            .set_color_format(ColorFormat::NV12_SINGLE_PLANE)
+            .set_element_type(element::u8)
+            .set_spatial_dynamic_shape();
+        p.input()
+            .preprocess()
+            .convert_color(ColorFormat::RGB)
+            .convert_layout()
+            .convert_element_type(element::f32)
+            .resize(ResizeAlgorithm::RESIZE_NEAREST);
         p.input().model().set_layout("NCHW");
         p.build();
         return f;
@@ -725,18 +881,13 @@ static RefPreprocessParams convert_color_nv12_layout_resize() {
 
 static RefPreprocessParams element_type_before_convert_color_nv12() {
     RefPreprocessParams res("element_type_before_convert_color_nv12");
-    res.abs_threshold = 1.f; // Allow small color conversion deviations
-    res.rel_threshold = 1.f; // Ignore relative pixel values comparison (100%)
+    res.abs_threshold = 1.f;  // Allow small color conversion deviations
+    res.rel_threshold = 1.f;  // Ignore relative pixel values comparison (100%)
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 2, 2, 3});
         auto p = PrePostProcessor(f);
-        p.input()
-                .tensor()
-                .set_element_type(element::u8)
-                .set_color_format(ColorFormat::NV12_TWO_PLANES);
-        p.input().preprocess()
-                .convert_element_type(element::f32)
-                .convert_color(ColorFormat::RGB);
+        p.input().tensor().set_element_type(element::u8).set_color_format(ColorFormat::NV12_TWO_PLANES);
+        p.input().preprocess().convert_element_type(element::f32).convert_color(ColorFormat::RGB);
         p.input().model().set_layout("NHWC");
         p.build();
         return f;
@@ -758,8 +909,8 @@ static RefPreprocessParams element_type_before_convert_color_nv12() {
 
 static RefPreprocessParams convert_color_i420_to_bgr_three_planes() {
     RefPreprocessParams res("convert_color_i420_to_bgr_three_planes");
-    res.abs_threshold = 1.f; // Allow small color conversion deviations
-    res.rel_threshold = 1.f; // Ignore relative pixel values comparison (100%)
+    res.abs_threshold = 1.f;  // Allow small color conversion deviations
+    res.rel_threshold = 1.f;  // Ignore relative pixel values comparison (100%)
     res.function = []() {
         auto f = create_simple_function(element::u8, PartialShape{1, 4, 4, 3});
         auto p = PrePostProcessor(f);
@@ -798,8 +949,8 @@ static RefPreprocessParams convert_color_i420_to_bgr_three_planes() {
 
 static RefPreprocessParams convert_color_i420_single_plane() {
     RefPreprocessParams res("convert_color_i420_single_plane");
-    res.abs_threshold = 1.f; // Allow small color conversion deviations
-    res.rel_threshold = 1.f; // Ignore relative pixel values comparison (100%)
+    res.abs_threshold = 1.f;  // Allow small color conversion deviations
+    res.rel_threshold = 1.f;  // Ignore relative pixel values comparison (100%)
     res.function = []() {
         auto f = create_simple_function(element::f32, PartialShape{1, 4, 4, 3});
         auto p = PrePostProcessor(f);
@@ -850,10 +1001,10 @@ static RefPreprocessParams set_shape_custom_crop() {
     std::vector<float> input_values(shape_size(input_shape));
     std::iota(input_values.begin(), input_values.end(), 0.f);
     res.inputs.emplace_back(element::f32, input_shape, input_values);
-    res.expected.emplace_back(Shape{2, 2, 2, 2}, element::f32, std::vector<float>{ 85,  86,  89,  90,
-                                                                                  101, 102, 105, 106,
-                                                                                  149, 150, 153, 154,
-                                                                                  165, 166, 169, 170});
+    res.expected.emplace_back(
+        Shape{2, 2, 2, 2},
+        element::f32,
+        std::vector<float>{85, 86, 89, 90, 101, 102, 105, 106, 149, 150, 153, 154, 165, 166, 169, 170});
     return res;
 }
 
@@ -871,11 +1022,8 @@ static RefPreprocessParams set_shape_with_resize() {
     auto input_size = 1 * 2 * 2 * 3;
     std::vector<float> input_values(input_size);
     std::iota(input_values.begin(), input_values.end(), 0.f);
-    res.inputs.emplace_back(element::f32, Shape{1, 2, 2, 3}, std::vector<float> {1, 2, 3,
-                                                                                 1, 2, 3,
-                                                                                 1, 2, 3,
-                                                                                 1, 2, 3});
-    res.expected.emplace_back(Shape{1, 3, 1, 1}, element::f32, std::vector<float>{ 1,  2,  3});
+    res.inputs.emplace_back(element::f32, Shape{1, 2, 2, 3}, std::vector<float>{1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3});
+    res.expected.emplace_back(Shape{1, 3, 1, 1}, element::f32, std::vector<float>{1, 2, 3});
     return res;
 }
 
@@ -893,10 +1041,10 @@ static RefPreprocessParams preprocess_crop_basic() {
     std::vector<float> input_values(shape_size(input_shape));
     std::iota(input_values.begin(), input_values.end(), 0.f);
     res.inputs.emplace_back(element::f32, input_shape, input_values);
-    res.expected.emplace_back(Shape{2, 2, 2, 2}, element::f32, std::vector<float>{ 85,  86,  89,  90,
-                                                                                   101, 102, 105, 106,
-                                                                                   149, 150, 153, 154,
-                                                                                   165, 166, 169, 170});
+    res.expected.emplace_back(
+        Shape{2, 2, 2, 2},
+        element::f32,
+        std::vector<float>{85, 86, 89, 90, 101, 102, 105, 106, 149, 150, 153, 154, 165, 166, 169, 170});
     return res;
 }
 
@@ -923,12 +1071,10 @@ static RefPreprocessParams postprocess_2_inputs_basic() {
     res.function = []() {
         auto f = create_n_inputs(2, element::f32, Shape{1, 3, 1, 2});
         auto p = PrePostProcessor(f);
-        p.output("tensor_output1")
-                .model().set_layout("NCHW");
+        p.output("tensor_output1").model().set_layout("NCHW");
         p.output("tensor_output1").postprocess().convert_layout();
         p.output("tensor_output1").tensor().set_layout("NHWC");
-        p.output("tensor_output2")
-                .postprocess().convert_element_type();
+        p.output("tensor_output2").postprocess().convert_element_type();
         p.output("tensor_output2").tensor().set_element_type(element::u8);
         p.build();
         return f;
@@ -945,18 +1091,38 @@ static RefPreprocessParams post_convert_layout_by_dims() {
     res.function = []() {
         auto f = create_simple_function(element::u8, {1, 2, 2, 3});
         auto p = PrePostProcessor(f);
-        p.output()
-                .postprocess().convert_layout({0, 3, 1, 2});
+        p.output().postprocess().convert_layout({0, 3, 1, 2});
         p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{1, 2, 2, 3}, element::u8, std::vector<uint8_t>{1,  2,  3,       // [H=0, W=0, RGB]
-                                                                                 4,  5,  6,       // [H=0, W=1]
-                                                                                 7,  8,  9,       // [H=1, W=0]
-                                                                                 10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::u8, std::vector<uint8_t>{1, 4, 7, 10,    // R
-                                                                                   2, 5, 8, 11,    // G
-                                                                                   3, 6, 9, 12});  // B
+    res.inputs.emplace_back(Shape{1, 2, 2, 3},
+                            element::u8,
+                            std::vector<uint8_t>{1,
+                                                 2,
+                                                 3,  // [H=0, W=0, RGB]
+                                                 4,
+                                                 5,
+                                                 6,  // [H=0, W=1]
+                                                 7,
+                                                 8,
+                                                 9,  // [H=1, W=0]
+                                                 10,
+                                                 11,
+                                                 12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::u8,
+                              std::vector<uint8_t>{1,
+                                                   4,
+                                                   7,
+                                                   10,  // R
+                                                   2,
+                                                   5,
+                                                   8,
+                                                   11,  // G
+                                                   3,
+                                                   6,
+                                                   9,
+                                                   12});  // B
     return res;
 }
 
@@ -965,18 +1131,39 @@ static RefPreprocessParams post_convert_layout_by_dims_multi() {
     res.function = []() {
         auto f = create_simple_function(element::f32, {1, 2, 2, 3});
         auto p = PrePostProcessor(f);
-        p.output().postprocess().convert_layout({0, 1, 3, 2}); // NHWC->NHCW;
-        p.output().postprocess().convert_layout({0, 2, 1, 3}); // NHCW->NCHW;
+        p.output().postprocess().convert_layout({0, 1, 3, 2});  // NHWC->NHCW;
+        p.output().postprocess().convert_layout({0, 2, 1, 3});  // NHCW->NCHW;
         p.build();
         return f;
     };
-    res.inputs.emplace_back(Shape{1, 2, 2, 3}, element::f32, std::vector<float>{1,  2,  3,       // [H=0, W=0]
-                                                                                4,  5,  6,       // [H=0, W=1]
-                                                                                7,  8,  9,       // [H=1, W=0]
-                                                                                10, 11, 12});    // [H=1, W=1]
-    res.expected.emplace_back(Shape{1, 3, 2, 2}, element::f32, std::vector<float>{1, 4, 7, 10,    // R
-                                                                                  2, 5, 8, 11,    // G
-                                                                                  3, 6, 9, 12});  // B
+    res.inputs.emplace_back(Shape{1, 2, 2, 3},
+                            element::f32,
+                            std::vector<float>{1,
+                                               2,
+                                               3,  // [H=0, W=0]
+                                               4,
+                                               5,
+                                               6,  // [H=0, W=1]
+                                               7,
+                                               8,
+                                               9,  // [H=1, W=0]
+                                               10,
+                                               11,
+                                               12});  // [H=1, W=1]
+    res.expected.emplace_back(Shape{1, 3, 2, 2},
+                              element::f32,
+                              std::vector<float>{1,
+                                                 4,
+                                                 7,
+                                                 10,  // R
+                                                 2,
+                                                 5,
+                                                 8,
+                                                 11,  // G
+                                                 3,
+                                                 6,
+                                                 9,
+                                                 12});  // B
     return res;
 }
 
@@ -985,16 +1172,13 @@ static RefPreprocessParams pre_and_post_processing() {
     res.function = []() {
         auto f = create_n_inputs(2, element::f32, Shape{1, 3, 1, 2});
         auto p = PrePostProcessor(f);
-        p.input(0)
-                .tensor().set_element_type(element::u8);
+        p.input(0).tensor().set_element_type(element::u8);
         p.input(0).preprocess().convert_element_type(element::f32).mean(1.f);
         p.input(1).preprocess().scale(2.f);
-        p.output("tensor_output1")
-                .model().set_layout("NCHW");
+        p.output("tensor_output1").model().set_layout("NCHW");
         p.output("tensor_output1").postprocess().convert_layout();
         p.output("tensor_output1").tensor().set_layout("NHWC");
-        p.output("tensor_output2")
-                .postprocess().convert_element_type();
+        p.output("tensor_output2").postprocess().convert_element_type();
         p.output("tensor_output2").tensor().set_element_type(element::u8);
         p.build();
         return f;
@@ -1056,18 +1240,15 @@ static RefPreprocessParams reverse_channels_nchw() {
 
 static RefPreprocessParams color_cut_last_channel() {
     RefPreprocessParams res("color_cut_last_channel");
-    auto input_tensor = reference_tests::Tensor(Shape{1, 2, 2, 4}, element::f32, std::vector<float>{1, 2, 3, 4,
-                                                                                   5, 6, 7, 8,
-                                                                                   3, 4, 5, 6,
-                                                                                   6, 7, 8, 9});
-    auto exp_3_channels = reference_tests::Tensor(Shape{1, 2, 2, 3}, element::f32, std::vector<float>{1, 2, 3,
-                                                                                     5, 6, 7,
-                                                                                     3, 4, 5,
-                                                                                     6, 7, 8});
-    auto inv_3_channels = reference_tests::Tensor(Shape{1, 2, 2, 3}, element::f32, std::vector<float>{3, 2, 1,
-                                                                                     7, 6, 5,
-                                                                                     5, 4, 3,
-                                                                                     8, 7, 6});
+    auto input_tensor = reference_tests::Tensor(Shape{1, 2, 2, 4},
+                                                element::f32,
+                                                std::vector<float>{1, 2, 3, 4, 5, 6, 7, 8, 3, 4, 5, 6, 6, 7, 8, 9});
+    auto exp_3_channels = reference_tests::Tensor(Shape{1, 2, 2, 3},
+                                                  element::f32,
+                                                  std::vector<float>{1, 2, 3, 5, 6, 7, 3, 4, 5, 6, 7, 8});
+    auto inv_3_channels = reference_tests::Tensor(Shape{1, 2, 2, 3},
+                                                  element::f32,
+                                                  std::vector<float>{3, 2, 1, 7, 6, 5, 5, 4, 3, 8, 7, 6});
     res.function = []() {
         auto f = create_n_inputs(4, element::f32, Shape{1, 2, 2, 3});
         auto prep = PrePostProcessor(f);
@@ -1096,7 +1277,8 @@ static RefPreprocessParams reverse_channels_dyn_layout() {
         auto f = create_simple_function(element::f32, PartialShape{1, 1, 3, 2});
         auto p = PrePostProcessor(f);
         p.input().tensor().set_color_format(ColorFormat::BGR).set_layout("...CN");
-        p.input().preprocess().convert_color(ColorFormat::RGB); p.build();
+        p.input().preprocess().convert_color(ColorFormat::RGB);
+        p.build();
         return f;
     };
 
@@ -1108,10 +1290,9 @@ static RefPreprocessParams reverse_channels_dyn_layout() {
 static RefPreprocessParams reverse_dyn_shape() {
     RefPreprocessParams res("reverse_dyn_shape");
     res.function = []() {
-        auto f = create_simple_function(element::u8, PartialShape{Dimension::dynamic(),
-                                                                  Dimension::dynamic(),
-                                                                  Dimension::dynamic(),
-                                                                  Dimension::dynamic()});
+        auto f = create_simple_function(
+            element::u8,
+            PartialShape{Dimension::dynamic(), Dimension::dynamic(), Dimension::dynamic(), Dimension::dynamic()});
         auto p = PrePostProcessor(f);
         p.input().tensor().set_layout("NCHW");
         p.input().preprocess().reverse_channels();
@@ -1119,18 +1300,21 @@ static RefPreprocessParams reverse_dyn_shape() {
         return f;
     };
 
-    res.inputs.emplace_back(element::u8, Shape{2, 2, 1, 3}, std::vector<uint8_t>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
-    res.expected.emplace_back(Shape{2, 2, 1, 3}, element::u8, std::vector<uint8_t>{4, 5, 6, 1, 2, 3, 10, 11, 12, 7, 8, 9});
+    res.inputs.emplace_back(element::u8,
+                            Shape{2, 2, 1, 3},
+                            std::vector<uint8_t>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
+    res.expected.emplace_back(Shape{2, 2, 1, 3},
+                              element::u8,
+                              std::vector<uint8_t>{4, 5, 6, 1, 2, 3, 10, 11, 12, 7, 8, 9});
     return res;
 }
 
 static RefPreprocessParams reverse_dyn_channels() {
     RefPreprocessParams res("reverse_dyn_channels");
     res.function = []() {
-        auto f = create_simple_function(element::u8, PartialShape{Dimension::dynamic(),
-                                                                  2,
-                                                                  Dimension::dynamic(),
-                                                                  Dimension::dynamic()});
+        auto f =
+            create_simple_function(element::u8,
+                                   PartialShape{Dimension::dynamic(), 2, Dimension::dynamic(), Dimension::dynamic()});
         auto p = PrePostProcessor(f);
         p.input().tensor().set_layout("NCHW");
         p.input().preprocess().reverse_channels();
@@ -1138,8 +1322,12 @@ static RefPreprocessParams reverse_dyn_channels() {
         return f;
     };
 
-    res.inputs.emplace_back(element::u8, Shape{2, 2, 1, 3}, std::vector<uint8_t>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
-    res.expected.emplace_back(Shape{2, 2, 1, 3}, element::u8, std::vector<uint8_t>{4, 5, 6, 1, 2, 3, 10, 11, 12, 7, 8, 9});
+    res.inputs.emplace_back(element::u8,
+                            Shape{2, 2, 1, 3},
+                            std::vector<uint8_t>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
+    res.expected.emplace_back(Shape{2, 2, 1, 3},
+                              element::u8,
+                              std::vector<uint8_t>{4, 5, 6, 1, 2, 3, 10, 11, 12, 7, 8, 9});
     return res;
 }
 
@@ -1154,63 +1342,66 @@ static RefPreprocessParams reverse_fully_dyn_shape() {
         return f;
     };
 
-    res.inputs.emplace_back(element::u8, Shape{2, 2, 1, 3}, std::vector<uint8_t>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
-    res.expected.emplace_back(Shape{2, 2, 1, 3}, element::u8, std::vector<uint8_t>{4, 5, 6, 1, 2, 3, 10, 11, 12, 7, 8, 9});
+    res.inputs.emplace_back(element::u8,
+                            Shape{2, 2, 1, 3},
+                            std::vector<uint8_t>{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
+    res.expected.emplace_back(Shape{2, 2, 1, 3},
+                              element::u8,
+                              std::vector<uint8_t>{4, 5, 6, 1, 2, 3, 10, 11, 12, 7, 8, 9});
     return res;
 }
 
 std::vector<RefPreprocessParams> allPreprocessTests() {
-    return std::vector<RefPreprocessParams> {
-            simple_mean_scale(),
-            scale_then_mean(),
-            convert_only(),
-            convert_element_type_and_scale(),
-            tensor_element_type_and_scale(),
-            custom_preprocessing(),
-            test_multiple(),
-            test_2_inputs_basic(),
-            mean_scale_vector_tensor_layout(),
-            mean_scale_dynamic_layout(),
-            resize_to_network_height(),
-            resize_to_network_width(),
-            resize_from_spatial_dims(),
-            resize_i8(),
-            resize_to_network_width_height(),
-            resize_to_specified_width_height(),
-            convert_layout_nhwc_to_nchw(),
-            convert_layout_nhwc_to_nchw_fully_dynamic(),
-            convert_layout_nhwc_to_net_no_tensor_shape(),
-            convert_layout_by_dims(),
-            convert_layout_by_dims_multi(),
-            convert_layout_by_dims_multi_layout(),
-            convert_layout_hwc_to_nchw(),
-            convert_layout_hwc_to_nchw_fully_dynamic(),
-            resize_and_convert_layout(),
-            convert_color_nv12_to_bgr_two_planes(),
-            convert_color_nv12_single_plane(),
-            convert_color_nv12_layout_resize(),
-            element_type_before_convert_color_nv12(),
-            convert_color_i420_to_bgr_three_planes(),
-            convert_color_i420_single_plane(),
-            preprocess_crop_basic(),
-            preprocess_crop_2axis_dynamic(),
-            set_shape_custom_crop(),
-            set_shape_with_resize(),
-            postprocess_2_inputs_basic(),
-            post_convert_layout_by_dims(),
-            post_convert_layout_by_dims_multi(),
-            pre_and_post_processing(),
-            rgb_to_bgr(),
-            bgr_to_rgb(),
-            color_cut_last_channel(),
-            reverse_channels_nchw(),
-            reverse_channels_dyn_layout(),
-            reverse_dyn_shape(),
-            reverse_dyn_channels(),
-            reverse_fully_dyn_shape()
-    };
+    return std::vector<RefPreprocessParams>{simple_mean_scale(),
+                                            scale_then_mean(),
+                                            convert_only(),
+                                            convert_element_type_and_scale(),
+                                            tensor_element_type_and_scale(),
+                                            custom_preprocessing(),
+                                            test_multiple(),
+                                            test_2_inputs_basic(),
+                                            mean_scale_vector_tensor_layout(),
+                                            mean_scale_dynamic_layout(),
+                                            resize_to_network_height(),
+                                            resize_to_network_width(),
+                                            resize_from_spatial_dims(),
+                                            resize_i8(),
+                                            resize_to_network_width_height(),
+                                            resize_to_specified_width_height(),
+                                            convert_layout_nhwc_to_nchw(),
+                                            convert_layout_nhwc_to_nchw_fully_dynamic(),
+                                            convert_layout_nhwc_to_net_no_tensor_shape(),
+                                            convert_layout_by_dims(),
+                                            convert_layout_by_dims_multi(),
+                                            convert_layout_by_dims_multi_layout(),
+                                            convert_layout_hwc_to_nchw(),
+                                            convert_layout_hwc_to_nchw_fully_dynamic(),
+                                            resize_and_convert_layout(),
+                                            convert_color_nv12_to_bgr_two_planes(),
+                                            convert_color_nv12_single_plane(),
+                                            convert_color_nv12_layout_resize(),
+                                            element_type_before_convert_color_nv12(),
+                                            convert_color_i420_to_bgr_three_planes(),
+                                            convert_color_i420_single_plane(),
+                                            preprocess_crop_basic(),
+                                            preprocess_crop_2axis_dynamic(),
+                                            set_shape_custom_crop(),
+                                            set_shape_with_resize(),
+                                            postprocess_2_inputs_basic(),
+                                            post_convert_layout_by_dims(),
+                                            post_convert_layout_by_dims_multi(),
+                                            pre_and_post_processing(),
+                                            rgb_to_bgr(),
+                                            bgr_to_rgb(),
+                                            color_cut_last_channel(),
+                                            reverse_channels_nchw(),
+                                            reverse_channels_dyn_layout(),
+                                            reverse_dyn_shape(),
+                                            reverse_dyn_channels(),
+                                            reverse_fully_dyn_shape()};
 }
 
-INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs, ReferencePreprocessTest,
+INSTANTIATE_TEST_SUITE_P(smoke_Comparison_With_Hardcoded_Refs,
+                         ReferencePreprocessTest,
                          ::testing::ValuesIn(allPreprocessTests()),
                          ReferencePreprocessTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp b/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
index 574b8f618be473..a8ba3ea35534ea 100644
--- a/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
+++ b/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
@@ -26,7 +26,7 @@ class ReferencePreprocessLegacyTest : public testing::Test, public ReferenceCNNT
     }
 };
 
-} // namespace
+}  // namespace
 
 static std::shared_ptr<Model> create_simple_function(element::Type type, const PartialShape& shape) {
     auto data1 = std::make_shared<op::v0::Parameter>(type, shape);
@@ -49,7 +49,7 @@ TEST_F(ReferencePreprocessLegacyTest, mean) {
 
     auto f2 = create_simple_function(element::f32, Shape{1, 3, 2, 2});
     legacy_network = InferenceEngine::CNNNetwork(f2);
-    auto &preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
+    auto& preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
     preProcess.init(3);
     preProcess[0]->meanValue = 1;
     preProcess[1]->meanValue = 1;
@@ -69,7 +69,7 @@ TEST_F(ReferencePreprocessLegacyTest, mean_scale) {
 
     auto f2 = create_simple_function(element::f32, Shape{1, 3, 20, 20});
     legacy_network = InferenceEngine::CNNNetwork(f2);
-    auto &preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
+    auto& preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
     preProcess.init(3);
     preProcess[0]->meanValue = 0;
     preProcess[1]->meanValue = 0;
@@ -92,7 +92,7 @@ TEST_F(ReferencePreprocessLegacyTest, resize) {
     p.input().model().set_layout("NCHW");
     p.build();
 
-    auto &preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
+    auto& preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
     preProcess.setResizeAlgorithm(InferenceEngine::ResizeAlgorithm::RESIZE_BILINEAR);
     Exec();
 }
@@ -120,7 +120,7 @@ TEST_F(ReferencePreprocessLegacyTest, bgrx_to_bgr) {
                                                 {1, 4, h, w},
                                                 InferenceEngine::Layout::NHWC);
     legacy_network.getInputsInfo().begin()->second->setLayout(InferenceEngine::NHWC);
-    auto &preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
+    auto& preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
     preProcess.setColorFormat(InferenceEngine::ColorFormat::BGRX);
     legacy_input_blobs["input1"] = InferenceEngine::make_shared_blob<uint8_t>(rgbx_plane_desc, rgbx_input.data());
 
@@ -150,7 +150,7 @@ TEST_F(ReferencePreprocessLegacyTest, rgbx_to_bgr) {
                                                 {1, 4, h, w},
                                                 InferenceEngine::Layout::NHWC);
     legacy_network.getInputsInfo().begin()->second->setLayout(InferenceEngine::NHWC);
-    auto &preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
+    auto& preProcess = legacy_network.getInputsInfo().begin()->second->getPreProcess();
     preProcess.setColorFormat(InferenceEngine::ColorFormat::RGBX);
     legacy_input_blobs["input1"] = InferenceEngine::make_shared_blob<uint8_t>(rgbx_plane_desc, rgbx_input.data());
 
diff --git a/src/plugins/template/tests/functional/subgraph_reference/preprocess_opencv.cpp b/src/plugins/template/tests/functional/subgraph_reference/preprocess_opencv.cpp
index 4aea7d4173c9b4..099cea661b5f6c 100644
--- a/src/plugins/template/tests/functional/subgraph_reference/preprocess_opencv.cpp
+++ b/src/plugins/template/tests/functional/subgraph_reference/preprocess_opencv.cpp
@@ -4,18 +4,17 @@
 
 #ifdef OPENCV_TEMPLATE_TESTS
 
-#include <gtest/gtest.h>
+#    include <gtest/gtest.h>
+#    include <opencv2/imgproc/types_c.h>
 
-#include <opencv2/imgproc.hpp>
-#include <opencv2/imgproc/types_c.h>
+#    include <opencv2/imgproc.hpp>
+#    include <openvino/core/preprocess/pre_post_process.hpp>
+#    include <shared_test_classes/base/layer_test_utils.hpp>
+#    include <shared_test_classes/single_layer/convert_color_i420.hpp>
+#    include <shared_test_classes/single_layer/convert_color_nv12.hpp>
 
-#include <openvino/core/preprocess/pre_post_process.hpp>
-#include <shared_test_classes/base/layer_test_utils.hpp>
-#include <shared_test_classes/single_layer/convert_color_i420.hpp>
-#include <shared_test_classes/single_layer/convert_color_nv12.hpp>
-
-#include "base_reference_test.hpp"
-#include "ngraph_functions/builders.hpp"
+#    include "base_reference_test.hpp"
+#    include "ngraph_functions/builders.hpp"
 
 using namespace ov;
 using namespace ov::preprocess;
@@ -31,8 +30,8 @@ class PreprocessOpenCVReferenceTest : public testing::Test, public CommonReferen
 
 /// \brief Test class with counting deviated pixels
 ///
-/// OpenCV contains custom implementation for 8U and 16U (all calculations 
-/// are done in INTs instead of FLOATs), so deviation in 1 color step 
+/// OpenCV contains custom implementation for 8U and 16U (all calculations
+/// are done in INTs instead of FLOATs), so deviation in 1 color step
 /// between pixels is expected
 class PreprocessOpenCVReferenceTest_8U : public PreprocessOpenCVReferenceTest {
 public:
@@ -44,11 +43,13 @@ class PreprocessOpenCVReferenceTest_8U : public PreprocessOpenCVReferenceTest {
         // Less than 2% of deviations with 1 color step. 2% is experimental value
         // For very precise (acceptable) float calculations - 1.4% deviation with G-API/OpenCV is observed
         LayerTestsDefinitions::NV12TestUtils::ValidateColors(refOutData[0].data<uint8_t>(),
-                actualOutData[0].data<uint8_t>(), refOutData[0].get_size(), 0.02);
+                                                             actualOutData[0].data<uint8_t>(),
+                                                             refOutData[0].get_size(),
+                                                             0.02);
     }
 };
 
-} // namespace
+}  // namespace
 
 static std::shared_ptr<Model> create_simple_function(element::Type type, const PartialShape& shape) {
     auto data1 = std::make_shared<op::v0::Parameter>(type, shape);
@@ -69,12 +70,12 @@ TEST_F(PreprocessOpenCVReferenceTest, convert_rgb_gray_fp32) {
     auto input_shape = Shape{1, input_height, input_width, 3};
     auto model_shape = Shape{1, input_height, input_width, 1};
 
-    auto input_img = std::vector<float> (shape_size(input_shape));
-    std::default_random_engine random(0); // hard-coded seed to make test results predictable
+    auto input_img = std::vector<float>(shape_size(input_shape));
+    std::default_random_engine random(0);  // hard-coded seed to make test results predictable
     std::uniform_int_distribution<int> distrib(-5, 300);
     for (std::size_t i = 0; i < shape_size(input_shape); i++)
         input_img[i] = static_cast<float>(distrib(random));
-    
+
     function = create_simple_function(element::f32, model_shape);
 
     inputData.clear();
@@ -84,7 +85,7 @@ TEST_F(PreprocessOpenCVReferenceTest, convert_rgb_gray_fp32) {
     p.input().preprocess().convert_color(ColorFormat::GRAY);
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), input_img.data());
 
     // Calculate reference expected values from OpenCV
@@ -102,8 +103,8 @@ TEST_F(PreprocessOpenCVReferenceTest, convert_bgr_gray_fp32) {
     auto input_shape = Shape{1, input_height, input_width, 3};
     auto model_shape = Shape{1, input_height, input_width, 1};
 
-    auto input_img = std::vector<float> (shape_size(input_shape));
-    std::default_random_engine random(0); // hard-coded seed to make test results predictable
+    auto input_img = std::vector<float>(shape_size(input_shape));
+    std::default_random_engine random(0);  // hard-coded seed to make test results predictable
     std::uniform_int_distribution<int> distrib(-5, 300);
     for (std::size_t i = 0; i < shape_size(input_shape); i++)
         input_img[i] = static_cast<float>(distrib(random));
@@ -117,7 +118,7 @@ TEST_F(PreprocessOpenCVReferenceTest, convert_bgr_gray_fp32) {
     p.input().preprocess().convert_color(ColorFormat::GRAY);
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), input_img.data());
 
     // Calculate reference expected values from OpenCV
@@ -136,8 +137,8 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_rgb_gray_u8) {
     auto input_shape = Shape{1, input_height, input_width, 3};
     auto model_shape = Shape{1, input_height, input_width, 1};
 
-    auto input_img = std::vector<float> (shape_size(input_shape));
-    std::default_random_engine random(0); // hard-coded seed to make test results predictable
+    auto input_img = std::vector<float>(shape_size(input_shape));
+    std::default_random_engine random(0);  // hard-coded seed to make test results predictable
     std::uniform_int_distribution<int> distrib(0, 255);
     for (std::size_t i = 0; i < shape_size(input_shape); i++)
         input_img[i] = static_cast<uint8_t>(distrib(random));
@@ -151,7 +152,7 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_rgb_gray_u8) {
     p.input().preprocess().convert_color(ColorFormat::GRAY);
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), input_img.data());
 
     // Calculate reference expected values from OpenCV
@@ -169,10 +170,10 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_bgr_gray_u8) {
     auto input_shape = Shape{1, input_height, input_width, 3};
     auto model_shape = Shape{1, input_height, input_width, 1};
 
-    auto input_img = std::vector<uint8_t> (shape_size(input_shape));
-    std::default_random_engine random(0); // hard-coded seed to make test results predictable
+    auto input_img = std::vector<uint8_t>(shape_size(input_shape));
+    std::default_random_engine random(0);  // hard-coded seed to make test results predictable
     std::uniform_int_distribution<int> distrib(0, 255);
-    for (std::size_t i = 0; i < shape_size(input_shape); i++) 
+    for (std::size_t i = 0; i < shape_size(input_shape); i++)
         input_img[i] = static_cast<uint8_t>(distrib(random));
 
     function = create_simple_function(element::u8, model_shape);
@@ -184,7 +185,7 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_bgr_gray_u8) {
     p.input().preprocess().convert_color(ColorFormat::GRAY);
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), input_img.data());
 
     // Calculate reference expected values from OpenCV
@@ -198,8 +199,8 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_bgr_gray_u8) {
 }
 
 TEST_F(PreprocessOpenCVReferenceTest_8U, convert_i420_full_color_range) {
-    size_t height = 64; // 64/2 = 32 values for R
-    size_t width = 64;  // 64/2 = 32 values for G
+    size_t height = 64;  // 64/2 = 32 values for R
+    size_t width = 64;   // 64/2 = 32 values for G
     int b_step = 5;
     int b_dim = 255 / b_step + 1;
 
@@ -217,14 +218,12 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_i420_full_color_range) {
     p.input().preprocess().convert_color(ColorFormat::BGR);
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), ov20_input_yuv.data());
 
     // Calculate reference expected values from OpenCV
-    cv::Mat picYV12 = cv::Mat(static_cast<int>(full_height) * 3 / 2,
-                              static_cast<int>(width),
-                              CV_8UC1,
-                              ov20_input_yuv.data());
+    cv::Mat picYV12 =
+        cv::Mat(static_cast<int>(full_height) * 3 / 2, static_cast<int>(width), CV_8UC1, ov20_input_yuv.data());
     cv::Mat picBGR;
     cv::cvtColor(picYV12, picBGR, CV_YUV2BGR_I420);
     refOutData.emplace_back(param->get_element_type(), func_shape, picBGR.data);
@@ -234,8 +233,8 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_i420_full_color_range) {
 }
 
 TEST_F(PreprocessOpenCVReferenceTest_8U, convert_nv12_full_color_range) {
-    size_t height = 64; // 64/2 = 32 values for R
-    size_t width = 64;  // 64/2 = 32 values for G
+    size_t height = 64;  // 64/2 = 32 values for R
+    size_t width = 64;   // 64/2 = 32 values for G
     int b_step = 5;
     int b_dim = 255 / b_step + 1;
 
@@ -253,14 +252,12 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_nv12_full_color_range) {
     p.input().preprocess().convert_color(ColorFormat::BGR);
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), ov20_input_yuv.data());
 
     // Calculate reference expected values from OpenCV
-    cv::Mat picYV12 = cv::Mat(static_cast<int>(full_height) * 3 / 2,
-                              static_cast<int>(width),
-                              CV_8UC1,
-                              ov20_input_yuv.data());
+    cv::Mat picYV12 =
+        cv::Mat(static_cast<int>(full_height) * 3 / 2, static_cast<int>(width), CV_8UC1, ov20_input_yuv.data());
     cv::Mat picBGR;
     cv::cvtColor(picYV12, picBGR, CV_YUV2BGR_NV12);
     refOutData.emplace_back(param->get_element_type(), func_shape, picBGR.data);
@@ -270,7 +267,7 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_nv12_full_color_range) {
 }
 
 TEST_F(PreprocessOpenCVReferenceTest_8U, convert_nv12_colored) {
-    auto input_yuv = std::vector<uint8_t> {235, 81, 235, 81, 109, 184};
+    auto input_yuv = std::vector<uint8_t>{235, 81, 235, 81, 109, 184};
     auto func_shape = Shape{1, 2, 2, 3};
     function = create_simple_function(element::u8, func_shape);
 
@@ -281,7 +278,7 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_nv12_colored) {
     p.input().preprocess().convert_color(ColorFormat::BGR);
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), input_yuv.data());
 
     // Calculate reference expected values from OpenCV
@@ -296,7 +293,7 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, convert_nv12_colored) {
 TEST_F(PreprocessOpenCVReferenceTest, resize_u8_simple_linear) {
     auto input_shape = Shape{1, 1, 2, 2};
     auto func_shape = Shape{1, 1, 1, 1};
-    auto input_img = std::vector<uint8_t> {5, 5, 5, 4};
+    auto input_img = std::vector<uint8_t>{5, 5, 5, 4};
     function = create_simple_function(element::u8, func_shape);
 
     inputData.clear();
@@ -307,7 +304,7 @@ TEST_F(PreprocessOpenCVReferenceTest, resize_u8_simple_linear) {
     p.input().model().set_layout("NCHW");
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), input_img.data());
 
     // Calculate reference expected values from OpenCV
@@ -326,8 +323,8 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, resize_u8_large_picture_linear) {
     const size_t func_width = 31;
     auto input_shape = Shape{1, 1, input_height, input_width};
     auto func_shape = Shape{1, 1, func_height, func_width};
-    auto input_img = std::vector<uint8_t> (shape_size(input_shape));
-    std::default_random_engine random(0); // hard-coded seed to make test results predictable
+    auto input_img = std::vector<uint8_t>(shape_size(input_shape));
+    std::default_random_engine random(0);  // hard-coded seed to make test results predictable
     std::uniform_int_distribution<int> distrib(0, 255);
     for (std::size_t i = 0; i < shape_size(input_shape); i++) {
         auto v = distrib(random);
@@ -343,7 +340,7 @@ TEST_F(PreprocessOpenCVReferenceTest_8U, resize_u8_large_picture_linear) {
     p.input().model().set_layout("NCHW");
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), input_img.data());
 
     // Calculate reference expected values from OpenCV
@@ -364,8 +361,8 @@ TEST_F(PreprocessOpenCVReferenceTest, resize_f32_large_picture_linear) {
     const size_t func_width = 31;
     auto input_shape = Shape{1, 1, input_height, input_width};
     auto func_shape = Shape{1, 1, func_height, func_width};
-    auto input_img = std::vector<float> (shape_size(input_shape));
-    std::default_random_engine random(0); // hard-coded seed to make test results predictable
+    auto input_img = std::vector<float>(shape_size(input_shape));
+    std::default_random_engine random(0);  // hard-coded seed to make test results predictable
     std::uniform_int_distribution<int> distrib(0, 255);
     for (std::size_t i = 0; i < shape_size(input_shape); i++) {
         input_img[i] = static_cast<float>(distrib(random));
@@ -380,7 +377,7 @@ TEST_F(PreprocessOpenCVReferenceTest, resize_f32_large_picture_linear) {
     p.input().model().set_layout("NCHW");
     function = p.build();
 
-    const auto &param = function->get_parameters()[0];
+    const auto& param = function->get_parameters()[0];
     inputData.emplace_back(param->get_element_type(), param->get_shape(), input_img.data());
 
     // Calculate reference expected values from OpenCV
@@ -400,7 +397,7 @@ TEST_F(PreprocessOpenCVReferenceTest, DISABLED_resize_f32_large_picture_cubic_sm
     auto input_shape = Shape{1, 1, input_height, input_width};
     auto func_shape = Shape{1, 1, func_height, func_width};
     auto element_type = element::f32;
-    auto input_img = std::vector<float> {1.f, 2.f, 3.f, 4.f, 4.f, 3.f, 2.f, 1.f, 1.f, 2.f, 3.f, 4.f, 4.f, 3.f, 2.f, 1.f};
+    auto input_img = std::vector<float>{1.f, 2.f, 3.f, 4.f, 4.f, 3.f, 2.f, 1.f, 1.f, 2.f, 3.f, 4.f, 4.f, 3.f, 2.f, 1.f};
     function = create_simple_function(element_type, func_shape);
     auto p = PrePostProcessor(function);
     p.input().tensor().set_spatial_static_shape(input_height, input_width);
@@ -419,4 +416,4 @@ TEST_F(PreprocessOpenCVReferenceTest, DISABLED_resize_f32_large_picture_cubic_sm
     Exec();
 }
 
-#endif // OPENCV_TEMPLATE_TESTS
+#endif  // OPENCV_TEMPLATE_TESTS

From 215a2f435b88e9298d6e33380842b347b97bd515 Mon Sep 17 00:00:00 2001
From: Anastasiia Pnevskaia <anastasiia.pnevskaia@intel.com>
Date: Tue, 19 Sep 2023 19:04:24 +0200
Subject: [PATCH 30/46] tf.Graph decoder accuracy fixes (#19903)

* Fixed outputs passing from decoder.

* Fixed get_variable method.

* Code style.

* Removed xfails from precommit models.

* Minor fix.

* Comment fixed.

* Added test.
---
 .../frontend/tensorflow/graph_iterator.py     | 16 +++++---
 .../frontend/tensorflow/node_decoder.py       | 14 ++++---
 .../src/openvino/frontend/tensorflow/utils.py |  2 +-
 src/frontends/tensorflow/src/input_model.cpp  | 30 +++++++++-----
 .../tensorflow/src/translate_session.cpp      | 17 +++++---
 .../ovc_python_api_tests/test_tf.py           | 40 +++++++++++++++++++
 .../tf_hub_tests/precommit_models             |  6 +--
 7 files changed, 95 insertions(+), 30 deletions(-)

diff --git a/src/bindings/python/src/openvino/frontend/tensorflow/graph_iterator.py b/src/bindings/python/src/openvino/frontend/tensorflow/graph_iterator.py
index ac7bb04958a3e4..29dc6b1ad58973 100644
--- a/src/bindings/python/src/openvino/frontend/tensorflow/graph_iterator.py
+++ b/src/bindings/python/src/openvino/frontend/tensorflow/graph_iterator.py
@@ -40,6 +40,10 @@ def get_input_names(self) -> list:
             return []
         inp_ops = filter(lambda op: op.type == "Placeholder", self.m_graph.get_operations())
         inp_names = []
+        if hasattr(self.m_graph, 'inputs') and self.m_graph.inputs:
+            for inp in self.m_graph.inputs:
+                inp_names.append(inp.op.name)
+            return inp_names
         for inp in inp_ops:
             assert isinstance(inp, tf.Operation), "Unknown node type. Expected tf.Operation, got {}".format(type(inp))
             assert hasattr(inp, "node_def") and isinstance(inp.node_def, tf.compat.v1.NodeDef), \
@@ -58,11 +62,13 @@ def get_output_names(self) -> list:
         # Note: used only for the library functions
         if not self.m_inner_graph:
             return []
-        # tf.Graph has ordered outputs which are stored in 'outputs' field,
-        # but using this field results in mismatch of outputs in inner graph and outputs in outer graph
-        # during the injection of subgraph.
-        # For this reason only nodes without outputs are considered graph outputs here
-        # as this approach does not lead to conflicts.
+
+        if hasattr(self.m_graph, 'outputs') and self.m_graph.outputs:
+            outputs = []
+            for out in self.m_graph.outputs:
+                outputs.append(out.name)
+            return outputs
+        # If graph has no 'outputs' field, find nodes without outputs and consider them graph outputs.
         # The order of outputs is important and wrong order may lead to conversion error.
         non_outputs = set()
         for op in self.m_graph.get_operations():
diff --git a/src/bindings/python/src/openvino/frontend/tensorflow/node_decoder.py b/src/bindings/python/src/openvino/frontend/tensorflow/node_decoder.py
index 0ecffc4040abe6..4fab05c17de380 100644
--- a/src/bindings/python/src/openvino/frontend/tensorflow/node_decoder.py
+++ b/src/bindings/python/src/openvino/frontend/tensorflow/node_decoder.py
@@ -54,6 +54,7 @@ def __init__(self, operation: tf.Operation, share_weights: bool, inner_graph: bo
         self.m_operation = operation
         self.m_inner_graph = inner_graph
         self.m_data_type = None
+        self.m_parsed_content = None
 
         # Copies value from inner buffer of TF_Operation to NodeDef class.
         self.m_node_def = self.m_operation.node_def
@@ -87,11 +88,11 @@ def __init__(self, operation: tf.Operation, share_weights: bool, inner_graph: bo
         if self.m_operation.type == "Placeholder":
             self.m_data_type = tf.dtypes.DType(self.m_node_def.attr["dtype"].type).name
 
-            if self.m_data_type == "resource" and not self.m_inner_graph:
+            if not self.m_inner_graph:
                 variable_value = TFGraphNodeDecoder.get_variable(self.m_operation)
                 if variable_value is not None:
                     # does not copy data
-                    self.m_parsed_content = variable_value.value().__array__()
+                    self.m_parsed_content = variable_value.__array__()
 
                     if isinstance(self.m_parsed_content, bytes):
                         self.m_data_type = "string"
@@ -103,7 +104,7 @@ def get_op_name(self) -> str:
     def get_op_type(self) -> str:
         if self.m_operation.type == "Placeholder":
             type_attr = tf.dtypes.DType(self.m_node_def.attr["dtype"].type)
-            if type_attr.name == "resource" and not self.m_inner_graph:
+            if not self.m_inner_graph and self.m_parsed_content is not None:
                 if TFGraphNodeDecoder.get_variable(self.m_operation) is not None:
                     return "Const"
                 raise Exception("Could not get variable for resource Placeholder {0}".format(self.m_operation.name))
@@ -116,10 +117,11 @@ def get_variable(operation):
             return None
         for var_tensor, op_tensor in tf_graph.captures:
             if operation.outputs[0].name == op_tensor.name:
-                resource_name = var_tensor._name
+                if var_tensor.dtype.name != 'resource':
+                    return var_tensor
                 for variable_value in operation.graph.variables:
-                    if variable_value.name == resource_name:
-                        return variable_value
+                    if id(variable_value.handle) == id(var_tensor):
+                        return variable_value.value()
                 return None
         return None
 
diff --git a/src/bindings/python/src/openvino/frontend/tensorflow/utils.py b/src/bindings/python/src/openvino/frontend/tensorflow/utils.py
index 056e0904b4c22f..f4ac5b0a121565 100644
--- a/src/bindings/python/src/openvino/frontend/tensorflow/utils.py
+++ b/src/bindings/python/src/openvino/frontend/tensorflow/utils.py
@@ -339,7 +339,7 @@ def create_tf_graph_iterator(input_model, placeholder_shapes, placeholder_data_t
         if hasattr(input_model, 'outputs') and hasattr(input_model, 'structured_outputs') and \
                 isinstance(input_model.structured_outputs, dict):
             external_names = sorted(list(input_model.structured_outputs.keys()))
-            internal_names = sorted([tensor.name for tensor in input_model.outputs])
+            internal_names = [tensor.name for tensor in input_model.outputs]
             if len(external_names) == len(internal_names):
                 for external_name, internal_name in zip(external_names, internal_names):
                     output_names_map = output_names_map or {}
diff --git a/src/frontends/tensorflow/src/input_model.cpp b/src/frontends/tensorflow/src/input_model.cpp
index 9ed378b9373762..6e2103ca463a10 100644
--- a/src/frontends/tensorflow/src/input_model.cpp
+++ b/src/frontends/tensorflow/src/input_model.cpp
@@ -259,15 +259,26 @@ void InputModel::InputModelTFImpl::load_places() {
         return;
     }
 
-    // treat terminal nodes as the models outputs for the frozen TF1 format
-    std::set<std::string> op_names_without_consumers;
-    std::set_difference(all_op_names.begin(),
-                        all_op_names.end(),
-                        op_names_with_consumers.begin(),
-                        op_names_with_consumers.end(),
-                        std::inserter(op_names_without_consumers, op_names_without_consumers.begin()));
-
-    for (const auto& output_name : op_names_without_consumers) {
+    auto out_names = m_graph_iterator->get_output_names();
+    if (!out_names.size()) {
+        // treat terminal nodes as the models outputs for the frozen TF1 format
+        std::set<std::string> op_names_without_consumers;
+        std::set_difference(all_op_names.begin(),
+                            all_op_names.end(),
+                            op_names_with_consumers.begin(),
+                            op_names_with_consumers.end(),
+                            std::inserter(op_names_without_consumers, op_names_without_consumers.begin()));
+        for (const auto& output_name : op_names_without_consumers) {
+            auto output_place = std::make_shared<TensorPlace>(m_input_model,
+                                                              ov::PartialShape({}),
+                                                              ov::element::dynamic,
+                                                              std::vector<std::string>{output_name});
+            m_tensor_places[output_name] = output_place;
+            m_outputs.push_back(output_place);
+        }
+        return;
+    }
+    for (const auto& output_name : out_names) {
         auto output_place = std::make_shared<TensorPlace>(m_input_model,
                                                           ov::PartialShape({}),
                                                           ov::element::dynamic,
@@ -312,7 +323,6 @@ std::vector<std::shared_ptr<OpPlace>> InputModel::InputModelTFImpl::topologicall
     // TODO: implement logic to check direct cycles in the graph
     // and break them
     // probably not only NextIteration can generate cycles
-
     for (const auto& output_place : m_outputs) {
         FRONT_END_GENERAL_CHECK(output_place->get_names().size() > 0, "TensorPlace must have at least one name.");
         auto output_place_name = output_place->get_names()[0];
diff --git a/src/frontends/tensorflow/src/translate_session.cpp b/src/frontends/tensorflow/src/translate_session.cpp
index ebb0dee99923fa..933bc0d900eba5 100644
--- a/src/frontends/tensorflow/src/translate_session.cpp
+++ b/src/frontends/tensorflow/src/translate_session.cpp
@@ -25,17 +25,24 @@ std::vector<T> reorder_ops_by_names(const std::vector<std::string>& names, const
                             "[TensorFlow Frontend] Internal error: cannot perform reordering of operations. The number "
                             "of names mismatches the number of operations.");
     std::vector<T> resulted_ops(ops.size(), nullptr);
+
     for (const auto& op : ops) {
         const auto& op_name = op->get_friendly_name();
         auto iter = std::find(names.begin(), names.end(), op_name);
         FRONT_END_GENERAL_CHECK(iter != names.end(),
                                 "[TensorFlow Frontend] Internal error: cannot perform reordering of operations. The "
                                 "requested name is not found among operations.");
-        auto ind = std::distance(names.begin(), iter);
-        FRONT_END_GENERAL_CHECK(resulted_ops[ind] == nullptr,
-                                "[TensorFlow Frontend] Internal error: incorrect reordering of operations. "
-                                "Found two operations that are mapped to the same name.");
-        resulted_ops[ind] = op;
+    }
+
+    size_t ind = 0;
+    for (const auto& name : names) {
+        for (const auto& op : ops) {
+            if (op->get_friendly_name() == name) {
+                resulted_ops[ind] = op;
+                ind++;
+                break;
+            }
+        }
     }
     return resulted_ops;
 };
diff --git a/tests/layer_tests/ovc_python_api_tests/test_tf.py b/tests/layer_tests/ovc_python_api_tests/test_tf.py
index 75e0d641c42fec..a311666eb83bf3 100644
--- a/tests/layer_tests/ovc_python_api_tests/test_tf.py
+++ b/tests/layer_tests/ovc_python_api_tests/test_tf.py
@@ -860,6 +860,46 @@ def __call__(self, input):
         assert CommonLayerTest().compare_ie_results_with_framework(ov_infer, {"Identity:0": fw_infer}, eps)
         assert CommonLayerTest().compare_ie_results_with_framework(ov_infer, {"Identity:0": 3.2}, eps)
 
+    def test_unnamed_variable(self, ie_device, precision, ir_version, temp_dir):
+        import tensorflow as tf
+        tf.compat.v1.reset_default_graph()
+
+        from openvino.tools.ovc import convert_model
+        from openvino.runtime import compile_model
+
+        class LayerModel(tf.Module):
+            def __init__(self):
+                super(LayerModel, self).__init__()
+                self.var1 = tf.Variable([1.6, 3.8])
+                self.var2 = tf.Variable(-0.5)
+
+
+            @tf.function
+            def sub_function(self, input):
+                return (input + self.var1) * self.var2
+
+            @tf.function(input_signature=[tf.TensorSpec([2], tf.float32)])
+            def __call__(self, input):
+                return self.sub_function(input)
+
+        if precision == 'FP32':
+            eps = 1e-4
+        else:
+            eps = 5e-2
+
+        test_input = np.array([2.0, 5.0]).astype(np.float32)
+
+        # Convert model to OV
+        fw_model = LayerModel()
+        ov_model = convert_model(fw_model)
+        cmp_model = compile_model(ov_model)
+
+        # Check model inference
+        ov_infer = cmp_model(test_input, ie_device)
+        fw_infer = fw_model(test_input).numpy()
+
+        assert CommonLayerTest().compare_ie_results_with_framework(ov_infer, {"Identity:0": fw_infer}, eps)
+        assert CommonLayerTest().compare_ie_results_with_framework(ov_infer, {"Identity:0": [-1.8, -4.4]}, eps)
 
 class TFConvertTest(unittest.TestCase):
     @pytest.mark.nightly
diff --git a/tests/model_hub_tests/tf_hub_tests/precommit_models b/tests/model_hub_tests/tf_hub_tests/precommit_models
index f9be334761d23c..3be4384dd1c576 100644
--- a/tests/model_hub_tests/tf_hub_tests/precommit_models
+++ b/tests/model_hub_tests/tf_hub_tests/precommit_models
@@ -6,13 +6,13 @@ imagenet/mobilenet_v2_100_224/feature_vector,https://tfhub.dev/google/imagenet/m
 efficientnet/lite0/classification,https://tfhub.dev/tensorflow/efficientnet/lite0/classification/2?tf-hub-format=compressed
 movenet/multipose/lightning,https://tfhub.dev/google/movenet/multipose/lightning/1?tf-hub-format=compressed
 imagenet/efficientnet_v2_imagenet1k_b0/feature_vector,https://tfhub.dev/google/imagenet/efficientnet_v2_imagenet1k_b0/feature_vector/2?tf-hub-format=compressed
-imagenet/mobilenet_v1_100_224/classification,https://tfhub.dev/google/imagenet/mobilenet_v1_100_224/classification/5?tf-hub-format=compressed,skip,119718 - Accuracy issue
+imagenet/mobilenet_v1_100_224/classification,https://tfhub.dev/google/imagenet/mobilenet_v1_100_224/classification/5?tf-hub-format=compressed
 magenta/arbitrary-image-stylization-v1-256,https://tfhub.dev/google/magenta/arbitrary-image-stylization-v1-256/2?tf-hub-format=compressed
-small_bert/bert_en_uncased_L-4_H-256_A-4,https://tfhub.dev/tensorflow/small_bert/bert_en_uncased_L-4_H-256_A-4/2?tf-hub-format=compressed,skip,119718 - Accuracy issue
+small_bert/bert_en_uncased_L-4_H-256_A-4,https://tfhub.dev/tensorflow/small_bert/bert_en_uncased_L-4_H-256_A-4/2?tf-hub-format=compressed
 movinet/a5/base/kinetics-600/classification,https://tfhub.dev/tensorflow/movinet/a5/base/kinetics-600/classification/3?tf-hub-format=compressed
 # secure notebook models
 unet/industrial/class_1,https://tfhub.dev/nvidia/unet/industrial/class_1/1?tf-hub-format=compressed
 movenet/singlepose/thunder,https://tfhub.dev/google/movenet/singlepose/thunder/4?tf-hub-format=compressed
 esrgan-tf2,https://tfhub.dev/captain-pool/esrgan-tf2/1?tf-hub-format=compressed
-film,https://tfhub.dev/google/film/1?tf-hub-format=compressed,skip,119718 - Accuracy issue
+film,https://tfhub.dev/google/film/1?tf-hub-format=compressed
 planet/vision/classifier/planet_v2,https://tfhub.dev/google/planet/vision/classifier/planet_v2/1?tf-hub-format=compressed
\ No newline at end of file

From 00bc4436a98d53e0ca168571554a28d083084ced Mon Sep 17 00:00:00 2001
From: Evgenya Nugmanova <evgeniia.nugmanova@intel.com>
Date: Tue, 19 Sep 2023 22:13:19 +0400
Subject: [PATCH 31/46] Allow avoiding Constant casting / printing
 VisualizeTree (#19845)

* Avoid Constant casting / printing when OV_VISUALIZE_TREE_CONST_MAX_ELEMENTS==0
Cast only requested amount of elements in Constant::cast_vector<>

* Refactor

* Revert style back

* Fix signed/unsigned comparison

* test

* Style

* Style
---
 src/core/include/openvino/op/constant.hpp | 80 +++++++++++++----------
 src/core/src/pass/visualize_tree.cpp      | 67 +++++++------------
 src/core/tests/constant.cpp               | 40 ++++++++++++
 3 files changed, 108 insertions(+), 79 deletions(-)

diff --git a/src/core/include/openvino/op/constant.hpp b/src/core/include/openvino/op/constant.hpp
index 00e48a7f392951..3c2d048e0db7bf 100644
--- a/src/core/include/openvino/op/constant.hpp
+++ b/src/core/include/openvino/op/constant.hpp
@@ -295,10 +295,11 @@ class OPENVINO_API Constant : public Op {
 
     /// \brief Return the Constant's value as a vector cast to type T
     ///
-    /// \tparam T  Type to which data vector's entries will be cast.
+    /// \tparam T             Type to which data vector's entries will be cast.
+    /// \param  num_elements  (Optional) Number of elements to cast. In default case returns all elements
     /// \return    Constant's data vector.
     template <typename T>
-    std::vector<T> cast_vector() const {
+    std::vector<T> cast_vector(int64_t num_elements = -1) const {
         auto source_type = get_element_type();
         std::vector<T> rc;
         using Type_t = element::Type_t;
@@ -306,54 +307,58 @@ class OPENVINO_API Constant : public Op {
 #    pragma warning(push)
 #    pragma warning(disable : 4244)
 #endif
+        size_t num_elements_in_constant = shape_size(m_shape);
+        size_t num_elements_to_cast =
+            (num_elements < 0 ? num_elements_in_constant
+                              : std::min(static_cast<size_t>(num_elements), num_elements_in_constant));
         switch (source_type) {
         case Type_t::boolean:
-            cast_vector<Type_t::boolean>(rc);
+            cast_vector<Type_t::boolean>(rc, num_elements_to_cast);
             break;
         case Type_t::bf16:
-            cast_vector<Type_t::bf16>(rc);
+            cast_vector<Type_t::bf16>(rc, num_elements_to_cast);
             break;
         case Type_t::f16:
-            cast_vector<Type_t::f16>(rc);
+            cast_vector<Type_t::f16>(rc, num_elements_to_cast);
             break;
         case Type_t::f32:
-            cast_vector<Type_t::f32>(rc);
+            cast_vector<Type_t::f32>(rc, num_elements_to_cast);
             break;
         case Type_t::f64:
-            cast_vector<Type_t::f64>(rc);
+            cast_vector<Type_t::f64>(rc, num_elements_to_cast);
             break;
         case Type_t::i4:
-            cast_vector<Type_t::i4>(rc);
+            cast_vector<Type_t::i4>(rc, num_elements_to_cast);
             break;
         case Type_t::i8:
-            cast_vector<Type_t::i8>(rc);
+            cast_vector<Type_t::i8>(rc, num_elements_to_cast);
             break;
         case Type_t::i16:
-            cast_vector<Type_t::i16>(rc);
+            cast_vector<Type_t::i16>(rc, num_elements_to_cast);
             break;
         case Type_t::i32:
-            cast_vector<Type_t::i32>(rc);
+            cast_vector<Type_t::i32>(rc, num_elements_to_cast);
             break;
         case Type_t::i64:
-            cast_vector<Type_t::i64>(rc);
+            cast_vector<Type_t::i64>(rc, num_elements_to_cast);
             break;
         case Type_t::u1:
-            cast_vector<Type_t::u1>(rc);
+            cast_vector<Type_t::u1>(rc, num_elements_to_cast);
             break;
         case Type_t::u4:
-            cast_vector<Type_t::u4>(rc);
+            cast_vector<Type_t::u4>(rc, num_elements_to_cast);
             break;
         case Type_t::u8:
-            cast_vector<Type_t::u8>(rc);
+            cast_vector<Type_t::u8>(rc, num_elements_to_cast);
             break;
         case Type_t::u16:
-            cast_vector<Type_t::u16>(rc);
+            cast_vector<Type_t::u16>(rc, num_elements_to_cast);
             break;
         case Type_t::u32:
-            cast_vector<Type_t::u32>(rc);
+            cast_vector<Type_t::u32>(rc, num_elements_to_cast);
             break;
         case Type_t::u64:
-            cast_vector<Type_t::u64>(rc);
+            cast_vector<Type_t::u64>(rc, num_elements_to_cast);
             break;
         default:
             OPENVINO_THROW("unsupported type");
@@ -438,15 +443,19 @@ class OPENVINO_API Constant : public Op {
               typename std::enable_if<Type != element::Type_t::u1 && Type != element::Type_t::u4 &&
                                           Type != element::Type_t::i4,
                                       bool>::type = true>
-    void cast_vector(std::vector<OUT_T>& output_vector) const {
+    void cast_vector(std::vector<OUT_T>& output_vector, size_t num_elements) const {
         // this function is workaround for waring during windows building
         // build complains for vector creation based on iterators
         // which point on different type than destination vector::value_type
         using IN_T = fundamental_type_for<Type>;
         auto source_vector = get_vector<IN_T>();
-        output_vector.reserve(source_vector.size());
+        auto output_size = std::min(num_elements, source_vector.size());
+        output_vector.reserve(output_size);
 
-        std::transform(source_vector.begin(), source_vector.end(), std::back_inserter(output_vector), [](IN_T c) {
+        std::transform(source_vector.begin(),
+                       source_vector.begin() + output_size,
+                       std::back_inserter(output_vector),
+                       [](IN_T c) {
 #ifdef __clang__
 #    pragma clang diagnostic push
 #    ifdef __has_warning
@@ -465,12 +474,13 @@ class OPENVINO_API Constant : public Op {
 #    pragma warning(disable : 4018)
 #    pragma warning(disable : 4804)
 #endif
-            if (!std::is_same<OUT_T, IN_T>::value) {
-                OPENVINO_ASSERT(!std::numeric_limits<IN_T>::is_signed || std::numeric_limits<OUT_T>::lowest() <= c,
-                                "Cannot cast vector from constant. Some values are outside the range.");
-                OPENVINO_ASSERT(std::numeric_limits<OUT_T>::max() >= c,
-                                "Cannot cast vector from constant. Some values are outside the range.");
-            }
+                           if (!std::is_same<OUT_T, IN_T>::value) {
+                               OPENVINO_ASSERT(
+                                   !std::numeric_limits<IN_T>::is_signed || std::numeric_limits<OUT_T>::lowest() <= c,
+                                   "Cannot cast vector from constant. Some values are outside the range.");
+                               OPENVINO_ASSERT(std::numeric_limits<OUT_T>::max() >= c,
+                                               "Cannot cast vector from constant. Some values are outside the range.");
+                           }
 #if defined(__clang__)
 #    pragma clang diagnostic pop
 #elif defined(__GNUC__)
@@ -478,16 +488,16 @@ class OPENVINO_API Constant : public Op {
 #elif defined(_MSC_VER)
 #    pragma warning(pop)
 #endif
-            return static_cast<OUT_T>(c);
-        });
+                           return static_cast<OUT_T>(c);
+                       });
     }
 
     template <element::Type_t Type,
               typename OUT_T,
               typename std::enable_if<Type == element::Type_t::u1, bool>::type = true>
-    void cast_vector(std::vector<OUT_T>& output) const {
+    void cast_vector(std::vector<OUT_T>& output, size_t num_elements) const {
         using IN_T = fundamental_type_for<Type>;
-        const auto element_number = shape_size(m_shape);
+        const auto element_number = std::min(num_elements, shape_size(m_shape));
         const auto source_begin = get_data_ptr<uint8_t>();
         const auto source_end = std::next(source_begin, (element_number + 7) / 8);
         const auto round_element_no = element_number % 8 ? element_number - element_number % 8 + 8 : element_number;
@@ -504,9 +514,9 @@ class OPENVINO_API Constant : public Op {
     template <element::Type_t Type,
               typename OUT_T,
               typename std::enable_if<Type == element::Type_t::u4, bool>::type = true>
-    void cast_vector(std::vector<OUT_T>& output) const {
+    void cast_vector(std::vector<OUT_T>& output, size_t num_elements) const {
         using IN_T = fundamental_type_for<Type>;
-        const auto element_number = shape_size(m_shape);
+        const auto element_number = std::min(num_elements, shape_size(m_shape));
         const auto source_begin = get_data_ptr<uint8_t>();
         const auto source_end = std::next(source_begin, (element_number + 1) / 2);
         const auto round_element_no = element_number % 2 ? element_number + 1 : element_number;
@@ -522,9 +532,9 @@ class OPENVINO_API Constant : public Op {
     template <element::Type_t Type,
               typename OUT_T,
               typename std::enable_if<Type == element::Type_t::i4, bool>::type = true>
-    void cast_vector(std::vector<OUT_T>& output) const {
+    void cast_vector(std::vector<OUT_T>& output, size_t num_elements) const {
         using IN_T = fundamental_type_for<Type>;
-        const auto element_number = shape_size(m_shape);
+        const auto element_number = std::min(num_elements, shape_size(m_shape));
         const auto source_begin = get_data_ptr<uint8_t>();
         const auto source_end = std::next(source_begin, (element_number + 1) / 2);
         const auto round_element_no = element_number % 2 ? element_number + 1 : element_number;
diff --git a/src/core/src/pass/visualize_tree.cpp b/src/core/src/pass/visualize_tree.cpp
index 58622688b47c3e..9aa4adf2378940 100644
--- a/src/core/src/pass/visualize_tree.cpp
+++ b/src/core/src/pass/visualize_tree.cpp
@@ -213,8 +213,6 @@ ov::pass::VisualizeTree::VisualizeTree(const std::string& file_name, node_modifi
 void ov::pass::VisualizeTree::add_node_arguments(std::shared_ptr<Node> node,
                                                  std::unordered_map<Node*, HeightMap>& height_maps,
                                                  size_t& fake_node_ctr) {
-    static const int const_max_elements = ov::util::getenv_int("OV_VISUALIZE_TREE_CONST_MAX_ELEMENTS", 7);
-
     size_t arg_index = 0;
     for (auto input_value : node->input_values()) {
         auto arg = input_value.get_node_shared_ptr();
@@ -227,7 +225,7 @@ void ov::pass::VisualizeTree::add_node_arguments(std::shared_ptr<Node> node,
                                                 "style=\"dashed\"",
                                                 color,
                                                 std::string("label=\"") + get_node_name(arg) + std::string("\n") +
-                                                    get_constant_value(arg, const_max_elements) + std::string("\"")};
+                                                    get_constant_value(arg) + std::string("\"")};
 
             if (m_node_modifiers && !arg->output(0).get_rt_info().empty()) {
                 m_node_modifiers(*arg, attributes);
@@ -280,13 +278,7 @@ std::string ov::pass::VisualizeTree::add_attributes(std::shared_ptr<Node> node)
 
 static std::string pretty_partial_shape(const ov::PartialShape& shape) {
     std::stringstream ss;
-
-    if (shape.rank().is_dynamic()) {
-        ss << "?";
-    } else {
-        ss << shape;
-    }
-
+    ss << shape;
     return ss.str();
 }
 
@@ -327,21 +319,11 @@ static std::string pretty_min_max_denormal_value(const std::vector<T>& values) {
 }
 
 template <typename T>
-static std::string pretty_value(const std::vector<T>& values, size_t max_elements, bool allow_obfuscate = false) {
+static std::string pretty_value(const std::vector<T>& values, bool allow_obfuscate = false) {
     std::stringstream ss;
     for (size_t i = 0; i < values.size(); ++i) {
-        if (i < max_elements) {
-            if (i != 0 && i % 8 == 0) {
-                ss << std::endl;
-            }
-        } else {
-            bool all_same = std::all_of(values.begin(), values.end(), [&](const T& el) {
-                return el == values[0];
-            });
-            ss << "..." << (all_same ? " same" : "");
-            break;
-        }
-
+        if (i != 0 && i % 8 == 0)
+            ss << std::endl;
         const auto& value = values[i];
         if (i > 0)
             ss << ", ";
@@ -361,46 +343,46 @@ static std::string pretty_value(const std::vector<T>& values, size_t max_element
     return ss.str();
 }
 
-static std::string get_value(const std::shared_ptr<ov::op::v0::Constant>& constant,
-                             size_t max_elements,
-                             bool allow_obfuscate = false) {
+static std::string get_value(const std::shared_ptr<ov::op::v0::Constant>& constant, bool allow_obfuscate = false) {
+    static const int max_elements = ov::util::getenv_int("OV_VISUALIZE_TREE_CONST_MAX_ELEMENTS", 7);
     std::stringstream ss;
+    ss << "[ ";
     switch (constant->get_output_element_type(0)) {
     case ov::element::Type_t::undefined:
-        ss << "[ undefined value ]";
-        break;
     case ov::element::Type_t::dynamic:
-        ss << "[ dynamic value ]";
-        break;
     case ov::element::Type_t::u1:
-        ss << "[ u1 value ]";
-        break;
     case ov::element::Type_t::u4:
-        ss << "[ u4 value ]";
-        break;
     case ov::element::Type_t::i4:
-        ss << "[ i4 value ]";
+        ss << constant->get_output_element_type(0).get_type_name() << " value";
         break;
     case ov::element::Type_t::bf16:
     case ov::element::Type_t::f16:
     case ov::element::Type_t::f32:
     case ov::element::Type_t::f64:
-        ss << "[" << pretty_value(constant->cast_vector<double>(), max_elements, allow_obfuscate) << "]";
+        ss << pretty_value(constant->cast_vector<double>(max_elements), allow_obfuscate);
         break;
     case ov::element::Type_t::i8:
     case ov::element::Type_t::i16:
     case ov::element::Type_t::i32:
     case ov::element::Type_t::i64:
-        ss << "[" << pretty_value(constant->cast_vector<int64_t>(), max_elements, allow_obfuscate) << "]";
+        ss << pretty_value(constant->cast_vector<int64_t>(max_elements), allow_obfuscate);
         break;
     case ov::element::Type_t::boolean:
     case ov::element::Type_t::u8:
     case ov::element::Type_t::u16:
     case ov::element::Type_t::u32:
     case ov::element::Type_t::u64:
-        ss << "[" << pretty_value(constant->cast_vector<uint64_t>(), max_elements, allow_obfuscate) << "]";
+        ss << pretty_value(constant->cast_vector<uint64_t>(max_elements), allow_obfuscate);
         break;
     }
+    const auto num_elements_in_constant = static_cast<int>(shape_size(constant->get_shape()));
+    if (num_elements_in_constant == 0)
+        ss << "empty";
+    else if (max_elements == 0)
+        ss << "suppressed";
+    else if (num_elements_in_constant > max_elements)
+        ss << ", ...";
+    ss << " ]";
     return ss.str();
 }
 
@@ -418,12 +400,9 @@ static std::string get_bounds_and_label_info(const ov::Output<ov::Node> output)
     if (size == 0) {
         label << "empty";
     } else {
-        static const int const_max_elements = ov::util::getenv_int("OV_VISUALIZE_TREE_CONST_MAX_ELEMENTS", 7);
-        label << " lower: "
-              << (lower ? get_value(std::make_shared<ov::op::v0::Constant>(lower), const_max_elements, true) : "NONE");
-        label << " upper: "
-              << (upper ? get_value(std::make_shared<ov::op::v0::Constant>(upper), const_max_elements, true) : "NONE");
-        label << " label: " << (value_label.empty() ? "NONE" : pretty_value(value_label, const_max_elements));
+        label << " lower: " << (lower ? get_value(std::make_shared<ov::op::v0::Constant>(lower), true) : "NONE");
+        label << " upper: " << (upper ? get_value(std::make_shared<ov::op::v0::Constant>(upper), true) : "NONE");
+        label << " label: " << (value_label.empty() ? "NONE" : pretty_value(value_label));
     }
     return label.str();
 }
diff --git a/src/core/tests/constant.cpp b/src/core/tests/constant.cpp
index 810affda0a6c36..45ad60d153627a 100644
--- a/src/core/tests/constant.cpp
+++ b/src/core/tests/constant.cpp
@@ -1779,3 +1779,43 @@ TEST(constant, lazy_bitwise_identical) {
     // '10' times is guaranteed to be faster here (typical value is ~200'000)
     EXPECT_GT(bitwise_check_count_only, bitwise_check_count * 10);
 }
+
+TEST(constant, cast_vector) {
+    std::vector<element::Type_t> types = {element::boolean,
+                                          element::bf16,
+                                          element::f16,
+                                          element::f32,
+                                          element::f64,
+                                          element::i4,
+                                          element::i8,
+                                          element::i16,
+                                          element::i32,
+                                          element::i64,
+                                          element::u1,
+                                          element::u4,
+                                          element::u8,
+                                          element::u16,
+                                          element::u32,
+                                          element::u64};
+    std::vector<int64_t> data = {0, 1, 0, 0, 1, 1, 0, 1};
+    std::vector<int64_t> expected_partial_data = {0, 1, 0, 0, 1, 1};
+
+    for (const auto& type : types) {
+        const auto& constant = op::v0::Constant::create(type, Shape{data.size()}, data);
+
+        const auto& default_casted = constant->cast_vector<int64_t>();
+        EXPECT_EQ(default_casted, data) << "Constant::cast_vector failed default casting for type " << type;
+
+        int64_t num_elements_for_partial_casting = static_cast<int64_t>(expected_partial_data.size());
+        const auto& partially_casted = constant->cast_vector<int64_t>(num_elements_for_partial_casting);
+        EXPECT_EQ(partially_casted, expected_partial_data)
+            << "Constant::cast_vector failed partial casting for type " << type;
+
+        int64_t num_elements_for_over_casting = static_cast<int64_t>(data.size()) + 10;
+        const auto& over_casted = constant->cast_vector<int64_t>(num_elements_for_over_casting);
+        EXPECT_EQ(over_casted, data) << "Constant::cast_vector failed for partial casting for type " << type;
+
+        EXPECT_TRUE(constant->cast_vector<int64_t>(0).empty())
+            << "Constant::cast_vector failed empty casting for type " << type;
+    }
+}

From 52e57e1777e30c370ed9dab6982143bb1a968687 Mon Sep 17 00:00:00 2001
From: Ilya Churaev <ilya.churaev@intel.com>
Date: Tue, 19 Sep 2023 22:26:57 +0400
Subject: [PATCH 32/46] Disable clang-format for legacy C API (#19944)

---
 src/bindings/c/src/CMakeLists.txt | 9 +++++----
 src/bindings/c/src/common.h       | 4 ++--
 2 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/src/bindings/c/src/CMakeLists.txt b/src/bindings/c/src/CMakeLists.txt
index 737dcc3d272a1e..e491424cb27afb 100644
--- a/src/bindings/c/src/CMakeLists.txt
+++ b/src/bindings/c/src/CMakeLists.txt
@@ -8,11 +8,12 @@ set(TARGET_NAME openvino_c)
 ov_deprecated_no_errors()
 add_definitions(-DIN_OV_COMPONENT)
 
-file(GLOB SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp)
-file(GLOB_RECURSE HEADERS ${OpenVINO_C_API_SOURCE_DIR}/include/*.h)
+file(GLOB SOURCES ${CMAKE_CURRENT_SOURCE_DIR}/*.h ${CMAKE_CURRENT_SOURCE_DIR}/*.cpp)
+file(GLOB_RECURSE LEGACY_HEADERS ${OpenVINO_C_API_SOURCE_DIR}/include/c_api/*.h)
+file(GLOB_RECURSE HEADERS ${OpenVINO_C_API_SOURCE_DIR}/include/openvino/*.h)
 
 # create library
-add_library(${TARGET_NAME} ${HEADERS} ${SOURCES})
+add_library(${TARGET_NAME} ${LEGACY_HEADERS} ${HEADERS} ${SOURCES})
 add_library(openvino::runtime::c ALIAS ${TARGET_NAME})
 
 target_link_libraries(${TARGET_NAME} PRIVATE openvino openvino::util)
@@ -24,7 +25,7 @@ if(NOT BUILD_SHARED_LIBS)
     target_compile_definitions(${TARGET_NAME} PUBLIC OPENVINO_STATIC_LIBRARY)
 endif()
 
-ov_add_clang_format_target(${TARGET_NAME}_clang FOR_TARGETS ${TARGET_NAME})
+ov_add_clang_format_target(${TARGET_NAME}_clang FOR_SOURCES ${HEADERS} ${SOURCES})
 
 set_target_properties(${TARGET_NAME} PROPERTIES INTERPROCEDURAL_OPTIMIZATION_RELEASE ${ENABLE_LTO})
 
diff --git a/src/bindings/c/src/common.h b/src/bindings/c/src/common.h
index 92e024a7123d65..ff2e0bcac07312 100644
--- a/src/bindings/c/src/common.h
+++ b/src/bindings/c/src/common.h
@@ -17,7 +17,7 @@
 #define CATCH_IE_EXCEPTION(StatusCode, ExceptionType) \
     catch (const InferenceEngine::ExceptionType&) {   \
         return ov_status_e::StatusCode;               \
-    }                                                 \
+    }
 
 #define CATCH_OV_EXCEPTION(StatusCode, ExceptionType) \
     catch (const ov::ExceptionType&) {                \
@@ -42,7 +42,7 @@
     CATCH_IE_EXCEPTION(INFER_CANCELLED, InferCancelled)       \
     catch (...) {                                             \
         return ov_status_e::UNKNOW_EXCEPTION;                 \
-    }                                                         \
+    }
 
 #define GET_PROPERTY_FROM_ARGS_LIST                     \
     std::string property_key = va_arg(args_ptr, char*); \

From b3ee79520f067ee4104bba4e3a886b3c9e096593 Mon Sep 17 00:00:00 2001
From: Anastasia Kuporosova <anastasia.kuporosova@intel.com>
Date: Tue, 19 Sep 2023 23:35:38 +0200
Subject: [PATCH 33/46] [PyOV][Docs] Add docs for if-op (#19899)

* [PyOV][Docs] Add docs for if-op

* code style

* add rtypes

* add dots
---
 .../python/src/pyopenvino/graph/ops/if.cpp    | 178 ++++++++++++++++--
 .../openvino/op/util/multi_subgraph_base.hpp  |  12 +-
 2 files changed, 171 insertions(+), 19 deletions(-)

diff --git a/src/bindings/python/src/pyopenvino/graph/ops/if.cpp b/src/bindings/python/src/pyopenvino/graph/ops/if.cpp
index 13de82c7acd3aa..d1eb84eb014d46 100644
--- a/src/bindings/python/src/pyopenvino/graph/ops/if.cpp
+++ b/src/bindings/python/src/pyopenvino/graph/ops/if.cpp
@@ -19,7 +19,17 @@ void regclass_graph_op_If(py::module m) {
     py::class_<ov::op::v8::If, std::shared_ptr<ov::op::v8::If>, ov::Node> cls(m, "if_op");
     cls.doc() = "openvino.impl.op.If wraps ov::op::v0::If";
     cls.def(py::init<>());
-    cls.def(py::init<const ov::Output<ov::Node>&>(), py::arg("execution_condition"));
+    cls.def(py::init<const ov::Output<ov::Node>&>(),
+            py::arg("execution_condition"),
+            R"(
+            Constructs If with condition.
+
+            :param execution_condition: condition node.
+            :type execution_condition: openvino.runtime.Output
+
+            :rtype: openvino.impl.op.If
+        )");
+
     cls.def(py::init([](const std::shared_ptr<ov::Node>& execution_condition) {
                 if (MultiSubgraphHelpers::is_constant_or_parameter(execution_condition)) {
                     return std::make_shared<ov::op::v8::If>(execution_condition->output(0));
@@ -29,18 +39,114 @@ void regclass_graph_op_If(py::module m) {
                     return std::make_shared<ov::op::v8::If>();
                 }
             }),
-            py::arg("execution_condition"));
-    cls.def("get_else_body", &ov::op::v8::If::get_else_body);
-    cls.def("set_then_body", &ov::op::v8::If::set_then_body, py::arg("body"));
-    cls.def("set_else_body", &ov::op::v8::If::set_else_body, py::arg("body"));
+            py::arg("execution_condition"),
+            R"(
+            Constructs If with condition.
+
+            :param execution_condition: condition node.
+            :type execution_condition: openvino.runtime.Node
+
+            :rtype: openvino.impl.op.If
+        )");
+
+    cls.def("get_else_body",
+            &ov::op::v8::If::get_else_body,
+            R"(
+            Gets else_body as Model object.
+
+            :return: else_body as Model object.
+            :rtype: openvino.Model
+        )");
+
+    cls.def("set_then_body",
+            &ov::op::v8::If::set_then_body,
+            py::arg("body"),
+            R"(
+            Sets new Model object as new then_body.
+
+            :param body: new body for 'then' branch.
+            :type body: openvino.Model
+
+            :rtype: None
+        )");
+
+    cls.def("set_else_body",
+            &ov::op::v8::If::set_else_body,
+            py::arg("body"),
+            R"(
+            Sets new Model object as new else_body.
+
+            :param body: new body for 'else' branch.
+            :type body: openvino.Model
+
+            :rtype: None
+        )");
+
     cls.def("set_input",
             &ov::op::v8::If::set_input,
             py::arg("value"),
             py::arg("then_parameter"),
-            py::arg("else_parameter"));
-    cls.def("set_output", &ov::op::v8::If::set_output, py::arg("then_result"), py::arg("else_result"));
-    cls.def("get_function", &ov::op::util::MultiSubGraphOp::get_function, py::arg("index"));
-    cls.def("set_function", &ov::op::util::MultiSubGraphOp::set_function, py::arg("index"), py::arg("func"));
+            py::arg("else_parameter"),
+            R"(
+            Sets new input to the operation associated with parameters of each sub-graphs.
+
+            :param value: input to operation.
+            :type value: openvino.runtime.Output
+
+            :param then_result: parameter for then_body or nullptr.
+            :type then_result: openvino.runtime.Node
+
+            :param else_result: parameter for else_body or nullptr.
+            :type else_result: openvino.runtime.Node
+
+            :rtype: None
+        )");
+
+    cls.def("set_output",
+            &ov::op::v8::If::set_output,
+            py::arg("then_result"),
+            py::arg("else_result"),
+            R"(
+            Sets new output from the operation associated with results of each sub-graphs.
+
+            :param then_result: result from then_body.
+            :type then_result: openvino.runtime.Node
+
+            :param else_result: result from else_body.
+            :type else_result: openvino.runtime.Node
+
+            :return: output from operation.
+            :rtype: openvino.runtime.Output
+        )");
+
+    cls.def("get_function",
+            &ov::op::util::MultiSubGraphOp::get_function,
+            py::arg("index"),
+            R"(
+            Gets internal sub-graph by index in MultiSubGraphOp.
+
+            :param index: sub-graph's index in op.
+            :type index: int
+            
+            :return: Model with sub-graph.
+            :rtype: openvino.Model
+        )");
+
+    cls.def("set_function",
+            &ov::op::util::MultiSubGraphOp::set_function,
+            py::arg("index"),
+            py::arg("func"),
+            R"(
+            Adds sub-graph to MultiSubGraphOp.
+
+            :param index: index of new sub-graph.
+            :type index: int
+
+            :param func: func new sub_graph as a Model.
+            :type func: openvino.Model
+
+            :rtype: None
+        )");
 
     cls.def(
         "set_input_descriptions",
@@ -48,7 +154,20 @@ void regclass_graph_op_If(py::module m) {
             self->set_input_descriptions(index, MultiSubgraphHelpers::list_to_input_descriptor(inputs));
         },
         py::arg("index"),
-        py::arg("inputs"));
+        py::arg("inputs"),
+        R"(
+            Sets list with connections between operation inputs and internal sub-graph parameters.
+
+            :param index: index of internal sub-graph.
+            :type index: int
+
+            :param inputs: list of input descriptions.
+            :type inputs: list[Union[openvino.runtime.op.util.MergedInputDescription,
+                                     openvino.runtime.op.util.InvariantInputDescription,
+                                     openvino.runtime.op.util.SliceInputDescription]]
+
+            :rtype: None
+        )");
 
     cls.def(
         "set_output_descriptions",
@@ -56,7 +175,19 @@ void regclass_graph_op_If(py::module m) {
             self->set_output_descriptions(index, MultiSubgraphHelpers::list_to_output_descriptor(outputs));
         },
         py::arg("index"),
-        py::arg("outputs"));
+        py::arg("outputs"),
+        R"(
+            Sets list with connections between operation outputs and internal sub-graph parameters.
+
+            :param index: index of internal sub-graph.
+            :type index: int
+
+            :param outputs: list of output descriptions.
+            :type outputs: list[Union[openvino.runtime.op.util.BodyOutputDescription,
+                                      openvino.runtime.op.util.ConcatOutputDescription]]
+
+            :rtype: None
+        )");
 
     cls.def(
         "get_output_descriptions",
@@ -69,7 +200,17 @@ void regclass_graph_op_If(py::module m) {
 
             return result;
         },
-        py::arg("index"));
+        py::arg("index"),
+        R"(
+            Gets list with connections between operation outputs and internal sub-graph parameters.
+
+            :param index: index of internal sub-graph.
+            :type index: int
+
+            :return: list of output descriptions.
+            :rtype: list[Union[openvino.runtime.op.util.BodyOutputDescription,
+                              openvino.runtime.op.util.ConcatOutputDescription]]
+        )");
 
     cls.def(
         "get_input_descriptions",
@@ -82,7 +223,18 @@ void regclass_graph_op_If(py::module m) {
 
             return result;
         },
-        py::arg("index"));
+        py::arg("index"),
+        R"(
+            Gets list with connections between operation inputs and internal sub-graph parameters.
+
+            :param index: index of internal sub-graph.
+            :type index: int
+
+            :return: list of input descriptions.
+            :rtype: list[Union[openvino.runtime.op.util.MergedInputDescription,
+                               openvino.runtime.op.util.InvariantInputDescription,
+                               openvino.runtime.op.util.SliceInputDescription]]
+        )");
 
     cls.def("__repr__", [](const ov::op::v8::If& self) {
         std::stringstream shapes_ss;
diff --git a/src/core/include/openvino/op/util/multi_subgraph_base.hpp b/src/core/include/openvino/op/util/multi_subgraph_base.hpp
index dbdb7b7d724b67..d4ee8eae9ca536 100644
--- a/src/core/include/openvino/op/util/multi_subgraph_base.hpp
+++ b/src/core/include/openvino/op/util/multi_subgraph_base.hpp
@@ -212,7 +212,7 @@ class OPENVINO_API MultiSubGraphOp : public Op {
     virtual void set_function(int index, const std::shared_ptr<Model>& func) {
         m_bodies[index] = func;
     }
-    /// \brief     Gets vector with connections beewtwen operation inputs
+    /// \brief     Gets vector with connections between operation inputs
     /// and internal sub-graph parameters
     ///
     /// \param index   index of internal sub-graph
@@ -220,7 +220,7 @@ class OPENVINO_API MultiSubGraphOp : public Op {
     const MultiSubgraphInputDescriptionVector& get_input_descriptions(int index) const {
         return m_input_descriptions[index];
     }
-    /// \brief     Gets vector with connections beewtwen operation inputs
+    /// \brief     Gets vector with connections between operation inputs
     /// and internal sub-graph parameters
     ///
     /// \param index   index of internal sub-graph
@@ -228,7 +228,7 @@ class OPENVINO_API MultiSubGraphOp : public Op {
     MultiSubgraphInputDescriptionVector& get_input_descriptions(int index) {
         return m_input_descriptions[index];
     }
-    /// \brief     Gets vector with connections beewtwen operation outputs
+    /// \brief     Gets vector with connections between operation outputs
     /// and internal sub-graph results
     ///
     /// \param index   index of internal sub-graph
@@ -236,7 +236,7 @@ class OPENVINO_API MultiSubGraphOp : public Op {
     const MultiSubgraphOutputDescriptionVector& get_output_descriptions(int index) const {
         return m_output_descriptions[index];
     }
-    /// \brief     Gets vector with connections beewtwen operation outputs
+    /// \brief     Gets vector with connections between operation outputs
     /// and internal sub-graph results
     ///
     /// \param index   index of internal sub-graph
@@ -244,7 +244,7 @@ class OPENVINO_API MultiSubGraphOp : public Op {
     MultiSubgraphOutputDescriptionVector& get_output_descriptions(int index) {
         return m_output_descriptions[index];
     }
-    /// \brief     Sets vector with connections beewtwen operation inputs
+    /// \brief     Sets vector with connections between operation inputs
     /// and internal sub-graph parameters
     ///
     /// \param index   index of internal sub-graph
@@ -253,7 +253,7 @@ class OPENVINO_API MultiSubGraphOp : public Op {
         m_input_descriptions[index] = inputs;
     }
 
-    /// \brief     Sets vector with connections beewtwen operation outputs
+    /// \brief     Sets vector with connections between operation outputs
     /// and internal sub-graph results
     ///
     /// \param index   index of internal sub-graph

From 631d6d398063b00b574771fe0aadda741d1e7223 Mon Sep 17 00:00:00 2001
From: Ilya Churaev <ilya.churaev@intel.com>
Date: Wed, 20 Sep 2023 03:36:44 +0400
Subject: [PATCH 34/46] Fixed leftovers after migration to new API (#19941)

* Fixed leftovers after migration to new API

* Fixed tests

* Fixed clang format

---------

Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
---
 src/core/CMakeLists.txt                       |  5 +-
 .../openvino/core/dimension_tracker.hpp       |  4 +-
 src/core/dev_api/shape_util.hpp               |  5 +-
 src/core/reference/src/op/if.cpp              |  1 -
 src/core/reference/src/op/loop.cpp            |  1 -
 .../reference/src/op/non_max_suppression.cpp  |  2 -
 src/core/reference/src/op/tensor_iterator.cpp |  1 -
 src/core/src/node.cpp                         |  1 -
 src/core/src/runtime/itensor.cpp              |  5 +-
 src/plugins/template/backend/ops/assign.cpp   |  1 -
 src/plugins/template/backend/ops/if.cpp       | 51 +++++++++----------
 .../template/backend/ops/interpolate.cpp      |  4 +-
 .../template/backend/ops/read_value.cpp       |  1 -
 .../template/backend/ops/roi_align.cpp        |  2 +-
 .../template/backend/ops/tensor_iterator.cpp  | 16 +++---
 src/plugins/template/src/plugin.cpp           |  6 +--
 .../behavior/ov_plugin/remote.cpp             |  4 +-
 .../single_layer_tests/convolution.cpp        | 11 ++--
 .../single_layer_tests/eltwise.cpp            | 44 ++++++++--------
 .../single_layer_tests/softmax.cpp            | 27 +++++-----
 .../base_reference_cnn_test.cpp               |  1 -
 .../subgraph_reference/preprocess.cpp         | 10 ++--
 .../subgraph_reference/preprocess_legacy.cpp  | 10 ++--
 23 files changed, 101 insertions(+), 112 deletions(-)

diff --git a/src/core/CMakeLists.txt b/src/core/CMakeLists.txt
index c12a30d5a6f639..869b9a02c49272 100644
--- a/src/core/CMakeLists.txt
+++ b/src/core/CMakeLists.txt
@@ -12,7 +12,8 @@ set(OV_CORE_DEV_API_PATH ${CMAKE_CURRENT_SOURCE_DIR}/dev_api)
 
 file(GLOB_RECURSE LIBRARY_SRC ${CMAKE_CURRENT_SOURCE_DIR}/src/*.cpp
                               ${CMAKE_CURRENT_SOURCE_DIR}/src/*.hpp)
-file(GLOB_RECURSE PUBLIC_HEADERS ${CMAKE_CURRENT_SOURCE_DIR}/include/*.hpp)
+file(GLOB_RECURSE PUBLIC_HEADERS ${OV_CORE_INCLUDE_PATH}/*.hpp)
+file(GLOB_RECURSE DEV_HEADERS ${OV_CORE_DEV_API_PATH}/*.hpp)
 
 add_subdirectory(builder)
 add_subdirectory(reference)
@@ -94,7 +95,7 @@ ov_abi_free_target(ngraph_obj)
 ov_ncc_naming_style(FOR_TARGET ngraph_obj
                     SOURCE_DIRECTORIES "${CMAKE_CURRENT_SOURCE_DIR}/include")
 
-ov_add_clang_format_target(ngraph_clang FOR_TARGETS ngraph_obj)
+ov_add_clang_format_target(ngraph_clang FOR_SOURCES ${LIBRARY_SRC} ${PUBLIC_HEADERS} ${DEV_HEADERS})
 
 if(NOT BUILD_SHARED_LIBS)
     target_compile_definitions(ngraph_obj PUBLIC OPENVINO_STATIC_LIBRARY)
diff --git a/src/core/dev_api/openvino/core/dimension_tracker.hpp b/src/core/dev_api/openvino/core/dimension_tracker.hpp
index 51f85727e2380c..198454cb28c496 100644
--- a/src/core/dev_api/openvino/core/dimension_tracker.hpp
+++ b/src/core/dev_api/openvino/core/dimension_tracker.hpp
@@ -34,6 +34,7 @@ class OPENVINO_API DimensionTracker {
     void set_up_for_tracking(ov::Dimension& d);
     void set_up_for_tracking(ov::Dimension& d, label_t label) const;
     static void reset_tracking_info(ov::Dimension& d);
+
 private:
     std::shared_ptr<TableOfEquivalence> m_table_of_equivalence;
 };
@@ -44,13 +45,14 @@ using ValTable = std::unordered_map<label_t, ov::Dimension>;
 
 class OPENVINO_API TableOfEquivalence {
 public:
-    explicit TableOfEquivalence(label_t label = 1) : current_label(label) {};
+    explicit TableOfEquivalence(label_t label = 1) : current_label(label){};
     void set_as_equal(const ov::Dimension& lhs, const ov::Dimension& rhs);
     bool are_equal(const ov::Dimension& lhs, const ov::Dimension& rhs);
 
     const EqTable& get_equivalence_table() const;
     const ValTable& get_value_equivalence_table() const;
     label_t get_next_label();
+
 private:
     label_t current_label;
     EqTable dimension_table_of_equivalence;
diff --git a/src/core/dev_api/shape_util.hpp b/src/core/dev_api/shape_util.hpp
index fb935ed51275d9..10acfcbc80f2fe 100644
--- a/src/core/dev_api/shape_util.hpp
+++ b/src/core/dev_api/shape_util.hpp
@@ -5,6 +5,7 @@
 #pragma once
 
 #include "openvino/core/shape.hpp"
+#include "openvino/op/util/attr_types.hpp"
 
 namespace ov {
 namespace util {
@@ -50,7 +51,7 @@ OPENVINO_API Shape reduce(const Shape& input, const AxisSet& axes);
 OPENVINO_API Shape reduce(const Shape& input, const AxisSet& axes, const bool keep_dims);
 
 /**
-  * @brief Creates reduced vector from input by removing elements.
+ * @brief Creates reduced vector from input by removing elements.
  *
  * @param input  Input vector for reduce calculation.
  * @param axes   Reduction axes.
@@ -76,6 +77,6 @@ OPENVINO_API Shape reduce_keep_dims(const Shape& input, const AxisSet& axes);
  *
  * @return Result shape from inputs with applied broadcast specification.
  */
-Shape get_broadcast_shape(const Shape& first, const Shape& second, const op::AutoBroadcastSpec& broadcast_spec);
+Shape get_broadcast_shape(const Shape& first, const Shape& second, const ov::op::AutoBroadcastSpec& broadcast_spec);
 }  // namespace util
 }  // namespace ov
diff --git a/src/core/reference/src/op/if.cpp b/src/core/reference/src/op/if.cpp
index 25a04a7057f106..4bffb99470e32d 100644
--- a/src/core/reference/src/op/if.cpp
+++ b/src/core/reference/src/op/if.cpp
@@ -35,7 +35,6 @@ void if_reference(const std::vector<std::shared_ptr<Model>>& bodies,
                      "Incorrect associating! If has not output with id ",
                      out_descr->m_output_index);
         auto res = outs_from_body[out_descr->m_body_value_index];
-        out[out_descr->m_output_index].set_shape(res.get_shape());
         res.copy_to(out[out_descr->m_output_index]);
     }
 }
diff --git a/src/core/reference/src/op/loop.cpp b/src/core/reference/src/op/loop.cpp
index 0582f18f438e59..39ad2c2d4f229f 100644
--- a/src/core/reference/src/op/loop.cpp
+++ b/src/core/reference/src/op/loop.cpp
@@ -196,7 +196,6 @@ void loop(const std::shared_ptr<Model>& func,
         for (const auto& desc : out_descs) {
             if (const auto& body_desc = std::dynamic_pointer_cast<op::v5::Loop::BodyOutputDescription>(desc)) {
                 const auto& res = body_outputs[body_desc->m_body_value_index];
-                out[body_desc->m_output_index].set_shape(res.get_shape());
                 res.copy_to(out[body_desc->m_output_index]);
             }
         }
diff --git a/src/core/reference/src/op/non_max_suppression.cpp b/src/core/reference/src/op/non_max_suppression.cpp
index 1dc7373bc17654..51609fd8059377 100644
--- a/src/core/reference/src/op/non_max_suppression.cpp
+++ b/src/core/reference/src/op/non_max_suppression.cpp
@@ -372,13 +372,11 @@ void nms_postprocessing(ov::TensorVector& outputs,
                         const std::vector<float>& selected_scores,
                         int64_t valid_outputs,
                         const ov::element::Type selected_scores_type) {
-    // outputs[0].set_element_type(output_type);
     outputs[0].set_shape(Shape{static_cast<size_t>(valid_outputs), 3});
 
     size_t num_of_outputs = outputs.size();
 
     if (num_of_outputs >= 2) {
-        // outputs[1].set_element_type(selected_scores_type);
         outputs[1].set_shape(Shape{static_cast<size_t>(valid_outputs), 3});
     }
 
diff --git a/src/core/reference/src/op/tensor_iterator.cpp b/src/core/reference/src/op/tensor_iterator.cpp
index 6ac83923f5b9a8..d0466d7cef1044 100644
--- a/src/core/reference/src/op/tensor_iterator.cpp
+++ b/src/core/reference/src/op/tensor_iterator.cpp
@@ -109,7 +109,6 @@ void tensor_iterator(uint64_t num_iterations,
         if (const auto& body_desc = std::dynamic_pointer_cast<op::v0::TensorIterator::BodyOutputDescription>(desc)) {
             // Copy output values from the last iteration
             const auto& res = body_outputs[body_desc->m_body_value_index];
-            out[body_desc->m_output_index].set_shape(res.get_shape());
             res.copy_to(out[body_desc->m_output_index]);
         }
     }
diff --git a/src/core/src/node.cpp b/src/core/src/node.cpp
index 1cce81d2f9fb7d..7f20ce4b991b6c 100644
--- a/src/core/src/node.cpp
+++ b/src/core/src/node.cpp
@@ -742,7 +742,6 @@ inline void update_output_tensors(ov::TensorVector& output_values, const ngraph:
             }
             if (output_values[i]) {
                 // Copy value to the original tensor
-                output_values[i].set_shape(tensor.get_shape());
                 tensor.copy_to(output_values[i]);
             } else {
                 // Tensor is not initialized, so create the new tensor
diff --git a/src/core/src/runtime/itensor.cpp b/src/core/src/runtime/itensor.cpp
index 9cde89a8cc1091..9149e3cb5c9bf2 100644
--- a/src/core/src/runtime/itensor.cpp
+++ b/src/core/src/runtime/itensor.cpp
@@ -10,6 +10,7 @@
 #include "openvino/runtime/allocator.hpp"
 #include "openvino/runtime/iremote_tensor.hpp"
 #include "openvino/runtime/properties.hpp"
+#include "shape_util.hpp"
 
 namespace ov {
 
@@ -63,8 +64,10 @@ void ITensor::copy_to(const std::shared_ptr<ov::ITensor>& dst) const {
                     " != dst: ",
                     dst->get_element_type(),
                     ")");
-    if (dst->get_shape() == ov::Shape{0})
+    OPENVINO_SUPPRESS_DEPRECATED_START
+    if (dst->get_shape() == ov::Shape{0} || ov::util::is_dynamic_shape(dst->get_shape()))
         dst->set_shape(get_shape());
+    OPENVINO_SUPPRESS_DEPRECATED_END
     OPENVINO_ASSERT(shapes_equal(get_shape(), dst->get_shape()),
                     "Tensor shapes are not equal. (src: ",
                     get_shape(),
diff --git a/src/plugins/template/backend/ops/assign.cpp b/src/plugins/template/backend/ops/assign.cpp
index 3f4b5f108d5662..b614afd862b395 100644
--- a/src/plugins/template/backend/ops/assign.cpp
+++ b/src/plugins/template/backend/ops/assign.cpp
@@ -7,7 +7,6 @@
 bool evaluate(const std::shared_ptr<ov::op::v3::Assign>& op,
               ov::TensorVector& outputs,
               const ov::TensorVector& inputs) {
-    outputs[0].set_shape(inputs[0].get_shape());
     inputs[0].copy_to(outputs[0]);
     return true;
 }
diff --git a/src/plugins/template/backend/ops/if.cpp b/src/plugins/template/backend/ops/if.cpp
index 8795d0bfa789b6..6a64bcd1da1eac 100644
--- a/src/plugins/template/backend/ops/if.cpp
+++ b/src/plugins/template/backend/ops/if.cpp
@@ -74,14 +74,14 @@ void function(const std::shared_ptr<ov::Model>& function, const ov::TensorVector
     const auto& parameters = function->get_parameters();
     const auto& parametersNumber = parameters.size();
     const auto& inputsNumber = inputs.size();
-    NGRAPH_CHECK(parametersNumber == inputsNumber,
-                 "Got function (",
-                 function->get_friendly_name(),
-                 ") with ",
-                 parametersNumber,
-                 " parameters, but ",
-                 inputsNumber,
-                 " input blobs");
+    OPENVINO_ASSERT(parametersNumber == inputsNumber,
+                    "Got function (",
+                    function->get_friendly_name(),
+                    ") with ",
+                    parametersNumber,
+                    " parameters, but ",
+                    inputsNumber,
+                    " input blobs");
 
     for (const auto& parameter : parameters) {
         const auto& parameterIndex = function->get_parameter_index(parameter);
@@ -91,16 +91,16 @@ void function(const std::shared_ptr<ov::Model>& function, const ov::TensorVector
 
         const auto& input = inputs[parameterIndex];
         const auto& inputSize = input.get_byte_size();
-        NGRAPH_CHECK(parameterSize == inputSize,
-                     "Got parameter (",
-                     parameter->get_friendly_name(),
-                     ") of size ",
-                     parameterSize,
-                     " bytes, but corresponding input with index ",
-                     parameterIndex,
-                     " has ",
-                     inputSize,
-                     " bytes");
+        OPENVINO_ASSERT(parameterSize == inputSize,
+                        "Got parameter (",
+                        parameter->get_friendly_name(),
+                        ") of size ",
+                        parameterSize,
+                        " bytes, but corresponding input with index ",
+                        parameterIndex,
+                        " has ",
+                        inputSize,
+                        " bytes");
     }
 
     const auto& results = function->get_results();
@@ -120,7 +120,7 @@ void if_reference(const std::vector<std::shared_ptr<ov::Model>>& bodies,
                   const std::vector<ov::op::util::MultiSubGraphOp::MultiSubgraphInputDescriptionVector>& input_descs,
                   ov::TensorVector& out,
                   const ov::TensorVector& args) {
-    NGRAPH_CHECK(args.size() > 0, "If operation must have input condition value");
+    OPENVINO_ASSERT(args.size() > 0, "If operation must have input condition value");
 
     auto condition_value = args[0].data<bool>()[0];
     auto branch_index = (condition_value) ? ov::op::v8::If::THEN_BODY_INDEX : ov::op::v8::If::ELSE_BODY_INDEX;
@@ -130,18 +130,17 @@ void if_reference(const std::vector<std::shared_ptr<ov::Model>>& bodies,
     auto inputs_size = args.size();
     auto output_size = out.size();
     for (const auto& input_desc : input_descs[branch_index]) {
-        NGRAPH_CHECK(inputs_size > input_desc->m_input_index,
-                     "Incorrect associating! If has not input with id ",
-                     input_desc->m_input_index);
+        OPENVINO_ASSERT(inputs_size > input_desc->m_input_index,
+                        "Incorrect associating! If has not input with id ",
+                        input_desc->m_input_index);
         inputs_to_body[input_desc->m_body_parameter_index] = args[input_desc->m_input_index];
     }
     function(bodies[branch_index], inputs_to_body, outs_from_body);
     for (const auto& out_descr : out_descs[branch_index]) {
-        NGRAPH_CHECK(output_size > out_descr->m_output_index,
-                     "Incorrect associating! If has not output with id ",
-                     out_descr->m_output_index);
+        OPENVINO_ASSERT(output_size > out_descr->m_output_index,
+                        "Incorrect associating! If has not output with id ",
+                        out_descr->m_output_index);
         auto res = outs_from_body[out_descr->m_body_value_index];
-        out[out_descr->m_output_index].set_shape(res.get_shape());
 
         res.copy_to(out[out_descr->m_output_index]);
     }
diff --git a/src/plugins/template/backend/ops/interpolate.cpp b/src/plugins/template/backend/ops/interpolate.cpp
index 16d3a425f5b486..1d1cc4caced291 100644
--- a/src/plugins/template/backend/ops/interpolate.cpp
+++ b/src/plugins/template/backend/ops/interpolate.cpp
@@ -176,7 +176,7 @@ static void pad_input_data(const uint8_t* data_ptr,
                            const ov::Shape& input_shape,
                            const ov::Shape& padded_input_shape,
                            const std::vector<size_t>& pads_begin) {
-    NGRAPH_SUPPRESS_DEPRECATED_START
+    OPENVINO_SUPPRESS_DEPRECATED_START
     ov::CoordinateTransform input_transform(input_shape);
     ov::CoordinateTransform padded_transform(padded_input_shape);
 
@@ -191,7 +191,7 @@ static void pad_input_data(const uint8_t* data_ptr,
         const uint8_t* src_ptr = data_ptr + type_size * input_transform.index(input_coord);
         memcpy(dst_ptr, src_ptr, type_size);
     }
-    NGRAPH_SUPPRESS_DEPRECATED_END
+    OPENVINO_SUPPRESS_DEPRECATED_END
 }
 
 namespace v11 {
diff --git a/src/plugins/template/backend/ops/read_value.cpp b/src/plugins/template/backend/ops/read_value.cpp
index 39d06f29c9ba80..0ab29885702e45 100644
--- a/src/plugins/template/backend/ops/read_value.cpp
+++ b/src/plugins/template/backend/ops/read_value.cpp
@@ -7,7 +7,6 @@
 bool evaluate(const std::shared_ptr<ov::op::v3::ReadValue>& op,
               ov::TensorVector& outputs,
               const ov::TensorVector& inputs) {
-    outputs[0].set_shape(inputs[0].get_shape());
     inputs[0].copy_to(outputs[0]);
     return true;
 }
diff --git a/src/plugins/template/backend/ops/roi_align.cpp b/src/plugins/template/backend/ops/roi_align.cpp
index 119c801cfe9fb8..cbbc00a9319c50 100644
--- a/src/plugins/template/backend/ops/roi_align.cpp
+++ b/src/plugins/template/backend/ops/roi_align.cpp
@@ -24,7 +24,7 @@ bool evaluate(const std::shared_ptr<ov::op::v9::ROIAlign>& op,
         break;
     }
     default: {
-        NGRAPH_CHECK(false, "unsupported PoolingMode ");
+        OPENVINO_THROW("unsupported PoolingMode ");
     }
     }
     ov::reference::roi_align<T>(inputs[0].data<const T>(),
diff --git a/src/plugins/template/backend/ops/tensor_iterator.cpp b/src/plugins/template/backend/ops/tensor_iterator.cpp
index 8b3fbd62874b27..d7398b5126fcb8 100644
--- a/src/plugins/template/backend/ops/tensor_iterator.cpp
+++ b/src/plugins/template/backend/ops/tensor_iterator.cpp
@@ -14,14 +14,14 @@ ov::reference::custom_evaluate_function evaluate =
     const auto& parameters = function->get_parameters();
     const auto& parametersNumber = parameters.size();
     const auto& inputsNumber = inputs.size();
-    NGRAPH_CHECK(parametersNumber == inputsNumber,
-                 "Got function (",
-                 function->get_friendly_name(),
-                 ") with ",
-                 parametersNumber,
-                 " parameters, but ",
-                 inputsNumber,
-                 " input blobs");
+    OPENVINO_ASSERT(parametersNumber == inputsNumber,
+                    "Got function (",
+                    function->get_friendly_name(),
+                    ") with ",
+                    parametersNumber,
+                    " parameters, but ",
+                    inputsNumber,
+                    " input blobs");
 
     const auto& results = function->get_results();
     outputs.reserve(results.size());
diff --git a/src/plugins/template/src/plugin.cpp b/src/plugins/template/src/plugin.cpp
index e1f3f114715222..b1166c4cea12d7 100644
--- a/src/plugins/template/src/plugin.cpp
+++ b/src/plugins/template/src/plugin.cpp
@@ -29,7 +29,7 @@ ov::template_plugin::Plugin::Plugin() {
     // TODO: fill with actual device name, backend engine
     set_device_name("TEMPLATE");
 
-    // create ngraph backend which performs inference using ngraph reference implementations
+    // create backend which performs inference using openvino reference implementations
     m_backend = ov::runtime::Backend::create();
 
     // create default stream executor with a given name
@@ -177,9 +177,9 @@ ov::SupportedOpsMap ov::template_plugin::Plugin::query_model(const std::shared_p
             // 1. It is needed to apply all transformations as it is done in compile_model
             transform_model(model);
         },
-        [&](std::shared_ptr<ngraph::Node> node) {
+        [&](std::shared_ptr<ov::Node> node) {
             // 2. Сheck whether node is supported
-            ngraph::OpSet op_super_set;
+            ov::OpSet op_super_set;
 #define _OPENVINO_OP_REG(NAME, NAMESPACE) op_super_set.insert<NAMESPACE::NAME>();
         // clang-format off
 #include "openvino/opsets/opset1_tbl.hpp"
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/remote.cpp b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/remote.cpp
index a434775dd4b33c..af2f01a5fd3404 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/remote.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/behavior/ov_plugin/remote.cpp
@@ -20,8 +20,8 @@ std::vector<std::pair<ov::AnyMap, ov::AnyMap>> generate_remote_params() {
 
 INSTANTIATE_TEST_SUITE_P(smoke_BehaviorTests,
                          OVRemoteTest,
-                         ::testing::Combine(::testing::Values(ngraph::element::f32),
-                                            ::testing::Values(::ov::test::utils::DEVICE_TEMPLATE),
+                         ::testing::Combine(::testing::Values(ov::element::f32),
+                                            ::testing::Values(ov::test::utils::DEVICE_TEMPLATE),
                                             ::testing::ValuesIn(template_config()),
                                             ::testing::ValuesIn(generate_remote_params())),
                          OVRemoteTest::getTestCaseName);
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp
index 9aff6a6bcdfb32..f1d1b2c31e2ec5 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/convolution.cpp
@@ -26,7 +26,7 @@ const std::vector<std::vector<ptrdiff_t>> padBegins = {{0, 0}, {0, 3}};
 const std::vector<std::vector<ptrdiff_t>> padEnds = {{0, 0}, {0, 3}};
 const std::vector<std::vector<size_t>> dilations = {{1, 1}, {3, 1}};
 const std::vector<size_t> numOutChannels = {1, 5};
-const std::vector<ngraph::op::PadType> padTypes = {ngraph::op::PadType::EXPLICIT, ngraph::op::PadType::VALID};
+const std::vector<ov::op::PadType> padTypes = {ov::op::PadType::EXPLICIT, ov::op::PadType::VALID};
 
 const auto conv2DParams_ExplicitPadding = ::testing::Combine(::testing::ValuesIn(kernels),
                                                              ::testing::ValuesIn(strides),
@@ -34,7 +34,7 @@ const auto conv2DParams_ExplicitPadding = ::testing::Combine(::testing::ValuesIn
                                                              ::testing::ValuesIn(padEnds),
                                                              ::testing::ValuesIn(dilations),
                                                              ::testing::ValuesIn(numOutChannels),
-                                                             ::testing::Values(ngraph::op::PadType::EXPLICIT));
+                                                             ::testing::Values(ov::op::PadType::EXPLICIT));
 // ! [test_convolution:declare_parameters]
 
 const auto conv2DParams_AutoPadValid = ::testing::Combine(::testing::ValuesIn(kernels),
@@ -43,7 +43,7 @@ const auto conv2DParams_AutoPadValid = ::testing::Combine(::testing::ValuesIn(ke
                                                           ::testing::Values(std::vector<ptrdiff_t>({0, 0})),
                                                           ::testing::ValuesIn(dilations),
                                                           ::testing::ValuesIn(numOutChannels),
-                                                          ::testing::Values(ngraph::op::PadType::VALID));
+                                                          ::testing::Values(ov::op::PadType::VALID));
 
 // ! [test_convolution:instantiate]
 INSTANTIATE_TEST_SUITE_P(Convolution2D_ExplicitPadding,
@@ -85,14 +85,15 @@ const auto conv3DParams_ExplicitPadding = ::testing::Combine(::testing::ValuesIn
                                                              ::testing::ValuesIn(paddings3d),
                                                              ::testing::ValuesIn(dilations3d),
                                                              ::testing::Values(5),
-                                                             ::testing::Values(ngraph::op::PadType::EXPLICIT));
+                                                             ::testing::Values(ov::op::PadType::EXPLICIT));
+
 const auto conv3DParams_AutoPadValid = ::testing::Combine(::testing::ValuesIn(kernels3d),
                                                           ::testing::ValuesIn(strides3d),
                                                           ::testing::Values(std::vector<ptrdiff_t>({0, 0, 0})),
                                                           ::testing::Values(std::vector<ptrdiff_t>({0, 0, 0})),
                                                           ::testing::ValuesIn(dilations3d),
                                                           ::testing::Values(5),
-                                                          ::testing::Values(ngraph::op::PadType::VALID));
+                                                          ::testing::Values(ov::op::PadType::VALID));
 
 INSTANTIATE_TEST_SUITE_P(smoke_Convolution3D_ExplicitPadding,
                          ConvolutionLayerTest,
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/eltwise.cpp b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/eltwise.cpp
index 1c2bfa338e78ed..8d034694905bd8 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/eltwise.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/eltwise.cpp
@@ -28,7 +28,7 @@ std::vector<std::vector<ov::Shape>> inShapesStatic = {
 };
 
 std::vector<std::vector<ov::test::InputShape>> inShapesDynamic = {
-    {{{ngraph::Dimension(1, 10), 200}, {{2, 200}, {1, 200}}}, {{ngraph::Dimension(1, 10), 200}, {{2, 200}, {5, 200}}}},
+    {{{ov::Dimension(1, 10), 200}, {{2, 200}, {1, 200}}}, {{ov::Dimension(1, 10), 200}, {{2, 200}, {5, 200}}}},
 };
 
 std::vector<ov::test::ElementType> netPrecisions = {
@@ -37,13 +37,13 @@ std::vector<ov::test::ElementType> netPrecisions = {
     ov::element::i32,
 };
 
-std::vector<ngraph::helpers::InputLayerType> secondaryInputTypes = {
-    ngraph::helpers::InputLayerType::CONSTANT,
-    ngraph::helpers::InputLayerType::PARAMETER,
+std::vector<ov::test::utils::InputLayerType> secondaryInputTypes = {
+    ov::test::utils::InputLayerType::CONSTANT,
+    ov::test::utils::InputLayerType::PARAMETER,
 };
 
-std::vector<ngraph::helpers::InputLayerType> secondaryInputTypesDynamic = {
-    ngraph::helpers::InputLayerType::PARAMETER,
+std::vector<ov::test::utils::InputLayerType> secondaryInputTypesDynamic = {
+    ov::test::utils::InputLayerType::PARAMETER,
 };
 
 std::vector<ov::test::utils::OpType> opTypes = {
@@ -55,19 +55,19 @@ std::vector<ov::test::utils::OpType> opTypesDynamic = {
     ov::test::utils::OpType::VECTOR,
 };
 
-std::vector<ngraph::helpers::EltwiseTypes> eltwiseOpTypes = {ngraph::helpers::EltwiseTypes::ADD,
-                                                             ngraph::helpers::EltwiseTypes::MULTIPLY,
-                                                             ngraph::helpers::EltwiseTypes::SUBTRACT,
-                                                             ngraph::helpers::EltwiseTypes::DIVIDE,
-                                                             ngraph::helpers::EltwiseTypes::FLOOR_MOD,
-                                                             ngraph::helpers::EltwiseTypes::SQUARED_DIFF,
-                                                             ngraph::helpers::EltwiseTypes::POWER,
-                                                             ngraph::helpers::EltwiseTypes::MOD};
-
-std::vector<ngraph::helpers::EltwiseTypes> eltwiseOpTypesDynamic = {
-    ngraph::helpers::EltwiseTypes::ADD,
-    ngraph::helpers::EltwiseTypes::MULTIPLY,
-    ngraph::helpers::EltwiseTypes::SUBTRACT,
+std::vector<ov::test::utils::EltwiseTypes> eltwiseOpTypes = {ov::test::utils::EltwiseTypes::ADD,
+                                                             ov::test::utils::EltwiseTypes::MULTIPLY,
+                                                             ov::test::utils::EltwiseTypes::SUBTRACT,
+                                                             ov::test::utils::EltwiseTypes::DIVIDE,
+                                                             ov::test::utils::EltwiseTypes::FLOOR_MOD,
+                                                             ov::test::utils::EltwiseTypes::SQUARED_DIFF,
+                                                             ov::test::utils::EltwiseTypes::POWER,
+                                                             ov::test::utils::EltwiseTypes::MOD};
+
+std::vector<ov::test::utils::EltwiseTypes> eltwiseOpTypesDynamic = {
+    ov::test::utils::EltwiseTypes::ADD,
+    ov::test::utils::EltwiseTypes::MULTIPLY,
+    ov::test::utils::EltwiseTypes::SUBTRACT,
 };
 
 ov::test::Config additional_config = {};
@@ -108,9 +108,9 @@ std::vector<std::vector<ov::Shape>> inShapesSingleThread = {
     {{2, 1, 2, 1, 2, 2}},
 };
 
-std::vector<ngraph::helpers::EltwiseTypes> eltwiseOpTypesSingleThread = {
-    ngraph::helpers::EltwiseTypes::ADD,
-    ngraph::helpers::EltwiseTypes::POWER,
+std::vector<ov::test::utils::EltwiseTypes> eltwiseOpTypesSingleThread = {
+    ov::test::utils::EltwiseTypes::ADD,
+    ov::test::utils::EltwiseTypes::POWER,
 };
 
 ov::AnyMap additional_config_single_thread = {{"CPU_THREADS_NUM", "1"}};
diff --git a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/softmax.cpp b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/softmax.cpp
index 83c03b7a881e3b..6b268c7f59cf04 100644
--- a/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/softmax.cpp
+++ b/src/plugins/template/tests/functional/shared_tests_instances/single_layer_tests/softmax.cpp
@@ -24,10 +24,10 @@ const std::vector<ov::Shape> inputStaticShape2D = {
 };
 
 const std::vector<ov::test::InputShape> inputDynamicShape2D = {
-    {{ngraph::Dimension::dynamic(), 10}, {{1, 10}, {2, 10}, {10, 10}}},
-    {{ngraph::Dimension(1, 10), 10}, {{1, 10}, {2, 10}, {10, 10}}},
-    {{10, ngraph::Dimension::dynamic()}, {{10, 1}, {10, 5}, {10, 10}}},
-    {{ngraph::Dimension::dynamic(), ngraph::Dimension::dynamic()}, {{1, 10}, {2, 10}, {10, 10}}}};
+    {{ov::Dimension::dynamic(), 10}, {{1, 10}, {2, 10}, {10, 10}}},
+    {{ov::Dimension(1, 10), 10}, {{1, 10}, {2, 10}, {10, 10}}},
+    {{10, ov::Dimension::dynamic()}, {{10, 1}, {10, 5}, {10, 10}}},
+    {{ov::Dimension::dynamic(), ov::Dimension::dynamic()}, {{1, 10}, {2, 10}, {10, 10}}}};
 
 const std::vector<int64_t> axis2D = {-2, -1, 0, 1};
 
@@ -65,11 +65,8 @@ const std::vector<ov::Shape> inputStaticShape4D = {
 };
 
 const std::vector<ov::test::InputShape> inputDynamicShape4D = {
-    {{ngraph::Dimension::dynamic(), 100, ngraph::Dimension(1, 10), 1}, {{1, 100, 1, 1}, {100, 100, 5, 1}}},
-    {{ngraph::Dimension::dynamic(),
-      ngraph::Dimension::dynamic(),
-      ngraph::Dimension::dynamic(),
-      ngraph::Dimension::dynamic()},
+    {{ov::Dimension::dynamic(), 100, ov::Dimension(1, 10), 1}, {{1, 100, 1, 1}, {100, 100, 5, 1}}},
+    {{ov::Dimension::dynamic(), ov::Dimension::dynamic(), ov::Dimension::dynamic(), ov::Dimension::dynamic()},
      {{1, 100, 1, 1}, {50, 100, 4, 1}, {2, 100, 10, 1}}},
 };
 
@@ -110,12 +107,12 @@ const std::vector<ov::Shape> inputStaticShape5D = {
 };
 
 const std::vector<ov::test::InputShape> inputDynamicShape5D = {
-    {{ngraph::Dimension::dynamic(), 100, ngraph::Dimension(1, 10), 1, 1}, {{1, 100, 1, 1, 1}, {100, 100, 5, 1, 1}}},
-    {{ngraph::Dimension::dynamic(),
-      ngraph::Dimension::dynamic(),
-      ngraph::Dimension::dynamic(),
-      ngraph::Dimension::dynamic(),
-      ngraph::Dimension::dynamic()},
+    {{ov::Dimension::dynamic(), 100, ov::Dimension(1, 10), 1, 1}, {{1, 100, 1, 1, 1}, {100, 100, 5, 1, 1}}},
+    {{ov::Dimension::dynamic(),
+      ov::Dimension::dynamic(),
+      ov::Dimension::dynamic(),
+      ov::Dimension::dynamic(),
+      ov::Dimension::dynamic()},
      {{1, 100, 1, 1, 1}, {50, 100, 4, 1, 1}, {2, 100, 10, 1, 1}}},
 };
 
diff --git a/src/plugins/template/tests/functional/subgraph_reference/base_reference_cnn_test.cpp b/src/plugins/template/tests/functional/subgraph_reference/base_reference_cnn_test.cpp
index 3086055af575ad..abdf47a4b8c3b0 100644
--- a/src/plugins/template/tests/functional/subgraph_reference/base_reference_cnn_test.cpp
+++ b/src/plugins/template/tests/functional/subgraph_reference/base_reference_cnn_test.cpp
@@ -6,7 +6,6 @@
 #include <gtest/gtest.h>
 
 #include "functional_test_utils/ov_plugin_cache.hpp"
-#include "ie_ngraph_utils.hpp"
 #include "openvino/core/type/element_type.hpp"
 #include "openvino/runtime/allocator.hpp"
 #include "openvino/runtime/tensor.hpp"
diff --git a/src/plugins/template/tests/functional/subgraph_reference/preprocess.cpp b/src/plugins/template/tests/functional/subgraph_reference/preprocess.cpp
index ea5c3465dbb31b..b4c35bb936a43f 100644
--- a/src/plugins/template/tests/functional/subgraph_reference/preprocess.cpp
+++ b/src/plugins/template/tests/functional/subgraph_reference/preprocess.cpp
@@ -4,15 +4,11 @@
 
 #include <gtest/gtest.h>
 
-#include <ie_core.hpp>
-#include <ie_ngraph_utils.hpp>
-#include <ngraph/ngraph.hpp>
-#include <openvino/core/preprocess/pre_post_process.hpp>
-#include <shared_test_classes/base/layer_test_utils.hpp>
 #include <vector>
 
-#include "../op_reference/base_reference_test.hpp"
-#include "ngraph_functions/builders.hpp"
+#include "base_reference_test.hpp"
+#include "openvino/core/preprocess/pre_post_process.hpp"
+#include "shared_test_classes/base/layer_test_utils.hpp"
 
 using namespace ov;
 using namespace ov::preprocess;
diff --git a/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp b/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
index a8ba3ea35534ea..e691495452d01c 100644
--- a/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
+++ b/src/plugins/template/tests/functional/subgraph_reference/preprocess_legacy.cpp
@@ -4,15 +4,13 @@
 
 #include <gtest/gtest.h>
 
-#include <ie_ngraph_utils.hpp>
-#include <openvino/core/preprocess/pre_post_process.hpp>
-#include <shared_test_classes/base/layer_test_utils.hpp>
-#include <shared_test_classes/single_layer/convert_color_i420.hpp>
-#include <shared_test_classes/single_layer/convert_color_nv12.hpp>
 #include <vector>
 
 #include "base_reference_cnn_test.hpp"
-#include "ngraph_functions/builders.hpp"
+#include "openvino/core/preprocess/pre_post_process.hpp"
+#include "shared_test_classes/base/layer_test_utils.hpp"
+#include "shared_test_classes/single_layer/convert_color_i420.hpp"
+#include "shared_test_classes/single_layer/convert_color_nv12.hpp"
 
 using namespace ov;
 using namespace ov::preprocess;

From 394e58fafb57e5aab964c4d7a2845ac5e0060fb3 Mon Sep 17 00:00:00 2001
From: Andrew Kwangwoong Park <andrew.park@intel.com>
Date: Wed, 20 Sep 2023 08:57:10 +0900
Subject: [PATCH 35/46] [GPU] Fix canonicalization for fused dep's shape
 (#19667)

* [GPU] Fix canonicalization for fused dep's shape

Signed-off-by: Andrew Park <andrew.park@intel.com>

* Update TC to reproducible on the latest master

Signed-off-by: Andrew Park <andrew.park@intel.com>

* Fix custom canonicalize shapes for Gather

---------

Signed-off-by: Andrew Park <andrew.park@intel.com>
---
 .../intel_gpu/src/graph/impls/ocl/gather.cpp  |  7 +++-
 .../test_cases/canonicalization_gpu_test.cpp  | 39 +++++++++++++++++++
 2 files changed, 45 insertions(+), 1 deletion(-)

diff --git a/src/plugins/intel_gpu/src/graph/impls/ocl/gather.cpp b/src/plugins/intel_gpu/src/graph/impls/ocl/gather.cpp
index 44842bb4aa8457..e16311614201bb 100644
--- a/src/plugins/intel_gpu/src/graph/impls/ocl/gather.cpp
+++ b/src/plugins/intel_gpu/src/graph/impls/ocl/gather.cpp
@@ -116,7 +116,12 @@ struct gather_impl : typed_primitive_impl_ocl<gather> {
             out_layout.format = format::adjust_to_rank(out_layout.format, output_pshape.size());
         }
 
-        return primitive_impl::static_canonicalize_shapes(updated_impl_params);
+        for (auto& input_layout : updated_impl_params.input_layouts) {
+            input_layout.set_partial_shape(extend_shape_to_rank_from_end(input_layout.get_partial_shape()));
+        }
+        out_layout.set_partial_shape(extend_shape_to_rank_from_end(out_layout.get_partial_shape()));
+
+        return updated_impl_params;
     }
 
     kernel_impl_params canonicalize_shapes(const kernel_impl_params& impl_params) const override {
diff --git a/src/plugins/intel_gpu/tests/unit/test_cases/canonicalization_gpu_test.cpp b/src/plugins/intel_gpu/tests/unit/test_cases/canonicalization_gpu_test.cpp
index eba4f33c887c6e..400152887e6ce9 100644
--- a/src/plugins/intel_gpu/tests/unit/test_cases/canonicalization_gpu_test.cpp
+++ b/src/plugins/intel_gpu/tests/unit/test_cases/canonicalization_gpu_test.cpp
@@ -226,6 +226,45 @@ TEST(canonicalization, gather) {
     }
 }
 
+struct fusing_gather_eltwise_params {
+    ov::PartialShape data_shape;
+    ov::Shape out_shape;
+    int64_t axis;
+    int64_t batch_dim;
+    bool support_neg_ind;
+};
+
+std::vector<std::pair<Shapes, fusing_gather_eltwise_params>> fusing_gather_eltwise_shapes_with_params {
+    {
+        {{{}, {}}, {{4624, 4, 1, 1}, {1, 1, 1, 1}, {1, 1, 1, 1}, {4624, 1, 1, 1}}, {{4624, 1, 1, 1}}},
+        {{4624, 4}, {4624}, 1, 0, true}
+    }
+};
+
+TEST(canonicalization, fusing_gather_eltwise) {
+    for (const auto& shapes : fusing_gather_eltwise_shapes_with_params) {
+        layout input_gather_layout = create_default_layout(shapes.second.data_shape);
+        layout indices_layout_first = create_default_layout(std::get<0>(shapes.first)[0]);
+        layout indices_layout_second = create_default_layout(std::get<0>(shapes.first)[0]);
+        layout input_mul_layout = create_default_layout(std::get<0>(shapes.first)[1]);
+
+        topology topology;
+        topology.add(input_layout("input", input_gather_layout));
+        topology.add(input_layout("indices_first", indices_layout_first));
+        topology.add(input_layout("indices_second", indices_layout_second));
+        topology.add(input_layout("data", input_mul_layout));
+        topology.add(gather("gather_first", input_info("input"), input_info("indices_first"), shapes.second.axis,
+                            shapes.second.out_shape, shapes.second.batch_dim, shapes.second.support_neg_ind));
+        topology.add(gather("gather_second", input_info("input"), input_info("indices_second"), shapes.second.axis,
+                            shapes.second.out_shape, shapes.second.batch_dim, shapes.second.support_neg_ind));
+        topology.add(eltwise("mul", {input_info("gather_first"), input_info("data")}, eltwise_mode::prod));
+        topology.add(eltwise("add", {input_info("gather_second"), input_info("mul")}, eltwise_mode::sum));
+        topology.add(reorder("out_reorder", input_info("add"), format::bfyx, data_types::f32));
+
+        canonicalization_test(topology, "gather_first", std::get<1>(shapes.first), std::get<2>(shapes.first), true);
+    }
+}
+
 struct fusing_gemm_eltwise_params {
     ov::PartialShape input_gemm_first;
     ov::PartialShape weights_gemm_first;

From 0f18d2a0eaacdc347a2e058d75489a787c05da84 Mon Sep 17 00:00:00 2001
From: Sofya Balandina <sofya.balandina@intel.com>
Date: Wed, 20 Sep 2023 03:05:01 +0100
Subject: [PATCH 36/46] [template] Add device ro props and fix compile_model
 props test (#19886)

---
 src/plugins/template/src/plugin.cpp                | 11 +++++++++--
 .../behavior/ov_executable_network/get_metric.cpp  |  2 +-
 .../src/behavior/ov_plugin/properties_tests.cpp    | 14 ++++++--------
 3 files changed, 16 insertions(+), 11 deletions(-)

diff --git a/src/plugins/template/src/plugin.cpp b/src/plugins/template/src/plugin.cpp
index b1166c4cea12d7..918bfbfb9b0fe0 100644
--- a/src/plugins/template/src/plugin.cpp
+++ b/src/plugins/template/src/plugin.cpp
@@ -223,7 +223,9 @@ ov::Any ov::template_plugin::Plugin::get_property(const std::string& name, const
                                                     ov::device::full_name,
                                                     ov::device::architecture,
                                                     ov::device::capabilities,
-                                                    ov::range_for_async_infer_requests};
+                                                    ov::device::type,
+                                                    ov::range_for_async_infer_requests,
+                                                    ov::execution_devices};
         return ro_properties;
     };
     const auto& default_rw_properties = []() {
@@ -259,8 +261,10 @@ ov::Any ov::template_plugin::Plugin::get_property(const std::string& name, const
         return decltype(ov::device::full_name)::value_type(device_name);
     } else if (ov::device::architecture == name) {
         // TODO: return device architecture for device specified by DEVICE_ID config
-        std::string arch = "TEMPLATE";
+        std::string arch = get_device_name();
         return decltype(ov::device::architecture)::value_type(arch);
+    } else if (ov::device::type == name) {
+        return decltype(ov::device::type)::value_type(ov::device::Type::INTEGRATED);
     } else if (ov::internal::caching_properties == name) {
         std::vector<ov::PropertyName> caching_properties = {ov::device::architecture};
         return decltype(ov::internal::caching_properties)::value_type(caching_properties);
@@ -268,6 +272,9 @@ ov::Any ov::template_plugin::Plugin::get_property(const std::string& name, const
         // TODO: fill actual list of supported capabilities: e.g. Template device supports only FP32 and EXPORT_IMPORT
         std::vector<std::string> capabilities = {ov::device::capability::FP32, ov::device::capability::EXPORT_IMPORT};
         return decltype(ov::device::capabilities)::value_type(capabilities);
+    } else if (ov::execution_devices == name) {
+        std::string dev = get_device_name();
+        return decltype(ov::execution_devices)::value_type{dev};
     } else if (ov::range_for_async_infer_requests == name) {
         // TODO: fill with actual values
         using uint = unsigned int;
diff --git a/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_executable_network/get_metric.cpp b/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_executable_network/get_metric.cpp
index ea0d0c25ad814c..3448f8d355161f 100644
--- a/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_executable_network/get_metric.cpp
+++ b/src/tests/functional/plugin/conformance/test_runner/api_conformance_runner/src/behavior/ov_executable_network/get_metric.cpp
@@ -15,7 +15,7 @@ using namespace ov::test::conformance;
 //
 
 INSTANTIATE_TEST_SUITE_P(
-        ov_compiled_model, OVClassCompiledModelGetPropertyTest,
+        ov_compiled_model_mandatory, OVClassCompiledModelGetPropertyTest,
         ::testing::ValuesIn(return_all_possible_device_combination()));
 
 //
diff --git a/src/tests/functional/plugin/shared/src/behavior/ov_plugin/properties_tests.cpp b/src/tests/functional/plugin/shared/src/behavior/ov_plugin/properties_tests.cpp
index b5cbff685b6340..349016b3fd0bed 100644
--- a/src/tests/functional/plugin/shared/src/behavior/ov_plugin/properties_tests.cpp
+++ b/src/tests/functional/plugin/shared/src/behavior/ov_plugin/properties_tests.cpp
@@ -208,9 +208,7 @@ TEST_P(OVSetPropComplieModleGetPropTests, SetPropertyAndComplieModelWithPropsWor
 
 std::vector<ov::AnyMap> OVPropertiesTestsWithCompileModelProps::getROMandatoryProperties() {
     std::vector<ov::AnyMap> res;
-    res.push_back({{ov::PropertyName(ov::model_name.name(), ov::model_name.mutability), nullptr}});
-    res.push_back({{ov::PropertyName(ov::device::full_name.name(), ov::model_name.mutability), nullptr}});
-    res.push_back({{ov::PropertyName(ov::optimal_number_of_infer_requests.name(), ov::optimal_number_of_infer_requests.mutability), nullptr}});
+    res.push_back({{ov::PropertyName(ov::device::full_name.name(), ov::device::full_name.mutability), nullptr}});
     res.push_back({{ov::PropertyName(ov::device::architecture.name(), ov::device::architecture.mutability), nullptr}});
     res.push_back({{ov::PropertyName(ov::device::type.name(), ov::device::type.mutability), nullptr}});
     res.push_back({{ov::PropertyName(ov::execution_devices.name(), ov::execution_devices.mutability), nullptr}});
@@ -286,11 +284,6 @@ std::vector<ov::AnyMap> OVPropertiesTestsWithCompileModelProps::getRWMandatoryPr
         }
     }
 
-    if (props.empty() || std::find(props.begin(), props.end(), ov::enable_mmap.name()) != props.end()) {
-        res.push_back({ov::enable_mmap(true)});
-        res.push_back({ov::enable_mmap(false)});
-    }
-
     if (props.empty() || std::find(props.begin(), props.end(), ov::streams::num.name()) != props.end()) {
         res.push_back({ov::streams::num(3)});
     }
@@ -332,6 +325,11 @@ std::vector<ov::AnyMap> OVPropertiesTestsWithCompileModelProps::getRWOptionalPro
         }
     }
 
+    if (props.empty() || std::find(props.begin(), props.end(), ov::enable_mmap.name()) != props.end()) {
+        res.push_back({ov::enable_mmap(true)});
+        res.push_back({ov::enable_mmap(false)});
+    }
+
     return res;
 }
 

From 5d8687ae30e394e89ed950baaa9aff9139635de1 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 20 Sep 2023 10:31:01 +0400
Subject: [PATCH 37/46] Bump SimenB/github-actions-cpu-cores from 1 to 2
 (#19965)

Bumps [SimenB/github-actions-cpu-cores](https://github.com/simenb/github-actions-cpu-cores) from 1 to 2.
- [Release notes](https://github.com/simenb/github-actions-cpu-cores/releases)
- [Commits](https://github.com/simenb/github-actions-cpu-cores/compare/v1...v2)

---
updated-dependencies:
- dependency-name: SimenB/github-actions-cpu-cores
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
---
 .github/workflows/linux_onnxruntime.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/linux_onnxruntime.yml b/.github/workflows/linux_onnxruntime.yml
index 5a96a821e92080..32ab86cb4ddd39 100644
--- a/.github/workflows/linux_onnxruntime.yml
+++ b/.github/workflows/linux_onnxruntime.yml
@@ -96,7 +96,7 @@ jobs:
       #
 
       - name: Get number of CPU cores
-        uses: SimenB/github-actions-cpu-cores@v1
+        uses: SimenB/github-actions-cpu-cores@v2
         id: cpu-cores
 
       - name: CMake configure

From a558ebd4bcfee0972659481ed14ba39dc2e22269 Mon Sep 17 00:00:00 2001
From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com>
Date: Wed, 20 Sep 2023 10:31:34 +0400
Subject: [PATCH 38/46] Bump actions/checkout from 3 to 4 (#19964)

Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to 4.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v3...v4)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
---
 .github/workflows/linux_onnxruntime.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/linux_onnxruntime.yml b/.github/workflows/linux_onnxruntime.yml
index 32ab86cb4ddd39..178aae4fefac6b 100644
--- a/.github/workflows/linux_onnxruntime.yml
+++ b/.github/workflows/linux_onnxruntime.yml
@@ -51,7 +51,7 @@ jobs:
       INSTALL_DIR: ${{ github.workspace }}/install/openvino
     steps:
       - name: Clone OpenVINO
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with:
           path: 'openvino'
           submodules: 'true'

From 7fe195a459cd0285ea66335e1f4d735831bfd88f Mon Sep 17 00:00:00 2001
From: Zhang Yi <yi3.zhang@intel.com>
Date: Wed, 20 Sep 2023 14:35:22 +0800
Subject: [PATCH 39/46] [Doc]Update cmake option for MLAS (#19963)

* [Doc]Update cmake option for MLAS

* Update docs/dev/cmake_options_for_custom_compilation.md

Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>

---------

Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
---
 docs/dev/cmake_options_for_custom_compilation.md | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/docs/dev/cmake_options_for_custom_compilation.md b/docs/dev/cmake_options_for_custom_compilation.md
index 1b4f3b7eb5752b..847997e067d5c3 100644
--- a/docs/dev/cmake_options_for_custom_compilation.md
+++ b/docs/dev/cmake_options_for_custom_compilation.md
@@ -114,6 +114,9 @@ This document provides description and default values for CMake options that can
     * `OFF` is default, because it increases binary size.
 * `SELECTIVE_BUILD` enables [[Conditional compilation|ConditionalCompilation]] feature.
     * `OFF` is default.
+* `ENABLE_MLAS_FOR_CPU` enables MLAS library for CPU plugin
+    * `ON` is default for x86_64 and AARCH64 platforms
+    * Affects only OpenVINO CPU plugin
 
 ## Building with OpenCV
 

From c67c0663fca88e172cac52553a04a768a36b4984 Mon Sep 17 00:00:00 2001
From: Ilya Lavrenov <ilya.lavrenov@intel.com>
Date: Wed, 20 Sep 2023 11:16:15 +0400
Subject: [PATCH 40/46] Use target python packages (#19928)

---
 src/bindings/python/CMakeLists.txt | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/bindings/python/CMakeLists.txt b/src/bindings/python/CMakeLists.txt
index a273184c4b8d1d..b46eaaf9883e16 100644
--- a/src/bindings/python/CMakeLists.txt
+++ b/src/bindings/python/CMakeLists.txt
@@ -33,7 +33,7 @@ function(ov_check_python_build_conditions)
     endif()
 
     # Try to find python3 and its libs
-    find_host_package(PythonInterp 3 ${find_package_mode})
+    find_package(PythonInterp 3 ${find_package_mode})
     if(PYTHONINTERP_FOUND)
         if(PYTHON_VERSION_MINOR GREATER_EQUAL 11)
             set(pybind11_min_version 2.9.2)
@@ -56,14 +56,14 @@ function(ov_check_python_build_conditions)
             if(EXISTS ${pybind11_tools_dir})
                 list(APPEND CMAKE_MODULE_PATH ${pybind11_tools_dir})
             else()
-                find_host_package(pybind11 ${pybind11_min_version} QUIET)
+                find_package(pybind11 ${pybind11_min_version} QUIET)
                 if(pybind11_FOUND)
                     list(APPEND CMAKE_MODULE_PATH "${pybind11_DIR}")
                 endif()
             endif()
             # use libraries with the same version as python itself
             set(PYBIND11_PYTHON_VERSION ${PYTHON_VERSION_STRING})
-            find_host_package(PythonLibsNew ${PYBIND11_PYTHON_VERSION} EXACT ${find_package_mode})
+            find_package(PythonLibsNew ${PYBIND11_PYTHON_VERSION} EXACT ${find_package_mode})
             set(PYTHONLIBSNEW_FOUND ${PYTHONLIBS_FOUND} PARENT_SCOPE)
         endfunction()
         # try to find python libraries
@@ -71,7 +71,7 @@ function(ov_check_python_build_conditions)
         if(PYTHONLIBSNEW_FOUND)
             # clear Python_ADDITIONAL_VERSIONS to find only python library matching PYTHON_EXECUTABLE
             unset(Python_ADDITIONAL_VERSIONS CACHE)
-            find_host_package(PythonLibs ${PYTHON_VERSION_STRING} EXACT ${find_package_mode})
+            find_package(PythonLibs ${PYTHON_VERSION_STRING} EXACT ${find_package_mode})
         endif()
         if(NOT PYTHONLIBS_FOUND)
             message(${message_mode} "Python development libraries are not found. OpenVINO Python API will be turned off (ENABLE_PYTHON is OFF)")

From 2c88fbf798b43a16bceed64430f6d4d0871a2ac5 Mon Sep 17 00:00:00 2001
From: Ekaterina Aidova <ekaterina.aidova@intel.com>
Date: Wed, 20 Sep 2023 11:26:18 +0400
Subject: [PATCH 41/46] [PT FE]: support mixed precision in aten::min/max
 (#19936)

* [PT FE]: support mixed precision in aten::min/max

* fix eltwise dtype alignment for float16
---
 src/frontends/pytorch/src/op/min_max.cpp      |  2 +
 src/frontends/pytorch/src/utils.cpp           |  8 ++--
 .../pytorch_tests/pytorch_layer_test_class.py |  7 ++--
 tests/layer_tests/pytorch_tests/test_add.py   |  6 +++
 tests/layer_tests/pytorch_tests/test_div.py   |  6 +++
 .../layer_tests/pytorch_tests/test_min_max.py | 40 ++++++++++++++-----
 tests/layer_tests/pytorch_tests/test_mul.py   |  6 +++
 7 files changed, 57 insertions(+), 18 deletions(-)

diff --git a/src/frontends/pytorch/src/op/min_max.cpp b/src/frontends/pytorch/src/op/min_max.cpp
index ad5c8224d3e143..c6b63f11e25d9f 100644
--- a/src/frontends/pytorch/src/op/min_max.cpp
+++ b/src/frontends/pytorch/src/op/min_max.cpp
@@ -33,6 +33,7 @@ OutputVector translate_max(const NodeContext& context) {
     // torch.max(input, other)
     if (context.input_is_none(2)) {
         auto y = context.get_input(1);
+        align_eltwise_input_types(context, x, y, true);
         return {context.mark_node(std::make_shared<v1::Maximum>(x, y))};
     }
     // torch.max(input, dim, keepdim), returns values and indicies
@@ -62,6 +63,7 @@ OutputVector translate_min(const NodeContext& context) {
     // torch.min(input, other)
     if (context.input_is_none(2)) {
         auto y = context.get_input(1);
+        align_eltwise_input_types(context, x, y, true);
         return {context.mark_node(std::make_shared<v1::Minimum>(x, y))};
     }
     // torch.min(input, dim, keepdim), returns values and indicies
diff --git a/src/frontends/pytorch/src/utils.cpp b/src/frontends/pytorch/src/utils.cpp
index 386ac393d35772..afd9b5ebf85216 100644
--- a/src/frontends/pytorch/src/utils.cpp
+++ b/src/frontends/pytorch/src/utils.cpp
@@ -422,9 +422,9 @@ void align_eltwise_input_types(const NodeContext& context, Output<Node>& lhs, Ou
         // if div we need to also align float types to highest bitness regardless of scalar
         if (!align_scalars)
             lhs_dst_type = element::f32;
-        rhs_dst_type = element::f32;
+        rhs_dst_type = lhs_type;
     } else if (is_rhs_scalar && !lhs_type.is_real() && rhs_type.is_real()) {
-        lhs_dst_type = element::f32;
+        lhs_dst_type = rhs_type;
         // if div we need to also align float types to highest bitness regardless of scalar
         if (!align_scalars)
             rhs_dst_type = element::f32;
@@ -437,9 +437,9 @@ void align_eltwise_input_types(const NodeContext& context, Output<Node>& lhs, Ou
     }
 
     if (!lhs_dst_type.is_real() && rhs_dst_type.is_real()) {
-        lhs_dst_type = element::f32;
+        lhs_dst_type = rhs_dst_type;
     } else if (lhs_dst_type.is_real() && !rhs_dst_type.is_real()) {
-        rhs_dst_type = element::f32;
+        rhs_dst_type = lhs_dst_type;
     }
     // Align bool to other type
     if (lhs_dst_type == element::boolean) {
diff --git a/tests/layer_tests/pytorch_tests/pytorch_layer_test_class.py b/tests/layer_tests/pytorch_tests/pytorch_layer_test_class.py
index 0f5638ea8c8d38..00cdc427056518 100644
--- a/tests/layer_tests/pytorch_tests/pytorch_layer_test_class.py
+++ b/tests/layer_tests/pytorch_tests/pytorch_layer_test_class.py
@@ -25,7 +25,8 @@ class PytorchLayerTest:
         "int64": Type.i64,
         "int16": Type.i16,
         "int8": Type.i8,
-        "uint8": Type.u8
+        "uint8": Type.u8,
+        "float16": Type.f16
     }
 
     @staticmethod
@@ -120,8 +121,8 @@ def use_torch_compile_backend():
                         continue
                     assert ov_type == fw_type, f"dtype validation failed: {ov_type} != {fw_type}"
                     continue
-                assert torch.tensor(np.array(
-                    ov_tensor)).dtype == fw_tensor.dtype, f"dtype validation failed: {torch.tensor(np.array(ov_tensor)).dtype} != {fw_tensor.dtype}"
+                ov_tensor_fw_format =  torch.tensor(np.array(ov_tensor))
+                assert ov_tensor_fw_format.dtype == fw_tensor.dtype, f"dtype validation failed: {ov_tensor_fw_format.dtype} != {fw_tensor.dtype}"
 
             # Compare Ie results with Framework results
             fw_eps = custom_eps if precision == 'FP32' else 5e-2
diff --git a/tests/layer_tests/pytorch_tests/test_add.py b/tests/layer_tests/pytorch_tests/test_add.py
index 8c3026a9c2c16d..7cf243b0577bcb 100644
--- a/tests/layer_tests/pytorch_tests/test_add.py
+++ b/tests/layer_tests/pytorch_tests/test_add.py
@@ -96,6 +96,12 @@ def forward3(self, lhs, rhs):
                               [torch.float32, torch.int32],
                               [torch.float32, torch.int64],
                               [torch.float32, torch.float64],
+                              [torch.float16, torch.uint8],
+                              [torch.uint8, torch.float16],
+                              [torch.float16, torch.int32],
+                              [torch.int32, torch.float16],
+                              [torch.float16, torch.int64],
+                              [torch.int64, torch.float16]
                               ])
     @pytest.mark.parametrize(("lhs_shape", "rhs_shape"), [([2, 3], [2, 3]),
                                                           ([2, 3], []),
diff --git a/tests/layer_tests/pytorch_tests/test_div.py b/tests/layer_tests/pytorch_tests/test_div.py
index 48eaba1a89bb3f..d6e696b62882d5 100644
--- a/tests/layer_tests/pytorch_tests/test_div.py
+++ b/tests/layer_tests/pytorch_tests/test_div.py
@@ -98,6 +98,12 @@ def forward3(self, lhs, rhs):
                               [torch.float32, torch.int32],
                               [torch.float32, torch.int64],
                               [torch.float32, torch.float64],
+                              [torch.float16, torch.uint8],
+                              [torch.uint8, torch.float16],
+                              [torch.float16, torch.int32],
+                              [torch.int32, torch.float16],
+                              [torch.float16, torch.int64],
+                              [torch.int64, torch.float16]
                               ])
     @pytest.mark.parametrize(("lhs_shape", "rhs_shape"), [([2, 3], [2, 3]),
                                                           ([2, 3], []),
diff --git a/tests/layer_tests/pytorch_tests/test_min_max.py b/tests/layer_tests/pytorch_tests/test_min_max.py
index 211cf76d06a472..1d03c837380ed3 100644
--- a/tests/layer_tests/pytorch_tests/test_min_max.py
+++ b/tests/layer_tests/pytorch_tests/test_min_max.py
@@ -7,19 +7,27 @@
 
 
 class TestMinMax(PytorchLayerTest):
-    def _prepare_input(self, second_input=False):
+    def _prepare_input(self, input_dtype="float32", second_input=False, second_input_dtype="float32"):
         import numpy as np
         if not second_input:
-            return (np.random.randn(1, 3, 10, 10).astype(np.float32),)
-        return (np.random.randn(1, 3, 10, 10).astype(np.float32), np.random.randn(1, 3, 10, 10).astype(np.float32))
+            return (np.random.randn(1, 3, 10, 10).astype(input_dtype),)
+        return (np.random.randn(1, 3, 10, 10).astype(input_dtype), np.random.randn(1, 3, 10, 10).astype(second_input_dtype))
 
-    def create_model(self, op_type, axes, keep_dims, single_input=True):
+    def create_model(self, op_type, axes, keep_dims, single_input=True, dtypes=("float32", "float32")):
         import torch
         op_types = {
             'max': torch.max,
             'min': torch.min
         }
 
+        dtypes_map = {
+            "float32": torch.float32,
+            "float64": torch.float64,
+            "int32": torch.int32,
+            "int64": torch.int64,
+            "uint8": torch.uint8
+        }
+
         op = op_types[op_type]
 
         class aten_min_max(torch.nn.Module):
@@ -41,17 +49,23 @@ def forward(self, x):
                 return self.op(x, self.axes, self.keep_dims)
 
         class aten_min_max_2args(torch.nn.Module):
-            def __init__(self, op):
+            def __init__(self, op, l_dtype, r_dtype):
                 super(aten_min_max_2args, self).__init__()
                 self.op = op
+                self.l_dtype = l_dtype
+                self.r_dtype = r_dtype
 
             def forward(self, x, y):
-                return self.op(x, y)
+                return self.op(x.to(self.l_dtype), y.to(self.r_dtype))
 
         ref_net = None
         if axes is None and keep_dims is None:
-            model_cls = aten_min_max(
-                op) if single_input else aten_min_max_2args(op)
+            if single_input:
+                model_cls = aten_min_max(op)
+            else:
+                l_dtype = dtypes_map[dtypes[0]]
+                r_dtype = dtypes_map[dtypes[1]]
+                model_cls = aten_min_max_2args(op, l_dtype, r_dtype)
         else:
             model_cls = aten_min_max_3args(op, axes, keep_dims)
 
@@ -66,11 +80,15 @@ def test_reduce_min_max(self, axes, keep_dims, op_type, ie_device, precision, ir
                                       single_input=True), ie_device, precision, ir_version)
 
     @pytest.mark.parametrize("op_type", ['min', 'max'])
+    @pytest.mark.parametrize("second_input_dtype", ["float32", "int32", "float64", "int64", "uint8"])
+    @pytest.mark.parametrize("first_input_dtype", ["float32", "int32", "float64", "int64", "uint8"])
     @pytest.mark.nightly
     @pytest.mark.precommit
-    def test_min_max(self, op_type, ie_device, precision, ir_version):
-        self._test(*self.create_model(op_type, None, None, single_input=False),
-                   ie_device, precision, ir_version, kwargs_to_prepare_input={"second_input": True})
+    def test_min_max(self, op_type, first_input_dtype, second_input_dtype, ie_device, precision, ir_version):
+        self._test(*self.create_model(op_type, None, None, single_input=False, dtypes=(first_input_dtype, second_input_dtype)),
+                   ie_device, precision, ir_version, kwargs_to_prepare_input=
+                   {"second_input": True, "input_dtype": first_input_dtype, "second_input_dtype": second_input_dtype}
+                   )
 
 
 class TestPrimMax(PytorchLayerTest):
diff --git a/tests/layer_tests/pytorch_tests/test_mul.py b/tests/layer_tests/pytorch_tests/test_mul.py
index 8e958f095697f0..f22fd7b03bc0cb 100644
--- a/tests/layer_tests/pytorch_tests/test_mul.py
+++ b/tests/layer_tests/pytorch_tests/test_mul.py
@@ -87,6 +87,12 @@ def forward3(self, lhs, rhs):
                               [torch.float32, torch.int32],
                               [torch.float32, torch.int64],
                               [torch.float32, torch.float64],
+                              [torch.float16, torch.uint8],
+                              [torch.uint8, torch.float16],
+                              [torch.float16, torch.int32],
+                              [torch.int32, torch.float16],
+                              [torch.float16, torch.int64],
+                              [torch.int64, torch.float16]
                               ])
     @pytest.mark.parametrize(("lhs_shape", "rhs_shape"), [([2, 3], [2, 3]),
                                                           ([2, 3], []),

From 604aed1384f95b164e6e152dada9c4602029902f Mon Sep 17 00:00:00 2001
From: Ilya Lavrenov <ilya.lavrenov@intel.com>
Date: Wed, 20 Sep 2023 12:24:40 +0400
Subject: [PATCH 42/46] Updated Windows build docs (#17631)

---
 docs/dev/build_windows.md   | 33 +++++----------------------------
 docs/dev/static_libaries.md |  2 +-
 2 files changed, 6 insertions(+), 29 deletions(-)

diff --git a/docs/dev/build_windows.md b/docs/dev/build_windows.md
index e63d4830904086..e598fdd33f04e7 100644
--- a/docs/dev/build_windows.md
+++ b/docs/dev/build_windows.md
@@ -25,29 +25,17 @@ Supported configurations:
     ```sh
     git clone https://github.com/openvinotoolkit/openvino.git
     cd openvino
-    git submodule update --init --recursive
-    ```
-   (Extra for WoA) To build on Windows on ARM with ARM plugin:
-    ```sh
-    git clone https://github.com/openvinotoolkit/openvino_contrib.git
-    cd openvino_contrib
-    git submodule update --init --recursive
+    git submodule update --init
     ```
 
 2. Create build directory:
     ```sh
     mkdir build && cd build
     ```
-3. In the `build` directory, run `cmake` to fetch project dependencies and generate a Visual Studio solution.
+3. In the `build` directory, run `cmake` to fetch project dependencies and generate a Visual Studio solution:
 
-   On Windows x86 64-bits:
-    ```sh
-    cmake -G "Visual Studio 16 2019" -DCMAKE_BUILD_TYPE=Release <openvino>
-    ```
-    
-   On Windows on ARM for ARM64 architecture:
     ```sh
-    cmake -G "Visual Studio 16 2019" -DOPENVINO_EXTRA_MODULES=<openvino_contrib>/modules/arm_plugin -DCMAKE_BUILD_TYPE=Release <openvino>
+    cmake -G "Visual Studio 17 2022" <openvino>
     ```
     
    > **HINT**: **Generating PDB Files and Debugging Your Build** <br>
@@ -62,16 +50,8 @@ Supported configurations:
 
 ### Additional Build Options
 
-- Internal JIT GEMM implementation is used by default.
-
-- Threading Building Blocks (TBB) is used by default. To build Inference Engine with OpenMP threading, set the `-DTHREADING=OMP` option.
-
-- Required versions of TBB and OpenCV packages are downloaded automatically by the CMake-based script. If you want to use the automatically-downloaded packages but you have already installed TBB or OpenCV packages configured in your environment, you may need to clean the `TBBROOT` and `OpenCV_DIR` environment variables before running the `cmake` command; otherwise they won'tnbe downloaded and the build may fail if incompatible versions were installed.
-
-- If the CMake-based build script can not find and download the OpenCV package that is supported on your platform, or if you want to use a custom build of the OpenCV library, refer to the [Use Custom OpenCV Builds](./cmake_options_for_custom_compilation.md#Building-with-custom-OpenCV) section for details.
-
 - To build the OpenVINO Runtime Python API:
-  1. First, install all additional packages (e.g., cython and opencv) listed in the file:
+  1. First, install all additional packages (e.g., cython) listed in the file:
       ```sh
       pip install -r <openvino>\src\bindings\python\src\compatibility\openvino\requirements-dev.txt
       ```
@@ -95,15 +75,12 @@ Supported configurations:
      pip install build/wheel/openvino-2023.0.0-9612-cp11-cp11-win_arm64.whl
      ```
 
-- OpenVINO runtime compilation options:
-  `-DENABLE_OV_ONNX_FRONTEND=ON` enables the building of the ONNX importer.
-
 ### Building OpenVINO with Ninja* Build System
 
 ```sh
 call "C:\Program Files (x86)\Microsoft Visual Studio\2019\Professional\VC\Auxiliary\Build\vcvars64.bat"
 cmake -G Ninja -Wno-dev -DCMAKE_BUILD_TYPE=Release ..
-cmake --build . --config Release
+ninja .
 ```
 
 ## See also
diff --git a/docs/dev/static_libaries.md b/docs/dev/static_libaries.md
index e001b6f24c5fc1..e538a37555f558 100644
--- a/docs/dev/static_libaries.md
+++ b/docs/dev/static_libaries.md
@@ -135,7 +135,7 @@ cmake -DCMAKE_TOOLCHAIN_FILE=<openvino source dir>/cmake/toolchains/mt.runtime.w
 
 * The enabled and tested capabilities of OpenVINO Runtime in a static build:
     * OpenVINO common runtime - work with `ov::Model`, perform model loading on particular device
-    * CPU and GNA inference plugins (**GPU and MYRIAD are not enabled**)
+    * CPU and GNA inference plugins (**GPU is not enabled**)
     * MULTI, HETERO, AUTO, and BATCH inference modes
     * IR, ONNX, PDPD, and TF frontends to read `ov::Model`
 * Static build support for building static libraries only for OpenVINO Runtime libraries. All other third-party prebuilt dependencies remain in the same format:

From f53d880b2c9cd08b20eecee59e6e5d296c875154 Mon Sep 17 00:00:00 2001
From: Ilya Lavrenov <ilya.lavrenov@intel.com>
Date: Wed, 20 Sep 2023 13:52:05 +0400
Subject: [PATCH 43/46] Updated dependabot config for GHA updates (#19970)

---
 .github/dependabot.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/.github/dependabot.yml b/.github/dependabot.yml
index 74661a77af5794..80e95ea5a9fe73 100644
--- a/.github/dependabot.yml
+++ b/.github/dependabot.yml
@@ -154,6 +154,7 @@ updates:
       time: "09:00"
       timezone: "Asia/Dubai"
     assignees:
-      - "ilyachur"
+      - "akashchi"
+      - "mryzhov"
       - "ilya-lavrenov"
     open-pull-requests-limit: 3

From 228ea4474313756b88b2376668aed26aaf037d72 Mon Sep 17 00:00:00 2001
From: Fang Xu <fang.xu@intel.com>
Date: Wed, 20 Sep 2023 19:17:48 +0530
Subject: [PATCH 44/46] [CPU] Use omp section instead of task in UpdateNodes
 logic (#19831)

---
 src/plugins/intel_cpu/src/graph.cpp | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/src/plugins/intel_cpu/src/graph.cpp b/src/plugins/intel_cpu/src/graph.cpp
index aa8acb24267c42..ed18c01c848af1 100644
--- a/src/plugins/intel_cpu/src/graph.cpp
+++ b/src/plugins/intel_cpu/src/graph.cpp
@@ -1308,17 +1308,16 @@ class UpdateNodes : public UpdateNodesBase {
         auto startCounter = m_prepareCounter.load();
 
         #pragma omp parallel
-        #pragma omp single
+        #pragma omp sections
         {
-            #pragma omp task
+            #pragma omp section
             {
                 updateDynParams(startCounter, stopIndx);
             }
-            #pragma omp task
+            #pragma omp section
             {
                 updateShapes(startCounter, stopIndx);
             }
-            #pragma omp taskwait
         }
     }
 };

From 85584760476adb9d73172747729f03b381b5eacf Mon Sep 17 00:00:00 2001
From: Aleksandr Voron <aleksandr.voron@intel.com>
Date: Wed, 20 Sep 2023 15:57:34 +0200
Subject: [PATCH 45/46] [CPU] [ARM] Enable SoftMax SLT tests on ARM (#19823)

---
 .../single_layer_tests/classes/softmax.cpp    | 75 ++++++++++++++++
 .../single_layer_tests/classes/softmax.hpp    | 41 +++++++++
 .../{ => instances/common}/softmax.cpp        | 89 ++-----------------
 3 files changed, 122 insertions(+), 83 deletions(-)
 create mode 100644 src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.cpp
 create mode 100644 src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.hpp
 rename src/plugins/intel_cpu/tests/functional/single_layer_tests/{ => instances/common}/softmax.cpp (72%)

diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.cpp
new file mode 100644
index 00000000000000..ac8a7149f88253
--- /dev/null
+++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.cpp
@@ -0,0 +1,75 @@
+// Copyright (C) 2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "softmax.hpp"
+#include "gtest/gtest.h"
+#include "test_utils/cpu_test_utils.hpp"
+
+using namespace InferenceEngine;
+using namespace CPUTestUtils;
+using namespace ngraph::helpers;
+using namespace ov::test;
+
+namespace CPULayerTestsDefinitions {
+
+std::string SoftMaxLayerCPUTest::getTestCaseName(const testing::TestParamInfo<softmaxCPUTestParams>& obj) {
+    CPUSpecificParams cpuParams;
+    ElementType inType;
+    SoftMaxConfig config;
+    std::string targetDevice;
+    std::tie(inType, config, targetDevice, cpuParams) = obj.param;
+
+    std::ostringstream result;
+    result << "netPRC=" << inType << "_";
+    result << "IS=" << ov::test::utils::partialShape2str({config.inputShape.first}) << "_";
+    result << "TS=";
+    for (const auto& shape : config.inputShape.second) {
+        result << "(";
+        result << ov::test::utils::vec2str(shape);
+        result << ")_";
+    }
+    result << "axis=" << config.axis << "_";
+    result << "trgDev=" << targetDevice;
+    result << CPUTestsBase::getTestCaseName(cpuParams);
+
+    return result.str();
+}
+
+void SoftMaxLayerCPUTest::SetUp() {
+    ElementType inType;
+    SoftMaxConfig config;
+    CPUSpecificParams cpuParams;
+    std::tie(inType, config, targetDevice, cpuParams) = this->GetParam();
+
+    std::tie(inFmts, outFmts, priority, selectedType) = cpuParams;
+    if (selectedType.empty()) {
+        selectedType = getPrimitiveType();
+    }
+
+    if (inType == ElementType::bf16) {
+        rel_threshold = 2e-2f;
+    }
+    selectedType = makeSelectedTypeStr(selectedType, inType);
+    init_input_shapes({config.inputShape});
+    ov::ParameterVector params;
+    for (auto&& shape : inputDynamicShapes) {
+        params.push_back(std::make_shared<ov::op::v0::Parameter>(inType, shape));
+    }
+    const auto paramOuts =
+        ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ngraph::op::Parameter>(params));
+
+    const auto softMax = std::make_shared<ngraph::opset1::Softmax>(paramOuts.at(0), config.axis);
+
+    function = makeNgraphFunction(inType, params, softMax, "SoftMax");
+}
+
+TEST_P(SoftMaxLayerCPUTest, CompareWithRefs) {
+    run();
+    CheckPluginRelatedResults(compiledModel, "Softmax");
+}
+
+namespace SoftMax {
+
+}  // namespace SoftMax
+}  // namespace CPULayerTestsDefinitions
diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.hpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.hpp
new file mode 100644
index 00000000000000..5465d1c06859c0
--- /dev/null
+++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/classes/softmax.hpp
@@ -0,0 +1,41 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include <ngraph_functions/builders.hpp>
+
+#include "shared_test_classes/base/ov_subgraph.hpp"
+#include "test_utils/cpu_test_utils.hpp"
+
+using namespace InferenceEngine;
+using namespace CPUTestUtils;
+using namespace ov::test;
+
+namespace CPULayerTestsDefinitions {
+
+struct SoftMaxConfig {
+    ov::test::InputShape inputShape;
+    size_t axis;
+};
+
+typedef std::tuple<ElementType,    // netPrecision
+                   SoftMaxConfig,  // softmaxTestConfig
+                   std::string,    // targetDevice
+                   CPUSpecificParams>
+    softmaxCPUTestParams;
+
+class SoftMaxLayerCPUTest : public testing::WithParamInterface<softmaxCPUTestParams>,
+                            virtual public SubgraphBaseTest,
+                            public CPUTestsBase {
+public:
+    static std::string getTestCaseName(const testing::TestParamInfo<softmaxCPUTestParams>& obj);
+
+protected:
+    void SetUp() override;
+};
+
+namespace SoftMax {
+
+
+}  // namespace SoftMax
+}  // namespace CPULayerTestsDefinitions
diff --git a/src/plugins/intel_cpu/tests/functional/single_layer_tests/softmax.cpp b/src/plugins/intel_cpu/tests/functional/single_layer_tests/instances/common/softmax.cpp
similarity index 72%
rename from src/plugins/intel_cpu/tests/functional/single_layer_tests/softmax.cpp
rename to src/plugins/intel_cpu/tests/functional/single_layer_tests/instances/common/softmax.cpp
index 70484a14b25c73..03655fd40a536d 100644
--- a/src/plugins/intel_cpu/tests/functional/single_layer_tests/softmax.cpp
+++ b/src/plugins/intel_cpu/tests/functional/single_layer_tests/instances/common/softmax.cpp
@@ -1,93 +1,17 @@
-// Copyright (C) 2018-2023 Intel Corporation
+// Copyright (C) 2023 Intel Corporation
 // SPDX-License-Identifier: Apache-2.0
 //
 
-#include <ngraph_functions/builders.hpp>
-
-#include "shared_test_classes/base/ov_subgraph.hpp"
+#include "single_layer_tests/classes/softmax.hpp"
 #include "test_utils/cpu_test_utils.hpp"
 
 using namespace InferenceEngine;
 using namespace CPUTestUtils;
+using namespace ngraph::helpers;
 using namespace ov::test;
 
 namespace CPULayerTestsDefinitions {
-
-struct SoftMaxConfig {
-    ov::test::InputShape inputShape;
-    size_t axis;
-};
-
-typedef std::tuple<ElementType,    // netPrecision
-                   SoftMaxConfig,  // softmaxTestConfig
-                   std::string,    // targetDevice
-                   CPUSpecificParams>
-    softmaxCPUTestParams;
-
-class SoftMaxLayerCPUTest : public testing::WithParamInterface<softmaxCPUTestParams>,
-                            virtual public SubgraphBaseTest,
-                            public CPUTestsBase {
-public:
-    static std::string getTestCaseName(const testing::TestParamInfo<softmaxCPUTestParams>& obj) {
-        CPUSpecificParams cpuParams;
-        ElementType inType;
-        SoftMaxConfig config;
-        std::string targetDevice;
-        std::tie(inType, config, targetDevice, cpuParams) = obj.param;
-
-        std::ostringstream result;
-        result << "netPRC=" << inType << "_";
-        result << "IS=" << ov::test::utils::partialShape2str({config.inputShape.first}) << "_";
-        result << "TS=";
-        for (const auto& shape : config.inputShape.second) {
-            result << "(";
-            result << ov::test::utils::vec2str(shape);
-            result << ")_";
-        }
-        result << "axis=" << config.axis << "_";
-        result << "trgDev=" << targetDevice;
-        result << CPUTestsBase::getTestCaseName(cpuParams);
-
-        return result.str();
-    }
-
-protected:
-    void SetUp() override {
-        ElementType inType;
-        SoftMaxConfig config;
-        CPUSpecificParams cpuParams;
-        std::tie(inType, config, targetDevice, cpuParams) = this->GetParam();
-
-        std::tie(inFmts, outFmts, priority, selectedType) = cpuParams;
-        if (selectedType.empty()) {
-            selectedType = getPrimitiveType();
-        }
-
-        if (inType == ElementType::bf16) {
-            rel_threshold = 2e-2f;
-        }
-        selectedType = makeSelectedTypeStr(selectedType, inType);
-        init_input_shapes({config.inputShape});
-        ov::ParameterVector params;
-        for (auto&& shape : inputDynamicShapes) {
-            params.push_back(std::make_shared<ov::op::v0::Parameter>(inType, shape));
-        }
-        const auto paramOuts =
-            ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ngraph::op::Parameter>(params));
-
-        const auto softMax = std::make_shared<ngraph::opset1::Softmax>(paramOuts.at(0), config.axis);
-
-        function = makeNgraphFunction(inType, params, softMax, "SoftMax");
-    }
-};
-
-TEST_P(SoftMaxLayerCPUTest, CompareWithRefs) {
-    run();
-    CheckPluginRelatedResults(compiledModel, "Softmax");
-}
-
-namespace {
-// not optimized cpu spec
+namespace SoftMax {
 const auto notOptimizedCPUSpec = CPUSpecificParams{{}, {}, {"ref_any"}, "ref_any"};
 
 const std::vector<SoftMaxConfig> optimizedConfigsFP32 = {
@@ -222,6 +146,5 @@ INSTANTIATE_TEST_SUITE_P(smoke_SoftMax_Unsupported_CPU,
                          SoftMaxLayerCPUTest,
                          UnsupportedParams,
                          SoftMaxLayerCPUTest::getTestCaseName);
-
-}  // namespace
-}  // namespace CPULayerTestsDefinitions
+} // namespace SoftMax
+} // namespace CPULayerTestsDefinitions
\ No newline at end of file

From c1a8380052f777d82c97a3c30f131a3771f3635a Mon Sep 17 00:00:00 2001
From: Evgenya Nugmanova <evgeniia.nugmanova@intel.com>
Date: Wed, 20 Sep 2023 18:00:07 +0400
Subject: [PATCH 46/46] Symbolic shape inference and graph optimizations
 (#19392)

* Symbolic shape inference and graph optimizations
- Prepares a place in CommonOptimizations pipeline for symbolic optimizations
- Introduces symbolic propagation and symbolic optimizations for ChainedMaximum, NopBroadcast and shape sub-graph optimization
- Introduces utility runtime info for TableOfEquivalence passing and disabling of value invalidation during shape inference

* Executes NgramFusion in a symbolic environment. Relaxes Ngram fusion pattern utilizing symbolic knowledge

* Remove debug model visualization

* rt_info copying to new Add operation

* Fix visualization and place validation in nicer place in symbolic transformation

* Fix Slice operation not to propagate labels if input and output dimension is fully dynamic

* Covering Vladislav comments

* Replace value invalidation followed by validation to revalidation since it does the same thing

* Adding back invalidation of cached values to Symbolic Propagation pass

* Fix StridedSlice label propagation. Code style

* Update src/common/transformations/tests/symbolic_transformations/nop_broadcast.cpp
---
 .../simplify_shape_of_sub_graph.hpp           |   4 +
 .../chained_maximum.hpp                       |  26 ++
 .../label_optimization.hpp                    |  37 +++
 .../nop_broadcast.hpp                         |  25 ++
 .../symbolic_optimizations.hpp                |  50 ++++
 .../symbolic_transformations/utils.hpp        |  43 +++
 .../include/transformations/utils/utils.hpp   |  28 +-
 .../common_optimizations.cpp                  |   4 +-
 .../moc_transformations.cpp                   |   2 +-
 .../common_optimizations/nop_elimination.cpp  |   3 +-
 .../simplify_shape_of_sub_graph.cpp           |   3 +
 .../chained_maximum.cpp                       |  50 ++++
 .../label_optimization.cpp                    | 265 ++++++++++++++++++
 .../nop_broadcast.cpp                         |  61 ++++
 .../symbolic_optimizations.cpp                | 146 ++++++++++
 .../symbolic_transformations/utils.cpp        |  34 +++
 .../src/transformations/utils/utils.cpp       |  22 +-
 .../chained_maximum.cpp                       | 134 +++++++++
 .../label_optimization.cpp                    |  97 +++++++
 .../nop_broadcast.cpp                         | 111 ++++++++
 .../openvino/core/dimension_tracker.hpp       |   2 +
 .../openvino/op/util/symbolic_info.hpp        |  54 ++++
 .../include/slice_shape_inference.hpp         |   3 +-
 .../include/strided_slice_shape_inference.hpp |   3 +-
 src/core/src/bound_evaluate.cpp               |  19 +-
 src/core/src/descriptor/tensor.cpp            |   3 +
 src/core/src/dimension_tracker.cpp            |   7 +-
 src/core/src/op/util/symbolic_info.cpp        |  83 ++++++
 src/core/src/pass/manager.cpp                 |   3 +-
 src/core/src/pass/visualize_tree.cpp          |  22 ++
 src/core/tests/type_prop/slice.cpp            |   2 +-
 .../cpu_opset/common/pass/ngram_fusion.cpp    |  50 ++--
 .../convert_to_cpu_specific_opset.hpp         |   4 +-
 33 files changed, 1359 insertions(+), 41 deletions(-)
 create mode 100644 src/common/transformations/include/transformations/symbolic_transformations/chained_maximum.hpp
 create mode 100644 src/common/transformations/include/transformations/symbolic_transformations/label_optimization.hpp
 create mode 100644 src/common/transformations/include/transformations/symbolic_transformations/nop_broadcast.hpp
 create mode 100644 src/common/transformations/include/transformations/symbolic_transformations/symbolic_optimizations.hpp
 create mode 100644 src/common/transformations/include/transformations/symbolic_transformations/utils.hpp
 create mode 100644 src/common/transformations/src/transformations/symbolic_transformations/chained_maximum.cpp
 create mode 100644 src/common/transformations/src/transformations/symbolic_transformations/label_optimization.cpp
 create mode 100644 src/common/transformations/src/transformations/symbolic_transformations/nop_broadcast.cpp
 create mode 100644 src/common/transformations/src/transformations/symbolic_transformations/symbolic_optimizations.cpp
 create mode 100644 src/common/transformations/src/transformations/symbolic_transformations/utils.cpp
 create mode 100644 src/common/transformations/tests/symbolic_transformations/chained_maximum.cpp
 create mode 100644 src/common/transformations/tests/symbolic_transformations/label_optimization.cpp
 create mode 100644 src/common/transformations/tests/symbolic_transformations/nop_broadcast.cpp
 create mode 100644 src/core/include/openvino/op/util/symbolic_info.hpp
 create mode 100644 src/core/src/op/util/symbolic_info.cpp

diff --git a/src/common/transformations/include/transformations/common_optimizations/simplify_shape_of_sub_graph.hpp b/src/common/transformations/include/transformations/common_optimizations/simplify_shape_of_sub_graph.hpp
index d4ff490bd2c388..7f2e533c5b79ed 100644
--- a/src/common/transformations/include/transformations/common_optimizations/simplify_shape_of_sub_graph.hpp
+++ b/src/common/transformations/include/transformations/common_optimizations/simplify_shape_of_sub_graph.hpp
@@ -41,7 +41,11 @@ class ov::pass::GroupedGatherElimination : public ov::pass::MatcherPass {
 class ov::pass::SimplifyShapeOfSubGraph : public ov::pass::ModelPass {
 public:
     OPENVINO_RTTI("SimplifyShapeOfSubGraph", "0");
+    explicit SimplifyShapeOfSubGraph(bool use_shapes = true) : m_use_shapes(use_shapes){};
     bool run_on_model(const std::shared_ptr<ov::Model>& m) override;
+
+private:
+    bool m_use_shapes;
 };
 
 /**
diff --git a/src/common/transformations/include/transformations/symbolic_transformations/chained_maximum.hpp b/src/common/transformations/include/transformations/symbolic_transformations/chained_maximum.hpp
new file mode 100644
index 00000000000000..caa2586ebeeea4
--- /dev/null
+++ b/src/common/transformations/include/transformations/symbolic_transformations/chained_maximum.hpp
@@ -0,0 +1,26 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <openvino/pass/graph_rewrite.hpp>
+#include <transformations_visibility.hpp>
+
+namespace ov {
+namespace pass {
+class TRANSFORMATIONS_API ChainedMaximumOptimization;
+}  // namespace pass
+}  // namespace ov
+
+/**
+ * @ingroup ie_transformation_common_api
+ * @brief Optimizes graphs based on value labels / symbols
+ *      Maximum(Maximum(A, B), B) -> Maximum(A, B)
+ *      Maximum(Maximum(A, B), A) -> Maximum(A, B)
+ */
+class ov::pass::ChainedMaximumOptimization : public ov::pass::MatcherPass {
+public:
+    OPENVINO_RTTI("ChainedMaximumOptimization", "0");
+    ChainedMaximumOptimization();
+};
\ No newline at end of file
diff --git a/src/common/transformations/include/transformations/symbolic_transformations/label_optimization.hpp b/src/common/transformations/include/transformations/symbolic_transformations/label_optimization.hpp
new file mode 100644
index 00000000000000..9260be86d2744a
--- /dev/null
+++ b/src/common/transformations/include/transformations/symbolic_transformations/label_optimization.hpp
@@ -0,0 +1,37 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+#include <openvino/pass/graph_rewrite.hpp>
+#include <openvino/pass/pass.hpp>
+#include <transformations_visibility.hpp>
+
+namespace ov {
+namespace pass {
+class TRANSFORMATIONS_API ApplyTableOfEquivalence;
+class TRANSFORMATIONS_API OptimizeLabelsUsedAsValues;
+}  // namespace pass
+}  // namespace ov
+
+/**
+ * @ingroup ie_transformation_common_api
+ * @brief Resets symbols / labels on output shapes and values according to table of symbol / label equivalence. It
+ * allows to reduce number of labels used in the model and to disambiguate label values.
+ */
+class ov::pass::ApplyTableOfEquivalence : public ov::pass::ModelPass {
+public:
+    OPENVINO_RTTI("ApplyTableOfEquivalence", "0");
+    bool run_on_model(const std::shared_ptr<ov::Model>& m) override;
+};
+
+/**
+ * @ingroup ie_transformation_common_api
+ * @brief Collects sources where each symbol / label initially appeared (on shape or shape sub-graph) and attaches all
+ * value usages of this label to this initial source
+ */
+class ov::pass::OptimizeLabelsUsedAsValues : public ov::pass::ModelPass {
+public:
+    OPENVINO_RTTI("OptimizeLabelsUsedAsValues", "0");
+    bool run_on_model(const std::shared_ptr<ov::Model>& m) override;
+};
\ No newline at end of file
diff --git a/src/common/transformations/include/transformations/symbolic_transformations/nop_broadcast.hpp b/src/common/transformations/include/transformations/symbolic_transformations/nop_broadcast.hpp
new file mode 100644
index 00000000000000..c6356277a42e81
--- /dev/null
+++ b/src/common/transformations/include/transformations/symbolic_transformations/nop_broadcast.hpp
@@ -0,0 +1,25 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <openvino/pass/graph_rewrite.hpp>
+#include <transformations_visibility.hpp>
+
+namespace ov {
+namespace pass {
+class TRANSFORMATIONS_API NopBroadcast;
+}  // namespace pass
+}  // namespace ov
+
+/**
+ * @ingroup ie_transformation_common_api
+ * @brief Optimizes out Broadcast(data, Maximum(shape, ones)) if labels on data and shape are equal
+ * Use case with data being empty should not be considered here since original graph has Maximum with ones
+ */
+class ov::pass::NopBroadcast : public ov::pass::MatcherPass {
+public:
+    OPENVINO_RTTI("NopBroadcast", "0");
+    NopBroadcast();
+};
\ No newline at end of file
diff --git a/src/common/transformations/include/transformations/symbolic_transformations/symbolic_optimizations.hpp b/src/common/transformations/include/transformations/symbolic_transformations/symbolic_optimizations.hpp
new file mode 100644
index 00000000000000..1cf3cf9577dc78
--- /dev/null
+++ b/src/common/transformations/include/transformations/symbolic_transformations/symbolic_optimizations.hpp
@@ -0,0 +1,50 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <openvino/pass/graph_rewrite.hpp>
+#include <openvino/pass/manager.hpp>
+#include <openvino/pass/pass.hpp>
+#include <openvino/pass/pattern/matcher.hpp>
+#include <transformations_visibility.hpp>
+
+namespace ov {
+namespace pass {
+class TRANSFORMATIONS_API SymbolicOptimizations;
+class TRANSFORMATIONS_API SymbolicPropagation;
+}  // namespace pass
+}  // namespace ov
+
+/**
+ * @ingroup ie_transformation_common_api
+ * @brief Runs optimizations which are based on symbolic shape inference
+ */
+class ov::pass::SymbolicOptimizations : public ov::pass::ModelPass {
+public:
+    OPENVINO_RTTI("SymbolicOptimizations", "0");
+    explicit SymbolicOptimizations(bool full_run = true);
+    bool run_on_model(const std::shared_ptr<ov::Model>& m) override;
+    std::shared_ptr<ov::pass::Manager> get_manager() {
+        return m_manager;
+    };
+
+private:
+    std::shared_ptr<ov::pass::Manager> m_manager;
+};
+
+/**
+ * @ingroup ie_transformation_common_api
+ * @brief Assigns labels / symbols to all tensors on shapes and values. Uses shape inference and other special rules to
+ * propagate labels / symbols
+ */
+class ov::pass::SymbolicPropagation : public ov::pass::ModelPass {
+public:
+    OPENVINO_RTTI("SymbolicPropagation");
+    SymbolicPropagation();
+    bool run_on_model(const std::shared_ptr<ov::Model>& m) override;
+
+private:
+    std::shared_ptr<ov::TableOfEquivalence> m_te;
+};
diff --git a/src/common/transformations/include/transformations/symbolic_transformations/utils.hpp b/src/common/transformations/include/transformations/symbolic_transformations/utils.hpp
new file mode 100644
index 00000000000000..2f3d84dfe825ff
--- /dev/null
+++ b/src/common/transformations/include/transformations/symbolic_transformations/utils.hpp
@@ -0,0 +1,43 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <transformations_visibility.hpp>
+
+#include "openvino/core/descriptor/tensor.hpp"
+#include "openvino/core/dimension.hpp"
+#include "openvino/core/partial_shape.hpp"
+#include "openvino/core/type/element_type.hpp"
+
+namespace ov {
+namespace symbol {
+namespace util {
+
+/// \brief Collects labels from shape. Labels of static dimensions are guaranteed to be ov::no_labels
+///
+/// \param shape    Shape object to collect labels from
+/// \param labels   TensorLabel object to collect labels to
+///
+/// \return Status of collecting the labels (false if rank is static else true)
+TRANSFORMATIONS_API bool get_labels(const ov::PartialShape& shape, ov::TensorLabel& labels);
+
+/// \brief Collects labels from tensor of Output object
+///
+/// \param output   Output object to collect labels from
+/// \param labels   TensorLabel object to collect labels to
+///
+/// \return Status of collecting the labels (false if tensor has no labels else true)
+TRANSFORMATIONS_API bool get_labels(const ov::Output<ov::Node>& output, ov::TensorLabel& labels);
+
+/// \brief Compares
+///
+/// \param lhs   TensorLabel object to compare
+/// \param rhs   TensorLabel object to compare
+///
+/// \return true if labels are unique and equal between lhs and rhs else false
+TRANSFORMATIONS_API bool are_unique_and_equal_labels(const ov::TensorLabel& lhs, const ov::TensorLabel& rhs);
+}  // namespace util
+}  // namespace symbol
+}  // namespace ov
diff --git a/src/common/transformations/include/transformations/utils/utils.hpp b/src/common/transformations/include/transformations/utils/utils.hpp
index 1af4dfbf1551e8..9a2036fff1b20d 100644
--- a/src/common/transformations/include/transformations/utils/utils.hpp
+++ b/src/common/transformations/include/transformations/utils/utils.hpp
@@ -214,11 +214,13 @@ TRANSFORMATIONS_API std::vector<Input<Node>> get_node_target_inputs(const std::s
 
 TRANSFORMATIONS_API std::shared_ptr<Node> node_to_get_shape_value_of_indices_from_shape_node(
     const std::shared_ptr<Node>& shape_node,
-    const std::vector<size_t>& indices);
+    const std::vector<size_t>& indices,
+    const std::vector<std::shared_ptr<Node>>& copy_rt_info_from = {});
 
 TRANSFORMATIONS_API std::shared_ptr<Node> node_to_get_shape_value_of_indices_from_shape_source(
     const Output<Node>& shape_source,
-    const std::vector<size_t>& indices);
+    const std::vector<size_t>& indices,
+    const std::vector<std::shared_ptr<Node>>& copy_rt_info_from = {});
 
 TRANSFORMATIONS_API bool is_dequantization_subgraph(const Output<Node>& node);
 
@@ -230,6 +232,28 @@ TRANSFORMATIONS_API bool is_constant_and_all_values_equal_int(const Output<Node>
 
 TRANSFORMATIONS_API bool is_on_constant_path(const ov::Output<ov::Node>& output);
 
+template <typename T>
+ov::pass::pattern::op::ValuePredicate constant_predicate(std::function<bool(const std::vector<T>&)> predicate) {
+    return pass::pattern::op::as_value_predicate([=](std::shared_ptr<Node> n) -> bool {
+        if (auto constant = as_type_ptr<v0::Constant>(n)) {
+            auto values = constant->cast_vector<T>();
+            return predicate(values);
+        }
+        return false;
+    });
+}
 }  // namespace util
 }  // namespace op
 }  // namespace ov
+
+#define INT_CONSTANT_WITH_PREDICATE(expression)                                                   \
+    pattern::wrap_type<op::v0::Constant>(                                                         \
+        ov::op::util::constant_predicate<int64_t>([](const std::vector<int64_t>& value) -> bool { \
+            return expression;                                                                    \
+        }))
+
+#define FLOAT_CONSTANT_WITH_PREDICATE(expression)                                             \
+    pattern::wrap_type<op::v0::Constant>(                                                     \
+        ov::op::util::constant_predicate<float>([](const std::vector<float>& value) -> bool { \
+            return expression;                                                                \
+        }))
diff --git a/src/common/transformations/src/transformations/common_optimizations/common_optimizations.cpp b/src/common/transformations/src/transformations/common_optimizations/common_optimizations.cpp
index 1638f2c4301e2b..8ad09f95dede3e 100644
--- a/src/common/transformations/src/transformations/common_optimizations/common_optimizations.cpp
+++ b/src/common/transformations/src/transformations/common_optimizations/common_optimizations.cpp
@@ -111,6 +111,7 @@
 #include "transformations/op_conversions/softmax_decomposition.hpp"
 #include "transformations/op_conversions/softsign_decomposition.hpp"
 #include "transformations/op_conversions/unique_decomposition.hpp"
+#include "transformations/symbolic_transformations/symbolic_optimizations.hpp"
 
 bool ov::pass::CommonOptimizations::run_on_model(const std::shared_ptr<ov::Model>& f) {
     RUN_ON_FUNCTION_SCOPE(CommonOptimizations);
@@ -230,7 +231,8 @@ bool ov::pass::CommonOptimizations::run_on_model(const std::shared_ptr<ov::Model
     // StridesOptimization should be at the very end
     // because we cannot insert any MaxPools since they may prevent
     // other optimizations
-    manager.register_pass<StridesOptimization>();
+    REGISTER_PASS(manager, StridesOptimization)
+    REGISTER_PASS(manager, SymbolicOptimizations)
     REGISTER_PASS(manager, Validate)
     manager.run_passes(f);
 
diff --git a/src/common/transformations/src/transformations/common_optimizations/moc_transformations.cpp b/src/common/transformations/src/transformations/common_optimizations/moc_transformations.cpp
index 0bdae82810317a..068e1f27a291e9 100644
--- a/src/common/transformations/src/transformations/common_optimizations/moc_transformations.cpp
+++ b/src/common/transformations/src/transformations/common_optimizations/moc_transformations.cpp
@@ -147,7 +147,7 @@ bool ov::pass::MOCTransformations::run_on_model(const std::shared_ptr<ov::Model>
         REGISTER_PASS(manager, Validate)
     }
     REGISTER_PASS(manager, ConvertQuantizeDequantize)
-    REGISTER_PASS(manager, SimplifyShapeOfSubGraph)
+    REGISTER_PASS(manager, SimplifyShapeOfSubGraph, m_use_shapes)
 
     if (!m_use_shapes) {
         manager.register_pass<ov::pass::DisableShapeOfConstantFolding>();
diff --git a/src/common/transformations/src/transformations/common_optimizations/nop_elimination.cpp b/src/common/transformations/src/transformations/common_optimizations/nop_elimination.cpp
index 9cbf24a6dae0e3..9ce5ea86b901ab 100644
--- a/src/common/transformations/src/transformations/common_optimizations/nop_elimination.cpp
+++ b/src/common/transformations/src/transformations/common_optimizations/nop_elimination.cpp
@@ -833,7 +833,8 @@ ov::pass::NopSliceBeforeGatherElements::NopSliceBeforeGatherElements() {
 
 ov::pass::PrepareShapeOpsForEliminationAroundBE::PrepareShapeOpsForEliminationAroundBE() {
     MATCHER_SCOPE(PrepareShapeOpsForEliminationAroundBE);
-    auto first_label = pattern::wrap_type<op::v1::Reshape, op::v0::Squeeze>(pattern::rank_equals(0));
+    auto first_label = pattern::wrap_type<op::v1::Reshape, op::v0::Squeeze, op::v1::StridedSlice, op::util::GatherBase>(
+        pattern::rank_equals(0));
     auto other_input_label = pattern::any_input(pattern::rank_equals(0));
     auto binary_op_label = pattern::wrap_type<op::util::BinaryElementwiseArithmetic,
                                               op::util::BinaryElementwiseComparison,
diff --git a/src/common/transformations/src/transformations/common_optimizations/simplify_shape_of_sub_graph.cpp b/src/common/transformations/src/transformations/common_optimizations/simplify_shape_of_sub_graph.cpp
index 00c84d5211581c..5ef33a33326e00 100644
--- a/src/common/transformations/src/transformations/common_optimizations/simplify_shape_of_sub_graph.cpp
+++ b/src/common/transformations/src/transformations/common_optimizations/simplify_shape_of_sub_graph.cpp
@@ -21,6 +21,7 @@
 #include "openvino/pass/manager.hpp"
 #include "openvino/pass/pattern/op/wrap_type.hpp"
 #include "transformations/common_optimizations/eliminate_unsqueeze_gather.hpp"
+#include "transformations/common_optimizations/nop_elimination.hpp"
 #include "transformations/common_optimizations/shared_ops_optimization.hpp"
 #include "transformations/utils/utils.hpp"
 
@@ -291,8 +292,10 @@ bool pass::SimplifyShapeOfSubGraph::run_on_model(const std::shared_ptr<Model>& f
     Manager manager;
     manager.set_per_pass_validation(false);
 
+    REGISTER_PASS(manager, PrepareShapeOpsForEliminationAroundBE)
     REGISTER_PASS(manager, SharedOpOptimization)
     REGISTER_PASS(manager, EliminateGatherUnsqueeze)  // should run after SharedOpOptimization
+    REGISTER_PASS(manager, NopElimination, m_use_shapes)
     REGISTER_PASS(manager, GroupedGatherElimination)
     // GatherNopElimination depends on shape, so it requires shape propagation
     // if previous transformations has resolved some dynamic shapes.
diff --git a/src/common/transformations/src/transformations/symbolic_transformations/chained_maximum.cpp b/src/common/transformations/src/transformations/symbolic_transformations/chained_maximum.cpp
new file mode 100644
index 00000000000000..02510be34dcb4a
--- /dev/null
+++ b/src/common/transformations/src/transformations/symbolic_transformations/chained_maximum.cpp
@@ -0,0 +1,50 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/symbolic_transformations/chained_maximum.hpp"
+
+#include <openvino/op/maximum.hpp>
+#include <openvino/pass/pattern/op/wrap_type.hpp>
+
+#include "itt.hpp"
+#include "openvino/core/dimension_tracker.hpp"
+#include "transformations/symbolic_transformations/utils.hpp"
+
+using namespace ov::symbol::util;
+
+ov::pass::ChainedMaximumOptimization::ChainedMaximumOptimization() {
+    MATCHER_SCOPE(ChainedMaximumOptimization);
+    auto A_input = pattern::any_input();
+    auto B_input = pattern::any_input();
+    auto C_input = pattern::any_input();
+    auto first_maximum = pattern::wrap_type<op::v1::Maximum>({A_input, B_input});
+    auto maximum = pattern::wrap_type<op::v1::Maximum>({first_maximum, C_input});
+
+    ov::matcher_pass_callback matcher_pass_callback = [=](pattern::Matcher& m) {
+        const auto& vm = m.get_pattern_value_map();
+
+        auto A = vm.at(A_input), B = vm.at(B_input), C = vm.at(C_input);
+        auto output_to_replace = vm.at(first_maximum);
+
+        ov::TensorLabel A_labels, B_labels, C_labels;
+        bool A_read = get_labels(A, A_labels);
+        bool B_read = get_labels(B, B_labels);
+        bool C_read = get_labels(C, C_labels);
+
+        if (!A_read && !B_read && !C_read)
+            return false;
+
+        if (are_unique_and_equal_labels(A_labels, C_labels)) {
+            // Matched Maximum(Maximum(A, B), C) with A == C -> Maximum(B, C)
+            return ov::replace_output_update_name(output_to_replace, B);
+        } else if (are_unique_and_equal_labels(B_labels, C_labels)) {
+            // Matched Maximum(Maximum(A, B), C) with B == C -> Maximum(A, C)
+            return ov::replace_output_update_name(output_to_replace, A);
+        }
+        return false;
+    };
+
+    auto m = std::make_shared<pattern::Matcher>(maximum, matcher_name);
+    register_matcher(m, matcher_pass_callback);
+}
diff --git a/src/common/transformations/src/transformations/symbolic_transformations/label_optimization.cpp b/src/common/transformations/src/transformations/symbolic_transformations/label_optimization.cpp
new file mode 100644
index 00000000000000..049fd0e72c06c3
--- /dev/null
+++ b/src/common/transformations/src/transformations/symbolic_transformations/label_optimization.cpp
@@ -0,0 +1,265 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/symbolic_transformations/label_optimization.hpp"
+
+#include <openvino/core/bound_evaluation_util.hpp>
+#include <openvino/core/dimension_tracker.hpp>
+#include <openvino/op/add.hpp>
+#include <openvino/op/concat.hpp>
+#include <openvino/op/convert.hpp>
+#include <openvino/op/gather.hpp>
+#include <openvino/op/reshape.hpp>
+#include <openvino/op/shape_of.hpp>
+#include <openvino/op/squeeze.hpp>
+#include <openvino/op/util/symbolic_info.hpp>
+
+#include "itt.hpp"
+#include "openvino/core/rt_info.hpp"
+#include "openvino/op/util/multi_subgraph_base.hpp"
+
+namespace {
+void update_label(const ov::EqTable& table, ov::label_t& label) {
+    if (label != ov::no_label && table.count(label)) {
+        const auto& alternative_label = *table.at(label)->begin();
+        if (alternative_label != ov::no_label)
+            label = std::min(label, alternative_label);
+    }
+}
+
+void apply_table_of_equivalence_on_model(const std::shared_ptr<ov::Model>& m, const ov::EqTable& table) {
+    for (const auto& op : m->get_ordered_ops()) {
+        // handle inner sub-graphs
+        if (auto multi_subgraph_op = std::dynamic_pointer_cast<ov::op::util::MultiSubGraphOp>(op))
+            for (const auto& sub_graph : multi_subgraph_op->get_functions())
+                if (sub_graph)
+                    apply_table_of_equivalence_on_model(sub_graph, table);
+
+        for (auto& output : op->outputs()) {
+            // shape relabeling
+            auto shape = output.get_partial_shape();
+            for (auto& d : shape) {
+                if (d.is_static())
+                    continue;
+                auto label = ov::DimensionTracker::get_label(d);
+                update_label(table, label);
+                if (label != ov::no_label)
+                    ov::DimensionTracker::set_label(d, label);
+            }
+            op->set_output_type(output.get_index(), output.get_element_type(), shape);
+            // value relabeling
+            auto value_labels = output.get_tensor().get_value_label();
+            for (auto& label : value_labels)
+                update_label(table, label);
+            output.get_tensor().set_value_label(value_labels);
+        }
+    }
+}
+}  // namespace
+
+bool ov::pass::ApplyTableOfEquivalence::run_on_model(const std::shared_ptr<ov::Model>& m) {
+    RUN_ON_FUNCTION_SCOPE(ApplyTableOfEquivalence);
+    if (auto te = ov::table_of_equivalence(m))
+        apply_table_of_equivalence_on_model(m, te->get_equivalence_table());
+    return false;
+}
+
+// label to source map
+using LTS_map = std::unordered_map<ov::label_t, ov::Output<ov::Node>>;
+
+namespace {
+int64_t get_idx_of_label_in_source(const ov::Output<ov::Node>& source, const ov::label_t& label) {
+    int64_t idx = -1;
+    if (label == ov::no_label)
+        return idx;
+    auto pshape = source.get_partial_shape();
+    auto rank = pshape.rank();
+    if (rank.is_dynamic())
+        return idx;
+    for (int64_t i = 0; i < rank.get_length(); ++i) {
+        auto l = ov::DimensionTracker::get_label(pshape[i]);
+        if (l == label) {
+            idx = i;
+            break;
+        }
+    }
+    return idx;
+}
+
+ov::Output<ov::Node> alternative_source_from_existing_value(const ov::label_t& label,
+                                                            const ov::Output<ov::Node>& original_output,
+                                                            LTS_map& label_value_source) {
+    auto alternative_source = ov::Output<ov::Node>();
+    if (label_value_source.count(label)) {
+        alternative_source = label_value_source[label];
+        const auto &original_shape = original_output.get_shape(), &alternative_shape = alternative_source.get_shape();
+        const auto &original_et = original_output.get_element_type(),
+                   &alternative_et = alternative_source.get_element_type();
+        if (alternative_shape != original_shape && (original_shape.empty() || original_shape == ov::Shape{0})) {
+            auto squeeze = std::make_shared<ov::op::v0::Squeeze>(alternative_source);
+            ov::copy_runtime_info(original_output.get_node_shared_ptr(), squeeze);
+            alternative_source = squeeze->output(0);
+        } else if (alternative_shape != original_shape) {
+            auto shape = ov::op::v0::Constant::create(ov::element::i64, {original_shape.size()}, original_shape);
+            auto reshape = std::make_shared<ov::op::v1::Reshape>(alternative_source, shape, false);
+            ov::copy_runtime_info(original_output.get_node_shared_ptr(), reshape);
+            alternative_source = reshape->output(0);
+        }
+        if (alternative_et != original_et) {
+            auto convert = std::make_shared<ov::op::v0::Convert>(alternative_source, original_et);
+            ov::copy_runtime_info(original_output.get_node_shared_ptr(), convert);
+            alternative_source = convert->output(0);
+        }
+    }
+    return alternative_source;
+}
+
+ov::Output<ov::Node> alternative_source_from_shape_source(const LTS_map& label_shape_source,
+                                                          const ov::label_t& label,
+                                                          const ov::Output<ov::Node>& original_output,
+                                                          LTS_map& label_value_source) {
+    auto alternative_source = ov::Output<ov::Node>();
+    if (label_shape_source.count(label)) {
+        // replacing via constructing the label source and saving it for the future
+        const auto& source = label_shape_source.at(label);
+        const int64_t& idx = get_idx_of_label_in_source(source, label);
+        if (idx == -1)
+            return alternative_source;
+        const auto& original_et = original_output.get_element_type();
+        std::shared_ptr<ov::Node> shape;
+        if (original_et == ov::element::i32 || original_et == ov::element::i64) {
+            shape = std::make_shared<ov::op::v3::ShapeOf>(source, original_et);
+        } else {
+            shape = std::make_shared<ov::op::v3::ShapeOf>(source);
+            ov::copy_runtime_info(original_output.get_node_shared_ptr(), shape);
+            shape = std::make_shared<ov::op::v0::Convert>(shape, original_et);
+        }
+        auto indices = ov::op::v0::Constant::create(ov::element::i64, original_output.get_shape(), {idx});
+        auto axis = ov::op::v0::Constant::create(ov::element::i64, {}, {0});
+        auto gather = std::make_shared<ov::op::v8::Gather>(shape, indices, axis);
+        ov::copy_runtime_info(original_output.get_node_shared_ptr(), {shape, indices, axis, gather});
+        alternative_source = gather;
+        label_value_source[label] = alternative_source;
+    }
+    return alternative_source;
+}
+
+ov::Output<ov::Node> get_alternative_source_from_value_or_shape_source(const LTS_map& label_shape_source,
+                                                                       const ov::label_t& label,
+                                                                       const ov::Output<ov::Node>& original_output,
+                                                                       LTS_map& label_value_source) {
+    auto alternative_source = ov::Output<ov::Node>();
+    if (label == ov::no_label)
+        return alternative_source;
+    alternative_source = alternative_source_from_existing_value(label, original_output, label_value_source);
+    if (!alternative_source.get_node_shared_ptr())
+        alternative_source =
+            alternative_source_from_shape_source(label_shape_source, label, original_output, label_value_source);
+    return alternative_source;
+}
+
+ov::Output<ov::Node> alternative_source_from_concat_input_sources(const LTS_map& label_shape_source,
+                                                                  const ov::label_t& label,
+                                                                  const ov::Output<ov::Node>& original_output,
+                                                                  LTS_map& label_value_source) {
+    auto alternative_source = ov::Output<ov::Node>();
+    if (label_shape_source.count(label)) {
+        const auto& source = label_shape_source.at(label);
+        auto concat = ov::as_type_ptr<ov::op::v0::Concat>(source.get_node_shared_ptr());
+        if (!concat || concat->get_input_size() != 2)
+            return alternative_source;
+        int64_t idx = get_idx_of_label_in_source(source, label);
+        if (idx == -1 || idx != concat->get_concatenation_axis())
+            return alternative_source;
+        // optimize using the knowledge of the Concat SI and what happens on the axis
+        const auto& lhs_pshape = concat->get_input_partial_shape(0);
+        const auto& rhs_pshape = concat->get_input_partial_shape(1);
+        if (lhs_pshape.rank().is_static() && rhs_pshape.rank().is_static()) {
+            auto lhs_label = ov::DimensionTracker::get_label(lhs_pshape[idx]);
+            auto lhs_alternative = get_alternative_source_from_value_or_shape_source(label_shape_source,
+                                                                                     lhs_label,
+                                                                                     original_output,
+                                                                                     label_value_source);
+
+            auto rhs_label = ov::DimensionTracker::get_label(rhs_pshape[idx]);
+            auto rhs_alternative = get_alternative_source_from_value_or_shape_source(label_shape_source,
+                                                                                     rhs_label,
+                                                                                     original_output,
+                                                                                     label_value_source);
+
+            if (lhs_alternative.get_node_shared_ptr() && rhs_alternative.get_node_shared_ptr()) {
+                alternative_source = std::make_shared<ov::op::v1::Add>(lhs_alternative, rhs_alternative);
+                ov::copy_runtime_info(original_output.get_node_shared_ptr(), alternative_source.get_node_shared_ptr());
+                alternative_source.get_tensor().set_value_label({label});
+                label_value_source[label] = alternative_source;
+            }
+        }
+    }
+    return alternative_source;
+}
+
+void optimize_value_usage(ov::Output<ov::Node>& output, LTS_map& label_shape_source, LTS_map& label_value_source) {
+    auto value_labels = output.get_tensor().get_value_label();
+    if (value_labels.size() != 1)
+        return;
+    auto label = value_labels[0];
+    if (label == ov::no_label)
+        return;
+    auto pshape = output.get_partial_shape();
+    if (pshape.is_dynamic() || ov::shape_size(pshape.to_shape()) != 1)
+        return;
+
+    ov::Output<ov::Node> alternative_source =
+        alternative_source_from_concat_input_sources(label_shape_source, label, output, label_value_source);
+    if (!alternative_source.get_node_shared_ptr())
+        alternative_source =
+            get_alternative_source_from_value_or_shape_source(label_shape_source, label, output, label_value_source);
+
+    if (alternative_source.get_node_shared_ptr() != nullptr) {
+        evaluate_both_bounds(alternative_source);
+        output.replace(alternative_source);
+    } else {
+        // in case we can not optimize it -- it is label which appeared just now on the value path
+        label_value_source[label] = output;
+    }
+}
+
+void save_shape_sources(const ov::Output<ov::Node>& output, LTS_map& label_shape_source) {
+    for (const auto& d : output.get_partial_shape()) {
+        if (d.is_static())
+            continue;
+        auto label = ov::DimensionTracker::get_label(d);
+        if (label == ov::no_label || label_shape_source.count(label))
+            continue;
+        label_shape_source[label] = output;
+    }
+}
+}  // namespace
+
+bool ov::pass::OptimizeLabelsUsedAsValues::run_on_model(const std::shared_ptr<ov::Model>& m) {
+    RUN_ON_FUNCTION_SCOPE(OptimizeLabelsUsedAsValues);
+    LTS_map label_shape_source;
+    LTS_map label_value_source;
+    for (const auto& op : m->get_ordered_ops()) {
+        // Result has output port which has shared (during validate_and_infer_type) tensor with input port.
+        // Transformations may replace input of Result. After replacement and before Result::validate_and_infer_type --
+        // output tensor of Result may contain inaccurate shape / labels due to the sharing with tensor which may be
+        // already detached from the model. To avoid creating ShapeOf from Result in these cases we exclude it from this
+        // optimization entirely
+        if (auto result = ov::as_type_ptr<op::v0::Result>(op))
+            continue;
+
+        // LTS maps aren't shared with sub-graphs because inner graph can not access outer graph for label sources
+        if (auto multi_subgraph_op = std::dynamic_pointer_cast<ov::op::util::MultiSubGraphOp>(op))
+            for (const auto& sub_graph : multi_subgraph_op->get_functions())
+                if (sub_graph)
+                    run_on_model(sub_graph);
+
+        for (auto& output : op->outputs()) {
+            optimize_value_usage(output, label_shape_source, label_value_source);
+            save_shape_sources(output, label_shape_source);
+        }
+    }
+    return true;
+}
diff --git a/src/common/transformations/src/transformations/symbolic_transformations/nop_broadcast.cpp b/src/common/transformations/src/transformations/symbolic_transformations/nop_broadcast.cpp
new file mode 100644
index 00000000000000..889bdd4b209d20
--- /dev/null
+++ b/src/common/transformations/src/transformations/symbolic_transformations/nop_broadcast.cpp
@@ -0,0 +1,61 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/symbolic_transformations/nop_broadcast.hpp"
+
+#include <openvino/core/dimension_tracker.hpp>
+#include <openvino/op/broadcast.hpp>
+#include <openvino/op/maximum.hpp>
+#include <openvino/op/shape_of.hpp>
+#include <openvino/pass/pattern/op/wrap_type.hpp>
+
+#include "compare.hpp"
+#include "itt.hpp"
+#include "openvino/pass/pattern/op/or.hpp"
+#include "transformations/symbolic_transformations/utils.hpp"
+#include "transformations/utils/utils.hpp"
+
+using namespace std;
+using namespace ov;
+using namespace ov::op;
+using namespace ov::symbol::util;
+
+namespace {
+shared_ptr<Node> broadcast_label(const OutputVector& inputs) {
+    return ov::pass::pattern::wrap_type<op::v1::Broadcast, op::v3::Broadcast>(inputs, [](Output<Node> output) {
+        const auto& op = output.get_node_shared_ptr();
+        auto data_rank = op->get_input_partial_shape(0).rank();
+        auto new_shape_shape = op->get_input_partial_shape(1);
+        return data_rank.is_static() && new_shape_shape.is_static() && data_rank == new_shape_shape[0];
+    });
+}
+}  // namespace
+
+ov::pass::NopBroadcast::NopBroadcast() {
+    MATCHER_SCOPE(NopBroadcast);
+    auto data_label = pattern::any_input(pattern::has_static_rank());
+
+    auto shape_label = pattern::wrap_type<op::v0::ShapeOf, op::v3::ShapeOf>();
+    auto ones = INT_CONSTANT_WITH_PREDICATE(std::all_of(value.begin(), value.end(), cmp::Equal<int64_t>(1)));
+    auto maximum = pattern::wrap_type<op::v1::Maximum>({shape_label, ones});
+
+    auto broadcast_3_ins = broadcast_label({data_label, maximum, pattern::any_input()});
+    auto broadcast_2_ins = broadcast_label({data_label, maximum});
+    auto broadcast = make_shared<pattern::op::Or>(OutputVector{broadcast_2_ins, broadcast_3_ins});
+
+    ov::matcher_pass_callback matcher_pass_callback = [=](pattern::Matcher& m) {
+        const auto& vm = m.get_pattern_value_map();
+        auto data = vm.at(data_label);
+        auto shape = vm.at(shape_label);
+
+        ov::TensorLabel data_labels, shape_labels;
+        if (!get_labels(data.get_partial_shape(), data_labels) || !get_labels(shape, shape_labels) ||
+            !are_unique_and_equal_labels(data_labels, shape_labels))
+            return false;
+        return ov::replace_output_update_name(m.get_match_root(), data);
+    };
+
+    auto m = std::make_shared<pattern::Matcher>(broadcast, matcher_name);
+    register_matcher(m, matcher_pass_callback);
+}
diff --git a/src/common/transformations/src/transformations/symbolic_transformations/symbolic_optimizations.cpp b/src/common/transformations/src/transformations/symbolic_transformations/symbolic_optimizations.cpp
new file mode 100644
index 00000000000000..7451df397ba33c
--- /dev/null
+++ b/src/common/transformations/src/transformations/symbolic_transformations/symbolic_optimizations.cpp
@@ -0,0 +1,146 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/symbolic_transformations/symbolic_optimizations.hpp"
+
+#include <openvino/core/dimension_tracker.hpp>
+#include <openvino/core/validation_util.hpp>
+#include <openvino/op/util/symbolic_info.hpp>
+#include <openvino/pass/manager.hpp>
+#include <transformations/common_optimizations/dimension_tracking.hpp>
+#include <transformations/common_optimizations/nop_elimination.hpp>
+#include <transformations/common_optimizations/shared_ops_optimization.hpp>
+#include <transformations/symbolic_transformations/chained_maximum.hpp>
+#include <transformations/symbolic_transformations/label_optimization.hpp>
+#include <transformations/symbolic_transformations/nop_broadcast.hpp>
+
+#include "itt.hpp"
+
+namespace {
+void symbolic_set_up_for_shape(ov::DimensionTracker& dt, ov::PartialShape& shape) {
+    if (shape.rank().is_dynamic())
+        return;
+    for (auto& d : shape) {
+        bool is_static = d.is_static(), has_label = ov::DimensionTracker::has_label(d);
+        if (is_static && has_label)
+            dt.reset_tracking_info(d);  // remove labels from static dims on shapes to reduce label clutter
+        if (is_static || has_label)
+            continue;
+        dt.set_up_for_tracking(d);
+    }
+}
+
+void special_case_range_label_propagation(const std::shared_ptr<ov::Node>& node) {
+    /* Label propagation through specific Range operation
+          start    shift
+            |  \   /
+            |   Add   step == 1
+            \    /    /
+               Range
+    */
+    if (!ov::is_type<ov::op::v0::Range>(node) && !ov::is_type<ov::op::v4::Range>(node))
+        return;
+
+    auto output_shape = node->get_output_partial_shape(0);
+    if (output_shape.rank().is_dynamic() || output_shape.size() != 1)
+        return;
+
+    OPENVINO_SUPPRESS_DEPRECATED_START
+    auto step_value = ov::get_constant_from_source(node->input_value(2));
+    OPENVINO_SUPPRESS_DEPRECATED_END
+    if (!step_value || step_value->cast_vector<int64_t>()[0] != 1)
+        return;
+
+    auto start_labels = node->get_input_tensor(0).get_value_label();
+    if (start_labels.size() != 1 || start_labels[0] == ov::no_label)
+        return;
+    auto start_label = start_labels[0];
+
+    auto stop_node = node->input_value(1).get_node_shared_ptr();
+    if (!ov::is_type<ov::op::v1::Add>(stop_node))
+        return;
+    auto add_in0_labels = stop_node->get_input_tensor(0).get_value_label();
+    if (add_in0_labels.size() != 1 || add_in0_labels[0] == ov::no_label)
+        return;
+    auto add_in0_label = add_in0_labels[0];
+
+    auto add_in1_labels = stop_node->get_input_tensor(1).get_value_label();
+    if (add_in1_labels.size() != 1 || add_in1_labels[0] == ov::no_label)
+        return;
+    auto add_in1_label = add_in1_labels[0];
+
+    if (add_in0_label == start_label)
+        ov::DimensionTracker::set_label(output_shape[0], add_in1_label);
+    else if (add_in1_label == start_label)
+        ov::DimensionTracker::set_label(output_shape[0], add_in0_label);
+    node->set_output_type(0, node->get_output_element_type(0), output_shape);
+}
+}  // namespace
+
+ov::pass::SymbolicPropagation::SymbolicPropagation() {
+    m_te = std::make_shared<ov::TableOfEquivalence>();
+}
+
+bool ov::pass::SymbolicPropagation::run_on_model(const std::shared_ptr<ov::Model>& m) {
+    RUN_ON_MODEL_SCOPE(SymbolicPropagation);
+
+    auto te = m_te;
+    ov::set_up_symbolic_info(m, te);
+    ov::DimensionTracker dt(te);
+
+    for (const auto& op : m->get_ordered_ops()) {
+        // since we disable invalidation with the following two lines, we have to invalidate manually here
+        op->invalidate_values();
+        for (auto& output : op->outputs())
+            ov::set_up_symbolic_info(output, te);
+        op->revalidate_and_infer_types();
+        // Recursively apply transformation for sub-graph based operations
+        if (auto multi_subgraph_op = std::dynamic_pointer_cast<op::util::MultiSubGraphOp>(op))
+            for (const auto& sub_graph : multi_subgraph_op->get_functions())
+                if (sub_graph)
+                    run_on_model(sub_graph);
+
+        // additional label propagation rules must be triggered here
+        special_case_range_label_propagation(op);
+        // additional label propagation rules must be triggered here
+
+        for (auto& output : op->outputs()) {
+            auto shape = output.get_partial_shape();
+            symbolic_set_up_for_shape(dt, shape);
+            OPENVINO_SUPPRESS_DEPRECATED_START
+            output.get_tensor().set_tensor_type(output.get_element_type(), shape);
+            OPENVINO_SUPPRESS_DEPRECATED_END
+        }
+    }
+    return true;
+}
+
+ov::pass::SymbolicOptimizations::SymbolicOptimizations(bool full_run) {
+    m_manager = std::make_shared<pass::Manager>();
+    m_manager->set_per_pass_validation(false);
+
+#define REGISTER_SYMBOLIC(region, ...) m_manager->register_pass<region>(__VA_ARGS__);
+
+    REGISTER_SYMBOLIC(SymbolicPropagation)
+    if (full_run) {
+        // symbolic based transformations allowing for better static dimension propagation
+        REGISTER_SYMBOLIC(ChainedMaximumOptimization)
+        REGISTER_SYMBOLIC(NopBroadcast)
+        // regular transformations which are needed right now since they clean up unnecessary operations
+        REGISTER_SYMBOLIC(NopElimination)        // Broadcast (Tile) Ones + Remove Slice Before GatherElements
+        REGISTER_SYMBOLIC(SharedOpOptimization)  // Shared GatherElements
+    }
+    // transformations which use labels for optimizations
+    REGISTER_SYMBOLIC(ApplyTableOfEquivalence)
+    if (full_run) {
+        REGISTER_SYMBOLIC(OptimizeLabelsUsedAsValues)  // reduce shape sub-graphs
+    }
+}
+
+bool ov::pass::SymbolicOptimizations::run_on_model(const std::shared_ptr<ov::Model>& m) {
+    RUN_ON_FUNCTION_SCOPE(SymbolicOptimizations);
+    m_manager->run_passes(m);
+    ov::remove_symbolic_info(m);
+    return true;
+}
diff --git a/src/common/transformations/src/transformations/symbolic_transformations/utils.cpp b/src/common/transformations/src/transformations/symbolic_transformations/utils.cpp
new file mode 100644
index 00000000000000..3fedc3bd4c85be
--- /dev/null
+++ b/src/common/transformations/src/transformations/symbolic_transformations/utils.cpp
@@ -0,0 +1,34 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/symbolic_transformations/utils.hpp"
+
+#include <openvino/core/dimension_tracker.hpp>
+#include <openvino/core/node.hpp>
+#include <transformations/utils/utils.hpp>
+
+bool ov::symbol::util::get_labels(const ov::PartialShape& shape, ov::TensorLabel& labels) {
+    if (shape.rank().is_dynamic())
+        return false;
+    labels.clear();
+    labels.reserve(shape.size());
+    for (const auto& d : shape)
+        labels.push_back((d.is_dynamic() ? ov::DimensionTracker::get_label(d) : ov::no_label));
+    return true;
+}
+
+bool ov::symbol::util::get_labels(const ov::Output<ov::Node>& output, ov::TensorLabel& labels) {
+    const auto& tensor = output.get_tensor();
+    labels = tensor.get_value_label();
+    return !labels.empty();
+}
+
+bool ov::symbol::util::are_unique_and_equal_labels(const ov::TensorLabel& lhs, const ov::TensorLabel& rhs) {
+    if (rhs.size() != lhs.size() || rhs.empty())
+        return false;
+    for (size_t i = 0; i < lhs.size(); ++i)
+        if (lhs[i] != rhs[i] || lhs[i] == ov::no_label)
+            return false;
+    return true;
+}
diff --git a/src/common/transformations/src/transformations/utils/utils.cpp b/src/common/transformations/src/transformations/utils/utils.cpp
index a62cd141b9f83b..62b1765e7ba275 100644
--- a/src/common/transformations/src/transformations/utils/utils.cpp
+++ b/src/common/transformations/src/transformations/utils/utils.cpp
@@ -162,16 +162,24 @@ std::vector<Input<Node>> get_node_target_inputs(const std::shared_ptr<Node>& nod
 
 std::shared_ptr<ov::Node> node_to_get_shape_value_of_indices_from_shape_node(
     const std::shared_ptr<ov::Node>& shape_node,
-    const std::vector<size_t>& indices) {
-    return make_try_fold<v7::Gather>(shape_node,
-                                     v0::Constant::create(ov::element::i64, {indices.size()}, indices),
-                                     v0::Constant::create(ov::element::i64, {}, {0}));
+    const std::vector<size_t>& indices,
+    const std::vector<std::shared_ptr<ov::Node>>& copy_rt_info_from) {
+    const auto& indices_op = v0::Constant::create(ov::element::i64, {indices.size()}, indices);
+    const auto& axis_op = v0::Constant::create(ov::element::i64, {}, {0});
+    auto op = make_try_fold<v7::Gather>(shape_node, indices_op, axis_op);
+    if (!copy_rt_info_from.empty())
+        ov::copy_runtime_info(copy_rt_info_from, {op, indices_op, axis_op});
+    return op;
 }
 
-std::shared_ptr<ov::Node> node_to_get_shape_value_of_indices_from_shape_source(const ov::Output<ov::Node>& shape_source,
-                                                                               const std::vector<size_t>& indices) {
+std::shared_ptr<ov::Node> node_to_get_shape_value_of_indices_from_shape_source(
+    const ov::Output<ov::Node>& shape_source,
+    const std::vector<size_t>& indices,
+    const std::vector<std::shared_ptr<ov::Node>>& copy_rt_info_from) {
     const auto& shape_node = make_try_fold<v3::ShapeOf>(shape_source);
-    return node_to_get_shape_value_of_indices_from_shape_node(shape_node, indices);
+    if (!copy_rt_info_from.empty())
+        ov::copy_runtime_info(copy_rt_info_from, shape_node);
+    return node_to_get_shape_value_of_indices_from_shape_node(shape_node, indices, copy_rt_info_from);
 }
 
 bool shapes_equal_except_dynamic_expected_batch(const ov::PartialShape& expected, const ov::PartialShape& actual) {
diff --git a/src/common/transformations/tests/symbolic_transformations/chained_maximum.cpp b/src/common/transformations/tests/symbolic_transformations/chained_maximum.cpp
new file mode 100644
index 00000000000000..f0507897fc4a36
--- /dev/null
+++ b/src/common/transformations/tests/symbolic_transformations/chained_maximum.cpp
@@ -0,0 +1,134 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/symbolic_transformations/chained_maximum.hpp"
+
+#include <gtest/gtest.h>
+
+#include <openvino/core/model.hpp>
+#include <openvino/op/broadcast.hpp>
+#include <openvino/op/maximum.hpp>
+#include <openvino/op/parameter.hpp>
+#include <openvino/op/shape_of.hpp>
+
+#include "common_test_utils/ov_test_utils.hpp"
+#include "openvino/core/dimension_tracker.hpp"
+#include "transformations/symbolic_transformations/symbolic_optimizations.hpp"
+
+using namespace ov;
+using namespace ov::op;
+using namespace std;
+
+TEST_F(TransformationTestsF, ChainedMaximumAC) {
+    // A == C
+    // Maximum(Maximum(A, B), C) -> Maximum(B, C)
+    {
+        auto input = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+
+        auto A = make_shared<v3::ShapeOf>(input);
+        auto B = v0::Constant::create(element::i64, {}, {1});
+        auto C = make_shared<v3::ShapeOf>(input);
+
+        auto maximum_0 = make_shared<v1::Maximum>(A, B);
+        auto maximum_1 = make_shared<v1::Maximum>(maximum_0, C);
+
+        auto data = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic());
+        auto broadcast = make_shared<v1::Broadcast>(data, maximum_1);
+
+        model = make_shared<Model>(NodeVector{broadcast}, ParameterVector{input, data});
+        manager.set_per_pass_validation(false);
+        manager.register_pass<pass::SymbolicPropagation>();
+        manager.register_pass<pass::ChainedMaximumOptimization>();
+    }
+    {
+        auto input = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+
+        auto B = v0::Constant::create(element::i64, {}, {1});
+        auto C = make_shared<v3::ShapeOf>(input);
+
+        auto maximum = make_shared<v1::Maximum>(B, C);
+
+        auto data = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic());
+        auto broadcast = make_shared<v1::Broadcast>(data, maximum);
+
+        model_ref = make_shared<Model>(NodeVector{broadcast}, ParameterVector{input, data});
+    }
+}
+
+TEST_F(TransformationTestsF, ChainedMaximumBC) {
+    // B == C
+    // Maximum(Maximum(A, B), C) -> Maximum(A, C)
+    {
+        auto input = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+
+        auto A = v0::Constant::create(element::i64, {}, {1});
+        auto B = make_shared<v3::ShapeOf>(input);
+        auto C = make_shared<v3::ShapeOf>(input);
+
+        auto maximum_0 = make_shared<v1::Maximum>(A, B);
+        auto maximum_1 = make_shared<v1::Maximum>(maximum_0, C);
+        auto data = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic());
+        auto broadcast = make_shared<v1::Broadcast>(data, maximum_1);
+
+        model = make_shared<Model>(NodeVector{broadcast}, ParameterVector{input, data});
+        manager.set_per_pass_validation(false);
+        manager.register_pass<pass::SymbolicPropagation>();
+        manager.register_pass<pass::ChainedMaximumOptimization>();
+    }
+    {
+        auto input = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+
+        auto A = v0::Constant::create(element::i64, {}, {1});
+        auto C = make_shared<v3::ShapeOf>(input);
+
+        auto maximum = make_shared<v1::Maximum>(A, C);
+
+        auto data = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic());
+        auto broadcast = make_shared<v1::Broadcast>(data, maximum);
+
+        model_ref = make_shared<Model>(NodeVector{broadcast}, ParameterVector{input, data});
+    }
+}
+
+TEST_F(TransformationTestsF, ChainedMaximumNegativeNoLabels) {
+    {
+        auto shape = PartialShape::dynamic(4);
+        auto input = make_shared<v0::Parameter>(element::f32, shape);
+
+        auto A = v0::Constant::create(element::i64, {}, {1});
+        auto B = make_shared<v3::ShapeOf>(input);
+        auto C = make_shared<v3::ShapeOf>(input);
+
+        auto maximum_0 = make_shared<v1::Maximum>(A, B);
+        auto maximum_1 = make_shared<v1::Maximum>(maximum_0, C);
+
+        auto data = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic());
+        auto broadcast = make_shared<v1::Broadcast>(data, maximum_1);
+
+        model = make_shared<Model>(NodeVector{broadcast}, ParameterVector{input, data});
+        manager.register_pass<pass::ChainedMaximumOptimization>();
+    }
+}
+
+TEST_F(TransformationTestsF, ChainedMaximumNegativeDifferentLabels) {
+    {
+        auto input_0 = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+        auto input_1 = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+
+        auto A = v0::Constant::create(element::i64, {}, {1});
+        auto B = make_shared<v3::ShapeOf>(input_0);
+        auto C = make_shared<v3::ShapeOf>(input_1);
+
+        auto maximum_0 = make_shared<v1::Maximum>(A, B);
+        auto maximum_1 = make_shared<v1::Maximum>(maximum_0, C);
+
+        auto data = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic());
+        auto broadcast = make_shared<v1::Broadcast>(data, maximum_1);
+
+        model = make_shared<Model>(NodeVector{broadcast}, ParameterVector{input_0, input_1, data});
+        manager.set_per_pass_validation(false);
+        manager.register_pass<pass::SymbolicPropagation>();
+        manager.register_pass<pass::ChainedMaximumOptimization>();
+    }
+}
diff --git a/src/common/transformations/tests/symbolic_transformations/label_optimization.cpp b/src/common/transformations/tests/symbolic_transformations/label_optimization.cpp
new file mode 100644
index 00000000000000..408467db47779f
--- /dev/null
+++ b/src/common/transformations/tests/symbolic_transformations/label_optimization.cpp
@@ -0,0 +1,97 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/symbolic_transformations/label_optimization.hpp"
+
+#include <gtest/gtest.h>
+
+#include "common_test_utils/ov_test_utils.hpp"
+#include "openvino/core/dimension_tracker.hpp"
+#include "openvino/op/add.hpp"
+#include "openvino/op/concat.hpp"
+#include "openvino/op/gather.hpp"
+#include "openvino/op/reshape.hpp"
+#include "openvino/op/shape_of.hpp"
+#include "openvino/op/util/symbolic_info.hpp"
+#include "openvino/pass/manager.hpp"
+#include "transformations/symbolic_transformations/symbolic_optimizations.hpp"
+#include "transformations/symbolic_transformations/utils.hpp"
+
+using namespace ov;
+using namespace ov::op;
+using namespace std;
+
+#define TEST_SHAPE(source, ...)                                                                 \
+    {                                                                                           \
+        auto expected_labels = ov::TensorLabel({__VA_ARGS__});                                  \
+        ov::TensorLabel labels;                                                                 \
+        EXPECT_TRUE(ov::symbol::util::get_labels(source->get_output_partial_shape(0), labels)); \
+        EXPECT_EQ(labels, expected_labels);                                                     \
+    }
+
+TEST(TransformationTests, ApplyTableOfEquivalence_Concat) {
+    auto input_1 = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+    auto input_2 = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+    auto concat = make_shared<v0::Concat>(OutputVector{input_1, input_2}, -1);
+    // shape inference notes that all the non-axis dimensions are equal to each other
+    auto model = make_shared<Model>(NodeVector{concat}, ParameterVector{input_2, input_1});
+
+    pass::Manager manager;
+    manager.set_per_pass_validation(false);
+    manager.register_pass<pass::SymbolicPropagation>();
+    manager.register_pass<pass::ApplyTableOfEquivalence>();
+    manager.run_passes(model);
+
+    TEST_SHAPE(input_1, {1, 2, 3, 4});
+    TEST_SHAPE(input_2, {1, 2, 3, 8});
+    TEST_SHAPE(concat, {1, 2, 3, 9});
+}
+
+TEST_F(TransformationTestsF, ApplyTableOfEquivalence_Concat_Values) {
+    {
+        auto input_1 = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+        auto input_2 = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+        auto concat = make_shared<v0::Concat>(OutputVector{input_1, input_2}, -1);
+
+        auto shape = make_shared<v0::ShapeOf>(concat);
+        auto gather = make_shared<v1::Gather>(shape,
+                                              v0::Constant::create(element::i64, {1}, {-1}),
+                                              v0::Constant::create(element::i64, {}, {0}));
+
+        auto reshape = make_shared<v1::Reshape>(
+            concat,
+            make_shared<v0::Concat>(OutputVector{gather, v0::Constant::create(element::i64, {1}, {-1})}, 0),
+            false);
+
+        model = make_shared<Model>(NodeVector{reshape}, ParameterVector{input_2, input_1});
+
+        manager.set_per_pass_validation(false);
+        manager.register_pass<pass::SymbolicPropagation>();
+        manager.register_pass<pass::ApplyTableOfEquivalence>();
+        manager.register_pass<pass::OptimizeLabelsUsedAsValues>();
+    }
+    {
+        auto input_1 = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+        auto input_2 = make_shared<v0::Parameter>(element::f32, PartialShape::dynamic(4));
+        auto concat = make_shared<v0::Concat>(OutputVector{input_1, input_2}, -1);
+
+        auto shape_1 = make_shared<v3::ShapeOf>(input_1);
+        auto gather_1 = make_shared<v8::Gather>(shape_1,
+                                                v0::Constant::create(element::i64, {1}, {3}),
+                                                v0::Constant::create(element::i64, {}, {0}));
+
+        auto shape_2 = make_shared<v3::ShapeOf>(input_2);
+        auto gather_2 = make_shared<v8::Gather>(shape_2,
+                                                v0::Constant::create(element::i64, {1}, {3}),
+                                                v0::Constant::create(element::i64, {}, {0}));
+
+        auto sum = make_shared<v1::Add>(gather_1, gather_2);
+
+        auto reshape = make_shared<v1::Reshape>(
+            concat,
+            make_shared<v0::Concat>(OutputVector{sum, v0::Constant::create(element::i64, {1}, {-1})}, 0),
+            false);
+        model_ref = make_shared<Model>(NodeVector{reshape}, ParameterVector{input_2, input_1});
+    }
+}
diff --git a/src/common/transformations/tests/symbolic_transformations/nop_broadcast.cpp b/src/common/transformations/tests/symbolic_transformations/nop_broadcast.cpp
new file mode 100644
index 00000000000000..63f97dfc7cb04b
--- /dev/null
+++ b/src/common/transformations/tests/symbolic_transformations/nop_broadcast.cpp
@@ -0,0 +1,111 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "transformations/symbolic_transformations/nop_broadcast.hpp"
+
+#include <gtest/gtest.h>
+
+#include <openvino/core/model.hpp>
+#include <openvino/op/broadcast.hpp>
+#include <openvino/op/maximum.hpp>
+#include <openvino/op/parameter.hpp>
+#include <openvino/op/relu.hpp>
+#include <openvino/op/shape_of.hpp>
+
+#include "common_test_utils/ov_test_utils.hpp"
+#include "openvino/core/dimension_tracker.hpp"
+
+using namespace ov;
+using namespace ov::op;
+using namespace std;
+
+namespace {
+void label_shape(ov::PartialShape& shape) {
+    auto table = std::make_shared<ov::TableOfEquivalence>(42);
+    auto tracker = ov::DimensionTracker(table);
+    tracker.set_up_for_tracking(shape);
+}
+}  // namespace
+
+TEST_F(TransformationTestsF, NopBroadcastOpset1) {
+    {
+        auto shape = PartialShape::dynamic(4);
+        label_shape(shape);  // we label shape with consecutive labels: 42, 43, 44, 45
+
+        auto data = make_shared<v0::Parameter>(element::f32, shape);
+
+        auto labeled_input = make_shared<v0::Parameter>(element::f32, shape);
+        auto shape_of = make_shared<v3::ShapeOf>(labeled_input);
+        auto ones = ov::op::v0::Constant::create(element::i64, {}, {1});
+        auto maximum = make_shared<v1::Maximum>(shape_of, ones);
+
+        auto broadcast = make_shared<v1::Broadcast>(data, maximum);
+        auto relu = make_shared<v0::Relu>(broadcast);
+
+        model = make_shared<Model>(NodeVector{relu}, ParameterVector{data, labeled_input});
+        manager.register_pass<pass::NopBroadcast>();
+    }
+    {
+        auto shape = PartialShape::dynamic(4);
+        label_shape(shape);  // we label shape with consecutive labels: 42, 43, 44, 45
+
+        auto data = make_shared<v0::Parameter>(element::f32, shape);
+        auto relu = make_shared<v0::Relu>(data);
+
+        auto labeled_input = make_shared<v0::Parameter>(element::f32, shape);
+
+        model_ref = make_shared<Model>(NodeVector{relu}, ParameterVector{data, labeled_input});
+    }
+}
+
+TEST_F(TransformationTestsF, NopBroadcastOpset3) {
+    {
+        auto shape = PartialShape::dynamic(4);
+        label_shape(shape);  // we label shape with consecutive labels: 42, 43, 44, 45
+
+        auto data = make_shared<v0::Parameter>(element::f32, shape);
+
+        auto labeled_input = make_shared<v0::Parameter>(element::f32, shape);
+        auto shape_of = make_shared<v3::ShapeOf>(labeled_input);
+        auto ones = ov::op::v0::Constant::create(element::i64, {4}, {1, 1, 1, 1});
+        auto maximum = make_shared<v1::Maximum>(shape_of, ones);
+
+        auto broadcast = make_shared<v3::Broadcast>(data, maximum);
+        auto relu = make_shared<v0::Relu>(broadcast);
+
+        model = make_shared<Model>(NodeVector{relu}, ParameterVector{data, labeled_input});
+        manager.register_pass<pass::NopBroadcast>();
+    }
+    {
+        auto shape = PartialShape::dynamic(4);
+        label_shape(shape);  // we label shape with consecutive labels: 42, 43, 44, 45
+
+        auto data = make_shared<v0::Parameter>(element::f32, shape);
+        auto relu = make_shared<v0::Relu>(data);
+
+        auto labeled_input = make_shared<v0::Parameter>(element::f32, shape);
+
+        model_ref = make_shared<Model>(NodeVector{relu}, ParameterVector{data, labeled_input});
+    }
+}
+
+TEST_F(TransformationTestsF, NopBroadcastNegative) {
+    {
+        auto shape = PartialShape::dynamic(1);
+        label_shape(shape);  // we label shape with consecutive labels: 42
+
+        auto data = make_shared<v0::Parameter>(element::f32, shape);
+
+        auto labeled_input = make_shared<v0::Parameter>(element::f32, shape);
+        auto shape_of = make_shared<v3::ShapeOf>(labeled_input);
+        auto ones = ov::op::v0::Constant::create(element::i64, {2}, {1, 1});
+        auto maximum = make_shared<v1::Maximum>(shape_of, ones);
+
+        auto broadcast = make_shared<v1::Broadcast>(data, maximum);
+        auto relu = make_shared<v0::Relu>(broadcast);
+
+        model = make_shared<Model>(NodeVector{relu}, ParameterVector{data, labeled_input});
+        manager.register_pass<pass::NopBroadcast>();
+    }
+}
diff --git a/src/core/dev_api/openvino/core/dimension_tracker.hpp b/src/core/dev_api/openvino/core/dimension_tracker.hpp
index 198454cb28c496..612ab4a01f8318 100644
--- a/src/core/dev_api/openvino/core/dimension_tracker.hpp
+++ b/src/core/dev_api/openvino/core/dimension_tracker.hpp
@@ -9,6 +9,7 @@
 #include <unordered_set>
 
 #include "openvino/core/dimension.hpp"
+#include "openvino/core/partial_shape.hpp"
 #include "openvino/core/type/element_type.hpp"
 
 namespace ov {
@@ -31,6 +32,7 @@ class OPENVINO_API DimensionTracker {
     void set_table_of_equivalence(ov::Dimension& d) const;
     static const std::shared_ptr<TableOfEquivalence>& get_table_of_equivalence(const ov::Dimension& d);
 
+    void set_up_for_tracking(ov::PartialShape& shape);
     void set_up_for_tracking(ov::Dimension& d);
     void set_up_for_tracking(ov::Dimension& d, label_t label) const;
     static void reset_tracking_info(ov::Dimension& d);
diff --git a/src/core/include/openvino/op/util/symbolic_info.hpp b/src/core/include/openvino/op/util/symbolic_info.hpp
new file mode 100644
index 00000000000000..fe58c4413d2baf
--- /dev/null
+++ b/src/core/include/openvino/op/util/symbolic_info.hpp
@@ -0,0 +1,54 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#pragma once
+
+#include <openvino/core/descriptor/tensor.hpp>
+
+#include "openvino/core/node.hpp"
+#include "openvino/core/runtime_attribute.hpp"
+#include "openvino/core/visibility.hpp"
+
+namespace ov {
+
+OPENVINO_API void set_up_symbolic_info(const std::shared_ptr<ov::Model>& model,
+                                       const std::shared_ptr<ov::TableOfEquivalence>& table);
+OPENVINO_API void set_up_symbolic_info(const ov::Output<ov::Node>& output,
+                                       const std::shared_ptr<ov::TableOfEquivalence>& table);
+
+OPENVINO_API void populate_tensor_with_missing_labels(ov::descriptor::Tensor& tensor);
+
+OPENVINO_API bool skip_invalidation(const ov::descriptor::Tensor& tensor);
+OPENVINO_API std::shared_ptr<ov::TableOfEquivalence> table_of_equivalence(const std::shared_ptr<ov::Model>& model);
+OPENVINO_API std::shared_ptr<ov::TableOfEquivalence> table_of_equivalence(const ov::descriptor::Tensor& tensor);
+
+OPENVINO_API void remove_symbolic_info(const std::shared_ptr<ov::Model>& model, bool outermost_model = true);
+
+/**
+ * @ingroup ie_runtime_attr_api
+ * @brief SymbolicInfo class represents runtime info attribute that instructs ov::Output objects to skip invalidation of
+ * partial values and labels during partial value propagation and keeps shared_ptr to TableOfEquivalence.
+ */
+class OPENVINO_API SymbolicInfo : public RuntimeAttribute {
+public:
+    OPENVINO_RTTI("SymbolicInfo", "0");
+    explicit SymbolicInfo(bool skip_invalidation, const std::shared_ptr<ov::TableOfEquivalence>& table)
+        : m_skip_invalidation{skip_invalidation},
+          m_table{table} {};
+    bool is_copyable() const override {
+        return false;
+    }
+    bool get_skip_invalidation() const {
+        return m_skip_invalidation;
+    }
+    std::shared_ptr<ov::TableOfEquivalence> get_table() const {
+        return m_table;
+    }
+
+private:
+    bool m_skip_invalidation;
+    std::shared_ptr<ov::TableOfEquivalence> m_table;
+};
+
+}  // namespace ov
diff --git a/src/core/shape_inference/include/slice_shape_inference.hpp b/src/core/shape_inference/include/slice_shape_inference.hpp
index 83a4c4fef3dfa0..cd6c3b018bdf68 100644
--- a/src/core/shape_inference/include/slice_shape_inference.hpp
+++ b/src/core/shape_inference/include/slice_shape_inference.hpp
@@ -136,7 +136,8 @@ std::vector<TRShape> shape_infer(const Slice* op,
             }
 
             auto& last_dim = out[out.size() - 1];
-            if (std::is_same<DimType, ov::Dimension>::value && (last_dim == input_dim)) {
+            if (std::is_same<DimType, ov::Dimension>::value &&
+                (last_dim == input_dim && last_dim != Dimension::dynamic())) {
                 // for equal ov::Dimension do merge to get input label (always success)
                 DimType::merge(last_dim, last_dim, input_dim);
             }
diff --git a/src/core/shape_inference/include/strided_slice_shape_inference.hpp b/src/core/shape_inference/include/strided_slice_shape_inference.hpp
index 2a870f158bf113..4806cded4dce5e 100644
--- a/src/core/shape_inference/include/strided_slice_shape_inference.hpp
+++ b/src/core/shape_inference/include/strided_slice_shape_inference.hpp
@@ -176,7 +176,8 @@ std::vector<TRShape> shape_infer(const StridedSlice* op,
                 const auto& stop = end_mask.count(axis) ? default_stop : (*end)[axis];
                 auto sliced_dim = slice::make_dim(input_dim, start, stop, stride);
 
-                if (std::is_same<DimType, ov::Dimension>::value && (sliced_dim == input_dim)) {
+                if (std::is_same<DimType, ov::Dimension>::value &&
+                    (sliced_dim == input_dim && sliced_dim != Dimension::dynamic())) {
                     // for equal ov::Dimension do merge to get input label (always success)
                     DimType::merge(sliced_dim, sliced_dim, input_dim);
                 }
diff --git a/src/core/src/bound_evaluate.cpp b/src/core/src/bound_evaluate.cpp
index 49e32619766082..38d09dbcdf6fe4 100644
--- a/src/core/src/bound_evaluate.cpp
+++ b/src/core/src/bound_evaluate.cpp
@@ -7,6 +7,7 @@
 #include "ngraph/validation_util.hpp"
 #include "openvino/core/dimension_tracker.hpp"
 #include "openvino/core/rt_info.hpp"
+#include "openvino/op/util/symbolic_info.hpp"
 #include "openvino/opsets/opset10.hpp"
 #include "shape_util.hpp"
 #include "tensor_conversion_util.hpp"
@@ -112,9 +113,16 @@ ov::Tensor evaluate_bound(const Output<Node>& output, bool is_upper, bool invali
                     }
                 }
 
-                if (node->evaluate_label(output_labels))
-                    for (size_t i = 0; i < outputs.size(); ++i)
-                        node->get_output_tensor(i).set_value_label(output_labels[i]);
+                bool labels_evaluated = node->evaluate_label(output_labels);
+                for (size_t i = 0; i < outputs.size(); ++i) {
+                    auto& out_tensor = node->get_output_tensor(i);
+                    if (!out_tensor.get_value_label().empty())
+                        continue;
+                    if (labels_evaluated)
+                        out_tensor.set_value_label(output_labels[i]);
+                    if (outputs[i])
+                        ov::populate_tensor_with_missing_labels(out_tensor);
+                }
 
                 for (const auto& input : input_values) {
                     auto& tensor = input.get_tensor();
@@ -329,8 +337,11 @@ std::pair<ov::Tensor, ov::Tensor> ov::evaluate_both_bounds(const Output<Node>& o
                     out_tensor.set_upper_value(outputs_upper[i]);
                 }
 
+                if (!out_tensor.get_value_label().empty())
+                    continue;
                 if (labels_evaluated)
-                    node->get_output_tensor(i).set_value_label(output_labels[i]);
+                    out_tensor.set_value_label(output_labels[i]);
+                ov::populate_tensor_with_missing_labels(node->get_output_tensor(i));
             }
             for (const auto& input : node->input_values()) {
                 auto& tensor = input.get_tensor();
diff --git a/src/core/src/descriptor/tensor.cpp b/src/core/src/descriptor/tensor.cpp
index c0b2cb973f4a89..18c9fd3ff18f96 100644
--- a/src/core/src/descriptor/tensor.cpp
+++ b/src/core/src/descriptor/tensor.cpp
@@ -6,6 +6,7 @@
 
 #include "openvino/core/except.hpp"
 #include "openvino/core/node.hpp"
+#include "openvino/op/util/symbolic_info.hpp"
 
 ov::descriptor::Tensor::Tensor(const element::Type& element_type,
                                const PartialShape& pshape,
@@ -46,6 +47,8 @@ void ov::descriptor::Tensor::set_element_type(const element::Type& element_type)
 OPENVINO_SUPPRESS_DEPRECATED_END
 
 void ov::descriptor::Tensor::invalidate_values() {
+    if (ov::skip_invalidation(*this))
+        return;
     m_upper_value = {};
     m_lower_value = {};
     m_value_label.clear();
diff --git a/src/core/src/dimension_tracker.cpp b/src/core/src/dimension_tracker.cpp
index ec8d48472408a9..07bb1f52435657 100644
--- a/src/core/src/dimension_tracker.cpp
+++ b/src/core/src/dimension_tracker.cpp
@@ -86,4 +86,9 @@ void DimensionTracker::set_up_for_tracking(Dimension& d) {
 void DimensionTracker::set_up_for_tracking(Dimension& d, label_t label) const {
     set_label(d, label);
     set_table_of_equivalence(d);
-}
\ No newline at end of file
+}
+
+void DimensionTracker::set_up_for_tracking(ov::PartialShape& shape) {
+    for (auto& d : shape)
+        set_up_for_tracking(d);
+}
diff --git a/src/core/src/op/util/symbolic_info.cpp b/src/core/src/op/util/symbolic_info.cpp
new file mode 100644
index 00000000000000..5dd2858a4ee507
--- /dev/null
+++ b/src/core/src/op/util/symbolic_info.cpp
@@ -0,0 +1,83 @@
+// Copyright (C) 2018-2023 Intel Corporation
+// SPDX-License-Identifier: Apache-2.0
+//
+
+#include "openvino/op/util/symbolic_info.hpp"
+
+#include <openvino/core/model.hpp>
+
+#include "openvino/core/dimension_tracker.hpp"
+#include "openvino/op/util/multi_subgraph_base.hpp"
+
+namespace {
+std::shared_ptr<ov::TableOfEquivalence> get_table(const ov::RTMap& rt_info) {
+    const auto& type = ov::SymbolicInfo::get_type_info_static();
+    if (!rt_info.count(type))
+        return nullptr;
+    return rt_info.at(type).as<ov::SymbolicInfo>().get_table();
+}
+}  // namespace
+
+void ov::set_up_symbolic_info(const std::shared_ptr<ov::Model>& model,
+                              const std::shared_ptr<ov::TableOfEquivalence>& table) {
+    auto& rt_info = model->get_rt_info();
+    rt_info[ov::SymbolicInfo::get_type_info_static()] = ov::SymbolicInfo(true, table);
+}
+
+void ov::set_up_symbolic_info(const ov::Output<ov::Node>& output,
+                              const std::shared_ptr<ov::TableOfEquivalence>& table) {
+    auto& rt_info = output.get_tensor().get_rt_info();
+    rt_info[ov::SymbolicInfo::get_type_info_static()] = ov::SymbolicInfo(true, table);
+}
+
+bool ov::skip_invalidation(const ov::descriptor::Tensor& tensor) {
+    const auto& rt_info = tensor.get_rt_info();
+    const auto& type = ov::SymbolicInfo::get_type_info_static();
+    return rt_info.count(type) && rt_info.at(type).as<ov::SymbolicInfo>().get_skip_invalidation();
+}
+
+std::shared_ptr<ov::TableOfEquivalence> ov::table_of_equivalence(const ov::descriptor::Tensor& tensor) {
+    const auto& rt_info = tensor.get_rt_info();
+    return get_table(rt_info);
+}
+
+std::shared_ptr<ov::TableOfEquivalence> ov::table_of_equivalence(const std::shared_ptr<ov::Model>& model) {
+    const auto& rt_info = model->get_rt_info();
+    return get_table(rt_info);
+}
+
+void ov::populate_tensor_with_missing_labels(ov::descriptor::Tensor& tensor) {
+    if (auto table = ov::table_of_equivalence(tensor)) {
+        auto label_values = tensor.get_value_label();
+        if (label_values.empty()) {
+            const auto& pshape = tensor.get_partial_shape();
+            if (pshape.is_dynamic())
+                return;
+            label_values.resize(ov::shape_size(pshape.to_shape()), ov::no_label);
+        }
+        for (auto& label : label_values)
+            if (label == ov::no_label)
+                label = table->get_next_label();
+        tensor.set_value_label(label_values);
+    }
+}
+
+void ov::remove_symbolic_info(const std::shared_ptr<ov::Model>& model, bool outermost_model) {
+    const auto& type = ov::SymbolicInfo::get_type_info_static();
+    auto& model_rt_info = model->get_rt_info();
+    if (model_rt_info.count(type))
+        model_rt_info.erase(type);
+    for (const auto& op : model->get_ops()) {
+        if (auto multi_subgraph_op = std::dynamic_pointer_cast<op::util::MultiSubGraphOp>(op))
+            for (const auto& sub_graph : multi_subgraph_op->get_functions())
+                if (sub_graph)
+                    remove_symbolic_info(sub_graph, false);
+        for (auto& output : op->outputs()) {
+            auto& rt_info = output.get_tensor().get_rt_info();
+            if (rt_info.count(type))
+                rt_info.erase(type);
+        }
+    }
+    if (outermost_model)
+        model->validate_nodes_and_infer_types();
+}
diff --git a/src/core/src/pass/manager.cpp b/src/core/src/pass/manager.cpp
index f55e0c8b57a4f2..804ee9af0bfea2 100644
--- a/src/core/src/pass/manager.cpp
+++ b/src/core/src/pass/manager.cpp
@@ -135,7 +135,8 @@ bool ov::pass::Manager::run_passes(shared_ptr<ov::Model> func) {
         index++;
         pass_timer.stop();
         if (profile_enabled) {
-            cout << setw(7) << pass_timer.get_milliseconds() << "ms " << pass->get_name() << "\n";
+            cout << setw(7) << pass_timer.get_milliseconds() << "ms" << (pass_applied ? " + " : "   ")
+                 << pass->get_name() << "\n";
         }
         function_changed = function_changed || pass_applied;
         needs_validate = pass_applied;
diff --git a/src/core/src/pass/visualize_tree.cpp b/src/core/src/pass/visualize_tree.cpp
index 9aa4adf2378940..15f1bc410b2189 100644
--- a/src/core/src/pass/visualize_tree.cpp
+++ b/src/core/src/pass/visualize_tree.cpp
@@ -11,6 +11,7 @@
 #include "openvino/core/type.hpp"
 #include "openvino/op/constant.hpp"
 #include "openvino/op/parameter.hpp"
+#include "openvino/op/util/multi_subgraph_base.hpp"
 #include "openvino/op/util/op_types.hpp"
 #include "openvino/util/common_util.hpp"
 #include "openvino/util/env_util.hpp"
@@ -165,6 +166,19 @@ static std::string get_attribute_values(const std::map<std::string, ov::Any>& at
     return ss.str();
 }
 
+static std::string name_of_subgraph_file(const std::shared_ptr<ov::Node> op,
+                                         const std::string& current_file_name,
+                                         const size_t& i) {
+    // friendly is never empty it is either friendly (set by user) or unique (auto-generated) name
+    auto node_name = op->get_friendly_name();
+    std::replace(node_name.begin(), node_name.end(), '/', '-');
+    auto postfix = "_node_" + node_name + "_subgraph_#" + std::to_string(i);
+    auto file_name = current_file_name;
+    auto insert_pos = file_name.find_last_of('.');
+    file_name.insert(insert_pos, postfix);
+    return file_name;
+}
+
 bool ov::pass::VisualizeTree::run_on_model(const std::shared_ptr<ov::Model>& f) {
     RUN_ON_MODEL_SCOPE(VisualizeTree);
     std::unordered_map<Node*, HeightMap> height_maps;
@@ -181,6 +195,14 @@ bool ov::pass::VisualizeTree::run_on_model(const std::shared_ptr<ov::Model>& f)
 
     for (auto it = nodes.rbegin(); it != nodes.rend(); ++it) {
         auto& node = *it;
+        if (auto multi_subgraph_op = std::dynamic_pointer_cast<op::util::MultiSubGraphOp>(node)) {
+            for (size_t i = 0; i < multi_subgraph_op->get_internal_subgraphs_size(); ++i)
+                if (const auto& sub_graph = multi_subgraph_op->get_function(i))
+                    ov::pass::VisualizeTree(name_of_subgraph_file(multi_subgraph_op, m_name, i),
+                                            m_node_modifiers,
+                                            m_dot_only)
+                        .run_on_model(sub_graph);
+        }
         for (auto& output : node->outputs()) {
             for (auto& input : output.get_target_inputs()) {
                 auto target_node = input.get_node();
diff --git a/src/core/tests/type_prop/slice.cpp b/src/core/tests/type_prop/slice.cpp
index b4ef1dcff27115..d62ce5001f928c 100644
--- a/src/core/tests/type_prop/slice.cpp
+++ b/src/core/tests/type_prop/slice.cpp
@@ -243,7 +243,7 @@ TEST(type_prop, slice_v8_basic_param_inputs_default_axes_labels_prop) {
     EXPECT_EQ(op->get_element_type(), et);
     EXPECT_EQ(op->get_output_partial_shape(0), expected_out_shape);
     EXPECT_THAT(get_shape_labels(op->get_output_partial_shape(0)),
-                ElementsAre(10, ov::no_label, ov::no_label, ov::no_label, 14, ov::no_label, 16, 17, 18));
+                ElementsAre(10, ov::no_label, ov::no_label, ov::no_label, ov::no_label, ov::no_label, 16, 17, 18));
 }
 
 TEST(type_prop, slice_v8_sss_param_inputs_mixed_neg_const_axes) {
diff --git a/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/ngram_fusion.cpp b/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/ngram_fusion.cpp
index c9b761470a133e..d941c247a005e8 100644
--- a/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/ngram_fusion.cpp
+++ b/src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/ngram_fusion.cpp
@@ -7,6 +7,7 @@
 #include <openvino/opsets/opset1.hpp>
 #include <openvino/opsets/opset10.hpp>
 #include <openvino/core/graph_util.hpp>
+#include <openvino/core/dimension_tracker.hpp>
 #include <openvino/pass/pattern/op/wrap_type.hpp>
 #include <openvino/pass/pattern/op/or.hpp>
 #include <transformations/utils/utils.hpp>
@@ -57,6 +58,12 @@ ov::intel_cpu::NgramFusion::NgramFusion() {
         auto idces_match = [](ov::Output<ov::Node> output) -> bool {
             return ov::pass::pattern::rank_equals(2)(output) && ov::pass::pattern::type_matches(ov::element::i32)(output);
         };
+        auto as_is_cropped_shape_match = [](ov::Output<ov::Node> output) -> bool {
+            const auto& labels = output.get_tensor().get_value_label();
+            return ov::pass::pattern::rank_equals(1)(output) && !labels.empty() && labels[0] != ov::no_label;
+        };
+
+        ov::label_t cropped_shape_label = ov::no_label;
 
         ov::Output<ov::Node> tokens;
         // "as_is" input validation
@@ -67,14 +74,11 @@ ov::intel_cpu::NgramFusion::NgramFusion() {
                                             ? ov::OutputVector{tokens_m, wrap_type<Constant>()}
                                             : ov::OutputVector{wrap_type<Constant>(), tokens_m, wrap_type<Constant>()};
             auto padded_tokens_m = wrap_type<Concat>(padded_tokens_inputs);
-            auto shape_of_m = wrap_type<ShapeOf>({tokens_m});
-            auto cropped_shape_m = wrap_type<StridedSlice>({shape_of_m, wrap_type<Constant>(), wrap_type<Constant>(), wrap_type<Constant>()});
-
+            auto cropped_shape_m = any_input(as_is_cropped_shape_match);
             auto ss_bias = wrap_type<Constant>();
             auto ss_biased_shape_m =
                 as_is_idx == 0 ? cropped_shape_m : wrap_type<Add>({cropped_shape_m, ss_bias});
-            auto ss_end_reshape_m = wrap_type<Reshape>({ss_biased_shape_m, any_input()});
-            auto cropped_tokens_m = wrap_type<StridedSlice>({padded_tokens_m, wrap_type<Constant>(), ss_end_reshape_m, wrap_type<Constant>()});
+            auto cropped_tokens_m = wrap_type<StridedSlice>({padded_tokens_m, wrap_type<Constant>(), ss_biased_shape_m, wrap_type<Constant>()});
             Matcher matcher(cropped_tokens_m);
 
             if (!matcher.match(inputs[as_is_idx])) {
@@ -93,15 +97,27 @@ ov::intel_cpu::NgramFusion::NgramFusion() {
                 concat_shape.rank() != tokens_shape.rank() || tokens_shape[1] * k != concat_shape[1]) {
                 return false;
             }
+            // save label of cropped_shape and check it against first dimension of tokens shape
+            cropped_shape_label = pattern_map.at(cropped_shape_m).get_tensor().get_value_label()[0];
+            if (ov::DimensionTracker::get_label(tokens_shape[0]) != cropped_shape_label)
+                return false;
         }
 
+        auto cropped_shape_label_match = [cropped_shape_label](ov::Output<ov::Node> output) -> bool {
+            const auto& labels = output.get_tensor().get_value_label();
+            return ov::pass::pattern::rank_equals(1)(output) && !labels.empty() && labels[0] != ov::no_label && labels[0] == cropped_shape_label;
+        };
+
+        auto tokens_label_match = [tokens_match, cropped_shape_label](ov::Output<ov::Node> output) -> bool {
+            return tokens_match(output) && ov::DimensionTracker::get_label(output.get_partial_shape()[0]) == cropped_shape_label;
+        };
+
         ov::Output<ov::Node> indices;
         // select branches validation
         {
             using namespace ov::opset1;
-            auto tokens_m = any_input(tokens_match);
-            auto shape_of_m = wrap_type<ShapeOf>({tokens_m});
-            auto cropped_shape_m = wrap_type<StridedSlice>({shape_of_m, wrap_type<Constant>(), wrap_type<Constant>(), wrap_type<Constant>()});
+            auto tokens_m = any_input(tokens_label_match);
+            auto cropped_shape_m = any_input(cropped_shape_label_match);
             auto idces_m = any_input(idces_match);
             auto idces_concat_inputs = as_is_idx == 0
                                             ? ov::OutputVector{idces_m, wrap_type<Constant>()}
@@ -111,17 +127,15 @@ ov::intel_cpu::NgramFusion::NgramFusion() {
             // left equal branch
             auto crop_left_bias_m = wrap_type<Constant>();
             auto crop_left_cropped_shape_m = std::make_shared<ov::pass::pattern::op::Or>(
-                ov::OutputVector{cropped_shape_m, wrap_type<Add>({cropped_shape_m, crop_left_bias_m})});
-            auto crop_left_reshape_m = wrap_type<Reshape>({crop_left_cropped_shape_m, any_input()});
-            auto idxes_crop_left_concat_m = wrap_type<Concat>({crop_left_reshape_m, wrap_type<Constant>()});
+                ov::OutputVector{wrap_type<Add>({cropped_shape_m, crop_left_bias_m}), cropped_shape_m});
+            auto idxes_crop_left_concat_m = wrap_type<Concat>({crop_left_cropped_shape_m, wrap_type<Constant>()});
             auto idxes_crop_left_m = wrap_type<StridedSlice>({idces_concat_m, wrap_type<Constant>(), idxes_crop_left_concat_m, wrap_type<Constant>()});
 
             // right equal branch
             auto crop_right_bias_m = wrap_type<Constant>();
             auto crop_right_cropped_shape_m = std::make_shared<ov::pass::pattern::op::Or>(
-                ov::OutputVector{cropped_shape_m, wrap_type<Add>({cropped_shape_m, crop_right_bias_m})});
-            auto crop_right_reshape_m = wrap_type<Reshape>({crop_right_cropped_shape_m, any_input()});
-            auto idxes_crop_right_concat_m = wrap_type<Concat>({crop_right_reshape_m, wrap_type<Constant>()});
+                ov::OutputVector{wrap_type<Add>({cropped_shape_m, crop_right_bias_m}), cropped_shape_m});
+            auto idxes_crop_right_concat_m = wrap_type<Concat>({crop_right_cropped_shape_m, wrap_type<Constant>()});
             auto idxes_crop_right_m = wrap_type<StridedSlice>({idces_concat_m, wrap_type<Constant>(), idxes_crop_right_concat_m, wrap_type<Constant>()});
 
             auto equal_m = wrap_type<Equal>({idxes_crop_left_m, idxes_crop_right_m});
@@ -135,13 +149,11 @@ ov::intel_cpu::NgramFusion::NgramFusion() {
 
             auto then_cropped_shape_bias_m = wrap_type<Constant>();
             auto then_cropped_shape_m = std::make_shared<ov::pass::pattern::op::Or>(
-                ov::OutputVector{cropped_shape_m, wrap_type<Add>({cropped_shape_m, then_cropped_shape_bias_m})});
-            auto then_crop_end_reshape_m = wrap_type<Reshape>({then_cropped_shape_m, wrap_type<Constant>()});
-            auto then_m = wrap_type<StridedSlice>({padded_tokens_m, wrap_type<Constant>(), then_crop_end_reshape_m, wrap_type<Constant>()});
+                ov::OutputVector{wrap_type<Add>({cropped_shape_m, then_cropped_shape_bias_m}), cropped_shape_m});
+            auto then_m = wrap_type<StridedSlice>({padded_tokens_m, wrap_type<Constant>(), then_cropped_shape_m, wrap_type<Constant>()});
 
             // else branch
-            auto else_target_shape_reshape_m = wrap_type<Reshape>({cropped_shape_m, any_input()});
-            auto else_target_shape_concat_m = wrap_type<Concat>({else_target_shape_reshape_m, wrap_type<Constant>()});
+            auto else_target_shape_concat_m = wrap_type<Concat>({cropped_shape_m, wrap_type<Constant>()});
             auto else_m = wrap_type<Broadcast>({wrap_type<Constant>(), else_target_shape_concat_m, wrap_type<Constant>()});
             auto select_m = wrap_type<Select>({condition_m, then_m, else_m});
             Matcher select_matcher(select_m);
diff --git a/src/plugins/intel_cpu/src/transformations/cpu_opset/convert_to_cpu_specific_opset.hpp b/src/plugins/intel_cpu/src/transformations/cpu_opset/convert_to_cpu_specific_opset.hpp
index 2836f0ea4f1aa7..3e2158e7a383f7 100644
--- a/src/plugins/intel_cpu/src/transformations/cpu_opset/convert_to_cpu_specific_opset.hpp
+++ b/src/plugins/intel_cpu/src/transformations/cpu_opset/convert_to_cpu_specific_opset.hpp
@@ -16,6 +16,7 @@
 #include "common/pass/convert_to_swish_cpu.hpp"
 #include "common/pass/move_fc_reshape_to_weights.hpp"
 #include "transformations/convert_precision.hpp"
+#include "transformations/symbolic_transformations/symbolic_optimizations.hpp"
 #include "transformations/utils/utils.hpp"
 #include "common/pass/rnn_sequences_optimization.hpp"
 #include "transformations/common_optimizations/reshape_sequence_fusion.hpp"
@@ -48,7 +49,8 @@ inline void ConvertToCPUSpecificOpset(std::shared_ptr<ngraph::Function> &nGraphF
     CPU_REGISTER_PASS_COMMON(manager, ov::pass::ReshapeSequenceFusion);
     CPU_REGISTER_PASS_COMMON(manager, ov::pass::ConstantFolding);
     CPU_REGISTER_PASS_COMMON(manager, ov::pass::ConvertPrecision, precisions_map {{ ngraph::element::i64, ngraph::element::i32 }});
-    CPU_REGISTER_PASS_COMMON(manager, NgramFusion);
+    auto symbolic_pipeline = CPU_REGISTER_PASS_COMMON(manager, ov::pass::SymbolicOptimizations, false);
+    symbolic_pipeline->get_manager()->register_pass<NgramFusion>();
     CPU_REGISTER_PASS_COMMON(manager, ov::pass::Validate);
 
     manager.run_passes(nGraphFunc);